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Personalized Product Descriptions with GenAI

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Overview

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Generative AI can be used to automate the creation of marketing content, including generating personalized product descriptions. This can save marketers significant time and effort, allowing them to focus on other aspects of their strategy.

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The real power of generative AI for product descriptions is the ability to dynamically create unique, personalized content for each customer segment or individual user. Previously, marketers would need to manually generate multiple copies of product descriptions for different customer attributes. Generative AI can automate this process, providing opportunities to tailor the descriptions to each user's preferences and context.

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Implementation in the Retail Demo Store

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The Retail Demo Store integrates the product service with Amazon Bedrock to retrieve personalized product descriptions based on the logged-in user's age and interests.

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Amazon Bedrock makes Foundation Models (FMs) accessible via an API, and in this demo, Anthropic's Claude v2 is the underlying FM used for generating the personalized descriptions.

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The prompt used to generate the personalized descriptions takes the following form:

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I'd like you to rewrite the following paragraph using the following instructions:
+"{instructions}"
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+"{original product description}"
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+Please put your rewrite in <p></p> tags.
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The instructions used are:

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Please generate an enhanced product description personalised for a customer aged {age range}, interested in {interests}.
+However, do not mention their age in the rewrite. 
+The product is named "{product name}" and is a product of type "{product type}" in the {product category} category.
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This allows the generative AI model to dynamically create a personalized product description based on the user's age and interests, without explicitly mentioning those details.

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Architecture

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The overall architecture of this demo involves the following components:

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  1. The user authenticates with Amazon Cognito and obtains an identity token, which is passed to subsequent API requests.
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  2. The Web UI uploads a product image to S3 and calls the API Gateway to request a personalized product description.
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  3. The API Gateway validates the identity token and proxies the request to a Lambda function.
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  4. The Lambda function retrieves the user's age and interests from the identity token, constructs the prompt, and calls Amazon Bedrock to generate the personalized description.
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  5. The generated description is returned to the Web UI for display.
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By integrating Generative AI through Amazon Bedrock, the Retail Demo Store is able to provide personalized product descriptions that are tailored to each individual user, improving the overall shopping experience.

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Geofencing and Location aware Personalization

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Geofencing and Location-aware Personalization

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The Retail Demo Store integrates Amazon Location Services to demonstrate how businesses can leverage location data to deliver personalized experiences and increase foot traffic to physical stores.

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Use Case

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Imagine a customer is out shopping and approaches one of your retail locations. As they get closer, you want to be able to detect their presence, deliver a personalized offer or notification, and potentially encourage them to come into the store to redeem the offer or pick up an online order.

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How it Works

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The Retail Demo Store uses Amazon Location Services to set up a geofence around a sample physical store location. As customers approach the store, their location is detected, and personalized messages are delivered to them through Amazon Pinpoint.

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The key components are:

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  1. Location Service: Defines the geofence around the physical store and tracks customer proximity.
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  2. Offers Service: Maintains a catalog of personalized offers that can be triggered based on customer location.
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  3. Pinpoint: Sends personalized push notifications, SMS, or email messages to customers when they enter the geofence.
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  4. Personalize: Integrates with Amazon Personalize to select the most relevant offer for each customer based on their profile and past behaviors.
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When a customer enters the geofence, the following happens:

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  1. The Location Service detects the customer's proximity to the store.
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  2. The Offers Service selects a personalized offer for the customer using Amazon Personalize.
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  3. Pinpoint delivers the personalized offer to the customer via their preferred communication channel (e.g., push notification, SMS, email).
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  4. The customer can then redeem the offer by visiting the store.
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Benefits

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  • Increased Foot Traffic: Personalized offers and notifications encourage customers to visit the physical store.
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  • Improved Customer Experience: Customers receive timely, relevant offers based on their location and preferences.
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  • Enhanced Omni-Channel Strategy: Integrating location data with other customer data (e.g., purchase history, browsing behavior) enables a more comprehensive, personalized customer experience across digital and physical channels.
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Try it Yourself

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To experience the Geofencing and Location-aware Personalization demo, deploy the Retail Demo Store and navigate to the "In Store View -> Location Geofence" section. You can then simulate a customer approaching the store and see the personalized offer delivered.

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Messaging and Engagement

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The Retail Demo Store integrates Amazon Pinpoint and Amazon Personalize to provide a seamless omni-channel personalization experience for the customer.

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Welcome Emails

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When a new user signs up for a Retail Demo Store account, Amazon Pinpoint is used to automatically send a welcome email. The email content is personalized based on the user's profile information, such as their name, and can include personalized product recommendations generated by Amazon Personalize.

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Abandoned Cart Emails

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If a user adds items to their cart but does not complete the purchase, Amazon Pinpoint is used to send an "abandoned cart" email. This email includes a coupon code to incentivize the user to return and complete their purchase. The product recommendations in the email are personalized based on the user's browsing and purchase history.

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SMS Alerts and Offers

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The Retail Demo Store also integrates SMS messaging powered by Amazon Pinpoint. Users can opt-in to receive text alerts, such as notifications when they are near a physical store location. These alerts can include personalized product offers generated by Amazon Personalize.

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Omni-Channel Personalization

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By connecting Amazon Pinpoint with Amazon Personalize, the Retail Demo Store is able to create a unified, omni-channel personalization experience. All customer interactions, whether on the website, in emails, or through SMS, are fed into the Personalize machine learning models. This allows the recommendations and offers to be consistently personalized across every touchpoint.

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Real-Time Segmentation

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Amazon Pinpoint enables the creation of real-time user segments based on the customer's behavior across web, mobile, email, and SMS channels. These dynamic segments can then be used to trigger personalized messaging campaigns through the channel most appropriate for each user.

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Overall, the Messaging and Engagement demo showcases how retailers can leverage the power of Amazon Pinpoint and Amazon Personalize to deliver a highly personalized, omni-channel customer experience that drives engagement and conversion.

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Personalization

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The Retail Demo Store showcases several personalization capabilities powered by Amazon Personalize, a machine learning service that makes it easy to add sophisticated personalization to applications. The personalization demos in the Retail Demo Store cover the following key use cases:

+ +

The product detail pages in the Retail Demo Store include a "Compare similar items" carousel that displays products similar to the one being viewed. This is implemented using the Similar-Items algorithm in Amazon Personalize, which recommends related items based on user behavior (co-occurrence in interactions data) and thematic similarity between products.

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The Similar-Items algorithm considers both how often products appear together in user histories, as well as the attributes of the products themselves, to identify items that are truly similar - even for long-tail or new products with limited historical data.

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Additionally, the Personalized-Ranking recipe is used to re-order the related items recommendations based on the current user's preferences, providing a personalized experience.

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The "Inspired by your shopping trends" section on the homepage displays personalized product recommendations for the current user, using the User-Personalization recipe in Amazon Personalize. This recipe balances recommending items the user is likely to engage with, based on their historical behavior, with exposing them to new and trending products.

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The User-Personalization recipe handles the "cold-start" challenge, where limited or no historical information is known about a user or an item, by incorporating user attributes and item metadata to make relevant recommendations.

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User Segmentation

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Amazon Personalize also enables advanced user segmentation, going beyond traditional rules-based approaches. The Item-Affinity and Item-Attribute-Affinity recipes can identify high-propensity user segments for specific products or product categories, without the need to maintain complex business rules.

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This allows retailers to efficiently target marketing campaigns, promotions, or merchandising strategies to the users most likely to engage.

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Real-Time Personalization

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The Retail Demo Store showcases how Amazon Personalize can be integrated with the web user interface to deliver real-time personalized experiences. As users interact with the storefront, their clickstream data is captured and sent to Personalize's real-time event tracking. Personalize then uses this data to update the user's profile and deliver personalized recommendations in subsequent page views.

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Measuring Personalization Impact

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The Retail Demo Store also includes workshops that demonstrate how to measure the impact of personalization using techniques like A/B testing, interleaving, and multi-armed bandit experiments. These allow you to rigorously evaluate the effectiveness of your personalization strategies and make data-driven decisions to optimize the customer experience.

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Overall, the personalization capabilities showcased in the Retail Demo Store illustrate how Amazon Personalize can be easily integrated to deliver sophisticated, scalable personalization for ecommerce applications - without the need for extensive machine learning expertise.

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Product search

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The Search demo in the Retail Demo Store showcases how to integrate Amazon OpenSearch Service (formerly Amazon Elasticsearch Service) to provide a powerful and customizable search experience for an ecommerce application.

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The current demo presents only type-ahead search at the moment, but the principles could be extended to support a fully fledged search solution.

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How it Works

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search

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The core components of the Search demo are:

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    Search Service: This is a RESTful web service that provides an API for querying the product catalog and returning search results. The service is deployed as a Docker container on Amazon ECS.

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    OpenSearch Cluster: Amazon OpenSearch Service is used to host the product index and power the search functionality. When the Retail Demo Store is initially deployed, the product catalog is automatically indexed in OpenSearch.

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    Web UI Integration: The Retail Demo Store's web user interface makes calls to the Search Service API when a user performs a search. The search results are then displayed to the user.

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Here's a step-by-step breakdown of how the Search demo works:

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  1. User Initiates a Search: A user enters a search query in the Retail Demo Store's web UI.
    2. +
  2. Web UI Calls Search Service: The web UI makes a request to the Search Service API, passing the user's search query.
    3. +
  3. Search Service Queries OpenSearch: The Search Service forwards the query to the OpenSearch cluster and retrieves the relevant product results.
    4. +
  4. Search Service rerank the results: The Search Service send the results to Amazon Personalize to rerank based on the current customer.
    5. +
  5. Web UI Displays Results: The web UI receives the search results and displays them to the user.
    6. +
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Conclusion

+

The Search demo in the Retail Demo Store showcases how to leverage Amazon OpenSearch Service to provide a scalable, customizable, and integrated search experience for an ecommerce application. By combining the power of OpenSearch with the overall architecture of the Retail Demo Store, businesses can deliver a highly engaging and responsive search functionality to their customers.

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Room Makeover: Revolutionizing Interior Design with GenAI

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In today's fast-paced world, consumers are constantly seeking new and innovative ways to personalize their living spaces. The Retail Demo Store's Room Makeover demo harnesses the power of cutting-edge AI technologies to enable an unprecedented level of personalization in interior design.

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The Challenge

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Traditionally, the process of reimagining a room's décor has been time-consuming and labor-intensive. Homeowners often struggle to visualize how different design elements would look in their existing spaces, leading to hesitation and missed opportunities.

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The Solution

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screenshot1

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The Room Makeover demo revolutionizes this experience by seamlessly integrating several AWS services to create a truly immersive and personalized interior design solution.

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    User Uploads Room Image: Customers can upload a photo of their existing room through a secure and intuitive web interface powered by AWS Amplify and Amazon Cognito.

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    Image Analysis: The uploaded image is then analyzed using Amazon Rekognition, which detects and identifies the key furniture and decor elements within the room.

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    Product Matching: The detected objects are matched against a product catalog using Amazon Bedrock's Titan Multimodal Embeddings model, which provides a rich understanding of product attributes and similarities.

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    Personalized Prompts: Combining the detected room elements with the product matches, the demo generates a personalized prompt that can be used to guide the AI-powered room redesign.

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    Stable Diffusion Generation: The prompt is then passed to a custom Stable Diffusion model deployed on Amazon SageMaker, which generates a new image depicting the room in the selected design style.

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    Continuous Optimization: The generated image is further analyzed to identify additional furniture and decor elements, which are matched back to the product catalog to allow customers to select and purchase straight from the generated room image.

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The Room Makeover demo offers several key benefits for businesses and consumers:

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    Personalization at Scale: By leveraging the power of AI, the demo can generate personalized room designs for each customer, at scale, rather than relying on manual, labor-intensive processes.

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    Increased Engagement and Conversion: The immersive, AI-powered experience helps customers visualize how their spaces could be transformed. The generated product in the image is automatically linked to the product catalog and features a direct "add to basket" functionality, driving increased engagement and ultimately, higher conversion rates.

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    Streamlined Workflows: The automated product matching and prompt generation capabilities reduce the time and effort required by interior design professionals, enabling them to focus on higher-value tasks.

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Conclusion

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The Room Makeover demo showcases the transformative potential of AI-powered personalization in the interior design industry. By seamlessly integrating cutting-edge AWS services, businesses can now offer their customers a truly innovative and engaging experience, ultimately driving growth and customer satisfaction.

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Available Demos

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The Retail Demo Store features several demo components that showcase different AWS services and capabilities:

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    Room Makeover: NEW

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    Combines Stable Diffusion, Anthropic Claude, Amazon Sagemaker, Amazon Bedrock, and Amazon Rekognition to generate re-styled rooms from user-uploaded images.

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    Personalized Product Descriptions: NEW

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    Uses Amazon Bedrock and Anthropic's Claude model to generate personalized product descriptions.

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    Personalization:

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    Powered by Amazon Personalize, demonstrating use cases like similar item recommendations, personalized ranking, and user segmentation.

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    Includes workshops on setting up and evaluating Personalize models.

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    Messaging and Engagement:

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    Uses Amazon Pinpoint for triggered email, SMS, and in-app messages (welcome emails, abandoned cart reminders, etc.).

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    Demonstrates omni-channel personalization by integrating Personalize and Pinpoint.

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    Geofencing and Location-aware Personalization:

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    Uses Amazon Location Services to create geofences and trigger personalized offers/pickup notifications.

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    Search

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    Integrates Amazon OpenSearch Service to power a scalable and customizable search experience for an ecommerce application

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    Enables businesses to deliver a highly engaging and responsive search functionality to their customers

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These demos showcase a wide range of AWS services and how they can be integrated to build compelling customer experiences for ecommerce, retail, and digital marketing use cases.

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Creating a Retail Demo Store account

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Before getting started, we advise you to use a Private Window (Firefox) or Incognito Window (Chrome) to make sure you don't mix different demo profiles in the same browser session

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Since several of the features of the Retail Demo Store require a user/customer account to demonstrate effectively, this section will describe the process of creating a user account using the Retail Demo Store’s web user interface. This process also provides a good demonstration of how Amazon Cognito is used to implement user account and authentication.

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Click the “Sign In” button in the right side of the top navigation bar. This will take you to the Sign In page. Click the “Create account” link at the bottom of the Sign In form as shown below. These forms are provided by Cognito.

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Figure 3. Create Account Link.

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Complete the “Sign Up Account” form by entering appropriate values in each field. Note that your password must meet the complexity requirements configured in Amazon Cognito (upper- and lower-cased characters, numbers, and special characters). In addition, be sure to enter a valid email address since Cognito will send you a confirmation code via email once you submit the form. Otherwise, the only way to confirm your account is manually in the Cognito User Pool page in the AWS console. If you need to create multiple accounts to demonstrate behavior across users, a useful tip is to append a different mailbox name (“+” notation) to the username portion of your email address for each user account. For example, login+user5@example.com. You will still receive emails addressed using this format in your inbox.

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Figure 4. Create Account page.

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Within a few seconds after pressing the “Create Account” button on the “Sign Up Account” form you should receive an email on the provided email address. The email will contain a 6-digit confirmation code. Enter this code on the “Confirm Sign Up” form and press the “Confirm” button. If you don’t receive a confirmation code, you can have it resent or you can manually confirm your user account in the Amazon Cognito User Pool page in the AWS console in the AWS account where the Retail Demo Store instance has been deployed.

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Figure 5. Confirm New Account.

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Once your user account has been confirmed, you can sign in to your account with your username and password.

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Figure 6. Sign In to Account.

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You can tell if you’re signed in if the “Sign In” button in the top navigation is replaced by your username.

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Deployment Instructions

+

These instructions are valid whenever you just want to demo the Retail Demo Store or if you would like to contribute enhancements or features to the Retail Demo Store, please read on for instructions on how to develop and test your changes.

+

Thanks for considering working with this project.

+
graph TB
+  B[Install the requirements];
+  B -->|if you want to customize the demo| C[Fork this Repo];
+  C --> D[Create a Github Personal Access Token]
+  B --> E;
+  D --> E[Create a Staging Bucket];
+  E --> F[Stage the code to this bucket];
+  F --> G[Deploy Cloudformation Template]
+

Step 1 : Requirements

+

Let's review the requirements before deploying the demo store (this was tested on a fresh EC2 instance for the Retail Demo Store. These install prerequisites apply to the Ubuntu AMI.)

+

Ensure the instance is up-to-date:

+
sudo apt update
+sudo apt upgrade
+
+

Verify Python:

+

python3 -V
+
+You need Python 3.12.3 or higher +If not: sudo apt install python3

+

Install Git and clone repo:

+
sudo apt install git
+mkdir RetailDemoStore
+cd RetailDemoStore/
+git clone https://github.com/aws-samples/retail-demo-store
+
+
+

Note

+

If you plan to customize the demo, we recommend using your fork instead of the aws-samples one (see fork this repo)

+
+

Packages required for building staging:

+
sudo apt install zip
+sudo apt install python3-pip
+sudo apt install python3.12-venv
+sudo apt install nodejs
+sudo apt install npm
+
+

Install and configure the AWS CLI:

+
curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
+unzip awscliv2.zip
+sudo ./aws/install
+aws configure
+
+

(optional) Fork this Repo

+

We recommend to create a fork of the Retail Demo Store respository in your own GitHub account. That enables you to customize the code before deployment.

+

(optional) Create a GitHub Personal Access Token

+

Create a GitHub Personal Access Token in your GitHub account.

+

Make sure that your token has the "repo", "repo:status", and "admin:repo_hook" permission scopes.

+

Save your access token in a secure location, you will use it the CloudFormation parameters at deployment time.

+

Step 2: Create a S3 Staging Bucket

+

Create a dedicated S3 bucket specifically for staging/deployment.

+
+

Warning

+

Ensure that versioning is enabled for this bucket.

+
+
+

Warning

+

Your staging bucket must be in the region with in which you plan to deploy the Retail Demo Store.

+
+

Enabling Event Notifications

+

Setting Up Event Notifications to Amazon EventBridge on an S3 Bucket

+

Follow these steps to configure your S3 bucket to send event notifications to Amazon EventBridge:

+
    +
  1. Navigate to your S3 bucket in the AWS Management Console.
    2. +
  2. Click on the Properties tab.
    3. +
  3. Scroll down to the Amazon EventBridge section.
    4. +
  4. Click the Edit button.
    5. +
  5. Toggle the option Send notifications to Amazon EventBridge for all events in this bucket to On.
    6. +
  6. Click Save changes.
    7. +
+

Bucket Permissions

+

The default stage script requires the ability to set the resources it uploads to your bucket as public read. Note that you do not need to set the bucket up to allow public listing of the resources in the bucket (this is not recommended).

+

If you plan to enable the automated Personalize campaign creation process at deployment time, you must allow access for Amazon Personalize to your bucket. Add the following bucket policy to your staging bucket.

+
{
+    "Version": "2012-10-17",
+    "Id": "PersonalizeS3BucketAccessPolicy",
+    "Statement": [
+        {
+            "Sid": "PersonalizeS3BucketAccessPolicy",
+            "Effect": "Allow",
+            "Principal": {
+                "Service": "personalize.amazonaws.com"
+            },
+            "Action": [
+                "s3:GetObject",
+                "s3:ListBucket"
+            ],
+            "Resource": [
+                "arn:aws:s3:::<your bucket name>",
+                "arn:aws:s3:::<your bucket name>/*"
+            ]
+        }
+    ]
+}
+
+

Step 3: Staging for Deployment

+

We recommend to use a Python 3 virtual environment. Current supported version of python is 3.12 (other versions may work but we haven't tested all versions)

+
python3.12 -m venv .venv/
+source .venv/bin/activate
+
+

The stage.sh script at the root of the repository must be used to upload the deployment resources to your staging S3 bucket if you use this option. The shell uses the local AWS credentials to build and push resources to your custom bucket.

+

Example on how to stage your project to a custom bucket and path (note the path is optional but, if specified, must end with '/'):

+
./stage.sh MY_CUSTOM_BUCKET S3_PATH/ --skip-virtualenv
+
+

Step 4: Deploy the Cloudformation template

+

The stage script will output a path to your master deployment CloudFormation template. You can use this link to your S3 bucket to start a new deployment via the CloudFormation console in your AWS Console. Please read and complete any required parameters. The mandatory parameters to fill up are:

+
    +
  • ResourceBucket
    • +
  • ResourceBucketRelativePath
    • +
  • CreateOpenSearchServiceLinkedRole
    • +
+

All the others will work by default, take the time to read and decide which parameters you want to use

+
+

Note

+

You can also use the command line below. (replace REGION, MY_CUSTOM_BUCKET and S3_PATH value). +This script deploys the retail demo store with standard options, you cannot change any parameters directly

+
./scripts/deploy-cloudformation-stacks.sh DEPLOYMENT_S3_BUCKET S3_PATH REGION STACK_NAME
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+ + + + + + + + + + \ No newline at end of file diff --git a/Deployment/integrations tests/index.html b/Deployment/integrations tests/index.html new file mode 100644 index 000000000..978ebb740 --- /dev/null +++ b/Deployment/integrations tests/index.html @@ -0,0 +1,2397 @@ + + + + + + + + + + + + + + + + + + + + + + + Integrations tests - Retail Demo Store - Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Integrations tests

+ +

Integration tests can be run on either

+
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  1. Local development (via Docker Compose)
    2. +
  2. Actual (deployed) AWS environment
    3. +
+

Running integration tests with GNU Make

+

Getting started

+

The Makefile in this folder allows tests to be ran in bulk (or by service/function) without any additional setup.

+

Run commands in this directory (src/run-tests)

+

Example usage:

+
# Run this only once to generate `.venv` folder with all dependencies in all `integ` folders
+make setup 
+
+# Run integation tests of all services
+make integ
+
+# Run integration test of a specific service (default to running against local Docker container)
+make integ SERVICE=recommendations
+
+# Run integration test of a specific on a target endpoint
+make integ SERVICE=recommendations RECOMMENDATIONS_API_URL=http://retai-LoadB-xxx-yyy.us-west-2.elb.amazonaws.com
+
+

List of environment variables used in the integration tests

+

You can find the list in <root_project_folder>/.env.template. All of them have default values and should work out of the box.

+

The important variables are the <SERVICE>_API_URL. They are used to redirect the tests to run against different URLs.

+

NB: For local development you may need to set up dependencies like local dynamodb before testing. Refer to individual service test READMEs for more detailed info on local dependencies

+

Targets

+

make

+

Runs default target (test).

+

make test

+

Run all tests of all types. Currently, only integration tests are supported.

+

make setup

+

Installs test requirements inside a virtual environment .venv.

+

make venv

+

Create virtual environment.

+

make integ SERVICE=

+

Depends on setup target. Run all integration tests. (Optional: Specify SERVICE parameter to run tests for that service only).

+

make clean

+

Remove virtual environment.

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+ + + + + + + + + + \ No newline at end of file diff --git a/Deployment/local-development/0-local-development-instructions/index.html b/Deployment/local-development/0-local-development-instructions/index.html new file mode 100644 index 000000000..ddc850ce9 --- /dev/null +++ b/Deployment/local-development/0-local-development-instructions/index.html @@ -0,0 +1,2344 @@ + + + + + + + + + + + + + + + + + + + + + + + Local Development Instructions - Retail Demo Store - Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Local Development Instructions

+

The Retail Demo Store's web services such as users, carts, orders, products, and others can be run locally on your development system using Docker Compose. You can choose to run them all locally or just one or two locally and the rest running in your AWS account. For example, suppose you're working on an enhancement or fix in the products service. You can run just that service locally to test your changes while all of the other services are running in your AWS account. If your changes require UI testing, you can run the web-ui in a local container as well configured to connect to your local product service instance while still having both of them connect to the other services running in your AWS account.

+

Before you can run the Retail Demo Store web services locally, you must first deploy the Retail Demo Store project to your AWS account and then clone this repository to your local machine. The instructions below provide additional details on configuration and how to setup the services to run locally. The docker-compose.yml file includes the configuration used by Docker Compose. Note that there are some dependencies between services which are noted.

+

Configuring your Environment

+

Besides cloning this repository to your local system, you also need to have the AWS CLI installed and configured locally.

+

Docker Compose will load the .env file to resolve environment variables referenced in the docker-compose.yml file. You can copy the .env.template file to .env +as a starting point. This is where you can customize variables to match your desired configuration.

+

You can find the common environment variables from your deployed stack in the CloudFormation output name ExportEnvVarScript. Use this CLI to get the output in a proper format.

+
aws cloudformation describe-stacks --stack-name retaildemostore \
+  --region REGION \
+  --query "Stacks[0].Outputs[?OutputKey=='ExportEnvVarScript'].OutputValue" \
+  --output text
+
+

Then you can copy and override variables for each service in your .env file.

+

Amazon ECR authorization

+

Since some of the Docker images are hosted in Amazon ECR, you must authenticate your shell session before running docker-compose. Otherwise, the images will not be able to be downloaded. Run the following command to authenticate before running docker-compose. You should only have to do this once per shell session.

+
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws
+
+

AWS credentials

+

Docker compose will pick variables set in your shell when building and launching the services. Make sure you set the correct environement variables in your shell before doing the docker compose up command. You can find more information about all the different ways of setting aws credentials in this documentation

+
export AWS_ACCESS_KEY_ID=xxx
+export AWS_SECRET_ACCESS_KEY=xxx
+export AWS_SESSION_TOKEN=xxx
+
+

Run All Services

+

The following command will build and launch all Retail Demo Store web services in your local Docker engine.

+
docker compose up --build
+
+

Run Specific Services

+

You can also choose to run specific services locally by appending the service names to the above command. For example, the following command builds and launches the products and web-ui services only. Note that some configuration of the web-ui environment will likely be needed to match your configuration.

+
docker compose up --build products web-ui
+
+

For instructions specific to each Retail Demo Store web service, view the README page in each service sub-directory.

+

Web UI Service

+

When deployed to AWS, the Web UI is hosted in an S3 bucket and served by CloudFront. For local development, you can deploy the Web UI in a Docker container. Since the Web UI makes REST API calls to all of the other services, you can configure the web-ui/.env file for which there is an example at web-ui/.env.template to point to services running either locally or deployed on AWS or a combination. Just update the appropiate environment variables to match your desired configuration.

+
+

Note

+

If you are going to work on frontend updates, instead of using docker you can run: +

npm install
+npm run dev
+
+Which makes frontend development easier

+
+

Swagger UI

+

There is a swagger-ui service in the docker-compose.yml. You can access it via localhost:8081. From there, you can select which service you want to check and send request against the service via Swagger UI.

+

The Dockerfile of swagger-ui copies OpenAPI spec from each service (located at <serviceName>/openapi/spec.yaml). If you add a new service, please ensure that you write the OpenAPI spec and update the Dockerfile to copy yours.

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+ + + + + + + + + + \ No newline at end of file diff --git a/Deployment/services/alexa/index.html b/Deployment/services/alexa/index.html new file mode 100644 index 000000000..edc32b8e3 --- /dev/null +++ b/Deployment/services/alexa/index.html @@ -0,0 +1,2124 @@ + + + + + + + + + + + + + + + + + + + + + + + Alexa Skill for C-Store Demo - Retail Demo Store - Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Alexa Skill for C-Store Demo

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For more details, including how to deploy, see workshops/5-Conversational/5.2-AlexaHandsfree.md.

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+ + + + + + + + + + \ No newline at end of file diff --git a/Deployment/services/carts/index.html b/Deployment/services/carts/index.html new file mode 100644 index 000000000..9d54ed545 --- /dev/null +++ b/Deployment/services/carts/index.html @@ -0,0 +1,2256 @@ + + + + + + + + + + + + + + + + + + + + + + + Carts Service - Retail Demo Store - Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Carts Service

+

The Carts web service provides a RESTful API for adding, changing, and deleting shopping carts. The Web UI makes calls to this service as a user adds and removes items from their cart and during checkout.

+

When deployed to AWS, CodePipeline is used to build and deploy the Carts service as a Docker container to Amazon ECS behind an Application Load Balancer. The Carts service can also be run locally in a Docker container. This makes it easier to iterate on and test changes locally before commiting.

+

Local Development

+
foo@bar:~$ docker compose up --build -d carts
+
+

Once the container is up and running, you can access it in your browser or with a utility such as Postman at http://localhost:8003.

+

Testing

+

To run integration tests for the carts service a Python virtual environment and local dynamodb is required. You must have Python 3.8+ installed on your system to run the commands below. The commands are written to be ran from the test directory of the carts service (src/carts/test).

+

Run Tests

+

To run integration tests for the carts service a Python virtual environment is required. You must have Python 3.8+ installed on your system to run the commands below. The commands are written to be ran from the test directory of the carts service (src/carts/test).

+

The following command will create a virtual environment. +

python3 -m venv .venv
+

+

Some environment variables are required to run the tests and need to be added to the virtual environment. The example below will work for local development. Change as required depending on environment. +

echo '
+export CARTS_API_URL="http://localhost:8003"
+export TEST_USERNAME="user1344"'>> .venv/bin/activate
+

+

To activate and enter the virtual environment. +

source .venv/bin/activate
+

+

To install requirements for the integration tests. +

pip install -r integ/requirements.txt
+

+

To run the tests. +

pytest integ/test_carts.py
+

+

You can exit the virtual environment with deactivate.

+

If you want to edit the request bodies for any of the PUT or POST request tests you can do so in json_request_bodies.json

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Location Service

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The location web service provides an API for retrieving store locations and +customer routes to support to Location Services demo in the Retail Demo Store. +To use the demo, see "Retail Geofencing and Location-aware Personalization" +in the in-app Demo Guide.

+

This service has two APIs. Check Swagger UI for the API details.

+

Local Development

+

The location service can be built and run locally (in Docker) using Docker Compose. See the local development instructions for details. From the ../src directory, run the following command to build and deploy the service locally.

+
foo@bar:~$ docker compose up --build location
+
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Once the container is up and running, you can access it in your browser or with a utility such as Postman at http://localhost:8008.

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Offers Service

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The Offers web service provides a RESTful API for retrieving coupons.

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To see this used, see "Retail Geofencing and Location-aware Personalization" +in the in-app Demo Guide.

+

When deployed to AWS, CodePipeline is used to build and deploy the Offers service as a Docker container to Amazon ECS behind an Application Load Balancer. The Offers service can also be run locally in a Docker container. This makes it easier to iterate on and test changes locally before commiting.

+

Local Development

+

The Offers service can be built and run locally (in Docker) using Docker Compose. See the local development instructions for details. From the ../src directory, run the following command to build and deploy the service locally.

+
foo@bar:~$ docker compose up --build offers
+
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Once the container is up and running, you can access it in your browser or with a utility such as Postman at http://localhost:8008.

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Orders Service

+

The Orders web service provides a RESTful API for creating and retrieving orders. The Web UI makes calls to this service when a user goes through the checkout process or when viewing their orders.

+

When deployed to AWS, CodePipeline is used to build and deploy the Orders service as a Docker container to Amazon ECS behind an Application Load Balancer. The Orders service can also be run locally in a Docker container. This makes it easier to iterate on and test changes locally before commiting.

+

Local Development

+

The Orders service can be built and run locally (in Docker) using Docker Compose. See the local development instructions for details. From the ../src directory, run the following command to build and deploy the service locally.

+
foo@bar:~$ docker-compose up --build orders
+
+

Once the container is up and running, you can access it in your browser or with a utility such as Postman at http://localhost:8004.

+

Testing

+

To run integration tests for the Orders service a Python virtual environment is required. You must have Python 3.8+ installed on your system to run the commands below. The commands are written to be ran from the test directory of the orders service (src/orders/test).

+

The following command will create a virtual environment. +

python3 -m venv .venv
+

+

Some environment variables are required to run the tests and need to be added to the virtual environment. The example below will work for local development. Change as required depending on environment. +

echo '
+export ORDERS_API_URL="http://localhost:8004"
+export TEST_ORDER_ID="1"
+export TEST_USERNAME="user1344"' >> .venv/bin/activate
+

+

To activate and enter the virtual environment. +

source .venv/bin/activate
+

+

To install requirements for the integration tests. +

pip install -r integ/requirements.txt
+

+

To run the tests. +

pytest integ/test-orders.py
+

+

You can exit the virtual environment with deactivate.

+

If you want to edit the request bodies for any of the PUT or POST request tests you can do so in json_request_bodies.json

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+ + + + + + + + + + \ No newline at end of file diff --git a/Deployment/services/products/index.html b/Deployment/services/products/index.html new file mode 100644 index 000000000..28f5813ef --- /dev/null +++ b/Deployment/services/products/index.html @@ -0,0 +1,2523 @@ + + + + + + + + + + + + + + + + + + + + + + + Products Service - Retail Demo Store - Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Products Service

+

The Products web service provides a RESTful API for retrieving product information. The Web UI makes calls to this service when a user is viewing products and categories and the Personalize workshop connects to this service to retrieve product information for building the items dataset.

+

When deployed to AWS, CodePipeline is used to build and deploy the Products service as a Docker container in Amazon ECS behind an Application Load Balancer. The Products service can also be run locally in a Docker container. This makes it easier to iterate on and test changes locally before commiting.

+

Local Development

+

The Products service can be built and run locally (in Docker) using Docker Compose. See the local development instructions for details. Since the Products service has a dependency on DynamoDB as its datastore, you can either connect to DynamoDB in your AWS account or run DynamoDB locally (default). The docker-compose.yml and template .env (.env.template) is already setup to run DynamoDB locally in Docker. If you want to connect to the real DynamoDB instead, you will need to configure your AWS credentials and comment the DDB_ENDPOINT_OVERRIDE environment variable since it is checked first. From the ../src directory, run the following command to build and deploy the service locally.

+
foo@bar:~$ docker compose up --build products
+
+

Once the container is up and running, you can access it in your browser or with a utility such as Postman at http://localhost:8001.

+

Alternatively, you can run the Products service directly, although you will need to setup the required environment variables (See the .env.template file mentioned above) and setup DynamoDB locally or through your AWS account.

+

From the (src/products/src) directory setup a virtual env: +

python3 -m venv .venv
+
+To activate and enter the virtual environment. +
source .venv/bin/activate
+
+Install the service dependencies: +
pip install -r requirements.txt
+
+Set the required Environment variables. For development, you can set the FLASK_CONFIG env variable to Development +
export FLASK_CONFIG=Development
+
+To run the service you can either type: +
flask run
+
+or +
python3 wsgi.py
+
+The Products service listens on port 8001, you can change this by setting the FLASK_RUN_PORT environment variable, e.g: +
set FLASK_RUN_PORT=xxxx
+

+

Initializing the Database

+

The DynamoDB tables can be created and loaded with sample data by calling the init endpoint: +

POST http://localhost:8001/init
+

+

Products API

+

The following entrypoints are supported by the Products service

+

GET /

+

Displays the service welcome page.

+

GET /products/all

+

Returns details on all products.

+

GET /products/id/{productIDs}

+

Returns details on the product(s) identified by {productIDs}. Multiple product IDs can be specified by separating each product ID by a comma. If a single product ID is specified, a single product will be returned. Otherwise, if multiple product IDs are specified, an array of products will be returned.

+

GET /products/featured

+

Returns details on all featured products. Featured products are those with featured attribute equal to true.

+

GET /products/category/{categoryName}

+

Returns details on all products within the category with the name {categoryName}.

+

PUT /products/id/{productID}

+

Updates the product identified by {productID}.

+

DELETE /products/id/{productID}

+

Deletes the product identified by {productID}.

+

POST /products

+

Creates a new product.

+

PUT /products/id/{productID}/inventory

+

Updates the current inventory value for the product identified by {productID}.

+

GET /categories/all

+

Returns details on all categories.

+

GET /categories/id/{categoryID}

+

Returns details on the category identified by {categoryID}.

+

Testing

+

To run integration tests for the Products service a Python virtual environment is required. You must have Python 3.8+ installed on your system to run the commands below. The commands are written to be ran from the test directory of the products service (src/products/test).

+

The following command will create a virtual environment. +

python3 -m venv .venv
+

+

Some environment variables are required to run the tests and need to be added to the virtual environment. The example below will work for local development. Change as required depending on environment. +

echo '
+export PRODUCTS_API_URL="http://localhost:8001"
+export TEST_PRODUCT_ID="8bffb5fb-624f-48a8-a99f-b8e9c64bbe29"
+export TEST_CATEGORY_NAME="tools"
+export TEST_CATEGORY_ID="16"' >> .venv/bin/activate
+

+

To activate and enter the virtual environment. +

source .venv/bin/activate
+

+

To install requirements for the integration tests. +

pip install -r integ/requirements.txt
+

+

To run the tests. +

pytest integ/test-products.py
+

+

You can exit the virtual environment with deactivate.

+

If you want to edit the request bodies for any of the PUT or POST request tests you can do so in json_request_bodies.json

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Recommendations Service

+

The Recommendations web service provides a RESTful API for retrieving personalized product recommendations, + related products, product reranking, and suggested discounts (powered by Amazon Personalize). + The Web UI makes calls to this service when a user is viewing the home view (recommended products), product detail view (related products), or the category view (personalized ranking of products). If Amazon Personalize campaigns have been created for these use-cases (either by the deployment Lambda option or by stepping through the Personalization workshop), then those campaigns will be called by the Recommendations service. Otherwise, the service will call the Products service to provide a suitable default behavior such as displaying featured products or products from the same category as the displayed product.

+

This service also provides support for running experiments for personalization approaches using techniques such as A/B testing, interleaving results testing, and multi-armed bandit testing. The Experimentation workshops are designed to walk you through how to setup, run, and evaluate experiments.

+

When deployed to AWS, CodePipeline is used to build and deploy the Recommendations service as a Docker container to Amazon ECS behind an Application Load Balancer. The Recommendations service can also be run locally in a Docker container. This makes it easier to iterate on and test changes locally before commiting.

+

Local Development

+

The Recommendations service can be built and run locally (in Docker) using Docker Compose. See the local development instructions for details. From the ../src directory, run the following command to build and deploy the service locally.

+
foo@bar:~$ docker compose up --build recommendations
+
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Once the container is up and running, you can access it in your browser or with a utility such as Postman at http://localhost:8005.

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Search Service

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The Search web service provides a RESTful API for retrieving product information based on a search term. The Web UI makes calls to this service when a user performs a search. Internally, this service makes calls to an OpenSearch cluster for search results. When deployed on AWS, Amazon OpenSearch Service is used. When deployed locally, a local OpenSearch node is used for searches.

+

When the Search service and Amazon OpenSearch are initially deployed to your AWS account, product information is not present in an index and therefore searches from the Web UI will not return results. There are two options for indexing products in OpenSearch when deploying to AWS. First, when deploying the Retail Demo Store project, the CloudFormation template has an option to index the product catalog in OpenSearch as part of the deployment process. The second option is to step through the Search workshop.

+

When deployed to AWS, CodePipeline is used to build and deploy the Search service as a Docker container to Amazon ECS behind an Application Load Balancer. The Search service can also be run locally in a Docker container. This makes it easier to iterate on and test changes locally before commiting.

+

Local Development

+

The Search service can be built and run locally (in Docker) using Docker Compose. See the local development instructions for details. From the ../src directory, run the following command to build and deploy OpenSearch and the Search service locally.

+
foo@bar:~$ docker compose up --build opensearch search
+
+

Once the container is up and running, you can access it in your browser or with a utility such as Postman at http://localhost:8006.

+

Indexing Products Locally

+

As explained above, when the Search service and OpenSearch are deployed, the product information does not exist in an OpenSearch index. When deploying locally, you can use the local_index_products.py script after starting the opensearch Docker container to create and load the products index.

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Users Service

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The Users web service provides a RESTful API for creating, updating, and retrieving users. The Web UI makes calls to this service when a user signs up or updates their profile.

+

When deployed to AWS, CodePipeline is used to build and deploy the Users service as a Docker container to Amazon ECS behind an Application Load Balancer. The Users service can also be run locally in a Docker container. This makes it easier to iterate on and test changes locally before commiting.

+

User Test Data

+

The Users service comes preloaded with 5,000 fake user profiles. The generate_users_json.py script was used to create these profiles. The resulting profiles data file is bundled with the Retail Demo Store deployment. Therefore, you should not need to run the generate users script under normal conditions.

+
+

The reason why so many profiles are preloaded is to support the sample sizes needed to simulate experiements in the Experimentation workshops.

+
+

Local Development

+

The Users service can be built and run locally (in Docker) using Docker Compose. See the local development instructions for details. From the ../src directory, run the following command to build and deploy the service locally.

+
foo@bar:~$ docker compose up --build users
+
+

Once the container is up and running, you can access it in your browser or with a utility such as Postman at http://localhost:8002.

+

Testing

+

To run integration tests for the Users service a Python virtual environment is required. You must have Python 3.8+ installed on your system to run the commands below. The commands are written to be ran from the test directory of the Users service (src/users/test).

+

The following command will create a virtual environment. +

python3 -m venv .venv
+

+

Some environment variables are required to run the tests and need to be added to the virtual environment. The example below will work for local development. Change as required depending on environment. +

echo '
+export USERS_API_URL="http://localhost:8002"
+export TEST_USER_ID="1"
+export TEST_USERNAME="user1"
+export TEST_IDENTITY_ID="eu-west-1:12345678-1234-1234-1234-c777c9720775"
+export TEST_PRIMARY_PERSONA="tools"
+export TEST_AGE_RANGE="18-24"' >> .venv/bin/activate
+

+

To activate and enter the virtual environment. +

source .venv/bin/activate
+

+

To install requirements for the integration tests. +

pip install -r integ/requirements.txt
+

+

To run the tests. +

pytest integ/test-users.py
+

+

You can exit the virtual environment with deactivate.

+

If you want to edit the request bodies for any of the PUT or POST request tests you can do so in json_request_bodies.json

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+ + + + + + + + + + \ No newline at end of file diff --git a/Deployment/services/videos/index.html b/Deployment/services/videos/index.html new file mode 100644 index 000000000..2a43c4e15 --- /dev/null +++ b/Deployment/services/videos/index.html @@ -0,0 +1,2237 @@ + + + + + + + + + + + + + + + + + + + + + + + Videos Service - Retail Demo Store - Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Videos Service

+

The Videos service streams product videos and synchronised metadata to Amazon Interactive Video Service and provides stream metadata (stream endpoints and products contained within the stream) via a Flask API. The Web UI makes calls to the service when a user views the 'Live' view. The endpoint provides a list of stream ingest endpoints, each with a list of their associated products, allowing the UI to present all products from the video before they appear in the stream.

+

When deployed to AWS, CodePipeline is used to build and deploy the Videos service as a Docker container to Amazon ECS behind an Application Load Balancer. The Videos service can also be run locally in a Docker container. This makes it easier to iterate on and test changes locally before commiting.

+

Deploying Channels & Streaming Video

+

IVS channels are created and managed by the CloudFormation template. The default CloudFormation settings do not create any new IVS streams - instead the demo directs the UI to four externally hosted IVS streams.

+

To create and use IVS channels hosted in your own account, the option 'Use default IVS streams' should be set to 'No' when deploying CloudFormation. In this case, one IVS channel will be created for each '.mkv' video found in the videos/ path of the staging S3 bucket. These videos should be uploaded by running the provided staging script - any videos in the local videos/ directory will be uploaded.

+

IMPORTANT: Amazon IVS is currently only supported in the N. Virginia (us-east-1), Oregon (us-west-2), and Ireland (eu-west-1) regions. Therefore, to deploy the Retail Demo Store in a region that does not support IVS, be sure to select to use the Default IVS Streams CloudFormation template parameter.

+

Custom Videos & Metadata

+

To enable full UI integration with custom videos, metadata must be embedded into the .mkv file.

+

Metadata must be created in the .srt format, with each timestamped entry containing data in the form: +{"productId": <PRODUCT_ID>}. The Videos service sends the metadata at the start of the timestamp. The latter section of the timestamp is not used. The file can either be edited manually or using an SRT editor (either software or online). An example metadata file can be seen here.

+

This metadata can then be combined with a video file to create an encoded .mkv file with embedded metadata by running the following command: +

ffmpeg -i <INPUT_VIDEO_PATH> -i <INPUT_METADATA_PATH>.srt -vf scale=640x360 -c:v libx264  \
+-pix_fmt yuv420p -profile:v main -tune fastdecode -x264opts “nal-hrd=cbr:no-scenecut” -minrate 3000 \
+-maxrate 3000  -g 60 -c:a aac -b:a 160k -ac 2 -ar 44100 <OUTPUT_FILE_PATH>.mkv
+
+An .mkv file created with this command is ready to be staged and should provide optimal UI integration. +The command also pre-encodes the video in a format designed to reduce the CPU & memory requirements of the Videos service.

+

Local Development

+

The Videos service can be built and run locally (in Docker) using Docker Compose. See the local development instructions for details. From the ../src directory, run the following command to build and deploy the service locally.

+
foo@bar:~$ docker compose up --build videos
+
+

Once the container is up and running, you can access it in your browser or with a utility such as Postman at http://localhost:8007.

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Troubleshoot

+

Known Issues/Limitations

+
    +
  • The application was written for demonstration and education purposes and not for production use.
    • +
  • You currently cannot deploy this project multiple times in the same AWS account and the same AWS region. However, you can deploy the project into separate supported regions within the same AWS account.
    • +
  • Make sure your CloudFormation stack name uses all lowercase letters.
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  • Currently only tested in the AWS regions provided in the deployment instructions above. The only limitation for deploying into other regions is availability of all required services.
      +
    • Amazon IVS is currently only supported in the N. Virginia (us-east-1), Oregon (us-west-2), and Ireland (eu-west-1) regions. Therefore, to deploy the Retail Demo Store in a region that does not support IVS, be sure to select to use the Default IVS Streams CloudFormation template parameter.
      • +
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+

Troubleshooting / FAQs

+

Q: When accessing the Retail Demo Store web application after deploying the project, a CloudFront error is displayed. What's wrong?

+

A: Sign in to the AWS account/region where the project was deployed and browse to CodePipeline. Verify that the pipeline with "WebUIPipeline" in the name has successfully been built. If it failed, inspect the details of the Build stage to diagnose the root cause.

+

Q: When accessing the Retail Demo Store web application after deploying the project, the home page shows spinning icons and products are never loaded. What's wrong?

+

A: The most likely cause is an error building or deploying one or more of the microservices. Sign in to the AWS account/region where the project was deployed and browse to CodePipeline. Verify that all of the Retail Demo Store pipelines have completed successfully. Inspect the details for any that have failed to determine the root cause. Sometimes just manually triggering a build/deploy will resolve the issue.

+

Q: This project is expensive to run (or keep running). How can I reduce the running cost of a deployment?

+

A: The most costly service in the project for an idle deployment is Amazon Personalize. You can eliminate Personalize idle costs by stopping all Amazon Personalize recommenders and deleting all campaigns in the Retail Demo Store dataset group for Personalize. This just shuts down the real-time inference endpoints; the datasets and ML models will remain. You should also change all of the recommender and campaign ARN parameter values in the AWS Systems Manager Parameter Store to NONE, leaving the parameter values for filters and the event tracker alone. These parameter names start with /retaildemostore/personalize/ (e.g., /retaildemostore/personalize/recommended-for-you-arn). Once you complete these steps, the storefront will fall back to default behavior for recommending products from the catalog. To reactive Personalize, start the recommenders and create campaigns and then set the recommender and/or campaign ARNs back in the Systems Manager Parameter Store. The storefront will automatically start showing recommendations from Personalize again.

+

Reporting Bugs

+

If you encounter a bug, please create a new issue with as much detail as possible and steps for reproducing the bug. See the Contributing Guidelines for more details.

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Datasets

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The Retail Demo Store uses all three supported dataset types +for Amazon Personalize: users, items, and interactions. Additionally, an Amazon Personalize Event Tracker is +utilized to capture real-time events in the web user interface which populate the Personalize-managed event +interactions dataset. AWS Amplify is used to send events to the Retail Demo Store’s Personalize Event Tracker.

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With the exception of the real-time event data which is created as a result of your browsing behavior in the web +user interface, the data in the users, items, and interactions datasets are composed of fictitious, or in the case +of interactions history, synthetically generated data.

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Enabling Shopper Profiles

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With Amazon Personalize Solutions and Campaigns created based on the generated users, items, and interactions +datasets, we can emulate (or assume) user profiles for different personas in the web user interface to see +recommendations that should be consistent with the persona. In order to emulate a profile, you must first sign in +to the user account you created for yourself.

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Once signed in, you'll see the shopper assigned to you on the top +right corner. You can switch the shopper at any time by clicking the name of the user and selecting the "Switch +shoppers" option.

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Personalized Product Descriptions

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Generative AI can be used to automate the creation of marketing content. This includes generating text for blogs, social media posts, and emails, as well as creating images and videos. +This can save marketers a significant amount of time and effort, allowing them to focus on other aspects of their marketing strategy.

+

Where it really shines is the ability to productionize marketing content creation, reducing the needs for marketers to create multiple copies for different customer segments. +Previously, marketers would need to generate many different copies for each granularity of customers (e.g. attriting customers who are between the age of 25-34 and loves food). +Generative AI can automate this process, providing the opportunities to dynamically create these contents.

+

This demo integrates the product service with Amazon Bedrock, to retrieve personalized product descriptions based on the logged-in user's age and interests.
+Amazon Bedrock makes Foundation Models (FMs) accessible via an API, and in this demo, Anthropic Claude v2 is the underlying FM used.

+

The prompt used to generate personalised product descriptions takes the following form:

+
  I'd like you to rewrite the following paragraph using the following instructions:
+  "{instructions}"
+
+  "{original product description}"
+
+  Please put your rewrite in &lt;p>&lt;/p> tags.
+
+

The instructions used are:

+
Please generate an enhanced product description personalised for a customer aged {age range}, interested in {interests}.
+However, do not mention their age in the rewrite.
+The product is named "{product name}" and is a product of type "{product type}" in the {product category} category.
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Room Makeover

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Imagine being able to instantly re-imagine a room in different decor styles. +This demo combines Stable Diffusion, Amazon Sagemaker, Amazon Bedrock and Amazon Rekognition to enable an innovative approach to generating re-styled rooms from an initial user uploadedimage.

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  1. The user authenticates with Amazon Cognito and obtains an identity token. This is passed through to all subsequent API requests to the API Gateway.
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  2. User selects a room image through the browser and the Web UI uses AWS Amplify Storage module to upload to S3.
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  3. The Web UI calls the API Gateway, passing in the S3 location of the uploaded image and the selected room style, to create a room generation request. A unique id is returned that can beused to retrieve the results.
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  4. The API Gateway uses a Lambda authorizer to validate the supplied identity token. It then proxies the request through to a Lambda function that validates and then persists the requestinto DynamoDB.
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  5. DynamoDB streams captures the newly inserted room request.
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  6. A lambda function triggers on each new record in the stream and starts an AWS Step Function to process the request.
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  7. The first step of the step function performs image analysis on the uploaded room image. The output of the step is a prompt that can passed to the Stable Diffusion model.
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    • Amazon Rekognition is used to detect objects in the image – such as sofa’s, chairs, and tables. It returns a list of objects, together with their associated bounding boxes.
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    • For each object detected, a cropped image is created using the bounding box coordinates.
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    • Each image is then converted into a base64 string and sent as a request to Amazon Bedrock to use the Titan Multimodal Embeddings G1 model to obtain an embedding representation of the image.
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    • For each embedding, a K-NN request is made to the Amazon OpenSearch service to obtain the closest product matches. The product match will also contain a caption – pre-generated by Anthropic’s Claude 3 Haiku model. The caption was generated by passing the product and prompting Claude 3 to describe what’s in the picture.
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    • To create the final prompt, an initial base prompt is looked up using the style selected by the customer, which is then combined with the top matching product’s captions using prompt weighting.
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  8. The uploaded room image and prompt are sent to the SageMaker Asynchronous Inference Endpoint. The Step Function pauses at this point until the inference process completes – implementedusing a callback task token.
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  9. The SageMaker Endpoint is deployed as a HuggingFace Deep Learning Container, which hosts a custom Stable Diffusion model that uses ControlNet to add depth conditioning of the uploadedimage to 1. the generation. When the model completes the inference process, it places the result in an S3 bucket and sends a notification to an Amazon SNS topic containing the location ofthe result 1. payload.
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  10. Amazon SNS invokes the Lambda function that is subscribed to the topic. The Lambda function calls-back into the Step Function to resume the process.
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  11. The final step of the Step Function loads the inference result, extracts the generated image, and places it in the bucket for the customer to access. The final image is also re-analyzedfollowing the process in step 7, so that new bounding boxes and similar products are retrieved.
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  12. The Web UI has been polling the API Gateway using the unique ID obtained from the initial request. The room generation response is updated throughout the process. A done state is returned, together with a reference to the final room image, which indicates to the frontend to render the results. The Amplify Storage API is used to generate a signed URL, so that theimage can be downloaded from S3.
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Pre-processing the product images

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The first step of the step function performs image analysis on the uploaded room image. The output of the step is a prompt that can passed to the Stable Diffusion model.

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  1. A S3 Batch Operations Job executes on the product images bucket and triggers a Lambda function for each image.
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  2. Lambda function resizes the product image and places resulting image in separate bucket.
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  3. Lambda function triggers on S3 create event in bucket.
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  4. Lambda function starts execution of express workflow to process image.
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  5. Embedding for image are retrieved using Titan Multimodal Embeddings model through Amazon Bedrock.
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  6. Product captions – descriptions of what the product image contains – are created by calling Anthropic Claude 3 Haiku model through Amazon Bedrock.
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  7. Embedding and caption are published to SQS.
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  8. Lambda function receives batches of captions & embeddings and indexes them into Amazon OpenSearch.
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The prompt used with the Claude 3 Haiku model to generate the product captions was as follows:

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Identify the {category} product in the image. Then identify the dominant color or colours of the {category} product. Be descriptive. Ignore the background. Name the product and then describe it without any preamble.
+&lt;example&gt;Sofa, deep, plush green color with a smooth, velvet-like texture. It features a rectangular shape with a modern, streamlined silhouette and two cylindrical cushions at either end, serving as armrests. The sofa has three seat cushions that create a single seating surface without separations, and the back cushion runs the length of the sofa in a single piece as well, contributing to its sleek design. There are no visible patterns or prints on the fabric, which gives it a rich, uniform look. The sofa's legs are short, cylindrical, and appear to be made of light-colored wood&lt;/example&gt;
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Retail Geofencing and Location-aware Personalization with Amazon Location Services

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Amazon Location Services is an Amazon provision of maps, location indexing, geofencing, user tracking, and routing. Geofencing can be used to set off chains of events just when they need to be set off - when your customer is in the right place, at the right time. In this demo we use it together with the ecommerce platform and Amazon Pinpoint to engage customers when they approach physical stores.

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Customers are inspired to opt in to share their location by being provided with personalized offers. These offers can be related to customer preferences, local stock levels, and more. In this demo we use Amazon Personalize to select an offer to show to a consumer that can be redeemed in-store. The consumer has the extra convenience and we have enaged with them in a targeted fashion and, moreover, attracted them into our bricks and mortar store where the experience will be, naturally, more personal than online.

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There is also an in-store interface that shows a sample view for store staff showing orders that are about to be collected, and transactional messaging for user and store staff around pickup that is triggered by the user approaching the store for pickup.

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Using the Location Services Demo

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To use the Amazon Location functionality, Location Services must be enabled in your region. First, ensure you are deploying Retail Demo Store in a region in which Location is enabled. Next, enable "Deploy Location Services resources" and "Deploy personalized offers and pickup notices using Location Services geofencing" when deploying or updating the solution from CloudFormation. A Location geofence will be set up for you.

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From any Retail Demo Store "Shop" menu You can access the Location "In-Store View" where you can see orders made to be collected from in-store. From there you can navigate to "Location Geofence" where you can see the Location Services-provided map and simulated user - from here you can initiate simulations of users travelling close to the default configured store either during a scenario where Location Services can be used to enable a quick collection of bought products and related messaging using Pinpoint Transactional Messaging to email, SMS or web ("collection" scenario), or where the user might be inspired to enter the store to make a new purhcase through the triggering of personalised messages sent using Pinpoint Campaigns to email, SMS and web, either containing offers chosen with Amazon Personalize or containing notices about unfinished shopping carts ("purchase" scenario).

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Enable email sending.

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If you are in the email "sandbox" for Pinpoint, then all recipient emails must be verified according to the below process, to ensure that the emails will be sent.

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  • After deploying the demo, navigate to your Pinpoint application called "retaildemostore" in the UI Console (https://console.aws.amazon.com/pinpoint/home making sure that the region is the same one in which you deployed your demo).
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  • Click on "Settings" > "Email" in the navigation menu.
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  • Under the "Identities" tab, click "Edit".
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  • Ensure the email channel for the project is set to "Enabled" (this will be set after Amazon Personalize campaigns are finished deploying, but you may set it beforehand).
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  • For the email that you used when you deployed the solution under "Reply-To email address", ensure that the email address is verified. Select this as your "Default sender address".
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  • For every email to which you plan to send emails, ensure that the email address is verified.
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  • Save the changes.
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Note that you can manage your email and SMS limits within the "Settings" > "Email" and "Settings" > "SMS and voice" menus available under your Pinpoint project. Also note that there are additional limits imposed when your account is in the Pinpoint "sandbox". +Enable SMS sending.

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Ensure any phone number in the Pinpoint database to which you intend to send promotional messages (the "purchase" journey above - for the "collection" journey, the phone number will be recorded against the order) has opted in to receive promotional messages. For more information on how to ensure this, see the "Two-Way SMS with Pinpoint" section in the Pinpoint messaging workshop. In brief, you need to (in the USA):

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  • Subscribe to a long-code that supports SMS through the Pinpoint UI so that Pinpoint has a number to send messages from (this is a requirement in the USA to send messages).
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  • Enable 2-way messaging on that long-code and choose the SNS PinpointIncomingTextAlerts topic that was deployed along with Retail Demo Store to send messages to, so that responses to verification SMS messages can be processed to opt in users.
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Personalized Emails: Welcome and Abandoned Cart

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Amazon Pinpoint enables organizations to deliver messages across email, text, mobile push, voice, and custom +channels like messenger apps and retail apps. These messages can be augmented with data output from ML services +like Amazon Personalize for Personalization, Recommendations, Next-Best-Actions, among other use cases. User +attributes from Amazon Personalize can be selected within the Amazon Pinpoint console or API in order to +personalize the content of email templates in real-time. Importantly, this enables organizations to deliver a +unified, omni-channel personalization experience.

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Here,

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    Pinpoint sends new users a welcome email after they sign up for a Retail Demo Store account. Check the email +entered during account creation and look for the Retail Demo Store welcome email. If you’d like to send the +email to a different email address, go to the Account settings page and enter the new one.

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    When Retail Demo Store users add items to their shopping cart but do not complete an order, Amazon Pinpoint +send an email with a coupon code encouraging them to finish their order. To see this feature, add a few items +to your shopping cart. In the shopping cart page, click on the button that says ”Trigger Abandoned Cart +email”. This action will emulate a signed out event and will trigger the abandoned cart email sent by Amazon +Pinpoint. Next, check the email account provided during account creation. The Abandoned Shopping Cart email will be in your +inbox.

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Text Messaging (SMS): Personalized Alerts and Promotions

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Amazon Pinpoint has deep configuration options for SMS (text) messaging and can deliver messages to every country +in the world. Retail / eCommerce organizations have many use cases for text messaging - including transactional +uses like purchase confirmations and marketing uses like promotions. These messages can be augmented with data +output from ML services like Amazon Personalize for Personalization, Recommendations, Next-Best-Actions, among +other use cases. User attributes from Amazon Personalize can be selected within the Amazon Pinpoint console or API +in order to personalize the content of templates in real-time. Importantly, this enables organizations to deliver +a unified, omni-channel personalization experience.

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This demo showcases personalized product recommendation via text message. Try this feature by opting-in to receive +text alerts.

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Enable SMS sending for the USA.

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In the USA it is a legal requirement that you subscribe to a phone number or +long code in order to be able to send text messages and receive them. +If you have not followed the Pinpoint messaging workshop to enable +messaging, but you set "Auto-Configure Pinpoint" to "Yes" when you deployed +the demo, you are almost set up. The following steps show how you can finish set-up:

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  1. Subscribe to a long-code or phone number that supports SMS through the Pinpoint UI so that Pinpoint has a number to send messages from.
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    1. Go to your Pinpoint AWS console in the region into which Retail Demo Store is deployed.
      2. +
    2. Choose "Settings ... SMS" or "Settings... Voice and SMS"
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    3. Click "Request phone number", choosing "United States" for the country.
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    4. Ensure the number type is "Toll-free" and that "SMS" option is checked.
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    5. Click "Next" then "Request".
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  2. Enable two-way SMSs to enable Retail Demo Store to receive messages sent to the dedicated number and opt in users.
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    1. Go back to "Settings ... SMS" or "Settings... Voice and SMS"
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    2. Click on your newly registered phone number under "Number settings"
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    4. Under "Incoming messages destination" click "Choose an existing SNS topic" and choose the topic that contains the text "PinpointIncomingTextAlertsSNSTopic" which was put there by CloudFormation when you deployed your store.
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  3. Tell Retail Demo Store about the phone number you have acquired.
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    1. So that Retail Demo Store can make use of the dedicated number you acquired above, take note of the number and navigate to Systems Manager AWS console in the region Retail Demo Store is deployed.
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    2. Find the parameter named "retaildemostore-pinpoint-sms-longcode" and click on "edit", then enter the value for your dedicated the phone number (including the country code as in +11234567890). You may also enter this information when deploying Retail Demo Store with CloudFormation.
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Opt in for text alerts.

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The home page, shopping cart page and every product page in the store include a field to opt-in. Enter the mobile phone number where you’d like to receive the one-time automated marketing message.

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You will receive a text message to confirm the subscription. Reply “Y” to confirm. Upon confirmation, you’ll receive a 20% discount code.

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Next, you’ll receive one text message with one personalized product recommendation. The message will include a URL that will redirect you to the Retail Demo Store

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Real-Time User Segmentation

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Amazon Pinpoint enables organizations to create user segments - or groups of customers - based on their behavior +across web/mobile applications, interactions over email, text, push notifications, and other channels, or based on +stored data. This is important in retail environments because customers deliver valuable intent data across +in-store, e-commerce, and customer engagement channels. Pinpoint enables organizations to create a single event +bus of all these interactions to inform segmentation, personalized messaging, and analytics.

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These segments can often be created and responded to in real-time. Here, your clickstreams in the Retail Demo +Store application are ingested by Amazon Pinpoint to create new user segments in real-time. These segments are +then used to deliver the targeted messages that receive throughout the demo.

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AWS Messaging And Targeting Blog

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“We want to send messages through dynamic segmentation.When we send a push notification, we need to +dynamically segment immediately. When we call AmazonPinpoint to say “Create this segment right now, for +this game event that’s happening right now, and thencreate this campaign right now, and then send it, and +Pinpoint does all of that in milliseconds.”

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Read full AWS Messaging & Targeting Blog post: +How Disney Streaming Services Uses Amazon Pinpoint to Send Personalized Messages to Millions of Users in Real Time

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Personalization

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Personalized user experiences are implemented across several features within the Retail Demo Store web user interface that demonstrate three core use-cases of Amazon Personalize as well as real-time recommendations.

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In order to demonstrate the personalization capabilities of the Retail Demo Store, the required Amazon Personalize Solutions and Campaigns must already be created and enabled via Amazon SSM Parameters. These Solutions and Campaigns can be created as part of the Personalization workshop bundled with the Retail Demo Store or automatically when the Retail Demo Store is deployed via CloudFormation. If you’re demonstrating with the Retail Demo Store this should already be done for you but still good to be aware if personalization features are not working as expected.

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Datasets

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The Retail Demo Store uses all three supported dataset types for Amazon Personalize: users, items, and interactions. Additionally, an Amazon Personalize Event Tracker is utilized to capture real-time events in the web user interface which populate the Personalize-managed event interactions dataset. AWS Amplify is used to send events to the Retail Demo Store’s Personalize Event Tracker.

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With the exception of the real-time event data which is created as a result of your browsing behavior in the web user interface, the data in the users, items, and interactions datasets are composed of fictitious, or in the case of interactions history, synthetically generated data.

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Shopper Personas

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To provide a more compelling and intuitive demo experience, each fictitious user in the Retail Demo Store is assigned a shopper persona. The persona is represented by three categories from the Retail Demo Store’s catalog which the user has an affinity. The affinity for each category is also weighted such that the first category is is highest weighted and the third category is the lowest. There are 16 combinations of categories that represent the personas used across all users.

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  • furniture_homedecor_housewares
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  • apparel_footwear_accessories
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For example, a user assigned with a persona of "footwear_jewelry_furniture" indicates that the user, at least historically, has been primarily interested in products from the Footwear category and to decreasing degrees of interest in products from the Jewelry and Furniture categories. That initial weighted interest is codified in the generation of the historical interaction dataset which is used to train Solutions in Amazon Personalize. So, for our "footwear_jewelry_furniture" user, interaction events are generated across products in all three of those categories to create a synthetic history of engaging in products matching that persona. Additionally, some products are tagged with an gender affinity. This is used when generating historical events to filter products against the gender of each user to further add realism to the recommendations.

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Events for multiple event types are generated to mimic shopping behavior. For example, most generated event types are 'View' to mimic users browsing the site. Occasional checkouts are simulated with 'AddToCart' followed by 'ViewCart', 'StartCheckout', and 'Purchase' events. The Personalize solutions/models are trained on the 'View' event type.

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Emulating Shopper Profiles

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With Amazon Personalize Solutions and Campaigns created based on the generated users, items, and interactions datasets, we can emulate (or assume) user profiles for different personas in the web user interface to see recommendations that should be consistent with the persona. In order to emulate a profile, you must first sign in to the user account you created for yourself as described in Creating a Retail Demo Store account. Once signed in, you can click on your username in the top right-corner and then select Switch Shoppers.

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Figure 7. Access Profile Page.

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You can have a shopper auto-selected for you or you can choose your own. In the shopper selection window, specify an age range and a primary shopping interest. Click Submit and a closely matching shopper is shown, confirm your choice or try again. Product recommendations should now match the persona of the shopper you've selected.

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It is recommended to open a new Incognito (Chrome) or Private (Firefox) browser window when testing personalization features of the web UI. The reason for this is because Amplify keeps all of your events tied to the same logical session. Signing out and back in as a different account does not change this behavior. You must close and reopen Private/Incognito windows to switch between profiles.

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Use-Case 1: Personalized Product Recommendations

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Amazon Personalize Recipe: User-Personalization

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The user personalization use-case is implemented on the bottom half of the Retail Demo Store home view when you are signed in to a Retail Demo Store user account. Be sure to emulate a shopper profile as described above so that a persona is linked to your session. Product recommendations in the “Inspired by your shopping trends” section are being powered by Amazon Personalize. If you’re not signed in, featured products will be displayed here instead.

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Since the Retail Demo Store is using a Personalize Event Tracker to record real-time interaction events, it is important to keep in mind that recommendations will change as a result of your clicking and browsing activity in the web application. Therefore, the recommendations may not match up to the original shopper persona used to train the model. This is a powerful demo feature, though, since it shows how Personalize adapts to evolving user intent. It can also show how recommendations adapt for new users (i.e. cold starting users).

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Figure 8. User recommendation use-case.

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Amazon Personalize Recipe: SIMS

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The related products use-case is implemented on the product detail page in the Retail Demo Store. Since inference calls to campaigns built with the SIMS recipe do not require a user, we are able to display related products using SIMS whether you are signed in as a user or anonymous.

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Figure 9. Related products use-case.

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Use-Case 3: Personalized Product Ranking

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Amazon Personalize Recipe: Personalized-Ranking

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When you are signed in as a Retail Demo Store user, the personalized ranking use-case is implemented on the category view in the Retail Demo Store. When you are an anonymous user, products are displayed in their natural order (i.e. not ranked). The most effective view to demonstrate this use-case is on the “Featured” product view. The reason for this is that this is the one category view that includes products from multiple categories. Therefore, the ranking should be more impactful.

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Figure 10. Personalized Ranking use-case.

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You can also see personalized ranking in product search results. That is, if you are signed in as a user, search results are reranked based on the user's historical and real-time activity.

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Event Tracking

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The following semantic interaction event types are instrumented in the Retail Demo Store web user interface. Each time a user (anonymous or known) performs one the following actions, an event is sent to both Amazon Pinpoint (signed in only) and an Amazon Personalize Event Tracker (if configured).

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To assess the impact of real-time event tracking in recommendations made by the user recommendations on the home page, follow these steps.

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  1. Sign in as (or create) a storefront user.
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  2. View the product recommendations displayed on the home page under the "Inspired by your shopping trends" header. Take note of the products being recommended.
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  3. View products from categories that are not being recommended by clicking on their "Details" button. When you view the details for a product, an event is fired and sent to the Personalize event tracker.
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  4. Return to the home page and you should see products being recommended that are the same or similar to the ones you just viewed.
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Event Instrumentation

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If you are demonstrating the Retail Demo Store to a more technical audience, you can illustrate how the events are sent to Pinpoint and Personalize in the background. To do so, open up the Developer Tools in the web browser you’re using (i.e. Chrome), select the Network view, and find the calls to “events” (Personalize) and “legacy” (Pinpoint). The screenshot below illustrates how to display the network call to the Personalize Event Tracker for the “put_events” endpoint. This is implemented using AWS Amplify to instrument events in the web user interface.

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Figure 11. Event instrumentation calls

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Filtering Recommendations

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Amazon Personalize supports the ability to create filters that can be used to filter (or exclude) items from being recommended that match a filter's criteria. The Retail Demo Store uses a filter to exclude products which have been recently purchased by the current user.

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As noted in the Event Tracking section above, the Retail Demo Store's web application sends an Purchase event for each product purchased by the user. We can use this event type in the following filter expression.

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The filter is created using the CreateFilter API. When a filter is created, a Filter ARN is generated which can then be used when retrieving recommendations to apply the filter.

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To demonstrate this capability, purchase one or more recommended products from the "Inspired by your shopping trends" section of the home page by adding them to your cart and checking out. Then return to the home page. The product(s) you just purchased should no longer be recommended.

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Batch Recommendations

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While real-time recommendations are highly recommended, Amazon Personalize does support batch recommendations. +Batch recommendations let you generate personalized recommendations for a large number of users, or similar items +for a large number of items, in one go, and then use them in batch processes, such as sending emails or +notifications.

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Batch recommendations

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AWS News Blog

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Batch Recommendations in Amazon Personalize

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Customers Who Viewed X Also Viewed

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Related item recommendations help users discover new products or compare existing items in your catalog. Amazon +Personalize recommends similar items in real-time, based on user behavior to create unique, relevant experiences +for your customers.

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Pretty simple idea, implemented via item-item collaborative filtering but basically look at how people are +interacting with particular products and then determine how similar things are at a global level based on that data. +Not user specific at all.

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What data should I provide?

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Amazon Personalize recognizes three types of historical data:

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  • Users – This data is intended to provide information about your users such as age, gender, or loyalty membership +which can be important signals in personalization systems.
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  • Items – This data is intended to provide information about your items, such as their description, price, SKU type, or + availability. In the case of unstructured text such as product descriptions, Personalize will use ML-based + natural language processing (NLP) to extract key information about your products to provide more relevant recommendations.
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  • Interactions – This data is historical interactions between users and items. It can also provide information on + your user's browsing context, such as their location or device (mobile, tablet, desktop, and so on).
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The user and item data are metadata types and only used in certain use cases. Please see the documentation +for further technical details.

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Each type of data that Amazon Personalize recognizes has required fields, reserved keywords and datatypes. Please +see table below for details.

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Amazon Personalize will train and deploy a model based on this data. Developers can then use a simple inference +API to get individualized recommendations at run-time and generate a personalized experience for the end users +according to the type of personalization model (e.g. user personalization, similar items or personalized +rankings). Amazon Personalize works best for large datasets that have over 50 users, 50 items, and 1500 +interactions.

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Frequently Bought Together

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Amazon Personalize Recipe: Frequently-Bought-Together

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A common cross-selling technique on e-commerce sites is recommending items that other users have frequently bought together. The idea +is to encourage users to add more products to their shopping cart and thereby increasing average order value and the bottom line. Amazon +Personalize implements this use case with the Frequently Bought Together retail recommender. This recommender can be deployed as part of your +shopping cart or checkout views or when users add new items to their cart.

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Machine Learning User Segmentation

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Amazon Personalize Recipes:

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Item-Affinity +Item-Attribute-Affinity

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Traditionally, user segmentation depends on demographic or psychographic information to sort users into predefined audiences. +More advanced techniques look to identify common behavioral patterns in the customer journey (such as frequent site visits, +recent purchases, or cart abandonment) using business rules to derive users' intent. These techniques rely on assumptions about +the users' preferences and intentions that limit their scalability, don't automatically learn from changing user behaviors, and +don't offer user experiences personalized for each user. User segmentation in Amazon Personalize uses ML techniques, developed +and perfected at Amazon, to learn what is relevant to users. Amazon Personalize automatically identifies high propensity users +without the need to develop and maintain an extensive and brittle catalog of rules. This means you can create more effective user +segments that scale with your catalog and learn from your users' changing behavior to deliver what matters to them.

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The Amazon Personalize User Segmentation recipes are simple to use. Provide Amazon Personalize with data about your items and your +users' interactions and Amazon Personalize will learn your users' preferences. When given an item or item-attribute Amazon Personalize +recommends a list of users sorted by their propensity to interact with the item or items that share the attribute.

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Some common retail use cases for user segmentation include marketing campaigns to promote excess inventory or new items added to a catalog. +With the Item-Affinity recipe, you can create segments of users with an affinity for existing items with excess or lazy inventory. +With the Item-Attribute-Affinity recipe, you can create segments of users with an affinity for new items based on their bahavior with +existing items with similar attributes.

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You can read more about User Segmentation on the .

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This project comes with a step-by-step workshop that will guide you through how to build an item attribute affinity custom solution and +run a batch segmentation job that will generate user segments based on affinity for product categories.

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Metrics and understanding impact

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You can measure the performance of ML recommender systems using offline and online metrics.

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Online metrics are the empirical results observed in your user’s interactions with real-time recommendations +provided in a live environment.

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Offline metrics allow you to view the effects of modifying hyperparameters and algorithms used to train your +models, calculated against historical data.

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Amazon Personalize generates offline metrics using test datasets derived from the historical data you provide. +These metrics showcase how the model recommendations performed against historical data. Offline metrics are a +great representation of how your hyperparameters and data features influence your model’s performance against +historical data. To find empirical evidence of the impact of Amazon Personalize recommendations on your business +metrics, such as click-through rate, conversion rate, or revenue, you should test these recommendations in a live +environment, getting them in front of your customers.

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AWS Machine Learning Blog

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Using A/B testing to measure the efficacy of recommendations generated by Amazon Personalize

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Machine learning (ML)-based recommender systems aren’t a new concept, but developing such a system can be a +resource-intensive task—from data management during training and inference, to managing scalable real-time +ML-based API endpoints. Amazon Personalize allows you to easily add sophisticated personalization +capabilities to your applications by using the same ML technology used on Amazon.com for…

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Read more

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AWS Partner Network (APN) Blog

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Measuring the Effectiveness of Personalization with Amplitude and Amazon Personalize

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This post will present an architecture that combines Amazon Personalize and Amplitude’s product +intelligence platform to track user behavior in real time.

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It’ll also show how to deploy a sample e-commerce application in your Amazon Web Services (AWS) account, +which includes a self-guided workshop created by Amplitude to help you become familiar with its +capabilities...

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Omni-Channel Personalization & ML Model Retraining

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By connecting Amazon Pinpoint with Amazon Personalize (or other ML services), organizations can take their +customers’ interactions across channels and feed them into their foundational Personalization models for +omni-channel ML model retraining.

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This enables organizations to utilize all of their customers’ digital interactions within a centralized ML model +to get smarter, faster. This also enables organizations to deliver personalized experiences in an omni-channel +fashion, meaning the experiences are harmonized and responsive across their channels of engagement.

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Case Study

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dominos

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Domino's Pizza Enterprises Ltd (DPE) is one of the largest pizza businesses in the world; their vision is to +be the leader in deliveries in every neighborhood.

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"The customer is at the heart of everything we do at Domino's and we are working relentlessly to improve and +enhance their experience. Using Amazon Personalize, we are able to achieve personalization at scale across +our entire customer base, which was previously impossible. Amazon Personalize enables us to apply context +about individual customers and their circumstances, and deliver customized communications such as special +deals and offers through our digital channels."

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Read full Domino's Pizza’s case study: +Domino’s Pizza Enterprises Delivers in Record Time Using AWS for Predictive Ordering

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Personalized Ranking

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Amazon Personalize Recipe: +Personalized-Ranking

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Regularly your business priorities require you to promote specific content or products, such as trending news, a +hit new TV show, seasonal merchandise, or a time bound promotional offer. Whether the source is a person, business +rules around product lifecycle management, or a line of code, Amazon Personalize enables you to re-rank your +product catalog to achieve your business priorities and best customer experience.

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Uses the same HRNN algorithm underneath User-Personalization but takes in a user AND a collection of items. This +will then look at the collection of items and rank them in order of most relevant to least for the user. This is +great for promoting a pre-selected collection of items and knowing what is the right thing to promote for a +particular user.

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You can see the personalized ranking use-case on the on the “Featured” products view. The products are re-ranked +based on the fictitious shopper's historical and real-time activity.

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Best Sellers: Popular by Purchases

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Amazon Personalize Recipe: +Popular-by-Purchases

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Recommends best selling products based on how many times customers have purchased an item. The best selling items have the most +"Purchase" interactions with unique users. The recipe returns the same best selling items for all users. Therefore, recommendations are +not personalized to the individual user and are useful when you want a system-wide representation of what's selling across the site.

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You may notice some items are annotated with a "Promoted" banner across the top of the product image. This banner indicates +products that match a promotional filter that is optionally applied when retrieving recommendations. Promotional filters are +a great way to ensure that a user-defined percentage of recommended items match a specific filter expression but are also +relevant to the user. This can be used to highlight products on sale or new products recently added to the catalog.

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Amazon Personalize Recipe: +Popular-by-Views

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Recommends popular products based on how many times customers have viewed an item. The most popular items have the most +"View" interactions with unique users. The recipe returns the same popular items for all users. Therefore, recommendations are +not personalized to the individual user and are useful when you want a system-wide representation of what's popular.

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Popular by Views is implemented used on the homepage to display popular items when there is not browsing +history for the current user (i.e. cold user). Once the known or anonymous user has more than three interactions (this +is an arbitrary number chosen in the Retail Demo Store's implementation), the storefront will switch to a personalized +recommendation using the Recommended For You retail recommender. You can tell when this transition is made when the homepage +grid header changes from "Popular products" to "Inspired by your shopping trends".

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You may notice some items are annotated with a "Promoted" banner across the top of the product image. This banner indicates +products that match a promotional filter that is optionally applied when retrieving recommendations. Promotional filters are +a great way to ensure that a user-defined percentage of recommended items match a specific filter expression but are also +relevant to the user. This can be used to highlight products on sale or new products recently added to the catalog.

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Real time personalization based on real time user activity

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Amazon Personalize can capture live events from your users to achieve real-time personalization. Amazon +Personalize can blend real-time user activity data with existing user profile and item information to recommend +the most relevant items, according to the user’s current session and activity.

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Do you have the infrastructure in place for real-time click streaming events back into Personalize? If not, don’t +worry, we can help!

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Build: Learn more about the AWS services available to build real-time streaming capabilities +Buy: AWS is partnering with multiple partners to translate and send your data to Amazon Personalize in the right +format.

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Provisioning capacity for real-time recommendations

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Customers are charged based on the transaction-per-second (TPS) capacity provisioned or used, whichever is + greater. When creating an Amazon Personalize campaign, a customer sets their minimum TPS capacity. TPS capacity + is measured on a TPS-hour basis (rounded up to the nearest hour). If the customer’s transaction load exceeds the + minimum provisioned capacity, Amazon Personalize will auto-scale based on the customer’s needs. In most cases + when a customer starts with Amazon Personalize, we recommend provisioning the minimum (1 TPS), then + experimenting to see the impact of Personalize for users. These learnings will help inform how to scale based on + their needs to avoid unexpected charges due to over-provisioning.

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Customer use case: KEEN

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KEEN is a values led, independently owned outdoor footwear brand with a mission to responsibly create +original and versatile products, improve lives, and inspire outside adventure. Founded in 2003, KEEN ignited +a revolution in the footwear industry with the introduction of the Newport sandal, launching the concept of +Hybrid footwear into the market and setting KEEN on a path of driving consistent product innovation that +exists today.

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"Over the past two years KEEN has been working to improve the way we engage our customers to bring them +increasingly relevant content for their outdoor footwear needs. Our goal is to educate our customers on the +best footwear options based on their desired outdoor activities. To really bring this capability to life we +turned to AWS and our partnership with Data in the Raw and develop a solution powered by Amazon Personalize +to use purchase and browsing history to best tailor recommendations and content for our customers along +their purchasing journey. With the initial use we looked to improve the experience for our browse abandon +customers through our email program. Initial results are encouraging, our open rates, Rev/M Sends, and Opt +out Rates were very healthy to begin with but with the implementation of Amazon Personalize we are seeing, +email CTR is up 67% over our control messaging. Rev/M Sends is up 49%, and because the content is even more +relevant, our Opt out Rate has dropped 36%. But where the rubber hits the road for me is on revenue. Test +emails have shown a 12.5% increase in revenue versus the control. It is clear that the AWS has given us +another ‘arrow in our quiver’. My only regret is this capability didn’t exist two years ago when we started +this journey."

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Customer use case: Data in the Raw

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Data in the Raw helps online retailers and content producers build scalable analytics and machine learning +infrastructures. With just one JavaScript tag, Data in the Raw can start automatically capturing users’ +unfiltered web data, from which they create a custom behavioral CRM on AWS. That CRM can be used with +business intelligence software and can help enable personalization, conversion rate optimization, user +experience/user interaction analysis, attribution modeling, and more. The company describes their offering +as a self-service big data pipeline to AWS.

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“In this time of one-size-fits-all personalization and expensive customer data platforms, Data in the Raw is +different. Unlike other platforms that sell users back their own data, our affordable pricing already +includes ownership of raw clickstream data. With the recent release of Amazon Personalize, our clients are +now shifting away from boring and bloated personalization platforms to build experiences that reach their +customers more efficiently. Not only do our clients save thousands of dollars using Data in the Raw and +Amazon Personalize, they have ultimate control over their own data and freedom to build what works for them. +With our core values of data democratization, Data in the Raw and Amazon Personalize are the perfect match.”

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Recommended For You

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Amazon Personalize Recipe: +Recommended-For-You

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Product and content recommendations tailored to a user's profile and habits are more likely to drive higher +engagement and conversion. Amazon Personalize helps tailor recommendations to users behavior, preferences, and history, boosting +their engagement and satisfaction in real-time, instead of providing a uniform experience. The Recommended For You recipe +also handles the “cold-start” challenge where limited or no historical information is known about an item or user. +Recommended For You in Amazon Personalize balances recommending fresh items with the most relevant based on a +user's unique preferences and behaviors while also automatically excluding products that have been recently purchased for +each user.

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You may notice some items are annotated with a "Promoted" banner across the top of the product image. This banner indicates +products that match a promotional filter that is optionally applied when retrieving recommendations. Promotional filters are +a great way to ensure that a user-defined percentage of recommended items match a specific filter expression but are also +relevant to the user. This can be used to highlight products on sale or new products recently added to the catalog.

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You can read more about promotional filters on the .

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Recommended For You is implemented in the “Inspired by your shopping trends” section of the homepage. Try using different +shoppers to experience the difference in personalized product recommendations offered.

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Find out why Amazon Personalize is right for your business

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Experience from Amazon: Over 20 years of personalization research and experience at + .

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Machine learning based personalization: Delivers higher quality product and content recommendations as well as + targeted marketing promotions using machine learning and customer’s data set.

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No machine learning experience required: All of the complicated and time consuming steps required to build, + train, and deploy a machine learning personalization solution are automated.

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Personalization in days, not months: Easily integrates into your existing websites, apps, SMS, and email + marketing systems so you can implement a sophisticated and scalable personalization solution in days, rather + than months.

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Proven success in improving customer engagement and conversion: Lotte Mart, a leading South Korean retailer + with over 600K coupon mobile app users, has seen a 40% increase in the number of products a consumer has not + previously purchased. StockX, a Detroit startup company revolutionizing ecommerce with a unique Bid/Ask + marketplace, added a Recommended For You product row to the homepage using + , + which ultimately became the top-performing homepage row. Mecca, a beauty retailer in Australia and New + Zealand, realized a 65% increase in e-mail click-through rates and a corresponding increase in email revenue + relating to the products recommended by Amazon Personalize. To personalize their customer experience further, + they are now extending the use of Amazon Personalize to additional areas including our website.

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Customer use case : MECCA

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MECCA brings our customers the best in global beauty across our retail stores and online channels in Australia and New Zealand. We’ve created a unique shopping experience for our customers in our 100+ stores, with an extensive collection of products from over 100 beauty brands, and exceptional service and beauty expertise.

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“At MECCA it’s about earning and keeping customer trust. We have challenged ourselves to translate our +highly personalized in-store service to our online experience. A fast and effective PoC with Amazon +Personalize, led by the MECCA technology and CRM teams, in collaboration with our partner Servian, +demonstrated how much we could achieve without developing our own recommendation engine. Since integrating +Personalize, we are seeing our customers respond positively to the new recommendations with a 65% increase +in e-mail click-through rates and a corresponding increase in email revenue relating to the products +recommended by Personalize. To personalize our customer experience further, we are now extending the use of +Personalize to additional areas including our website.“

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Related Items Recommendations

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Amazon Personalize Recipe: +SIMS

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Similar item recommendations help users discover new products or compare existing items in your catalog. Amazon +Personalize recommends similar items in real-time, based on user behavior to create unique, relevant experiences +for your customers.

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Pretty simple idea, implemented via item-item collaborative filtering but basically look at how people are +interacting with particular things and then determine how similar things are at a global level based on that data. +Not user specific at all.

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The similar item recommendations use case is implemented in all the product detail pages under “Compare similar items” carousel UI widget.

+

Customer use case : StockX

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“StockX is a Detroit startup company revolutionizing ecommerce with a unique Bid/Ask marketplace—our +platform models the New York Stock Exchange and treats goods like sneakers and streetwear as high-value, +tradable commodities. With a transparent market experience, StockX provides access to authentic, highly +sought-after products at true market price.”

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“Recommended for You was a massive win for both our team and StockX as a whole. We’re quickly learning the +potency of integrating ML into all facets of the company. Our success led to key decision-makers requesting +we integrate Amazon Personalize into more of the StockX experience and expand our ML endeavors. It’s safe to +say that personalization is now a first-class citizen here.”

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Sam Bean and Nic Roberts II at StockX.

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Read full AWS Machine Learning Blog: +Pioneering personalized user experiences at StockX with Amazon Personalize

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Related Items Recommendations

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Amazon Personalize Recipe: +Similar-Items +with +Personalized-Ranking

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Related item recommendations help users discover new products or compare existing items in your catalog. Amazon +Personalize recommends related items in real-time, based on user behavior and thematically similar item attributes to create unique, relevant experiences +for your customers.

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This user experience is implemented using the Similar-Items algorithm that considers co-occurrence in interactions data (how often these items appear together across user histories) +and thematic similarity (what is similar about the items in your catalog) when making recommendations to better quantify similarity for less popular or new items in +your catalog. The product detail page in this demo takes it a step further by using the Personalized-Ranking recipe to rerank related items recommendations for each user. This adds a level of +personalization to the user experience.

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You can read more about the Similar-Items recipe on the .

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The similar item recommendations use case is implemented in all the product detail pages under the “Compare similar items” +carousel widget. The order of items is personalized to each user by leveraging the Personalized-Ranking recipe to reorder +related items based on the current user's interest.

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AWS Machine Learning Blog

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“StockX is a Detroit startup company revolutionizing ecommerce with a unique Bid/Ask marketplace—our +platform models the New York Stock Exchange and treats goods like sneakers and streetwear as high-value, +tradable commodities. With a transparent market experience, StockX provides access to authentic, highly +sought-after products at true market price.”

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“Recommended for You was a massive win for both our team and StockX as a whole. We’re quickly learning the +potency of integrating ML into all facets of the company. Our success led to key decision-makers requesting +we integrate Amazon Personalize into more of the StockX experience and expand our ML endeavors. It’s safe to +say that personalization is now a first-class citizen here.”

+

Sam Bean and Nic Roberts II at StockX.

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Read full AWS Machine Learning Blog: +Pioneering personalized user experiences at StockX with Amazon Personalize

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Related Items Recommendations with Generative AI Theme

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Amazon Personalize Recipe: + Similar-Items + with + Content Generator

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Related item recommendations help users discover new products or compare existing items in your catalog. Amazon + Personalize recommends related items based on user behavior and thematically similar item attributes to create unique, relevant experiences + for your customers.

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This user experience is implemented using the Similar-Items algorithm that considers co-occurrence in interactions data (how often these items appear together across user histories) + and thematic similarity (what is similar about the items in your catalog) when making recommendations to better quantify similarity for less popular or new items in + your catalog. For this product detail page, the was + used to create a descriptive theme for the set of similar items. This descriptive theme is being used as the title/label over the related items on this page. Explore the product detail + page for other featured products in the Retail Demo Store catalog to see additional generated themes.

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You can read more about the and + on the Amazon Personalize blog.

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User Personalization

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Amazon Personalize Recipe: +User-Personalization

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Product and content recommendations tailored to a user’s profile and habits are more likely to drive higher +conversion. Amazon Personalize helps tailor recommendations to users behavior, preferences, and history, boosting +their engagement and satisfaction in real-time, instead of providing a uniform experience. User personalization +also handles the “cold-start” challenge where limited or no historical information is known about an item or user. +User personalization in Amazon Personalize balances recommending fresh items with the most relevant based on a +user’s unique preferences and behaviors.

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User personalization is implemented in the “Inspired by your shopping trends” section. Try using different +shoppers to experience the difference in personalized product recommendations offered.

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If you’re not signed in, featured products will be displayed instead.

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Shopper Personas

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To provide a more compelling and intuitive demo experience, each fictitious user in the Retail Demo Store is +assigned a shopper persona. The persona is represented by three categories from the Retail Demo Store’s catalog +which the user has an affinity. The affinity for each category is also weighted such that the first category is is +highest weighted and the third category is the lowest. There are sixteen combinations of categories that represent +the personas used across all users.

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  • furniture_homedecor_housewares
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For example, a user assigned with a persona of "footwear_outdoors_apparel" indicates that the user, at least +historically, has been primarily interested in products from the Footwear category and to decreasing degrees of +interest in products from the Outdoors and Apparel categories. That initial weighted interest is codified in the +generation of the historical interaction dataset which is used to train Solutions in Amazon Personalize. So, for +our "footwear_outdoors_apparel" user, interaction events are generated across products in all three of those +categories to create a synthetic history of engaging in products matching that persona. Additionally, some +products are tagged with an gender affinity. This is used when generating historical events to filter products +against the gender of each user to further add realism to the recommendations.

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Events for multiple event types are generated to mimic shopping behavior. For example, most generated event types +are 'View' to mimic users browsing the site. Occasional checkouts are simulated with 'AddToCart' +followed by 'ViewCart', 'StartCheckout', and 'Purchase' events. The Personalize solutions/models are +trained on the 'View' event type.

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Index

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Introduction

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Note

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This part of the documentation is also inside the demo itself (look for the "demo guide" on the bottom of each page)

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The Retail Demo Store +is an open source solution which integrates Amazon Personalize, Amazon Pinpoint and Amazon Lex in a retail web +application demo and workshop platform. The Retail Demo Store is intended to be used as an education tool (not +designed for production usage) for AWS customers to demonstrate how AWS can be used to build compelling customer +experiences for eCommerce, Retail and Digital Marketing use cases.

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The Retail Demo Store is a fictitious online store that includes users (shoppers), products, carts and orders as +well as services for search and recommendations and it helps demonstrate how the product recommendations change +based on shopper’s preferences, real-time behavior and history.

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Throughout the demo store experience, users are delivered (or have the option to be delivered) engagements across +multiple channels including email and text (SMS). These messages occur at key moments in the shopper lifecycle, +such as signup and abandoned cart. As users interact with the demo store and their emails/texts, real-time +segments based on their behavior are created and then personalized engagements across channels are delivered. By +utilizing Amazon Pinpoint and Amazon Personalize together, shopper interactions across each of these channels +(store, email, SMS) are ingested as a single event stream and fed into the demo store personalization model, +achieving omni-channel ML model retraining. On the other side, the ML personalization model is used to deliver +personalized experiences across each of these channels a harmonized way.

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Architecture

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The core of the Retail Demo Store is a polyglot microservice architecture deployed as a collection of RESTful + web services in Amazon Elastic Container Service (ECS). Several AWS managed services are leveraged to provide + build, deployment, authentication, messaging, search, and personalization capabilities. The web user interface + is a single page application built using responsive web design frameworks and techniques, producing a native + app-like experience tailored to the user's device. See the Workshops for details.

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Architecture

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How the Retail Demo Store works

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The Retail Demo Store is designed to display how personalization works and the impact it can have on a shoppers + experience. The demo has two main components: first, the storefront user interface and second, the demo guide + which walks the user through all the different components of the web application demo. .

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The storefront user interface is the actual online store. The products presented will change based on the + shopping preferences of the fictitious “shopper” profile selected. Users will be prompted to select a “shopper” + after account creation or sign in and will be able to switch “shopper” by selecting the “shopper”details on the + top-right corner. The demo guide is an educational component that sits on top of the store-front and is designed + to guide users.

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The demo guide provides more information on how to use the demo during customer meetings. It also includes the + services and use cases enabled in the demo, as well as some frequently asked Personalize topics.

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Xa({viewport$:e}){if(!B("header.autohide"))return I(!1);let t=e.pipe(m(({offset:{y:n}})=>n),Be(2,1),m(([n,i])=>[nMath.abs(i-n.y)>100),m(([,[n]])=>n),K()),o=ze("search");return z([e,o]).pipe(m(([{offset:n},i])=>n.y>400&&!i),K(),v(n=>n?r:I(!1)),Q(!1))}function Kn(e,t){return C(()=>z([ge(e),Xa(t)])).pipe(m(([{height:r},o])=>({height:r,hidden:o})),K((r,o)=>r.height===o.height&&r.hidden===o.hidden),G(1))}function Yn(e,{header$:t,main$:r}){return C(()=>{let o=new g,n=o.pipe(Z(),ie(!0));o.pipe(ee("active"),He(t)).subscribe(([{active:a},{hidden:s}])=>{e.classList.toggle("md-header--shadow",a&&!s),e.hidden=s});let i=ue(P("[title]",e)).pipe(b(()=>B("content.tooltips")),ne(a=>Qn(a)));return r.subscribe(o),t.pipe(W(n),m(a=>$({ref:e},a)),Re(i.pipe(W(n))))})}function Za(e,{viewport$:t,header$:r}){return mr(e,{viewport$:t,header$:r}).pipe(m(({offset:{y:o}})=>{let{height:n}=ce(e);return{active:o>=n}}),ee("active"))}function Bn(e,t){return C(()=>{let r=new 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I(...e).pipe(ne(o=>h(o,"change").pipe(m(()=>o))),Q(e[r]),m(o=>({index:e.indexOf(o),color:{media:o.getAttribute("data-md-color-media"),scheme:o.getAttribute("data-md-color-scheme"),primary:o.getAttribute("data-md-color-primary"),accent:o.getAttribute("data-md-color-accent")}})),G(1))}function Jn(e){let t=P("input",e),r=x("meta",{name:"theme-color"});document.head.appendChild(r);let o=x("meta",{name:"color-scheme"});document.head.appendChild(o);let n=Pt("(prefers-color-scheme: light)");return C(()=>{let i=new g;return i.subscribe(a=>{if(document.body.setAttribute("data-md-color-switching",""),a.color.media==="(prefers-color-scheme)"){let s=matchMedia("(prefers-color-scheme: light)"),p=document.querySelector(s.matches?"[data-md-color-media='(prefers-color-scheme: light)']":"[data-md-color-media='(prefers-color-scheme: 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Jr=Mt(Br());function ts(e){e.setAttribute("data-md-copying","");let t=e.closest("[data-copy]"),r=t?t.getAttribute("data-copy"):e.innerText;return e.removeAttribute("data-md-copying"),r.trimEnd()}function Zn({alert$:e}){Jr.default.isSupported()&&new j(t=>{new Jr.default("[data-clipboard-target], [data-clipboard-text]",{text:r=>r.getAttribute("data-clipboard-text")||ts(R(r.getAttribute("data-clipboard-target")))}).on("success",r=>t.next(r))}).pipe(w(t=>{t.trigger.focus()}),m(()=>Ee("clipboard.copied"))).subscribe(e)}function ei(e,t){return e.protocol=t.protocol,e.hostname=t.hostname,e}function rs(e,t){let r=new Map;for(let o of P("url",e)){let n=R("loc",o),i=[ei(new URL(n.textContent),t)];r.set(`${i[0]}`,i);for(let a of P("[rel=alternate]",o)){let s=a.getAttribute("href");s!=null&&i.push(ei(new URL(s),t))}}return r}function ur(e){return un(new URL("sitemap.xml",e)).pipe(m(t=>rs(t,new URL(e))),de(()=>I(new Map)))}function os(e,t){if(!(e.target instanceof Element))return S;let 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g,n=on(e.parentElement).pipe(b(Boolean)),i=e.parentElement,a=R(":scope > :first-child",e),s=R(":scope > :last-child",e);ze("search").subscribe(l=>s.setAttribute("role",l?"list":"presentation")),o.pipe(re(r),Wr(t.pipe(Ae(jt)))).subscribe(([{items:l},{value:f}])=>{switch(l.length){case 0:a.textContent=f.length?Ee("search.result.none"):Ee("search.result.placeholder");break;case 1:a.textContent=Ee("search.result.one");break;default:let u=sr(l.length);a.textContent=Ee("search.result.other",u)}});let p=o.pipe(w(()=>s.innerHTML=""),v(({items:l})=>O(I(...l.slice(0,10)),I(...l.slice(10)).pipe(Be(4),Vr(n),v(([f])=>f)))),m(Mn),pe());return p.subscribe(l=>s.appendChild(l)),p.pipe(ne(l=>{let f=fe("details",l);return typeof f=="undefined"?S:h(f,"toggle").pipe(W(o),m(()=>f))})).subscribe(l=>{l.open===!1&&l.offsetTop<=i.scrollTop&&i.scrollTo({top:l.offsetTop})}),t.pipe(b(dr),m(({data:l})=>l)).pipe(w(l=>o.next(l)),_(()=>o.complete()),m(l=>$({ref:e},l)))}function ms(e,{query$:t}){return t.pipe(m(({value:r})=>{let o=ye();return o.hash="",r=r.replace(/\s+/g,"+").replace(/&/g,"%26").replace(/=/g,"%3D"),o.search=`q=${r}`,{url:o}}))}function mi(e,t){let r=new g,o=r.pipe(Z(),ie(!0));return r.subscribe(({url:n})=>{e.setAttribute("data-clipboard-text",e.href),e.href=`${n}`}),h(e,"click").pipe(W(o)).subscribe(n=>n.preventDefault()),ms(e,t).pipe(w(n=>r.next(n)),_(()=>r.complete()),m(n=>$({ref:e},n)))}function fi(e,{worker$:t,keyboard$:r}){let o=new g,n=Se("search-query"),i=O(h(n,"keydown"),h(n,"focus")).pipe(ve(se),m(()=>n.value),K());return o.pipe(He(i),m(([{suggest:s},p])=>{let c=p.split(/([\s-]+)/);if(s!=null&&s.length&&c[c.length-1]){let l=s[s.length-1];l.startsWith(c[c.length-1])&&(c[c.length-1]=l)}else c.length=0;return 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n){let{childNodes:c}=x("span",null,p);s.replaceWith(...Array.from(c))}return{ref:e,nodes:n}}))}function fs(e,{viewport$:t,main$:r}){let o=e.closest(".md-grid"),n=o.offsetTop-o.parentElement.offsetTop;return z([r,t]).pipe(m(([{offset:i,height:a},{offset:{y:s}}])=>(a=a+Math.min(n,Math.max(0,s-i))-n,{height:a,locked:s>=i+n})),K((i,a)=>i.height===a.height&&i.locked===a.locked))}function Zr(e,o){var n=o,{header$:t}=n,r=so(n,["header$"]);let i=R(".md-sidebar__scrollwrap",e),{y:a}=Ve(i);return C(()=>{let s=new g,p=s.pipe(Z(),ie(!0)),c=s.pipe(Me(0,me));return c.pipe(re(t)).subscribe({next([{height:l},{height:f}]){i.style.height=`${l-2*a}px`,e.style.top=`${f}px`},complete(){i.style.height="",e.style.top=""}}),c.pipe(Ae()).subscribe(()=>{for(let l of P(".md-nav__link--active[href]",e)){if(!l.clientHeight)continue;let f=l.closest(".md-sidebar__scrollwrap");if(typeof f!="undefined"){let u=l.offsetTop-f.offsetTop,{height:d}=ce(f);f.scrollTo({top:u-d/2})}}}),ue(P("label[tabindex]",e)).pipe(ne(l=>h(l,"click").pipe(ve(se),m(()=>l),W(p)))).subscribe(l=>{let f=R(`[id="${l.htmlFor}"]`);R(`[aria-labelledby="${l.id}"]`).setAttribute("aria-expanded",`${f.checked}`)}),fs(e,r).pipe(w(l=>s.next(l)),_(()=>s.complete()),m(l=>$({ref:e},l)))})}function hi(e,t){if(typeof t!="undefined"){let r=`https://api.github.com/repos/${e}/${t}`;return st(je(`${r}/releases/latest`).pipe(de(()=>S),m(o=>({version:o.tag_name})),De({})),je(r).pipe(de(()=>S),m(o=>({stars:o.stargazers_count,forks:o.forks_count})),De({}))).pipe(m(([o,n])=>$($({},o),n)))}else{let r=`https://api.github.com/users/${e}`;return je(r).pipe(m(o=>({repositories:o.public_repos})),De({}))}}function bi(e,t){let r=`https://${e}/api/v4/projects/${encodeURIComponent(t)}`;return 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"src/templates/assets/javascripts/polyfills/index.ts"], + "sourcesContent": ["(function (global, factory) {\n typeof exports === 'object' && typeof module !== 'undefined' ? factory() :\n typeof define === 'function' && define.amd ? define(factory) :\n (factory());\n}(this, (function () { 'use strict';\n\n /**\n * Applies the :focus-visible polyfill at the given scope.\n * A scope in this case is either the top-level Document or a Shadow Root.\n *\n * @param {(Document|ShadowRoot)} scope\n * @see https://github.com/WICG/focus-visible\n */\n function applyFocusVisiblePolyfill(scope) {\n var hadKeyboardEvent = true;\n var hadFocusVisibleRecently = false;\n var hadFocusVisibleRecentlyTimeout = null;\n\n var inputTypesAllowlist = {\n text: true,\n search: true,\n url: true,\n tel: true,\n email: true,\n password: true,\n number: true,\n date: true,\n month: true,\n week: true,\n time: true,\n datetime: true,\n 'datetime-local': true\n };\n\n /**\n * Helper function for legacy browsers and iframes which sometimes focus\n * elements like document, body, and non-interactive SVG.\n * @param {Element} el\n */\n function isValidFocusTarget(el) {\n if (\n el &&\n el !== document &&\n el.nodeName !== 'HTML' &&\n el.nodeName !== 'BODY' &&\n 'classList' in el &&\n 'contains' in el.classList\n ) {\n return true;\n }\n return false;\n }\n\n /**\n * Computes whether the given element should automatically trigger the\n * `focus-visible` class being added, i.e. whether it should always match\n * `:focus-visible` when focused.\n * @param {Element} el\n * @return {boolean}\n */\n function focusTriggersKeyboardModality(el) {\n var type = el.type;\n var tagName = el.tagName;\n\n if (tagName === 'INPUT' && inputTypesAllowlist[type] && !el.readOnly) {\n return true;\n }\n\n if (tagName === 'TEXTAREA' && !el.readOnly) {\n return true;\n }\n\n if (el.isContentEditable) {\n return true;\n }\n\n return false;\n }\n\n /**\n * Add the `focus-visible` class to the given element if it was not added by\n * the author.\n * @param {Element} el\n */\n function addFocusVisibleClass(el) {\n if (el.classList.contains('focus-visible')) {\n return;\n }\n el.classList.add('focus-visible');\n el.setAttribute('data-focus-visible-added', '');\n }\n\n /**\n * Remove the `focus-visible` class from the given element if it was not\n * originally added by the author.\n * @param {Element} el\n */\n function removeFocusVisibleClass(el) {\n if (!el.hasAttribute('data-focus-visible-added')) {\n return;\n }\n el.classList.remove('focus-visible');\n el.removeAttribute('data-focus-visible-added');\n }\n\n /**\n * If the most recent user interaction was via the keyboard;\n * and the key press did not include a meta, alt/option, or control key;\n * then the modality is keyboard. Otherwise, the modality is not keyboard.\n * Apply `focus-visible` to any current active element and keep track\n * of our keyboard modality state with `hadKeyboardEvent`.\n * @param {KeyboardEvent} e\n */\n function onKeyDown(e) {\n if (e.metaKey || e.altKey || e.ctrlKey) {\n return;\n }\n\n if (isValidFocusTarget(scope.activeElement)) {\n addFocusVisibleClass(scope.activeElement);\n }\n\n hadKeyboardEvent = true;\n }\n\n /**\n * If at any point a user clicks with a pointing device, ensure that we change\n * the modality away from keyboard.\n * This avoids the situation where a user presses a key on an already focused\n * element, and then clicks on a different element, focusing it with a\n * pointing device, while we still think we're in keyboard modality.\n * @param {Event} e\n */\n function onPointerDown(e) {\n hadKeyboardEvent = false;\n }\n\n /**\n * On `focus`, add the `focus-visible` class to the target if:\n * - the target received focus as a result of keyboard navigation, or\n * - the event target is an element that will likely require interaction\n * via the keyboard (e.g. a text box)\n * @param {Event} e\n */\n function onFocus(e) {\n // Prevent IE from focusing the document or HTML element.\n if (!isValidFocusTarget(e.target)) {\n return;\n }\n\n if (hadKeyboardEvent || focusTriggersKeyboardModality(e.target)) {\n addFocusVisibleClass(e.target);\n }\n }\n\n /**\n * On `blur`, remove the `focus-visible` class from the target.\n * @param {Event} e\n */\n function onBlur(e) {\n if (!isValidFocusTarget(e.target)) {\n return;\n }\n\n if (\n e.target.classList.contains('focus-visible') ||\n e.target.hasAttribute('data-focus-visible-added')\n ) {\n // To detect a tab/window switch, we look for a blur event followed\n // rapidly by a visibility change.\n // If we don't see a visibility change within 100ms, it's probably a\n // regular focus change.\n hadFocusVisibleRecently = true;\n window.clearTimeout(hadFocusVisibleRecentlyTimeout);\n hadFocusVisibleRecentlyTimeout = window.setTimeout(function() {\n hadFocusVisibleRecently = false;\n }, 100);\n removeFocusVisibleClass(e.target);\n }\n }\n\n /**\n * If the user changes tabs, keep track of whether or not the previously\n * focused element had .focus-visible.\n * @param {Event} e\n */\n function onVisibilityChange(e) {\n if (document.visibilityState === 'hidden') {\n // If the tab becomes active again, the browser will handle calling focus\n // on the element (Safari actually calls it twice).\n // If this tab change caused a blur on an element with focus-visible,\n // re-apply the class when the user switches back to the tab.\n if (hadFocusVisibleRecently) {\n hadKeyboardEvent = true;\n }\n addInitialPointerMoveListeners();\n }\n }\n\n /**\n * Add a group of listeners to detect usage of any pointing devices.\n * These listeners will be added when the polyfill first loads, and anytime\n * the window is blurred, so that they are active when the window regains\n * focus.\n */\n function addInitialPointerMoveListeners() {\n document.addEventListener('mousemove', onInitialPointerMove);\n document.addEventListener('mousedown', onInitialPointerMove);\n document.addEventListener('mouseup', onInitialPointerMove);\n document.addEventListener('pointermove', onInitialPointerMove);\n document.addEventListener('pointerdown', onInitialPointerMove);\n document.addEventListener('pointerup', onInitialPointerMove);\n document.addEventListener('touchmove', onInitialPointerMove);\n document.addEventListener('touchstart', onInitialPointerMove);\n document.addEventListener('touchend', onInitialPointerMove);\n }\n\n function removeInitialPointerMoveListeners() {\n document.removeEventListener('mousemove', onInitialPointerMove);\n document.removeEventListener('mousedown', onInitialPointerMove);\n document.removeEventListener('mouseup', onInitialPointerMove);\n document.removeEventListener('pointermove', onInitialPointerMove);\n document.removeEventListener('pointerdown', onInitialPointerMove);\n document.removeEventListener('pointerup', onInitialPointerMove);\n document.removeEventListener('touchmove', onInitialPointerMove);\n document.removeEventListener('touchstart', onInitialPointerMove);\n document.removeEventListener('touchend', onInitialPointerMove);\n }\n\n /**\n * When the polfyill first loads, assume the user is in keyboard modality.\n * If any event is received from a pointing device (e.g. mouse, pointer,\n * touch), turn off keyboard modality.\n * This accounts for situations where focus enters the page from the URL bar.\n * @param {Event} e\n */\n function onInitialPointerMove(e) {\n // Work around a Safari quirk that fires a mousemove on whenever the\n // window blurs, even if you're tabbing out of the page. \u00AF\\_(\u30C4)_/\u00AF\n if (e.target.nodeName && e.target.nodeName.toLowerCase() === 'html') {\n return;\n }\n\n hadKeyboardEvent = false;\n removeInitialPointerMoveListeners();\n }\n\n // For some kinds of state, we are interested in changes at the global scope\n // only. For example, global pointer input, global key presses and global\n // visibility change should affect the state at every scope:\n document.addEventListener('keydown', onKeyDown, true);\n document.addEventListener('mousedown', onPointerDown, true);\n document.addEventListener('pointerdown', onPointerDown, true);\n document.addEventListener('touchstart', onPointerDown, true);\n document.addEventListener('visibilitychange', onVisibilityChange, true);\n\n addInitialPointerMoveListeners();\n\n // For focus and blur, we specifically care about state changes in the local\n // scope. This is because focus / blur events that originate from within a\n // shadow root are not re-dispatched from the host element if it was already\n // the active element in its own scope:\n scope.addEventListener('focus', onFocus, true);\n scope.addEventListener('blur', onBlur, true);\n\n // We detect that a node is a ShadowRoot by ensuring that it is a\n // DocumentFragment and also has a host property. This check covers native\n // implementation and polyfill implementation transparently. If we only cared\n // about the native implementation, we could just check if the scope was\n // an instance of a ShadowRoot.\n if (scope.nodeType === Node.DOCUMENT_FRAGMENT_NODE && scope.host) {\n // Since a ShadowRoot is a special kind of DocumentFragment, it does not\n // have a root element to add a class to. So, we add this attribute to the\n // host element instead:\n scope.host.setAttribute('data-js-focus-visible', '');\n } else if (scope.nodeType === Node.DOCUMENT_NODE) {\n document.documentElement.classList.add('js-focus-visible');\n document.documentElement.setAttribute('data-js-focus-visible', '');\n }\n }\n\n // It is important to wrap all references to global window and document in\n // these checks to support server-side rendering use cases\n // @see https://github.com/WICG/focus-visible/issues/199\n if (typeof window !== 'undefined' && typeof document !== 'undefined') {\n // Make the polyfill helper globally available. This can be used as a signal\n // to interested libraries that wish to coordinate with the polyfill for e.g.,\n // applying the polyfill to a shadow root:\n window.applyFocusVisiblePolyfill = applyFocusVisiblePolyfill;\n\n // Notify interested libraries of the polyfill's presence, in case the\n // polyfill was loaded lazily:\n var event;\n\n try {\n event = new CustomEvent('focus-visible-polyfill-ready');\n } catch (error) {\n // IE11 does not support using CustomEvent as a constructor directly:\n event = document.createEvent('CustomEvent');\n event.initCustomEvent('focus-visible-polyfill-ready', false, false, {});\n }\n\n window.dispatchEvent(event);\n }\n\n if (typeof document !== 'undefined') {\n // Apply the polyfill to the global document, so that no JavaScript\n // coordination is required to use the polyfill in the top-level document:\n applyFocusVisiblePolyfill(document);\n }\n\n})));\n", "/*!\n * escape-html\n * Copyright(c) 2012-2013 TJ Holowaychuk\n * Copyright(c) 2015 Andreas Lubbe\n * Copyright(c) 2015 Tiancheng \"Timothy\" Gu\n * MIT Licensed\n */\n\n'use strict';\n\n/**\n * Module variables.\n * @private\n */\n\nvar matchHtmlRegExp = /[\"'&<>]/;\n\n/**\n * Module exports.\n * @public\n */\n\nmodule.exports = escapeHtml;\n\n/**\n * Escape special characters in the given string of html.\n *\n * @param {string} string The string to escape for inserting into HTML\n * @return {string}\n * @public\n */\n\nfunction escapeHtml(string) {\n var str = '' + string;\n var match = matchHtmlRegExp.exec(str);\n\n if (!match) {\n return str;\n }\n\n var escape;\n var html = '';\n var index = 0;\n var lastIndex = 0;\n\n for (index = match.index; index < str.length; index++) {\n switch (str.charCodeAt(index)) {\n case 34: // \"\n escape = '"';\n break;\n case 38: // &\n escape = '&';\n break;\n case 39: // '\n escape = ''';\n break;\n case 60: // <\n escape = '<';\n break;\n case 62: // >\n escape = '>';\n break;\n default:\n continue;\n }\n\n if (lastIndex !== index) {\n html += str.substring(lastIndex, index);\n }\n\n lastIndex = index + 1;\n html += escape;\n }\n\n return lastIndex !== index\n ? html + str.substring(lastIndex, index)\n : html;\n}\n", "/*!\n * clipboard.js v2.0.11\n * https://clipboardjs.com/\n *\n * Licensed MIT \u00A9 Zeno Rocha\n */\n(function webpackUniversalModuleDefinition(root, factory) {\n\tif(typeof exports === 'object' && typeof module === 'object')\n\t\tmodule.exports = factory();\n\telse if(typeof define === 'function' && define.amd)\n\t\tdefine([], factory);\n\telse if(typeof exports === 'object')\n\t\texports[\"ClipboardJS\"] = factory();\n\telse\n\t\troot[\"ClipboardJS\"] = factory();\n})(this, function() {\nreturn /******/ (function() { // webpackBootstrap\n/******/ \tvar __webpack_modules__ = ({\n\n/***/ 686:\n/***/ (function(__unused_webpack_module, __webpack_exports__, __webpack_require__) {\n\n\"use strict\";\n\n// EXPORTS\n__webpack_require__.d(__webpack_exports__, {\n \"default\": function() { return /* binding */ clipboard; }\n});\n\n// EXTERNAL MODULE: ./node_modules/tiny-emitter/index.js\nvar tiny_emitter = __webpack_require__(279);\nvar tiny_emitter_default = /*#__PURE__*/__webpack_require__.n(tiny_emitter);\n// EXTERNAL MODULE: ./node_modules/good-listener/src/listen.js\nvar listen = __webpack_require__(370);\nvar listen_default = /*#__PURE__*/__webpack_require__.n(listen);\n// EXTERNAL MODULE: ./node_modules/select/src/select.js\nvar src_select = __webpack_require__(817);\nvar select_default = /*#__PURE__*/__webpack_require__.n(src_select);\n;// CONCATENATED MODULE: ./src/common/command.js\n/**\n * Executes a given operation type.\n * @param {String} type\n * @return {Boolean}\n */\nfunction command(type) {\n try {\n return document.execCommand(type);\n } catch (err) {\n return false;\n }\n}\n;// CONCATENATED MODULE: ./src/actions/cut.js\n\n\n/**\n * Cut action wrapper.\n * @param {String|HTMLElement} target\n * @return {String}\n */\n\nvar ClipboardActionCut = function ClipboardActionCut(target) {\n var selectedText = select_default()(target);\n command('cut');\n return selectedText;\n};\n\n/* harmony default export */ var actions_cut = (ClipboardActionCut);\n;// CONCATENATED MODULE: ./src/common/create-fake-element.js\n/**\n * Creates a fake textarea element with a value.\n * @param {String} value\n * @return {HTMLElement}\n */\nfunction createFakeElement(value) {\n var isRTL = document.documentElement.getAttribute('dir') === 'rtl';\n var fakeElement = document.createElement('textarea'); // Prevent zooming on iOS\n\n fakeElement.style.fontSize = '12pt'; // Reset box model\n\n fakeElement.style.border = '0';\n fakeElement.style.padding = '0';\n fakeElement.style.margin = '0'; // Move element out of screen horizontally\n\n fakeElement.style.position = 'absolute';\n fakeElement.style[isRTL ? 'right' : 'left'] = '-9999px'; // Move element to the same position vertically\n\n var yPosition = window.pageYOffset || document.documentElement.scrollTop;\n fakeElement.style.top = \"\".concat(yPosition, \"px\");\n fakeElement.setAttribute('readonly', '');\n fakeElement.value = value;\n return fakeElement;\n}\n;// CONCATENATED MODULE: ./src/actions/copy.js\n\n\n\n/**\n * Create fake copy action wrapper using a fake element.\n * @param {String} target\n * @param {Object} options\n * @return {String}\n */\n\nvar fakeCopyAction = function fakeCopyAction(value, options) {\n var fakeElement = createFakeElement(value);\n options.container.appendChild(fakeElement);\n var selectedText = select_default()(fakeElement);\n command('copy');\n fakeElement.remove();\n return selectedText;\n};\n/**\n * Copy action wrapper.\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @return {String}\n */\n\n\nvar ClipboardActionCopy = function ClipboardActionCopy(target) {\n var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n container: document.body\n };\n var selectedText = '';\n\n if (typeof target === 'string') {\n selectedText = fakeCopyAction(target, options);\n } else if (target instanceof HTMLInputElement && !['text', 'search', 'url', 'tel', 'password'].includes(target === null || target === void 0 ? void 0 : target.type)) {\n // If input type doesn't support `setSelectionRange`. Simulate it. https://developer.mozilla.org/en-US/docs/Web/API/HTMLInputElement/setSelectionRange\n selectedText = fakeCopyAction(target.value, options);\n } else {\n selectedText = select_default()(target);\n command('copy');\n }\n\n return selectedText;\n};\n\n/* harmony default export */ var actions_copy = (ClipboardActionCopy);\n;// CONCATENATED MODULE: ./src/actions/default.js\nfunction _typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { _typeof = function _typeof(obj) { return typeof obj; }; } else { _typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return _typeof(obj); }\n\n\n\n/**\n * Inner function which performs selection from either `text` or `target`\n * properties and then executes copy or cut operations.\n * @param {Object} options\n */\n\nvar ClipboardActionDefault = function ClipboardActionDefault() {\n var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n // Defines base properties passed from constructor.\n var _options$action = options.action,\n action = _options$action === void 0 ? 'copy' : _options$action,\n container = options.container,\n target = options.target,\n text = options.text; // Sets the `action` to be performed which can be either 'copy' or 'cut'.\n\n if (action !== 'copy' && action !== 'cut') {\n throw new Error('Invalid \"action\" value, use either \"copy\" or \"cut\"');\n } // Sets the `target` property using an element that will be have its content copied.\n\n\n if (target !== undefined) {\n if (target && _typeof(target) === 'object' && target.nodeType === 1) {\n if (action === 'copy' && target.hasAttribute('disabled')) {\n throw new Error('Invalid \"target\" attribute. Please use \"readonly\" instead of \"disabled\" attribute');\n }\n\n if (action === 'cut' && (target.hasAttribute('readonly') || target.hasAttribute('disabled'))) {\n throw new Error('Invalid \"target\" attribute. You can\\'t cut text from elements with \"readonly\" or \"disabled\" attributes');\n }\n } else {\n throw new Error('Invalid \"target\" value, use a valid Element');\n }\n } // Define selection strategy based on `text` property.\n\n\n if (text) {\n return actions_copy(text, {\n container: container\n });\n } // Defines which selection strategy based on `target` property.\n\n\n if (target) {\n return action === 'cut' ? actions_cut(target) : actions_copy(target, {\n container: container\n });\n }\n};\n\n/* harmony default export */ var actions_default = (ClipboardActionDefault);\n;// CONCATENATED MODULE: ./src/clipboard.js\nfunction clipboard_typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { clipboard_typeof = function _typeof(obj) { return typeof obj; }; } else { clipboard_typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return clipboard_typeof(obj); }\n\nfunction _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\nfunction _defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } }\n\nfunction _createClass(Constructor, protoProps, staticProps) { if (protoProps) _defineProperties(Constructor.prototype, protoProps); if (staticProps) _defineProperties(Constructor, staticProps); return Constructor; }\n\nfunction _inherits(subClass, superClass) { if (typeof superClass !== \"function\" && superClass !== null) { throw new TypeError(\"Super expression must either be null or a function\"); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, writable: true, configurable: true } }); if (superClass) _setPrototypeOf(subClass, superClass); }\n\nfunction _setPrototypeOf(o, p) { _setPrototypeOf = Object.setPrototypeOf || function _setPrototypeOf(o, p) { o.__proto__ = p; return o; }; return _setPrototypeOf(o, p); }\n\nfunction _createSuper(Derived) { var hasNativeReflectConstruct = _isNativeReflectConstruct(); return function _createSuperInternal() { var Super = _getPrototypeOf(Derived), result; if (hasNativeReflectConstruct) { var NewTarget = _getPrototypeOf(this).constructor; result = Reflect.construct(Super, arguments, NewTarget); } else { result = Super.apply(this, arguments); } return _possibleConstructorReturn(this, result); }; }\n\nfunction _possibleConstructorReturn(self, call) { if (call && (clipboard_typeof(call) === \"object\" || typeof call === \"function\")) { return call; } return _assertThisInitialized(self); }\n\nfunction _assertThisInitialized(self) { if (self === void 0) { throw new ReferenceError(\"this hasn't been initialised - super() hasn't been called\"); } return self; }\n\nfunction _isNativeReflectConstruct() { if (typeof Reflect === \"undefined\" || !Reflect.construct) return false; if (Reflect.construct.sham) return false; if (typeof Proxy === \"function\") return true; try { Date.prototype.toString.call(Reflect.construct(Date, [], function () {})); return true; } catch (e) { return false; } }\n\nfunction _getPrototypeOf(o) { _getPrototypeOf = Object.setPrototypeOf ? Object.getPrototypeOf : function _getPrototypeOf(o) { return o.__proto__ || Object.getPrototypeOf(o); }; return _getPrototypeOf(o); }\n\n\n\n\n\n\n/**\n * Helper function to retrieve attribute value.\n * @param {String} suffix\n * @param {Element} element\n */\n\nfunction getAttributeValue(suffix, element) {\n var attribute = \"data-clipboard-\".concat(suffix);\n\n if (!element.hasAttribute(attribute)) {\n return;\n }\n\n return element.getAttribute(attribute);\n}\n/**\n * Base class which takes one or more elements, adds event listeners to them,\n * and instantiates a new `ClipboardAction` on each click.\n */\n\n\nvar Clipboard = /*#__PURE__*/function (_Emitter) {\n _inherits(Clipboard, _Emitter);\n\n var _super = _createSuper(Clipboard);\n\n /**\n * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n * @param {Object} options\n */\n function Clipboard(trigger, options) {\n var _this;\n\n _classCallCheck(this, Clipboard);\n\n _this = _super.call(this);\n\n _this.resolveOptions(options);\n\n _this.listenClick(trigger);\n\n return _this;\n }\n /**\n * Defines if attributes would be resolved using internal setter functions\n * or custom functions that were passed in the constructor.\n * @param {Object} options\n */\n\n\n _createClass(Clipboard, [{\n key: \"resolveOptions\",\n value: function resolveOptions() {\n var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n this.action = typeof options.action === 'function' ? options.action : this.defaultAction;\n this.target = typeof options.target === 'function' ? options.target : this.defaultTarget;\n this.text = typeof options.text === 'function' ? options.text : this.defaultText;\n this.container = clipboard_typeof(options.container) === 'object' ? options.container : document.body;\n }\n /**\n * Adds a click event listener to the passed trigger.\n * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n */\n\n }, {\n key: \"listenClick\",\n value: function listenClick(trigger) {\n var _this2 = this;\n\n this.listener = listen_default()(trigger, 'click', function (e) {\n return _this2.onClick(e);\n });\n }\n /**\n * Defines a new `ClipboardAction` on each click event.\n * @param {Event} e\n */\n\n }, {\n key: \"onClick\",\n value: function onClick(e) {\n var trigger = e.delegateTarget || e.currentTarget;\n var action = this.action(trigger) || 'copy';\n var text = actions_default({\n action: action,\n container: this.container,\n target: this.target(trigger),\n text: this.text(trigger)\n }); // Fires an event based on the copy operation result.\n\n this.emit(text ? 'success' : 'error', {\n action: action,\n text: text,\n trigger: trigger,\n clearSelection: function clearSelection() {\n if (trigger) {\n trigger.focus();\n }\n\n window.getSelection().removeAllRanges();\n }\n });\n }\n /**\n * Default `action` lookup function.\n * @param {Element} trigger\n */\n\n }, {\n key: \"defaultAction\",\n value: function defaultAction(trigger) {\n return getAttributeValue('action', trigger);\n }\n /**\n * Default `target` lookup function.\n * @param {Element} trigger\n */\n\n }, {\n key: \"defaultTarget\",\n value: function defaultTarget(trigger) {\n var selector = getAttributeValue('target', trigger);\n\n if (selector) {\n return document.querySelector(selector);\n }\n }\n /**\n * Allow fire programmatically a copy action\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @returns Text copied.\n */\n\n }, {\n key: \"defaultText\",\n\n /**\n * Default `text` lookup function.\n * @param {Element} trigger\n */\n value: function defaultText(trigger) {\n return getAttributeValue('text', trigger);\n }\n /**\n * Destroy lifecycle.\n */\n\n }, {\n key: \"destroy\",\n value: function destroy() {\n this.listener.destroy();\n }\n }], [{\n key: \"copy\",\n value: function copy(target) {\n var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n container: document.body\n };\n return actions_copy(target, options);\n }\n /**\n * Allow fire programmatically a cut action\n * @param {String|HTMLElement} target\n * @returns Text cutted.\n */\n\n }, {\n key: \"cut\",\n value: function cut(target) {\n return actions_cut(target);\n }\n /**\n * Returns the support of the given action, or all actions if no action is\n * given.\n * @param {String} [action]\n */\n\n }, {\n key: \"isSupported\",\n value: function isSupported() {\n var action = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : ['copy', 'cut'];\n var actions = typeof action === 'string' ? [action] : action;\n var support = !!document.queryCommandSupported;\n actions.forEach(function (action) {\n support = support && !!document.queryCommandSupported(action);\n });\n return support;\n }\n }]);\n\n return Clipboard;\n}((tiny_emitter_default()));\n\n/* harmony default export */ var clipboard = (Clipboard);\n\n/***/ }),\n\n/***/ 828:\n/***/ (function(module) {\n\nvar DOCUMENT_NODE_TYPE = 9;\n\n/**\n * A polyfill for Element.matches()\n */\nif (typeof Element !== 'undefined' && !Element.prototype.matches) {\n var proto = Element.prototype;\n\n proto.matches = proto.matchesSelector ||\n proto.mozMatchesSelector ||\n proto.msMatchesSelector ||\n proto.oMatchesSelector ||\n proto.webkitMatchesSelector;\n}\n\n/**\n * Finds the closest parent that matches a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @return {Function}\n */\nfunction closest (element, selector) {\n while (element && element.nodeType !== DOCUMENT_NODE_TYPE) {\n if (typeof element.matches === 'function' &&\n element.matches(selector)) {\n return element;\n }\n element = element.parentNode;\n }\n}\n\nmodule.exports = closest;\n\n\n/***/ }),\n\n/***/ 438:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar closest = __webpack_require__(828);\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction _delegate(element, selector, type, callback, useCapture) {\n var listenerFn = listener.apply(this, arguments);\n\n element.addEventListener(type, listenerFn, useCapture);\n\n return {\n destroy: function() {\n element.removeEventListener(type, listenerFn, useCapture);\n }\n }\n}\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element|String|Array} [elements]\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction delegate(elements, selector, type, callback, useCapture) {\n // Handle the regular Element usage\n if (typeof elements.addEventListener === 'function') {\n return _delegate.apply(null, arguments);\n }\n\n // Handle Element-less usage, it defaults to global delegation\n if (typeof type === 'function') {\n // Use `document` as the first parameter, then apply arguments\n // This is a short way to .unshift `arguments` without running into deoptimizations\n return _delegate.bind(null, document).apply(null, arguments);\n }\n\n // Handle Selector-based usage\n if (typeof elements === 'string') {\n elements = document.querySelectorAll(elements);\n }\n\n // Handle Array-like based usage\n return Array.prototype.map.call(elements, function (element) {\n return _delegate(element, selector, type, callback, useCapture);\n });\n}\n\n/**\n * Finds closest match and invokes callback.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Function}\n */\nfunction listener(element, selector, type, callback) {\n return function(e) {\n e.delegateTarget = closest(e.target, selector);\n\n if (e.delegateTarget) {\n callback.call(element, e);\n }\n }\n}\n\nmodule.exports = delegate;\n\n\n/***/ }),\n\n/***/ 879:\n/***/ (function(__unused_webpack_module, exports) {\n\n/**\n * Check if argument is a HTML element.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.node = function(value) {\n return value !== undefined\n && value instanceof HTMLElement\n && value.nodeType === 1;\n};\n\n/**\n * Check if argument is a list of HTML elements.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.nodeList = function(value) {\n var type = Object.prototype.toString.call(value);\n\n return value !== undefined\n && (type === '[object NodeList]' || type === '[object HTMLCollection]')\n && ('length' in value)\n && (value.length === 0 || exports.node(value[0]));\n};\n\n/**\n * Check if argument is a string.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.string = function(value) {\n return typeof value === 'string'\n || value instanceof String;\n};\n\n/**\n * Check if argument is a function.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.fn = function(value) {\n var type = Object.prototype.toString.call(value);\n\n return type === '[object Function]';\n};\n\n\n/***/ }),\n\n/***/ 370:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar is = __webpack_require__(879);\nvar delegate = __webpack_require__(438);\n\n/**\n * Validates all params and calls the right\n * listener function based on its target type.\n *\n * @param {String|HTMLElement|HTMLCollection|NodeList} target\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listen(target, type, callback) {\n if (!target && !type && !callback) {\n throw new Error('Missing required arguments');\n }\n\n if (!is.string(type)) {\n throw new TypeError('Second argument must be a String');\n }\n\n if (!is.fn(callback)) {\n throw new TypeError('Third argument must be a Function');\n }\n\n if (is.node(target)) {\n return listenNode(target, type, callback);\n }\n else if (is.nodeList(target)) {\n return listenNodeList(target, type, callback);\n }\n else if (is.string(target)) {\n return listenSelector(target, type, callback);\n }\n else {\n throw new TypeError('First argument must be a String, HTMLElement, HTMLCollection, or NodeList');\n }\n}\n\n/**\n * Adds an event listener to a HTML element\n * and returns a remove listener function.\n *\n * @param {HTMLElement} node\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNode(node, type, callback) {\n node.addEventListener(type, callback);\n\n return {\n destroy: function() {\n node.removeEventListener(type, callback);\n }\n }\n}\n\n/**\n * Add an event listener to a list of HTML elements\n * and returns a remove listener function.\n *\n * @param {NodeList|HTMLCollection} nodeList\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNodeList(nodeList, type, callback) {\n Array.prototype.forEach.call(nodeList, function(node) {\n node.addEventListener(type, callback);\n });\n\n return {\n destroy: function() {\n Array.prototype.forEach.call(nodeList, function(node) {\n node.removeEventListener(type, callback);\n });\n }\n }\n}\n\n/**\n * Add an event listener to a selector\n * and returns a remove listener function.\n *\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenSelector(selector, type, callback) {\n return delegate(document.body, selector, type, callback);\n}\n\nmodule.exports = listen;\n\n\n/***/ }),\n\n/***/ 817:\n/***/ (function(module) {\n\nfunction select(element) {\n var selectedText;\n\n if (element.nodeName === 'SELECT') {\n element.focus();\n\n selectedText = element.value;\n }\n else if (element.nodeName === 'INPUT' || element.nodeName === 'TEXTAREA') {\n var isReadOnly = element.hasAttribute('readonly');\n\n if (!isReadOnly) {\n element.setAttribute('readonly', '');\n }\n\n element.select();\n element.setSelectionRange(0, element.value.length);\n\n if (!isReadOnly) {\n element.removeAttribute('readonly');\n }\n\n selectedText = element.value;\n }\n else {\n if (element.hasAttribute('contenteditable')) {\n element.focus();\n }\n\n var selection = window.getSelection();\n var range = document.createRange();\n\n range.selectNodeContents(element);\n selection.removeAllRanges();\n selection.addRange(range);\n\n selectedText = selection.toString();\n }\n\n return selectedText;\n}\n\nmodule.exports = select;\n\n\n/***/ }),\n\n/***/ 279:\n/***/ (function(module) {\n\nfunction E () {\n // Keep this empty so it's easier to inherit from\n // (via https://github.com/lipsmack from https://github.com/scottcorgan/tiny-emitter/issues/3)\n}\n\nE.prototype = {\n on: function (name, callback, ctx) {\n var e = this.e || (this.e = {});\n\n (e[name] || (e[name] = [])).push({\n fn: callback,\n ctx: ctx\n });\n\n return this;\n },\n\n once: function (name, callback, ctx) {\n var self = this;\n function listener () {\n self.off(name, listener);\n callback.apply(ctx, arguments);\n };\n\n listener._ = callback\n return this.on(name, listener, ctx);\n },\n\n emit: function (name) {\n var data = [].slice.call(arguments, 1);\n var evtArr = ((this.e || (this.e = {}))[name] || []).slice();\n var i = 0;\n var len = evtArr.length;\n\n for (i; i < len; i++) {\n evtArr[i].fn.apply(evtArr[i].ctx, data);\n }\n\n return this;\n },\n\n off: function (name, callback) {\n var e = this.e || (this.e = {});\n var evts = e[name];\n var liveEvents = [];\n\n if (evts && callback) {\n for (var i = 0, len = evts.length; i < len; i++) {\n if (evts[i].fn !== callback && evts[i].fn._ !== callback)\n liveEvents.push(evts[i]);\n }\n }\n\n // Remove event from queue to prevent memory leak\n // Suggested by https://github.com/lazd\n // Ref: https://github.com/scottcorgan/tiny-emitter/commit/c6ebfaa9bc973b33d110a84a307742b7cf94c953#commitcomment-5024910\n\n (liveEvents.length)\n ? e[name] = liveEvents\n : delete e[name];\n\n return this;\n }\n};\n\nmodule.exports = E;\nmodule.exports.TinyEmitter = E;\n\n\n/***/ })\n\n/******/ \t});\n/************************************************************************/\n/******/ \t// The module cache\n/******/ \tvar __webpack_module_cache__ = {};\n/******/ \t\n/******/ \t// The require function\n/******/ \tfunction __webpack_require__(moduleId) {\n/******/ \t\t// Check if module is in cache\n/******/ \t\tif(__webpack_module_cache__[moduleId]) {\n/******/ \t\t\treturn __webpack_module_cache__[moduleId].exports;\n/******/ \t\t}\n/******/ \t\t// Create a new module (and put it into the cache)\n/******/ \t\tvar module = __webpack_module_cache__[moduleId] = {\n/******/ \t\t\t// no module.id needed\n/******/ \t\t\t// no module.loaded needed\n/******/ \t\t\texports: {}\n/******/ \t\t};\n/******/ \t\n/******/ \t\t// Execute the module function\n/******/ \t\t__webpack_modules__[moduleId](module, module.exports, __webpack_require__);\n/******/ \t\n/******/ \t\t// Return the exports of the module\n/******/ \t\treturn module.exports;\n/******/ \t}\n/******/ \t\n/************************************************************************/\n/******/ \t/* webpack/runtime/compat get default export */\n/******/ \t!function() {\n/******/ \t\t// getDefaultExport function for compatibility with non-harmony modules\n/******/ \t\t__webpack_require__.n = function(module) {\n/******/ \t\t\tvar getter = module && module.__esModule ?\n/******/ \t\t\t\tfunction() { return module['default']; } :\n/******/ \t\t\t\tfunction() { return module; };\n/******/ \t\t\t__webpack_require__.d(getter, { a: getter });\n/******/ \t\t\treturn getter;\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/define property getters */\n/******/ \t!function() {\n/******/ \t\t// define getter functions for harmony exports\n/******/ \t\t__webpack_require__.d = function(exports, definition) {\n/******/ \t\t\tfor(var key in definition) {\n/******/ \t\t\t\tif(__webpack_require__.o(definition, key) && !__webpack_require__.o(exports, key)) {\n/******/ \t\t\t\t\tObject.defineProperty(exports, key, { enumerable: true, get: definition[key] });\n/******/ \t\t\t\t}\n/******/ \t\t\t}\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/hasOwnProperty shorthand */\n/******/ \t!function() {\n/******/ \t\t__webpack_require__.o = function(obj, prop) { return Object.prototype.hasOwnProperty.call(obj, prop); }\n/******/ \t}();\n/******/ \t\n/************************************************************************/\n/******/ \t// module exports must be returned from runtime so entry inlining is disabled\n/******/ \t// startup\n/******/ \t// Load entry module and return exports\n/******/ \treturn __webpack_require__(686);\n/******/ })()\n.default;\n});", "/*\n * Copyright (c) 2016-2024 Martin Donath \n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport \"focus-visible\"\n\nimport {\n EMPTY,\n NEVER,\n Observable,\n Subject,\n defer,\n delay,\n filter,\n map,\n merge,\n mergeWith,\n shareReplay,\n switchMap\n} from \"rxjs\"\n\nimport { configuration, feature } from \"./_\"\nimport {\n at,\n getActiveElement,\n getOptionalElement,\n requestJSON,\n setLocation,\n setToggle,\n watchDocument,\n watchKeyboard,\n watchLocation,\n watchLocationTarget,\n watchMedia,\n watchPrint,\n watchScript,\n watchViewport\n} from \"./browser\"\nimport {\n getComponentElement,\n getComponentElements,\n mountAnnounce,\n mountBackToTop,\n mountConsent,\n mountContent,\n mountDialog,\n mountHeader,\n mountHeaderTitle,\n mountPalette,\n mountProgress,\n mountSearch,\n mountSearchHiglight,\n mountSidebar,\n mountSource,\n mountTableOfContents,\n mountTabs,\n watchHeader,\n watchMain\n} from \"./components\"\nimport {\n SearchIndex,\n setupClipboardJS,\n setupInstantNavigation,\n setupVersionSelector\n} from \"./integrations\"\nimport {\n patchEllipsis,\n patchIndeterminate,\n patchScrollfix,\n patchScrolllock\n} from \"./patches\"\nimport \"./polyfills\"\n\n/* ----------------------------------------------------------------------------\n * Functions - @todo refactor\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch search index\n *\n * @returns Search index observable\n */\nfunction fetchSearchIndex(): Observable {\n if (location.protocol === \"file:\") {\n return watchScript(\n `${new URL(\"search/search_index.js\", config.base)}`\n )\n .pipe(\n // @ts-ignore - @todo fix typings\n map(() => __index),\n shareReplay(1)\n )\n } else {\n return requestJSON(\n new URL(\"search/search_index.json\", config.base)\n )\n }\n}\n\n/* ----------------------------------------------------------------------------\n * Application\n * ------------------------------------------------------------------------- */\n\n/* Yay, JavaScript is available */\ndocument.documentElement.classList.remove(\"no-js\")\ndocument.documentElement.classList.add(\"js\")\n\n/* Set up navigation observables and subjects */\nconst document$ = watchDocument()\nconst location$ = watchLocation()\nconst target$ = watchLocationTarget(location$)\nconst keyboard$ = watchKeyboard()\n\n/* Set up media observables */\nconst viewport$ = watchViewport()\nconst tablet$ = watchMedia(\"(min-width: 960px)\")\nconst screen$ = watchMedia(\"(min-width: 1220px)\")\nconst print$ = watchPrint()\n\n/* Retrieve search index, if search is enabled */\nconst config = configuration()\nconst index$ = document.forms.namedItem(\"search\")\n ? fetchSearchIndex()\n : NEVER\n\n/* Set up Clipboard.js integration */\nconst alert$ = new Subject()\nsetupClipboardJS({ alert$ })\n\n/* Set up progress indicator */\nconst progress$ = new Subject()\n\n/* Set up instant navigation, if enabled */\nif (feature(\"navigation.instant\"))\n setupInstantNavigation({ location$, viewport$, progress$ })\n .subscribe(document$)\n\n/* Set up version selector */\nif (config.version?.provider === \"mike\")\n setupVersionSelector({ document$ })\n\n/* Always close drawer and search on navigation */\nmerge(location$, target$)\n .pipe(\n delay(125)\n )\n .subscribe(() => {\n setToggle(\"drawer\", false)\n setToggle(\"search\", false)\n })\n\n/* Set up global keyboard handlers */\nkeyboard$\n .pipe(\n filter(({ mode }) => mode === \"global\")\n )\n .subscribe(key => {\n switch (key.type) {\n\n /* Go to previous page */\n case \"p\":\n case \",\":\n const prev = getOptionalElement(\"link[rel=prev]\")\n if (typeof prev !== \"undefined\")\n setLocation(prev)\n break\n\n /* Go to next page */\n case \"n\":\n case \".\":\n const next = getOptionalElement(\"link[rel=next]\")\n if (typeof next !== \"undefined\")\n setLocation(next)\n break\n\n /* Expand navigation, see https://bit.ly/3ZjG5io */\n case \"Enter\":\n const active = getActiveElement()\n if (active instanceof HTMLLabelElement)\n active.click()\n }\n })\n\n/* Set up patches */\npatchEllipsis({ viewport$, document$ })\npatchIndeterminate({ document$, tablet$ })\npatchScrollfix({ document$ })\npatchScrolllock({ viewport$, tablet$ })\n\n/* Set up header and main area observable */\nconst header$ = watchHeader(getComponentElement(\"header\"), { viewport$ })\nconst main$ = document$\n .pipe(\n map(() => getComponentElement(\"main\")),\n switchMap(el => watchMain(el, { viewport$, header$ })),\n shareReplay(1)\n )\n\n/* Set up control component observables */\nconst control$ = merge(\n\n /* Consent */\n ...getComponentElements(\"consent\")\n .map(el => mountConsent(el, { target$ })),\n\n /* Dialog */\n ...getComponentElements(\"dialog\")\n .map(el => mountDialog(el, { alert$ })),\n\n /* Color palette */\n ...getComponentElements(\"palette\")\n .map(el => mountPalette(el)),\n\n /* Progress bar */\n ...getComponentElements(\"progress\")\n .map(el => mountProgress(el, { progress$ })),\n\n /* Search */\n ...getComponentElements(\"search\")\n .map(el => mountSearch(el, { index$, keyboard$ })),\n\n /* Repository information */\n ...getComponentElements(\"source\")\n .map(el => mountSource(el))\n)\n\n/* Set up content component observables */\nconst content$ = defer(() => merge(\n\n /* Announcement bar */\n ...getComponentElements(\"announce\")\n .map(el => mountAnnounce(el)),\n\n /* Content */\n ...getComponentElements(\"content\")\n .map(el => mountContent(el, { viewport$, target$, print$ })),\n\n /* Search highlighting */\n ...getComponentElements(\"content\")\n .map(el => feature(\"search.highlight\")\n ? mountSearchHiglight(el, { index$, location$ })\n : EMPTY\n ),\n\n /* Header */\n ...getComponentElements(\"header\")\n .map(el => mountHeader(el, { viewport$, header$, main$ })),\n\n /* Header title */\n ...getComponentElements(\"header-title\")\n .map(el => mountHeaderTitle(el, { viewport$, header$ })),\n\n /* Sidebar */\n ...getComponentElements(\"sidebar\")\n .map(el => el.getAttribute(\"data-md-type\") === \"navigation\"\n ? at(screen$, () => mountSidebar(el, { viewport$, header$, main$ }))\n : at(tablet$, () => mountSidebar(el, { viewport$, header$, main$ }))\n ),\n\n /* Navigation tabs */\n ...getComponentElements(\"tabs\")\n .map(el => mountTabs(el, { viewport$, header$ })),\n\n /* Table of contents */\n ...getComponentElements(\"toc\")\n .map(el => mountTableOfContents(el, {\n viewport$, header$, main$, target$\n })),\n\n /* Back-to-top button */\n ...getComponentElements(\"top\")\n .map(el => mountBackToTop(el, { viewport$, header$, main$, target$ }))\n))\n\n/* Set up component observables */\nconst component$ = document$\n .pipe(\n switchMap(() => content$),\n mergeWith(control$),\n shareReplay(1)\n )\n\n/* Subscribe to all components */\ncomponent$.subscribe()\n\n/* ----------------------------------------------------------------------------\n * Exports\n * ------------------------------------------------------------------------- */\n\nwindow.document$ = document$ /* Document observable */\nwindow.location$ = location$ /* Location subject */\nwindow.target$ = target$ /* Location target observable */\nwindow.keyboard$ = keyboard$ /* Keyboard observable */\nwindow.viewport$ = viewport$ /* Viewport observable */\nwindow.tablet$ = tablet$ /* Media tablet observable */\nwindow.screen$ = screen$ /* Media screen observable */\nwindow.print$ = print$ /* Media print observable */\nwindow.alert$ = alert$ /* Alert subject */\nwindow.progress$ = progress$ /* Progress indicator subject */\nwindow.component$ = component$ /* Component observable */\n", "/******************************************************************************\nCopyright (c) Microsoft Corporation.\n\nPermission to use, copy, modify, and/or distribute this software for any\npurpose with or without fee is hereby granted.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\nREGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\nAND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\nINDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\nLOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\nOTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\nPERFORMANCE OF THIS SOFTWARE.\n***************************************************************************** */\n/* global Reflect, Promise, SuppressedError, Symbol, Iterator */\n\nvar extendStatics = function(d, b) {\n extendStatics = Object.setPrototypeOf ||\n ({ __proto__: [] } instanceof Array && function (d, b) { d.__proto__ = b; }) ||\n function (d, b) { for (var p in b) if (Object.prototype.hasOwnProperty.call(b, p)) d[p] = b[p]; };\n return extendStatics(d, b);\n};\n\nexport function __extends(d, b) {\n if (typeof b !== \"function\" && b !== null)\n throw new TypeError(\"Class extends value \" + String(b) + \" is not a constructor or null\");\n extendStatics(d, b);\n function __() { this.constructor = d; }\n d.prototype = b === null ? Object.create(b) : (__.prototype = b.prototype, new __());\n}\n\nexport var __assign = function() {\n __assign = Object.assign || function __assign(t) {\n for (var s, i = 1, n = arguments.length; i < n; i++) {\n s = arguments[i];\n for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p)) t[p] = s[p];\n }\n return t;\n }\n return __assign.apply(this, arguments);\n}\n\nexport function __rest(s, e) {\n var t = {};\n for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)\n t[p] = s[p];\n if (s != null && typeof Object.getOwnPropertySymbols === \"function\")\n for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {\n if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))\n t[p[i]] = s[p[i]];\n }\n return t;\n}\n\nexport function __decorate(decorators, target, key, desc) {\n var c = arguments.length, r = c < 3 ? target : desc === null ? desc = Object.getOwnPropertyDescriptor(target, key) : desc, d;\n if (typeof Reflect === \"object\" && typeof Reflect.decorate === \"function\") r = Reflect.decorate(decorators, target, key, desc);\n else for (var i = decorators.length - 1; i >= 0; i--) if (d = decorators[i]) r = (c < 3 ? d(r) : c > 3 ? d(target, key, r) : d(target, key)) || r;\n return c > 3 && r && Object.defineProperty(target, key, r), r;\n}\n\nexport function __param(paramIndex, decorator) {\n return function (target, key) { decorator(target, key, paramIndex); }\n}\n\nexport function __esDecorate(ctor, descriptorIn, decorators, contextIn, initializers, extraInitializers) {\n function accept(f) { if (f !== void 0 && typeof f !== \"function\") throw new TypeError(\"Function expected\"); return f; }\n var kind = contextIn.kind, key = kind === \"getter\" ? \"get\" : kind === \"setter\" ? \"set\" : \"value\";\n var target = !descriptorIn && ctor ? contextIn[\"static\"] ? ctor : ctor.prototype : null;\n var descriptor = descriptorIn || (target ? Object.getOwnPropertyDescriptor(target, contextIn.name) : {});\n var _, done = false;\n for (var i = decorators.length - 1; i >= 0; i--) {\n var context = {};\n for (var p in contextIn) context[p] = p === \"access\" ? {} : contextIn[p];\n for (var p in contextIn.access) context.access[p] = contextIn.access[p];\n context.addInitializer = function (f) { if (done) throw new TypeError(\"Cannot add initializers after decoration has completed\"); extraInitializers.push(accept(f || null)); };\n var result = (0, decorators[i])(kind === \"accessor\" ? { get: descriptor.get, set: descriptor.set } : descriptor[key], context);\n if (kind === \"accessor\") {\n if (result === void 0) continue;\n if (result === null || typeof result !== \"object\") throw new TypeError(\"Object expected\");\n if (_ = accept(result.get)) descriptor.get = _;\n if (_ = accept(result.set)) descriptor.set = _;\n if (_ = accept(result.init)) initializers.unshift(_);\n }\n else if (_ = accept(result)) {\n if (kind === \"field\") initializers.unshift(_);\n else descriptor[key] = _;\n }\n }\n if (target) Object.defineProperty(target, contextIn.name, descriptor);\n done = true;\n};\n\nexport function __runInitializers(thisArg, initializers, value) {\n var useValue = arguments.length > 2;\n for (var i = 0; i < initializers.length; i++) {\n value = useValue ? initializers[i].call(thisArg, value) : initializers[i].call(thisArg);\n }\n return useValue ? value : void 0;\n};\n\nexport function __propKey(x) {\n return typeof x === \"symbol\" ? x : \"\".concat(x);\n};\n\nexport function __setFunctionName(f, name, prefix) {\n if (typeof name === \"symbol\") name = name.description ? \"[\".concat(name.description, \"]\") : \"\";\n return Object.defineProperty(f, \"name\", { configurable: true, value: prefix ? \"\".concat(prefix, \" \", name) : name });\n};\n\nexport function __metadata(metadataKey, metadataValue) {\n if (typeof Reflect === \"object\" && typeof Reflect.metadata === \"function\") return Reflect.metadata(metadataKey, metadataValue);\n}\n\nexport function __awaiter(thisArg, _arguments, P, generator) {\n function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }\n return new (P || (P = Promise))(function (resolve, reject) {\n function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }\n function rejected(value) { try { step(generator[\"throw\"](value)); } catch (e) { reject(e); } }\n function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }\n step((generator = generator.apply(thisArg, _arguments || [])).next());\n });\n}\n\nexport function __generator(thisArg, body) {\n var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g = Object.create((typeof Iterator === \"function\" ? Iterator : Object).prototype);\n return g.next = verb(0), g[\"throw\"] = verb(1), g[\"return\"] = verb(2), typeof Symbol === \"function\" && (g[Symbol.iterator] = function() { return this; }), g;\n function verb(n) { return function (v) { return step([n, v]); }; }\n function step(op) {\n if (f) throw new TypeError(\"Generator is already executing.\");\n while (g && (g = 0, op[0] && (_ = 0)), _) try {\n if (f = 1, y && (t = op[0] & 2 ? y[\"return\"] : op[0] ? y[\"throw\"] || ((t = y[\"return\"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;\n if (y = 0, t) op = [op[0] & 2, t.value];\n switch (op[0]) {\n case 0: case 1: t = op; break;\n case 4: _.label++; return { value: op[1], done: false };\n case 5: _.label++; y = op[1]; op = [0]; continue;\n case 7: op = _.ops.pop(); _.trys.pop(); continue;\n default:\n if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }\n if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }\n if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }\n if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }\n if (t[2]) _.ops.pop();\n _.trys.pop(); continue;\n }\n op = body.call(thisArg, _);\n } catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }\n if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };\n }\n}\n\nexport var __createBinding = Object.create ? (function(o, m, k, k2) {\n if (k2 === undefined) k2 = k;\n var desc = Object.getOwnPropertyDescriptor(m, k);\n if (!desc || (\"get\" in desc ? !m.__esModule : desc.writable || desc.configurable)) {\n desc = { enumerable: true, get: function() { return m[k]; } };\n }\n Object.defineProperty(o, k2, desc);\n}) : (function(o, m, k, k2) {\n if (k2 === undefined) k2 = k;\n o[k2] = m[k];\n});\n\nexport function __exportStar(m, o) {\n for (var p in m) if (p !== \"default\" && !Object.prototype.hasOwnProperty.call(o, p)) __createBinding(o, m, p);\n}\n\nexport function __values(o) {\n var s = typeof Symbol === \"function\" && Symbol.iterator, m = s && o[s], i = 0;\n if (m) return m.call(o);\n if (o && typeof o.length === \"number\") return {\n next: function () {\n if (o && i >= o.length) o = void 0;\n return { value: o && o[i++], done: !o };\n }\n };\n throw new TypeError(s ? \"Object is not iterable.\" : \"Symbol.iterator is not defined.\");\n}\n\nexport function __read(o, n) {\n var m = typeof Symbol === \"function\" && o[Symbol.iterator];\n if (!m) return o;\n var i = m.call(o), r, ar = [], e;\n try {\n while ((n === void 0 || n-- > 0) && !(r = i.next()).done) ar.push(r.value);\n }\n catch (error) { e = { error: error }; }\n finally {\n try {\n if (r && !r.done && (m = i[\"return\"])) m.call(i);\n }\n finally { if (e) throw e.error; }\n }\n return ar;\n}\n\n/** @deprecated */\nexport function __spread() {\n for (var ar = [], i = 0; i < arguments.length; i++)\n ar = ar.concat(__read(arguments[i]));\n return ar;\n}\n\n/** @deprecated */\nexport function __spreadArrays() {\n for (var s = 0, i = 0, il = arguments.length; i < il; i++) s += arguments[i].length;\n for (var r = Array(s), k = 0, i = 0; i < il; i++)\n for (var a = arguments[i], j = 0, jl = a.length; j < jl; j++, k++)\n r[k] = a[j];\n return r;\n}\n\nexport function __spreadArray(to, from, pack) {\n if (pack || arguments.length === 2) for (var i = 0, l = from.length, ar; i < l; i++) {\n if (ar || !(i in from)) {\n if (!ar) ar = Array.prototype.slice.call(from, 0, i);\n ar[i] = from[i];\n }\n }\n return to.concat(ar || Array.prototype.slice.call(from));\n}\n\nexport function __await(v) {\n return this instanceof __await ? (this.v = v, this) : new __await(v);\n}\n\nexport function __asyncGenerator(thisArg, _arguments, generator) {\n if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\n var g = generator.apply(thisArg, _arguments || []), i, q = [];\n return i = Object.create((typeof AsyncIterator === \"function\" ? AsyncIterator : Object).prototype), verb(\"next\"), verb(\"throw\"), verb(\"return\", awaitReturn), i[Symbol.asyncIterator] = function () { return this; }, i;\n function awaitReturn(f) { return function (v) { return Promise.resolve(v).then(f, reject); }; }\n function verb(n, f) { if (g[n]) { i[n] = function (v) { return new Promise(function (a, b) { q.push([n, v, a, b]) > 1 || resume(n, v); }); }; if (f) i[n] = f(i[n]); } }\n function resume(n, v) { try { step(g[n](v)); } catch (e) { settle(q[0][3], e); } }\n function step(r) { r.value instanceof __await ? Promise.resolve(r.value.v).then(fulfill, reject) : settle(q[0][2], r); }\n function fulfill(value) { resume(\"next\", value); }\n function reject(value) { resume(\"throw\", value); }\n function settle(f, v) { if (f(v), q.shift(), q.length) resume(q[0][0], q[0][1]); }\n}\n\nexport function __asyncDelegator(o) {\n var i, p;\n return i = {}, verb(\"next\"), verb(\"throw\", function (e) { throw e; }), verb(\"return\"), i[Symbol.iterator] = function () { return this; }, i;\n function verb(n, f) { i[n] = o[n] ? function (v) { return (p = !p) ? { value: __await(o[n](v)), done: false } : f ? f(v) : v; } : f; }\n}\n\nexport function __asyncValues(o) {\n if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\n var m = o[Symbol.asyncIterator], i;\n return m ? m.call(o) : (o = typeof __values === \"function\" ? __values(o) : o[Symbol.iterator](), i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i);\n function verb(n) { i[n] = o[n] && function (v) { return new Promise(function (resolve, reject) { v = o[n](v), settle(resolve, reject, v.done, v.value); }); }; }\n function settle(resolve, reject, d, v) { Promise.resolve(v).then(function(v) { resolve({ value: v, done: d }); }, reject); }\n}\n\nexport function __makeTemplateObject(cooked, raw) {\n if (Object.defineProperty) { Object.defineProperty(cooked, \"raw\", { value: raw }); } else { cooked.raw = raw; }\n return cooked;\n};\n\nvar __setModuleDefault = Object.create ? (function(o, v) {\n Object.defineProperty(o, \"default\", { enumerable: true, value: v });\n}) : function(o, v) {\n o[\"default\"] = v;\n};\n\nexport function __importStar(mod) {\n if (mod && mod.__esModule) return mod;\n var result = {};\n if (mod != null) for (var k in mod) if (k !== \"default\" && Object.prototype.hasOwnProperty.call(mod, k)) __createBinding(result, mod, k);\n __setModuleDefault(result, mod);\n return result;\n}\n\nexport function __importDefault(mod) {\n return (mod && mod.__esModule) ? mod : { default: mod };\n}\n\nexport function __classPrivateFieldGet(receiver, state, kind, f) {\n if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a getter\");\n if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot read private member from an object whose class did not declare it\");\n return kind === \"m\" ? f : kind === \"a\" ? f.call(receiver) : f ? f.value : state.get(receiver);\n}\n\nexport function __classPrivateFieldSet(receiver, state, value, kind, f) {\n if (kind === \"m\") throw new TypeError(\"Private method is not writable\");\n if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a setter\");\n if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot write private member to an object whose class did not declare it\");\n return (kind === \"a\" ? f.call(receiver, value) : f ? f.value = value : state.set(receiver, value)), value;\n}\n\nexport function __classPrivateFieldIn(state, receiver) {\n if (receiver === null || (typeof receiver !== \"object\" && typeof receiver !== \"function\")) throw new TypeError(\"Cannot use 'in' operator on non-object\");\n return typeof state === \"function\" ? receiver === state : state.has(receiver);\n}\n\nexport function __addDisposableResource(env, value, async) {\n if (value !== null && value !== void 0) {\n if (typeof value !== \"object\" && typeof value !== \"function\") throw new TypeError(\"Object expected.\");\n var dispose, inner;\n if (async) {\n if (!Symbol.asyncDispose) throw new TypeError(\"Symbol.asyncDispose is not defined.\");\n dispose = value[Symbol.asyncDispose];\n }\n if (dispose === void 0) {\n if (!Symbol.dispose) throw new TypeError(\"Symbol.dispose is not defined.\");\n dispose = value[Symbol.dispose];\n if (async) inner = dispose;\n }\n if (typeof dispose !== \"function\") throw new TypeError(\"Object not disposable.\");\n if (inner) dispose = function() { try { inner.call(this); } catch (e) { return Promise.reject(e); } };\n env.stack.push({ value: value, dispose: dispose, async: async });\n }\n else if (async) {\n env.stack.push({ async: true });\n }\n return value;\n}\n\nvar _SuppressedError = typeof SuppressedError === \"function\" ? SuppressedError : function (error, suppressed, message) {\n var e = new Error(message);\n return e.name = \"SuppressedError\", e.error = error, e.suppressed = suppressed, e;\n};\n\nexport function __disposeResources(env) {\n function fail(e) {\n env.error = env.hasError ? new _SuppressedError(e, env.error, \"An error was suppressed during disposal.\") : e;\n env.hasError = true;\n }\n var r, s = 0;\n function next() {\n while (r = env.stack.pop()) {\n try {\n if (!r.async && s === 1) return s = 0, env.stack.push(r), Promise.resolve().then(next);\n if (r.dispose) {\n var result = r.dispose.call(r.value);\n if (r.async) return s |= 2, Promise.resolve(result).then(next, function(e) { fail(e); return next(); });\n }\n else s |= 1;\n }\n catch (e) {\n fail(e);\n }\n }\n if (s === 1) return env.hasError ? Promise.reject(env.error) : Promise.resolve();\n if (env.hasError) throw env.error;\n }\n return next();\n}\n\nexport default {\n __extends,\n __assign,\n __rest,\n __decorate,\n __param,\n __metadata,\n __awaiter,\n __generator,\n __createBinding,\n __exportStar,\n __values,\n __read,\n __spread,\n __spreadArrays,\n __spreadArray,\n __await,\n __asyncGenerator,\n __asyncDelegator,\n __asyncValues,\n __makeTemplateObject,\n __importStar,\n __importDefault,\n __classPrivateFieldGet,\n __classPrivateFieldSet,\n __classPrivateFieldIn,\n __addDisposableResource,\n __disposeResources,\n};\n", "/**\n * Returns true if the object is a function.\n * @param value The value to check\n */\nexport function isFunction(value: any): value is (...args: any[]) => any {\n return typeof value === 'function';\n}\n", "/**\n * Used to create Error subclasses until the community moves away from ES5.\n *\n * This is because compiling from TypeScript down to ES5 has issues with subclassing Errors\n * as well as other built-in types: https://github.com/Microsoft/TypeScript/issues/12123\n *\n * @param createImpl A factory function to create the actual constructor implementation. The returned\n * function should be a named function that calls `_super` internally.\n */\nexport function createErrorClass(createImpl: (_super: any) => any): T {\n const _super = (instance: any) => {\n Error.call(instance);\n instance.stack = new Error().stack;\n };\n\n const ctorFunc = createImpl(_super);\n ctorFunc.prototype = Object.create(Error.prototype);\n ctorFunc.prototype.constructor = ctorFunc;\n return ctorFunc;\n}\n", "import { createErrorClass } from './createErrorClass';\n\nexport interface UnsubscriptionError extends Error {\n readonly errors: any[];\n}\n\nexport interface UnsubscriptionErrorCtor {\n /**\n * @deprecated Internal implementation detail. Do not construct error instances.\n * Cannot be tagged as internal: https://github.com/ReactiveX/rxjs/issues/6269\n */\n new (errors: any[]): UnsubscriptionError;\n}\n\n/**\n * An error thrown when one or more errors have occurred during the\n * `unsubscribe` of a {@link Subscription}.\n */\nexport const UnsubscriptionError: UnsubscriptionErrorCtor = createErrorClass(\n (_super) =>\n function UnsubscriptionErrorImpl(this: any, errors: (Error | string)[]) {\n _super(this);\n this.message = errors\n ? `${errors.length} errors occurred during unsubscription:\n${errors.map((err, i) => `${i + 1}) ${err.toString()}`).join('\\n ')}`\n : '';\n this.name = 'UnsubscriptionError';\n this.errors = errors;\n }\n);\n", "/**\n * Removes an item from an array, mutating it.\n * @param arr The array to remove the item from\n * @param item The item to remove\n */\nexport function arrRemove(arr: T[] | undefined | null, item: T) {\n if (arr) {\n const index = arr.indexOf(item);\n 0 <= index && arr.splice(index, 1);\n }\n}\n", "import { isFunction } from './util/isFunction';\nimport { UnsubscriptionError } from './util/UnsubscriptionError';\nimport { SubscriptionLike, TeardownLogic, Unsubscribable } from './types';\nimport { arrRemove } from './util/arrRemove';\n\n/**\n * Represents a disposable resource, such as the execution of an Observable. A\n * Subscription has one important method, `unsubscribe`, that takes no argument\n * and just disposes the resource held by the subscription.\n *\n * Additionally, subscriptions may be grouped together through the `add()`\n * method, which will attach a child Subscription to the current Subscription.\n * When a Subscription is unsubscribed, all its children (and its grandchildren)\n * will be unsubscribed as well.\n *\n * @class Subscription\n */\nexport class Subscription implements SubscriptionLike {\n /** @nocollapse */\n public static EMPTY = (() => {\n const empty = new Subscription();\n empty.closed = true;\n return empty;\n })();\n\n /**\n * A flag to indicate whether this Subscription has already been unsubscribed.\n */\n public closed = false;\n\n private _parentage: Subscription[] | Subscription | null = null;\n\n /**\n * The list of registered finalizers to execute upon unsubscription. Adding and removing from this\n * list occurs in the {@link #add} and {@link #remove} methods.\n */\n private _finalizers: Exclude[] | null = null;\n\n /**\n * @param initialTeardown A function executed first as part of the finalization\n * process that is kicked off when {@link #unsubscribe} is called.\n */\n constructor(private initialTeardown?: () => void) {}\n\n /**\n * Disposes the resources held by the subscription. May, for instance, cancel\n * an ongoing Observable execution or cancel any other type of work that\n * started when the Subscription was created.\n * @return {void}\n */\n unsubscribe(): void {\n let errors: any[] | undefined;\n\n if (!this.closed) {\n this.closed = true;\n\n // Remove this from it's parents.\n const { _parentage } = this;\n if (_parentage) {\n this._parentage = null;\n if (Array.isArray(_parentage)) {\n for (const parent of _parentage) {\n parent.remove(this);\n }\n } else {\n _parentage.remove(this);\n }\n }\n\n const { initialTeardown: initialFinalizer } = this;\n if (isFunction(initialFinalizer)) {\n try {\n initialFinalizer();\n } catch (e) {\n errors = e instanceof UnsubscriptionError ? e.errors : [e];\n }\n }\n\n const { _finalizers } = this;\n if (_finalizers) {\n this._finalizers = null;\n for (const finalizer of _finalizers) {\n try {\n execFinalizer(finalizer);\n } catch (err) {\n errors = errors ?? [];\n if (err instanceof UnsubscriptionError) {\n errors = [...errors, ...err.errors];\n } else {\n errors.push(err);\n }\n }\n }\n }\n\n if (errors) {\n throw new UnsubscriptionError(errors);\n }\n }\n }\n\n /**\n * Adds a finalizer to this subscription, so that finalization will be unsubscribed/called\n * when this subscription is unsubscribed. If this subscription is already {@link #closed},\n * because it has already been unsubscribed, then whatever finalizer is passed to it\n * will automatically be executed (unless the finalizer itself is also a closed subscription).\n *\n * Closed Subscriptions cannot be added as finalizers to any subscription. Adding a closed\n * subscription to a any subscription will result in no operation. (A noop).\n *\n * Adding a subscription to itself, or adding `null` or `undefined` will not perform any\n * operation at all. (A noop).\n *\n * `Subscription` instances that are added to this instance will automatically remove themselves\n * if they are unsubscribed. Functions and {@link Unsubscribable} objects that you wish to remove\n * will need to be removed manually with {@link #remove}\n *\n * @param teardown The finalization logic to add to this subscription.\n */\n add(teardown: TeardownLogic): void {\n // Only add the finalizer if it's not undefined\n // and don't add a subscription to itself.\n if (teardown && teardown !== this) {\n if (this.closed) {\n // If this subscription is already closed,\n // execute whatever finalizer is handed to it automatically.\n execFinalizer(teardown);\n } else {\n if (teardown instanceof Subscription) {\n // We don't add closed subscriptions, and we don't add the same subscription\n // twice. Subscription unsubscribe is idempotent.\n if (teardown.closed || teardown._hasParent(this)) {\n return;\n }\n teardown._addParent(this);\n }\n (this._finalizers = this._finalizers ?? []).push(teardown);\n }\n }\n }\n\n /**\n * Checks to see if a this subscription already has a particular parent.\n * This will signal that this subscription has already been added to the parent in question.\n * @param parent the parent to check for\n */\n private _hasParent(parent: Subscription) {\n const { _parentage } = this;\n return _parentage === parent || (Array.isArray(_parentage) && _parentage.includes(parent));\n }\n\n /**\n * Adds a parent to this subscription so it can be removed from the parent if it\n * unsubscribes on it's own.\n *\n * NOTE: THIS ASSUMES THAT {@link _hasParent} HAS ALREADY BEEN CHECKED.\n * @param parent The parent subscription to add\n */\n private _addParent(parent: Subscription) {\n const { _parentage } = this;\n this._parentage = Array.isArray(_parentage) ? (_parentage.push(parent), _parentage) : _parentage ? [_parentage, parent] : parent;\n }\n\n /**\n * Called on a child when it is removed via {@link #remove}.\n * @param parent The parent to remove\n */\n private _removeParent(parent: Subscription) {\n const { _parentage } = this;\n if (_parentage === parent) {\n this._parentage = null;\n } else if (Array.isArray(_parentage)) {\n arrRemove(_parentage, parent);\n }\n }\n\n /**\n * Removes a finalizer from this subscription that was previously added with the {@link #add} method.\n *\n * Note that `Subscription` instances, when unsubscribed, will automatically remove themselves\n * from every other `Subscription` they have been added to. This means that using the `remove` method\n * is not a common thing and should be used thoughtfully.\n *\n * If you add the same finalizer instance of a function or an unsubscribable object to a `Subscription` instance\n * more than once, you will need to call `remove` the same number of times to remove all instances.\n *\n * All finalizer instances are removed to free up memory upon unsubscription.\n *\n * @param teardown The finalizer to remove from this subscription\n */\n remove(teardown: Exclude): void {\n const { _finalizers } = this;\n _finalizers && arrRemove(_finalizers, teardown);\n\n if (teardown instanceof Subscription) {\n teardown._removeParent(this);\n }\n }\n}\n\nexport const EMPTY_SUBSCRIPTION = Subscription.EMPTY;\n\nexport function isSubscription(value: any): value is Subscription {\n return (\n value instanceof Subscription ||\n (value && 'closed' in value && isFunction(value.remove) && isFunction(value.add) && isFunction(value.unsubscribe))\n );\n}\n\nfunction execFinalizer(finalizer: Unsubscribable | (() => void)) {\n if (isFunction(finalizer)) {\n finalizer();\n } else {\n finalizer.unsubscribe();\n }\n}\n", "import { Subscriber } from './Subscriber';\nimport { ObservableNotification } from './types';\n\n/**\n * The {@link GlobalConfig} object for RxJS. It is used to configure things\n * like how to react on unhandled errors.\n */\nexport const config: GlobalConfig = {\n onUnhandledError: null,\n onStoppedNotification: null,\n Promise: undefined,\n useDeprecatedSynchronousErrorHandling: false,\n useDeprecatedNextContext: false,\n};\n\n/**\n * The global configuration object for RxJS, used to configure things\n * like how to react on unhandled errors. Accessible via {@link config}\n * object.\n */\nexport interface GlobalConfig {\n /**\n * A registration point for unhandled errors from RxJS. These are errors that\n * cannot were not handled by consuming code in the usual subscription path. For\n * example, if you have this configured, and you subscribe to an observable without\n * providing an error handler, errors from that subscription will end up here. This\n * will _always_ be called asynchronously on another job in the runtime. This is because\n * we do not want errors thrown in this user-configured handler to interfere with the\n * behavior of the library.\n */\n onUnhandledError: ((err: any) => void) | null;\n\n /**\n * A registration point for notifications that cannot be sent to subscribers because they\n * have completed, errored or have been explicitly unsubscribed. By default, next, complete\n * and error notifications sent to stopped subscribers are noops. However, sometimes callers\n * might want a different behavior. For example, with sources that attempt to report errors\n * to stopped subscribers, a caller can configure RxJS to throw an unhandled error instead.\n * This will _always_ be called asynchronously on another job in the runtime. This is because\n * we do not want errors thrown in this user-configured handler to interfere with the\n * behavior of the library.\n */\n onStoppedNotification: ((notification: ObservableNotification, subscriber: Subscriber) => void) | null;\n\n /**\n * The promise constructor used by default for {@link Observable#toPromise toPromise} and {@link Observable#forEach forEach}\n * methods.\n *\n * @deprecated As of version 8, RxJS will no longer support this sort of injection of a\n * Promise constructor. If you need a Promise implementation other than native promises,\n * please polyfill/patch Promise as you see appropriate. Will be removed in v8.\n */\n Promise?: PromiseConstructorLike;\n\n /**\n * If true, turns on synchronous error rethrowing, which is a deprecated behavior\n * in v6 and higher. This behavior enables bad patterns like wrapping a subscribe\n * call in a try/catch block. It also enables producer interference, a nasty bug\n * where a multicast can be broken for all observers by a downstream consumer with\n * an unhandled error. DO NOT USE THIS FLAG UNLESS IT'S NEEDED TO BUY TIME\n * FOR MIGRATION REASONS.\n *\n * @deprecated As of version 8, RxJS will no longer support synchronous throwing\n * of unhandled errors. All errors will be thrown on a separate call stack to prevent bad\n * behaviors described above. Will be removed in v8.\n */\n useDeprecatedSynchronousErrorHandling: boolean;\n\n /**\n * If true, enables an as-of-yet undocumented feature from v5: The ability to access\n * `unsubscribe()` via `this` context in `next` functions created in observers passed\n * to `subscribe`.\n *\n * This is being removed because the performance was severely problematic, and it could also cause\n * issues when types other than POJOs are passed to subscribe as subscribers, as they will likely have\n * their `this` context overwritten.\n *\n * @deprecated As of version 8, RxJS will no longer support altering the\n * context of next functions provided as part of an observer to Subscribe. Instead,\n * you will have access to a subscription or a signal or token that will allow you to do things like\n * unsubscribe and test closed status. Will be removed in v8.\n */\n useDeprecatedNextContext: boolean;\n}\n", "import type { TimerHandle } from './timerHandle';\ntype SetTimeoutFunction = (handler: () => void, timeout?: number, ...args: any[]) => TimerHandle;\ntype ClearTimeoutFunction = (handle: TimerHandle) => void;\n\ninterface TimeoutProvider {\n setTimeout: SetTimeoutFunction;\n clearTimeout: ClearTimeoutFunction;\n delegate:\n | {\n setTimeout: SetTimeoutFunction;\n clearTimeout: ClearTimeoutFunction;\n }\n | undefined;\n}\n\nexport const timeoutProvider: TimeoutProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n setTimeout(handler: () => void, timeout?: number, ...args) {\n const { delegate } = timeoutProvider;\n if (delegate?.setTimeout) {\n return delegate.setTimeout(handler, timeout, ...args);\n }\n return setTimeout(handler, timeout, ...args);\n },\n clearTimeout(handle) {\n const { delegate } = timeoutProvider;\n return (delegate?.clearTimeout || clearTimeout)(handle as any);\n },\n delegate: undefined,\n};\n", "import { config } from '../config';\nimport { timeoutProvider } from '../scheduler/timeoutProvider';\n\n/**\n * Handles an error on another job either with the user-configured {@link onUnhandledError},\n * or by throwing it on that new job so it can be picked up by `window.onerror`, `process.on('error')`, etc.\n *\n * This should be called whenever there is an error that is out-of-band with the subscription\n * or when an error hits a terminal boundary of the subscription and no error handler was provided.\n *\n * @param err the error to report\n */\nexport function reportUnhandledError(err: any) {\n timeoutProvider.setTimeout(() => {\n const { onUnhandledError } = config;\n if (onUnhandledError) {\n // Execute the user-configured error handler.\n onUnhandledError(err);\n } else {\n // Throw so it is picked up by the runtime's uncaught error mechanism.\n throw err;\n }\n });\n}\n", "/* tslint:disable:no-empty */\nexport function noop() { }\n", "import { CompleteNotification, NextNotification, ErrorNotification } from './types';\n\n/**\n * A completion object optimized for memory use and created to be the\n * same \"shape\" as other notifications in v8.\n * @internal\n */\nexport const COMPLETE_NOTIFICATION = (() => createNotification('C', undefined, undefined) as CompleteNotification)();\n\n/**\n * Internal use only. Creates an optimized error notification that is the same \"shape\"\n * as other notifications.\n * @internal\n */\nexport function errorNotification(error: any): ErrorNotification {\n return createNotification('E', undefined, error) as any;\n}\n\n/**\n * Internal use only. Creates an optimized next notification that is the same \"shape\"\n * as other notifications.\n * @internal\n */\nexport function nextNotification(value: T) {\n return createNotification('N', value, undefined) as NextNotification;\n}\n\n/**\n * Ensures that all notifications created internally have the same \"shape\" in v8.\n *\n * TODO: This is only exported to support a crazy legacy test in `groupBy`.\n * @internal\n */\nexport function createNotification(kind: 'N' | 'E' | 'C', value: any, error: any) {\n return {\n kind,\n value,\n error,\n };\n}\n", "import { config } from '../config';\n\nlet context: { errorThrown: boolean; error: any } | null = null;\n\n/**\n * Handles dealing with errors for super-gross mode. Creates a context, in which\n * any synchronously thrown errors will be passed to {@link captureError}. Which\n * will record the error such that it will be rethrown after the call back is complete.\n * TODO: Remove in v8\n * @param cb An immediately executed function.\n */\nexport function errorContext(cb: () => void) {\n if (config.useDeprecatedSynchronousErrorHandling) {\n const isRoot = !context;\n if (isRoot) {\n context = { errorThrown: false, error: null };\n }\n cb();\n if (isRoot) {\n const { errorThrown, error } = context!;\n context = null;\n if (errorThrown) {\n throw error;\n }\n }\n } else {\n // This is the general non-deprecated path for everyone that\n // isn't crazy enough to use super-gross mode (useDeprecatedSynchronousErrorHandling)\n cb();\n }\n}\n\n/**\n * Captures errors only in super-gross mode.\n * @param err the error to capture\n */\nexport function captureError(err: any) {\n if (config.useDeprecatedSynchronousErrorHandling && context) {\n context.errorThrown = true;\n context.error = err;\n }\n}\n", "import { isFunction } from './util/isFunction';\nimport { Observer, ObservableNotification } from './types';\nimport { isSubscription, Subscription } from './Subscription';\nimport { config } from './config';\nimport { reportUnhandledError } from './util/reportUnhandledError';\nimport { noop } from './util/noop';\nimport { nextNotification, errorNotification, COMPLETE_NOTIFICATION } from './NotificationFactories';\nimport { timeoutProvider } from './scheduler/timeoutProvider';\nimport { captureError } from './util/errorContext';\n\n/**\n * Implements the {@link Observer} interface and extends the\n * {@link Subscription} class. While the {@link Observer} is the public API for\n * consuming the values of an {@link Observable}, all Observers get converted to\n * a Subscriber, in order to provide Subscription-like capabilities such as\n * `unsubscribe`. Subscriber is a common type in RxJS, and crucial for\n * implementing operators, but it is rarely used as a public API.\n *\n * @class Subscriber\n */\nexport class Subscriber extends Subscription implements Observer {\n /**\n * A static factory for a Subscriber, given a (potentially partial) definition\n * of an Observer.\n * @param next The `next` callback of an Observer.\n * @param error The `error` callback of an\n * Observer.\n * @param complete The `complete` callback of an\n * Observer.\n * @return A Subscriber wrapping the (partially defined)\n * Observer represented by the given arguments.\n * @nocollapse\n * @deprecated Do not use. Will be removed in v8. There is no replacement for this\n * method, and there is no reason to be creating instances of `Subscriber` directly.\n * If you have a specific use case, please file an issue.\n */\n static create(next?: (x?: T) => void, error?: (e?: any) => void, complete?: () => void): Subscriber {\n return new SafeSubscriber(next, error, complete);\n }\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n protected isStopped: boolean = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n protected destination: Subscriber | Observer; // this `any` is the escape hatch to erase extra type param (e.g. R)\n\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n * There is no reason to directly create an instance of Subscriber. This type is exported for typings reasons.\n */\n constructor(destination?: Subscriber | Observer) {\n super();\n if (destination) {\n this.destination = destination;\n // Automatically chain subscriptions together here.\n // if destination is a Subscription, then it is a Subscriber.\n if (isSubscription(destination)) {\n destination.add(this);\n }\n } else {\n this.destination = EMPTY_OBSERVER;\n }\n }\n\n /**\n * The {@link Observer} callback to receive notifications of type `next` from\n * the Observable, with a value. The Observable may call this method 0 or more\n * times.\n * @param {T} [value] The `next` value.\n * @return {void}\n */\n next(value?: T): void {\n if (this.isStopped) {\n handleStoppedNotification(nextNotification(value), this);\n } else {\n this._next(value!);\n }\n }\n\n /**\n * The {@link Observer} callback to receive notifications of type `error` from\n * the Observable, with an attached `Error`. Notifies the Observer that\n * the Observable has experienced an error condition.\n * @param {any} [err] The `error` exception.\n * @return {void}\n */\n error(err?: any): void {\n if (this.isStopped) {\n handleStoppedNotification(errorNotification(err), this);\n } else {\n this.isStopped = true;\n this._error(err);\n }\n }\n\n /**\n * The {@link Observer} callback to receive a valueless notification of type\n * `complete` from the Observable. Notifies the Observer that the Observable\n * has finished sending push-based notifications.\n * @return {void}\n */\n complete(): void {\n if (this.isStopped) {\n handleStoppedNotification(COMPLETE_NOTIFICATION, this);\n } else {\n this.isStopped = true;\n this._complete();\n }\n }\n\n unsubscribe(): void {\n if (!this.closed) {\n this.isStopped = true;\n super.unsubscribe();\n this.destination = null!;\n }\n }\n\n protected _next(value: T): void {\n this.destination.next(value);\n }\n\n protected _error(err: any): void {\n try {\n this.destination.error(err);\n } finally {\n this.unsubscribe();\n }\n }\n\n protected _complete(): void {\n try {\n this.destination.complete();\n } finally {\n this.unsubscribe();\n }\n }\n}\n\n/**\n * This bind is captured here because we want to be able to have\n * compatibility with monoid libraries that tend to use a method named\n * `bind`. In particular, a library called Monio requires this.\n */\nconst _bind = Function.prototype.bind;\n\nfunction bind any>(fn: Fn, thisArg: any): Fn {\n return _bind.call(fn, thisArg);\n}\n\n/**\n * Internal optimization only, DO NOT EXPOSE.\n * @internal\n */\nclass ConsumerObserver implements Observer {\n constructor(private partialObserver: Partial>) {}\n\n next(value: T): void {\n const { partialObserver } = this;\n if (partialObserver.next) {\n try {\n partialObserver.next(value);\n } catch (error) {\n handleUnhandledError(error);\n }\n }\n }\n\n error(err: any): void {\n const { partialObserver } = this;\n if (partialObserver.error) {\n try {\n partialObserver.error(err);\n } catch (error) {\n handleUnhandledError(error);\n }\n } else {\n handleUnhandledError(err);\n }\n }\n\n complete(): void {\n const { partialObserver } = this;\n if (partialObserver.complete) {\n try {\n partialObserver.complete();\n } catch (error) {\n handleUnhandledError(error);\n }\n }\n }\n}\n\nexport class SafeSubscriber extends Subscriber {\n constructor(\n observerOrNext?: Partial> | ((value: T) => void) | null,\n error?: ((e?: any) => void) | null,\n complete?: (() => void) | null\n ) {\n super();\n\n let partialObserver: Partial>;\n if (isFunction(observerOrNext) || !observerOrNext) {\n // The first argument is a function, not an observer. The next\n // two arguments *could* be observers, or they could be empty.\n partialObserver = {\n next: (observerOrNext ?? undefined) as (((value: T) => void) | undefined),\n error: error ?? undefined,\n complete: complete ?? undefined,\n };\n } else {\n // The first argument is a partial observer.\n let context: any;\n if (this && config.useDeprecatedNextContext) {\n // This is a deprecated path that made `this.unsubscribe()` available in\n // next handler functions passed to subscribe. This only exists behind a flag\n // now, as it is *very* slow.\n context = Object.create(observerOrNext);\n context.unsubscribe = () => this.unsubscribe();\n partialObserver = {\n next: observerOrNext.next && bind(observerOrNext.next, context),\n error: observerOrNext.error && bind(observerOrNext.error, context),\n complete: observerOrNext.complete && bind(observerOrNext.complete, context),\n };\n } else {\n // The \"normal\" path. Just use the partial observer directly.\n partialObserver = observerOrNext;\n }\n }\n\n // Wrap the partial observer to ensure it's a full observer, and\n // make sure proper error handling is accounted for.\n this.destination = new ConsumerObserver(partialObserver);\n }\n}\n\nfunction handleUnhandledError(error: any) {\n if (config.useDeprecatedSynchronousErrorHandling) {\n captureError(error);\n } else {\n // Ideal path, we report this as an unhandled error,\n // which is thrown on a new call stack.\n reportUnhandledError(error);\n }\n}\n\n/**\n * An error handler used when no error handler was supplied\n * to the SafeSubscriber -- meaning no error handler was supplied\n * do the `subscribe` call on our observable.\n * @param err The error to handle\n */\nfunction defaultErrorHandler(err: any) {\n throw err;\n}\n\n/**\n * A handler for notifications that cannot be sent to a stopped subscriber.\n * @param notification The notification being sent\n * @param subscriber The stopped subscriber\n */\nfunction handleStoppedNotification(notification: ObservableNotification, subscriber: Subscriber) {\n const { onStoppedNotification } = config;\n onStoppedNotification && timeoutProvider.setTimeout(() => onStoppedNotification(notification, subscriber));\n}\n\n/**\n * The observer used as a stub for subscriptions where the user did not\n * pass any arguments to `subscribe`. Comes with the default error handling\n * behavior.\n */\nexport const EMPTY_OBSERVER: Readonly> & { closed: true } = {\n closed: true,\n next: noop,\n error: defaultErrorHandler,\n complete: noop,\n};\n", "/**\n * Symbol.observable or a string \"@@observable\". Used for interop\n *\n * @deprecated We will no longer be exporting this symbol in upcoming versions of RxJS.\n * Instead polyfill and use Symbol.observable directly *or* use https://www.npmjs.com/package/symbol-observable\n */\nexport const observable: string | symbol = (() => (typeof Symbol === 'function' && Symbol.observable) || '@@observable')();\n", "/**\n * This function takes one parameter and just returns it. Simply put,\n * this is like `(x: T): T => x`.\n *\n * ## Examples\n *\n * This is useful in some cases when using things like `mergeMap`\n *\n * ```ts\n * import { interval, take, map, range, mergeMap, identity } from 'rxjs';\n *\n * const source$ = interval(1000).pipe(take(5));\n *\n * const result$ = source$.pipe(\n * map(i => range(i)),\n * mergeMap(identity) // same as mergeMap(x => x)\n * );\n *\n * result$.subscribe({\n * next: console.log\n * });\n * ```\n *\n * Or when you want to selectively apply an operator\n *\n * ```ts\n * import { interval, take, identity } from 'rxjs';\n *\n * const shouldLimit = () => Math.random() < 0.5;\n *\n * const source$ = interval(1000);\n *\n * const result$ = source$.pipe(shouldLimit() ? take(5) : identity);\n *\n * result$.subscribe({\n * next: console.log\n * });\n * ```\n *\n * @param x Any value that is returned by this function\n * @returns The value passed as the first parameter to this function\n */\nexport function identity(x: T): T {\n return x;\n}\n", "import { identity } from './identity';\nimport { UnaryFunction } from '../types';\n\nexport function pipe(): typeof identity;\nexport function pipe(fn1: UnaryFunction): UnaryFunction;\nexport function pipe(fn1: UnaryFunction, fn2: UnaryFunction): UnaryFunction;\nexport function pipe(fn1: UnaryFunction, fn2: UnaryFunction, fn3: UnaryFunction): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction,\n fn9: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction,\n fn9: UnaryFunction,\n ...fns: UnaryFunction[]\n): UnaryFunction;\n\n/**\n * pipe() can be called on one or more functions, each of which can take one argument (\"UnaryFunction\")\n * and uses it to return a value.\n * It returns a function that takes one argument, passes it to the first UnaryFunction, and then\n * passes the result to the next one, passes that result to the next one, and so on. \n */\nexport function pipe(...fns: Array>): UnaryFunction {\n return pipeFromArray(fns);\n}\n\n/** @internal */\nexport function pipeFromArray(fns: Array>): UnaryFunction {\n if (fns.length === 0) {\n return identity as UnaryFunction;\n }\n\n if (fns.length === 1) {\n return fns[0];\n }\n\n return function piped(input: T): R {\n return fns.reduce((prev: any, fn: UnaryFunction) => fn(prev), input as any);\n };\n}\n", "import { Operator } from './Operator';\nimport { SafeSubscriber, Subscriber } from './Subscriber';\nimport { isSubscription, Subscription } from './Subscription';\nimport { TeardownLogic, OperatorFunction, Subscribable, Observer } from './types';\nimport { observable as Symbol_observable } from './symbol/observable';\nimport { pipeFromArray } from './util/pipe';\nimport { config } from './config';\nimport { isFunction } from './util/isFunction';\nimport { errorContext } from './util/errorContext';\n\n/**\n * A representation of any set of values over any amount of time. This is the most basic building block\n * of RxJS.\n *\n * @class Observable\n */\nexport class Observable implements Subscribable {\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n */\n source: Observable | undefined;\n\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n */\n operator: Operator | undefined;\n\n /**\n * @constructor\n * @param {Function} subscribe the function that is called when the Observable is\n * initially subscribed to. This function is given a Subscriber, to which new values\n * can be `next`ed, or an `error` method can be called to raise an error, or\n * `complete` can be called to notify of a successful completion.\n */\n constructor(subscribe?: (this: Observable, subscriber: Subscriber) => TeardownLogic) {\n if (subscribe) {\n this._subscribe = subscribe;\n }\n }\n\n // HACK: Since TypeScript inherits static properties too, we have to\n // fight against TypeScript here so Subject can have a different static create signature\n /**\n * Creates a new Observable by calling the Observable constructor\n * @owner Observable\n * @method create\n * @param {Function} subscribe? the subscriber function to be passed to the Observable constructor\n * @return {Observable} a new observable\n * @nocollapse\n * @deprecated Use `new Observable()` instead. Will be removed in v8.\n */\n static create: (...args: any[]) => any = (subscribe?: (subscriber: Subscriber) => TeardownLogic) => {\n return new Observable(subscribe);\n };\n\n /**\n * Creates a new Observable, with this Observable instance as the source, and the passed\n * operator defined as the new observable's operator.\n * @method lift\n * @param operator the operator defining the operation to take on the observable\n * @return a new observable with the Operator applied\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n * If you have implemented an operator using `lift`, it is recommended that you create an\n * operator by simply returning `new Observable()` directly. See \"Creating new operators from\n * scratch\" section here: https://rxjs.dev/guide/operators\n */\n lift(operator?: Operator): Observable {\n const observable = new Observable();\n observable.source = this;\n observable.operator = operator;\n return observable;\n }\n\n subscribe(observerOrNext?: Partial> | ((value: T) => void)): Subscription;\n /** @deprecated Instead of passing separate callback arguments, use an observer argument. Signatures taking separate callback arguments will be removed in v8. Details: https://rxjs.dev/deprecations/subscribe-arguments */\n subscribe(next?: ((value: T) => void) | null, error?: ((error: any) => void) | null, complete?: (() => void) | null): Subscription;\n /**\n * Invokes an execution of an Observable and registers Observer handlers for notifications it will emit.\n *\n * Use it when you have all these Observables, but still nothing is happening.\n *\n * `subscribe` is not a regular operator, but a method that calls Observable's internal `subscribe` function. It\n * might be for example a function that you passed to Observable's constructor, but most of the time it is\n * a library implementation, which defines what will be emitted by an Observable, and when it be will emitted. This means\n * that calling `subscribe` is actually the moment when Observable starts its work, not when it is created, as it is often\n * the thought.\n *\n * Apart from starting the execution of an Observable, this method allows you to listen for values\n * that an Observable emits, as well as for when it completes or errors. You can achieve this in two\n * of the following ways.\n *\n * The first way is creating an object that implements {@link Observer} interface. It should have methods\n * defined by that interface, but note that it should be just a regular JavaScript object, which you can create\n * yourself in any way you want (ES6 class, classic function constructor, object literal etc.). In particular, do\n * not attempt to use any RxJS implementation details to create Observers - you don't need them. Remember also\n * that your object does not have to implement all methods. If you find yourself creating a method that doesn't\n * do anything, you can simply omit it. Note however, if the `error` method is not provided and an error happens,\n * it will be thrown asynchronously. Errors thrown asynchronously cannot be caught using `try`/`catch`. Instead,\n * use the {@link onUnhandledError} configuration option or use a runtime handler (like `window.onerror` or\n * `process.on('error)`) to be notified of unhandled errors. Because of this, it's recommended that you provide\n * an `error` method to avoid missing thrown errors.\n *\n * The second way is to give up on Observer object altogether and simply provide callback functions in place of its methods.\n * This means you can provide three functions as arguments to `subscribe`, where the first function is equivalent\n * of a `next` method, the second of an `error` method and the third of a `complete` method. Just as in case of an Observer,\n * if you do not need to listen for something, you can omit a function by passing `undefined` or `null`,\n * since `subscribe` recognizes these functions by where they were placed in function call. When it comes\n * to the `error` function, as with an Observer, if not provided, errors emitted by an Observable will be thrown asynchronously.\n *\n * You can, however, subscribe with no parameters at all. This may be the case where you're not interested in terminal events\n * and you also handled emissions internally by using operators (e.g. using `tap`).\n *\n * Whichever style of calling `subscribe` you use, in both cases it returns a Subscription object.\n * This object allows you to call `unsubscribe` on it, which in turn will stop the work that an Observable does and will clean\n * up all resources that an Observable used. Note that cancelling a subscription will not call `complete` callback\n * provided to `subscribe` function, which is reserved for a regular completion signal that comes from an Observable.\n *\n * Remember that callbacks provided to `subscribe` are not guaranteed to be called asynchronously.\n * It is an Observable itself that decides when these functions will be called. For example {@link of}\n * by default emits all its values synchronously. Always check documentation for how given Observable\n * will behave when subscribed and if its default behavior can be modified with a `scheduler`.\n *\n * #### Examples\n *\n * Subscribe with an {@link guide/observer Observer}\n *\n * ```ts\n * import { of } from 'rxjs';\n *\n * const sumObserver = {\n * sum: 0,\n * next(value) {\n * console.log('Adding: ' + value);\n * this.sum = this.sum + value;\n * },\n * error() {\n * // We actually could just remove this method,\n * // since we do not really care about errors right now.\n * },\n * complete() {\n * console.log('Sum equals: ' + this.sum);\n * }\n * };\n *\n * of(1, 2, 3) // Synchronously emits 1, 2, 3 and then completes.\n * .subscribe(sumObserver);\n *\n * // Logs:\n * // 'Adding: 1'\n * // 'Adding: 2'\n * // 'Adding: 3'\n * // 'Sum equals: 6'\n * ```\n *\n * Subscribe with functions ({@link deprecations/subscribe-arguments deprecated})\n *\n * ```ts\n * import { of } from 'rxjs'\n *\n * let sum = 0;\n *\n * of(1, 2, 3).subscribe(\n * value => {\n * console.log('Adding: ' + value);\n * sum = sum + value;\n * },\n * undefined,\n * () => console.log('Sum equals: ' + sum)\n * );\n *\n * // Logs:\n * // 'Adding: 1'\n * // 'Adding: 2'\n * // 'Adding: 3'\n * // 'Sum equals: 6'\n * ```\n *\n * Cancel a subscription\n *\n * ```ts\n * import { interval } from 'rxjs';\n *\n * const subscription = interval(1000).subscribe({\n * next(num) {\n * console.log(num)\n * },\n * complete() {\n * // Will not be called, even when cancelling subscription.\n * console.log('completed!');\n * }\n * });\n *\n * setTimeout(() => {\n * subscription.unsubscribe();\n * console.log('unsubscribed!');\n * }, 2500);\n *\n * // Logs:\n * // 0 after 1s\n * // 1 after 2s\n * // 'unsubscribed!' after 2.5s\n * ```\n *\n * @param {Observer|Function} observerOrNext (optional) Either an observer with methods to be called,\n * or the first of three possible handlers, which is the handler for each value emitted from the subscribed\n * Observable.\n * @param {Function} error (optional) A handler for a terminal event resulting from an error. If no error handler is provided,\n * the error will be thrown asynchronously as unhandled.\n * @param {Function} complete (optional) A handler for a terminal event resulting from successful completion.\n * @return {Subscription} a subscription reference to the registered handlers\n * @method subscribe\n */\n subscribe(\n observerOrNext?: Partial> | ((value: T) => void) | null,\n error?: ((error: any) => void) | null,\n complete?: (() => void) | null\n ): Subscription {\n const subscriber = isSubscriber(observerOrNext) ? observerOrNext : new SafeSubscriber(observerOrNext, error, complete);\n\n errorContext(() => {\n const { operator, source } = this;\n subscriber.add(\n operator\n ? // We're dealing with a subscription in the\n // operator chain to one of our lifted operators.\n operator.call(subscriber, source)\n : source\n ? // If `source` has a value, but `operator` does not, something that\n // had intimate knowledge of our API, like our `Subject`, must have\n // set it. We're going to just call `_subscribe` directly.\n this._subscribe(subscriber)\n : // In all other cases, we're likely wrapping a user-provided initializer\n // function, so we need to catch errors and handle them appropriately.\n this._trySubscribe(subscriber)\n );\n });\n\n return subscriber;\n }\n\n /** @internal */\n protected _trySubscribe(sink: Subscriber): TeardownLogic {\n try {\n return this._subscribe(sink);\n } catch (err) {\n // We don't need to return anything in this case,\n // because it's just going to try to `add()` to a subscription\n // above.\n sink.error(err);\n }\n }\n\n /**\n * Used as a NON-CANCELLABLE means of subscribing to an observable, for use with\n * APIs that expect promises, like `async/await`. You cannot unsubscribe from this.\n *\n * **WARNING**: Only use this with observables you *know* will complete. If the source\n * observable does not complete, you will end up with a promise that is hung up, and\n * potentially all of the state of an async function hanging out in memory. To avoid\n * this situation, look into adding something like {@link timeout}, {@link take},\n * {@link takeWhile}, or {@link takeUntil} amongst others.\n *\n * #### Example\n *\n * ```ts\n * import { interval, take } from 'rxjs';\n *\n * const source$ = interval(1000).pipe(take(4));\n *\n * async function getTotal() {\n * let total = 0;\n *\n * await source$.forEach(value => {\n * total += value;\n * console.log('observable -> ' + value);\n * });\n *\n * return total;\n * }\n *\n * getTotal().then(\n * total => console.log('Total: ' + total)\n * );\n *\n * // Expected:\n * // 'observable -> 0'\n * // 'observable -> 1'\n * // 'observable -> 2'\n * // 'observable -> 3'\n * // 'Total: 6'\n * ```\n *\n * @param next a handler for each value emitted by the observable\n * @return a promise that either resolves on observable completion or\n * rejects with the handled error\n */\n forEach(next: (value: T) => void): Promise;\n\n /**\n * @param next a handler for each value emitted by the observable\n * @param promiseCtor a constructor function used to instantiate the Promise\n * @return a promise that either resolves on observable completion or\n * rejects with the handled error\n * @deprecated Passing a Promise constructor will no longer be available\n * in upcoming versions of RxJS. This is because it adds weight to the library, for very\n * little benefit. If you need this functionality, it is recommended that you either\n * polyfill Promise, or you create an adapter to convert the returned native promise\n * to whatever promise implementation you wanted. Will be removed in v8.\n */\n forEach(next: (value: T) => void, promiseCtor: PromiseConstructorLike): Promise;\n\n forEach(next: (value: T) => void, promiseCtor?: PromiseConstructorLike): Promise {\n promiseCtor = getPromiseCtor(promiseCtor);\n\n return new promiseCtor((resolve, reject) => {\n const subscriber = new SafeSubscriber({\n next: (value) => {\n try {\n next(value);\n } catch (err) {\n reject(err);\n subscriber.unsubscribe();\n }\n },\n error: reject,\n complete: resolve,\n });\n this.subscribe(subscriber);\n }) as Promise;\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): TeardownLogic {\n return this.source?.subscribe(subscriber);\n }\n\n /**\n * An interop point defined by the es7-observable spec https://github.com/zenparsing/es-observable\n * @method Symbol.observable\n * @return {Observable} this instance of the observable\n */\n [Symbol_observable]() {\n return this;\n }\n\n /* tslint:disable:max-line-length */\n pipe(): Observable;\n pipe(op1: OperatorFunction): Observable;\n pipe(op1: OperatorFunction, op2: OperatorFunction): Observable;\n pipe(op1: OperatorFunction, op2: OperatorFunction, op3: OperatorFunction): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction,\n op9: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction,\n op9: OperatorFunction,\n ...operations: OperatorFunction[]\n ): Observable;\n /* tslint:enable:max-line-length */\n\n /**\n * Used to stitch together functional operators into a chain.\n * @method pipe\n * @return {Observable} the Observable result of all of the operators having\n * been called in the order they were passed in.\n *\n * ## Example\n *\n * ```ts\n * import { interval, filter, map, scan } from 'rxjs';\n *\n * interval(1000)\n * .pipe(\n * filter(x => x % 2 === 0),\n * map(x => x + x),\n * scan((acc, x) => acc + x)\n * )\n * .subscribe(x => console.log(x));\n * ```\n */\n pipe(...operations: OperatorFunction[]): Observable {\n return pipeFromArray(operations)(this);\n }\n\n /* tslint:disable:max-line-length */\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(): Promise;\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(PromiseCtor: typeof Promise): Promise;\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(PromiseCtor: PromiseConstructorLike): Promise;\n /* tslint:enable:max-line-length */\n\n /**\n * Subscribe to this Observable and get a Promise resolving on\n * `complete` with the last emission (if any).\n *\n * **WARNING**: Only use this with observables you *know* will complete. If the source\n * observable does not complete, you will end up with a promise that is hung up, and\n * potentially all of the state of an async function hanging out in memory. To avoid\n * this situation, look into adding something like {@link timeout}, {@link take},\n * {@link takeWhile}, or {@link takeUntil} amongst others.\n *\n * @method toPromise\n * @param [promiseCtor] a constructor function used to instantiate\n * the Promise\n * @return A Promise that resolves with the last value emit, or\n * rejects on an error. If there were no emissions, Promise\n * resolves with undefined.\n * @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise\n */\n toPromise(promiseCtor?: PromiseConstructorLike): Promise {\n promiseCtor = getPromiseCtor(promiseCtor);\n\n return new promiseCtor((resolve, reject) => {\n let value: T | undefined;\n this.subscribe(\n (x: T) => (value = x),\n (err: any) => reject(err),\n () => resolve(value)\n );\n }) as Promise;\n }\n}\n\n/**\n * Decides between a passed promise constructor from consuming code,\n * A default configured promise constructor, and the native promise\n * constructor and returns it. If nothing can be found, it will throw\n * an error.\n * @param promiseCtor The optional promise constructor to passed by consuming code\n */\nfunction getPromiseCtor(promiseCtor: PromiseConstructorLike | undefined) {\n return promiseCtor ?? config.Promise ?? Promise;\n}\n\nfunction isObserver(value: any): value is Observer {\n return value && isFunction(value.next) && isFunction(value.error) && isFunction(value.complete);\n}\n\nfunction isSubscriber(value: any): value is Subscriber {\n return (value && value instanceof Subscriber) || (isObserver(value) && isSubscription(value));\n}\n", "import { Observable } from '../Observable';\nimport { Subscriber } from '../Subscriber';\nimport { OperatorFunction } from '../types';\nimport { isFunction } from './isFunction';\n\n/**\n * Used to determine if an object is an Observable with a lift function.\n */\nexport function hasLift(source: any): source is { lift: InstanceType['lift'] } {\n return isFunction(source?.lift);\n}\n\n/**\n * Creates an `OperatorFunction`. Used to define operators throughout the library in a concise way.\n * @param init The logic to connect the liftedSource to the subscriber at the moment of subscription.\n */\nexport function operate(\n init: (liftedSource: Observable, subscriber: Subscriber) => (() => void) | void\n): OperatorFunction {\n return (source: Observable) => {\n if (hasLift(source)) {\n return source.lift(function (this: Subscriber, liftedSource: Observable) {\n try {\n return init(liftedSource, this);\n } catch (err) {\n this.error(err);\n }\n });\n }\n throw new TypeError('Unable to lift unknown Observable type');\n };\n}\n", "import { Subscriber } from '../Subscriber';\n\n/**\n * Creates an instance of an `OperatorSubscriber`.\n * @param destination The downstream subscriber.\n * @param onNext Handles next values, only called if this subscriber is not stopped or closed. Any\n * error that occurs in this function is caught and sent to the `error` method of this subscriber.\n * @param onError Handles errors from the subscription, any errors that occur in this handler are caught\n * and send to the `destination` error handler.\n * @param onComplete Handles completion notification from the subscription. Any errors that occur in\n * this handler are sent to the `destination` error handler.\n * @param onFinalize Additional teardown logic here. This will only be called on teardown if the\n * subscriber itself is not already closed. This is called after all other teardown logic is executed.\n */\nexport function createOperatorSubscriber(\n destination: Subscriber,\n onNext?: (value: T) => void,\n onComplete?: () => void,\n onError?: (err: any) => void,\n onFinalize?: () => void\n): Subscriber {\n return new OperatorSubscriber(destination, onNext, onComplete, onError, onFinalize);\n}\n\n/**\n * A generic helper for allowing operators to be created with a Subscriber and\n * use closures to capture necessary state from the operator function itself.\n */\nexport class OperatorSubscriber extends Subscriber {\n /**\n * Creates an instance of an `OperatorSubscriber`.\n * @param destination The downstream subscriber.\n * @param onNext Handles next values, only called if this subscriber is not stopped or closed. Any\n * error that occurs in this function is caught and sent to the `error` method of this subscriber.\n * @param onError Handles errors from the subscription, any errors that occur in this handler are caught\n * and send to the `destination` error handler.\n * @param onComplete Handles completion notification from the subscription. Any errors that occur in\n * this handler are sent to the `destination` error handler.\n * @param onFinalize Additional finalization logic here. This will only be called on finalization if the\n * subscriber itself is not already closed. This is called after all other finalization logic is executed.\n * @param shouldUnsubscribe An optional check to see if an unsubscribe call should truly unsubscribe.\n * NOTE: This currently **ONLY** exists to support the strange behavior of {@link groupBy}, where unsubscription\n * to the resulting observable does not actually disconnect from the source if there are active subscriptions\n * to any grouped observable. (DO NOT EXPOSE OR USE EXTERNALLY!!!)\n */\n constructor(\n destination: Subscriber,\n onNext?: (value: T) => void,\n onComplete?: () => void,\n onError?: (err: any) => void,\n private onFinalize?: () => void,\n private shouldUnsubscribe?: () => boolean\n ) {\n // It's important - for performance reasons - that all of this class's\n // members are initialized and that they are always initialized in the same\n // order. This will ensure that all OperatorSubscriber instances have the\n // same hidden class in V8. This, in turn, will help keep the number of\n // hidden classes involved in property accesses within the base class as\n // low as possible. If the number of hidden classes involved exceeds four,\n // the property accesses will become megamorphic and performance penalties\n // will be incurred - i.e. inline caches won't be used.\n //\n // The reasons for ensuring all instances have the same hidden class are\n // further discussed in this blog post from Benedikt Meurer:\n // https://benediktmeurer.de/2018/03/23/impact-of-polymorphism-on-component-based-frameworks-like-react/\n super(destination);\n this._next = onNext\n ? function (this: OperatorSubscriber, value: T) {\n try {\n onNext(value);\n } catch (err) {\n destination.error(err);\n }\n }\n : super._next;\n this._error = onError\n ? function (this: OperatorSubscriber, err: any) {\n try {\n onError(err);\n } catch (err) {\n // Send any errors that occur down stream.\n destination.error(err);\n } finally {\n // Ensure finalization.\n this.unsubscribe();\n }\n }\n : super._error;\n this._complete = onComplete\n ? function (this: OperatorSubscriber) {\n try {\n onComplete();\n } catch (err) {\n // Send any errors that occur down stream.\n destination.error(err);\n } finally {\n // Ensure finalization.\n this.unsubscribe();\n }\n }\n : super._complete;\n }\n\n unsubscribe() {\n if (!this.shouldUnsubscribe || this.shouldUnsubscribe()) {\n const { closed } = this;\n super.unsubscribe();\n // Execute additional teardown if we have any and we didn't already do so.\n !closed && this.onFinalize?.();\n }\n }\n}\n", "import { Subscription } from '../Subscription';\n\ninterface AnimationFrameProvider {\n schedule(callback: FrameRequestCallback): Subscription;\n requestAnimationFrame: typeof requestAnimationFrame;\n cancelAnimationFrame: typeof cancelAnimationFrame;\n delegate:\n | {\n requestAnimationFrame: typeof requestAnimationFrame;\n cancelAnimationFrame: typeof cancelAnimationFrame;\n }\n | undefined;\n}\n\nexport const animationFrameProvider: AnimationFrameProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n schedule(callback) {\n let request = requestAnimationFrame;\n let cancel: typeof cancelAnimationFrame | undefined = cancelAnimationFrame;\n const { delegate } = animationFrameProvider;\n if (delegate) {\n request = delegate.requestAnimationFrame;\n cancel = delegate.cancelAnimationFrame;\n }\n const handle = request((timestamp) => {\n // Clear the cancel function. The request has been fulfilled, so\n // attempting to cancel the request upon unsubscription would be\n // pointless.\n cancel = undefined;\n callback(timestamp);\n });\n return new Subscription(() => cancel?.(handle));\n },\n requestAnimationFrame(...args) {\n const { delegate } = animationFrameProvider;\n return (delegate?.requestAnimationFrame || requestAnimationFrame)(...args);\n },\n cancelAnimationFrame(...args) {\n const { delegate } = animationFrameProvider;\n return (delegate?.cancelAnimationFrame || cancelAnimationFrame)(...args);\n },\n delegate: undefined,\n};\n", "import { createErrorClass } from './createErrorClass';\n\nexport interface ObjectUnsubscribedError extends Error {}\n\nexport interface ObjectUnsubscribedErrorCtor {\n /**\n * @deprecated Internal implementation detail. Do not construct error instances.\n * Cannot be tagged as internal: https://github.com/ReactiveX/rxjs/issues/6269\n */\n new (): ObjectUnsubscribedError;\n}\n\n/**\n * An error thrown when an action is invalid because the object has been\n * unsubscribed.\n *\n * @see {@link Subject}\n * @see {@link BehaviorSubject}\n *\n * @class ObjectUnsubscribedError\n */\nexport const ObjectUnsubscribedError: ObjectUnsubscribedErrorCtor = createErrorClass(\n (_super) =>\n function ObjectUnsubscribedErrorImpl(this: any) {\n _super(this);\n this.name = 'ObjectUnsubscribedError';\n this.message = 'object unsubscribed';\n }\n);\n", "import { Operator } from './Operator';\nimport { Observable } from './Observable';\nimport { Subscriber } from './Subscriber';\nimport { Subscription, EMPTY_SUBSCRIPTION } from './Subscription';\nimport { Observer, SubscriptionLike, TeardownLogic } from './types';\nimport { ObjectUnsubscribedError } from './util/ObjectUnsubscribedError';\nimport { arrRemove } from './util/arrRemove';\nimport { errorContext } from './util/errorContext';\n\n/**\n * A Subject is a special type of Observable that allows values to be\n * multicasted to many Observers. Subjects are like EventEmitters.\n *\n * Every Subject is an Observable and an Observer. You can subscribe to a\n * Subject, and you can call next to feed values as well as error and complete.\n */\nexport class Subject extends Observable implements SubscriptionLike {\n closed = false;\n\n private currentObservers: Observer[] | null = null;\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n observers: Observer[] = [];\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n isStopped = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n hasError = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n thrownError: any = null;\n\n /**\n * Creates a \"subject\" by basically gluing an observer to an observable.\n *\n * @nocollapse\n * @deprecated Recommended you do not use. Will be removed at some point in the future. Plans for replacement still under discussion.\n */\n static create: (...args: any[]) => any = (destination: Observer, source: Observable): AnonymousSubject => {\n return new AnonymousSubject(destination, source);\n };\n\n constructor() {\n // NOTE: This must be here to obscure Observable's constructor.\n super();\n }\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n lift(operator: Operator): Observable {\n const subject = new AnonymousSubject(this, this);\n subject.operator = operator as any;\n return subject as any;\n }\n\n /** @internal */\n protected _throwIfClosed() {\n if (this.closed) {\n throw new ObjectUnsubscribedError();\n }\n }\n\n next(value: T) {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n if (!this.currentObservers) {\n this.currentObservers = Array.from(this.observers);\n }\n for (const observer of this.currentObservers) {\n observer.next(value);\n }\n }\n });\n }\n\n error(err: any) {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n this.hasError = this.isStopped = true;\n this.thrownError = err;\n const { observers } = this;\n while (observers.length) {\n observers.shift()!.error(err);\n }\n }\n });\n }\n\n complete() {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n this.isStopped = true;\n const { observers } = this;\n while (observers.length) {\n observers.shift()!.complete();\n }\n }\n });\n }\n\n unsubscribe() {\n this.isStopped = this.closed = true;\n this.observers = this.currentObservers = null!;\n }\n\n get observed() {\n return this.observers?.length > 0;\n }\n\n /** @internal */\n protected _trySubscribe(subscriber: Subscriber): TeardownLogic {\n this._throwIfClosed();\n return super._trySubscribe(subscriber);\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n this._throwIfClosed();\n this._checkFinalizedStatuses(subscriber);\n return this._innerSubscribe(subscriber);\n }\n\n /** @internal */\n protected _innerSubscribe(subscriber: Subscriber) {\n const { hasError, isStopped, observers } = this;\n if (hasError || isStopped) {\n return EMPTY_SUBSCRIPTION;\n }\n this.currentObservers = null;\n observers.push(subscriber);\n return new Subscription(() => {\n this.currentObservers = null;\n arrRemove(observers, subscriber);\n });\n }\n\n /** @internal */\n protected _checkFinalizedStatuses(subscriber: Subscriber) {\n const { hasError, thrownError, isStopped } = this;\n if (hasError) {\n subscriber.error(thrownError);\n } else if (isStopped) {\n subscriber.complete();\n }\n }\n\n /**\n * Creates a new Observable with this Subject as the source. You can do this\n * to create custom Observer-side logic of the Subject and conceal it from\n * code that uses the Observable.\n * @return {Observable} Observable that the Subject casts to\n */\n asObservable(): Observable {\n const observable: any = new Observable();\n observable.source = this;\n return observable;\n }\n}\n\n/**\n * @class AnonymousSubject\n */\nexport class AnonymousSubject extends Subject {\n constructor(\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n public destination?: Observer,\n source?: Observable\n ) {\n super();\n this.source = source;\n }\n\n next(value: T) {\n this.destination?.next?.(value);\n }\n\n error(err: any) {\n this.destination?.error?.(err);\n }\n\n complete() {\n this.destination?.complete?.();\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n return this.source?.subscribe(subscriber) ?? EMPTY_SUBSCRIPTION;\n }\n}\n", "import { Subject } from './Subject';\nimport { Subscriber } from './Subscriber';\nimport { Subscription } from './Subscription';\n\n/**\n * A variant of Subject that requires an initial value and emits its current\n * value whenever it is subscribed to.\n *\n * @class BehaviorSubject\n */\nexport class BehaviorSubject extends Subject {\n constructor(private _value: T) {\n super();\n }\n\n get value(): T {\n return this.getValue();\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n const subscription = super._subscribe(subscriber);\n !subscription.closed && subscriber.next(this._value);\n return subscription;\n }\n\n getValue(): T {\n const { hasError, thrownError, _value } = this;\n if (hasError) {\n throw thrownError;\n }\n this._throwIfClosed();\n return _value;\n }\n\n next(value: T): void {\n super.next((this._value = value));\n }\n}\n", "import { TimestampProvider } from '../types';\n\ninterface DateTimestampProvider extends TimestampProvider {\n delegate: TimestampProvider | undefined;\n}\n\nexport const dateTimestampProvider: DateTimestampProvider = {\n now() {\n // Use the variable rather than `this` so that the function can be called\n // without being bound to the provider.\n return (dateTimestampProvider.delegate || Date).now();\n },\n delegate: undefined,\n};\n", "import { Subject } from './Subject';\nimport { TimestampProvider } from './types';\nimport { Subscriber } from './Subscriber';\nimport { Subscription } from './Subscription';\nimport { dateTimestampProvider } from './scheduler/dateTimestampProvider';\n\n/**\n * A variant of {@link Subject} that \"replays\" old values to new subscribers by emitting them when they first subscribe.\n *\n * `ReplaySubject` has an internal buffer that will store a specified number of values that it has observed. Like `Subject`,\n * `ReplaySubject` \"observes\" values by having them passed to its `next` method. When it observes a value, it will store that\n * value for a time determined by the configuration of the `ReplaySubject`, as passed to its constructor.\n *\n * When a new subscriber subscribes to the `ReplaySubject` instance, it will synchronously emit all values in its buffer in\n * a First-In-First-Out (FIFO) manner. The `ReplaySubject` will also complete, if it has observed completion; and it will\n * error if it has observed an error.\n *\n * There are two main configuration items to be concerned with:\n *\n * 1. `bufferSize` - This will determine how many items are stored in the buffer, defaults to infinite.\n * 2. `windowTime` - The amount of time to hold a value in the buffer before removing it from the buffer.\n *\n * Both configurations may exist simultaneously. So if you would like to buffer a maximum of 3 values, as long as the values\n * are less than 2 seconds old, you could do so with a `new ReplaySubject(3, 2000)`.\n *\n * ### Differences with BehaviorSubject\n *\n * `BehaviorSubject` is similar to `new ReplaySubject(1)`, with a couple of exceptions:\n *\n * 1. `BehaviorSubject` comes \"primed\" with a single value upon construction.\n * 2. `ReplaySubject` will replay values, even after observing an error, where `BehaviorSubject` will not.\n *\n * @see {@link Subject}\n * @see {@link BehaviorSubject}\n * @see {@link shareReplay}\n */\nexport class ReplaySubject extends Subject {\n private _buffer: (T | number)[] = [];\n private _infiniteTimeWindow = true;\n\n /**\n * @param bufferSize The size of the buffer to replay on subscription\n * @param windowTime The amount of time the buffered items will stay buffered\n * @param timestampProvider An object with a `now()` method that provides the current timestamp. This is used to\n * calculate the amount of time something has been buffered.\n */\n constructor(\n private _bufferSize = Infinity,\n private _windowTime = Infinity,\n private _timestampProvider: TimestampProvider = dateTimestampProvider\n ) {\n super();\n this._infiniteTimeWindow = _windowTime === Infinity;\n this._bufferSize = Math.max(1, _bufferSize);\n this._windowTime = Math.max(1, _windowTime);\n }\n\n next(value: T): void {\n const { isStopped, _buffer, _infiniteTimeWindow, _timestampProvider, _windowTime } = this;\n if (!isStopped) {\n _buffer.push(value);\n !_infiniteTimeWindow && _buffer.push(_timestampProvider.now() + _windowTime);\n }\n this._trimBuffer();\n super.next(value);\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n this._throwIfClosed();\n this._trimBuffer();\n\n const subscription = this._innerSubscribe(subscriber);\n\n const { _infiniteTimeWindow, _buffer } = this;\n // We use a copy here, so reentrant code does not mutate our array while we're\n // emitting it to a new subscriber.\n const copy = _buffer.slice();\n for (let i = 0; i < copy.length && !subscriber.closed; i += _infiniteTimeWindow ? 1 : 2) {\n subscriber.next(copy[i] as T);\n }\n\n this._checkFinalizedStatuses(subscriber);\n\n return subscription;\n }\n\n private _trimBuffer() {\n const { _bufferSize, _timestampProvider, _buffer, _infiniteTimeWindow } = this;\n // If we don't have an infinite buffer size, and we're over the length,\n // use splice to truncate the old buffer values off. Note that we have to\n // double the size for instances where we're not using an infinite time window\n // because we're storing the values and the timestamps in the same array.\n const adjustedBufferSize = (_infiniteTimeWindow ? 1 : 2) * _bufferSize;\n _bufferSize < Infinity && adjustedBufferSize < _buffer.length && _buffer.splice(0, _buffer.length - adjustedBufferSize);\n\n // Now, if we're not in an infinite time window, remove all values where the time is\n // older than what is allowed.\n if (!_infiniteTimeWindow) {\n const now = _timestampProvider.now();\n let last = 0;\n // Search the array for the first timestamp that isn't expired and\n // truncate the buffer up to that point.\n for (let i = 1; i < _buffer.length && (_buffer[i] as number) <= now; i += 2) {\n last = i;\n }\n last && _buffer.splice(0, last + 1);\n }\n }\n}\n", "import { Scheduler } from '../Scheduler';\nimport { Subscription } from '../Subscription';\nimport { SchedulerAction } from '../types';\n\n/**\n * A unit of work to be executed in a `scheduler`. An action is typically\n * created from within a {@link SchedulerLike} and an RxJS user does not need to concern\n * themselves about creating and manipulating an Action.\n *\n * ```ts\n * class Action extends Subscription {\n * new (scheduler: Scheduler, work: (state?: T) => void);\n * schedule(state?: T, delay: number = 0): Subscription;\n * }\n * ```\n *\n * @class Action\n */\nexport class Action extends Subscription {\n constructor(scheduler: Scheduler, work: (this: SchedulerAction, state?: T) => void) {\n super();\n }\n /**\n * Schedules this action on its parent {@link SchedulerLike} for execution. May be passed\n * some context object, `state`. May happen at some point in the future,\n * according to the `delay` parameter, if specified.\n * @param {T} [state] Some contextual data that the `work` function uses when\n * called by the Scheduler.\n * @param {number} [delay] Time to wait before executing the work, where the\n * time unit is implicit and defined by the Scheduler.\n * @return {void}\n */\n public schedule(state?: T, delay: number = 0): Subscription {\n return this;\n }\n}\n", "import type { TimerHandle } from './timerHandle';\ntype SetIntervalFunction = (handler: () => void, timeout?: number, ...args: any[]) => TimerHandle;\ntype ClearIntervalFunction = (handle: TimerHandle) => void;\n\ninterface IntervalProvider {\n setInterval: SetIntervalFunction;\n clearInterval: ClearIntervalFunction;\n delegate:\n | {\n setInterval: SetIntervalFunction;\n clearInterval: ClearIntervalFunction;\n }\n | undefined;\n}\n\nexport const intervalProvider: IntervalProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n setInterval(handler: () => void, timeout?: number, ...args) {\n const { delegate } = intervalProvider;\n if (delegate?.setInterval) {\n return delegate.setInterval(handler, timeout, ...args);\n }\n return setInterval(handler, timeout, ...args);\n },\n clearInterval(handle) {\n const { delegate } = intervalProvider;\n return (delegate?.clearInterval || clearInterval)(handle as any);\n },\n delegate: undefined,\n};\n", "import { Action } from './Action';\nimport { SchedulerAction } from '../types';\nimport { Subscription } from '../Subscription';\nimport { AsyncScheduler } from './AsyncScheduler';\nimport { intervalProvider } from './intervalProvider';\nimport { arrRemove } from '../util/arrRemove';\nimport { TimerHandle } from './timerHandle';\n\nexport class AsyncAction extends Action {\n public id: TimerHandle | undefined;\n public state?: T;\n // @ts-ignore: Property has no initializer and is not definitely assigned\n public delay: number;\n protected pending: boolean = false;\n\n constructor(protected scheduler: AsyncScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n public schedule(state?: T, delay: number = 0): Subscription {\n if (this.closed) {\n return this;\n }\n\n // Always replace the current state with the new state.\n this.state = state;\n\n const id = this.id;\n const scheduler = this.scheduler;\n\n //\n // Important implementation note:\n //\n // Actions only execute once by default, unless rescheduled from within the\n // scheduled callback. This allows us to implement single and repeat\n // actions via the same code path, without adding API surface area, as well\n // as mimic traditional recursion but across asynchronous boundaries.\n //\n // However, JS runtimes and timers distinguish between intervals achieved by\n // serial `setTimeout` calls vs. a single `setInterval` call. An interval of\n // serial `setTimeout` calls can be individually delayed, which delays\n // scheduling the next `setTimeout`, and so on. `setInterval` attempts to\n // guarantee the interval callback will be invoked more precisely to the\n // interval period, regardless of load.\n //\n // Therefore, we use `setInterval` to schedule single and repeat actions.\n // If the action reschedules itself with the same delay, the interval is not\n // canceled. If the action doesn't reschedule, or reschedules with a\n // different delay, the interval will be canceled after scheduled callback\n // execution.\n //\n if (id != null) {\n this.id = this.recycleAsyncId(scheduler, id, delay);\n }\n\n // Set the pending flag indicating that this action has been scheduled, or\n // has recursively rescheduled itself.\n this.pending = true;\n\n this.delay = delay;\n // If this action has already an async Id, don't request a new one.\n this.id = this.id ?? this.requestAsyncId(scheduler, this.id, delay);\n\n return this;\n }\n\n protected requestAsyncId(scheduler: AsyncScheduler, _id?: TimerHandle, delay: number = 0): TimerHandle {\n return intervalProvider.setInterval(scheduler.flush.bind(scheduler, this), delay);\n }\n\n protected recycleAsyncId(_scheduler: AsyncScheduler, id?: TimerHandle, delay: number | null = 0): TimerHandle | undefined {\n // If this action is rescheduled with the same delay time, don't clear the interval id.\n if (delay != null && this.delay === delay && this.pending === false) {\n return id;\n }\n // Otherwise, if the action's delay time is different from the current delay,\n // or the action has been rescheduled before it's executed, clear the interval id\n if (id != null) {\n intervalProvider.clearInterval(id);\n }\n\n return undefined;\n }\n\n /**\n * Immediately executes this action and the `work` it contains.\n * @return {any}\n */\n public execute(state: T, delay: number): any {\n if (this.closed) {\n return new Error('executing a cancelled action');\n }\n\n this.pending = false;\n const error = this._execute(state, delay);\n if (error) {\n return error;\n } else if (this.pending === false && this.id != null) {\n // Dequeue if the action didn't reschedule itself. Don't call\n // unsubscribe(), because the action could reschedule later.\n // For example:\n // ```\n // scheduler.schedule(function doWork(counter) {\n // /* ... I'm a busy worker bee ... */\n // var originalAction = this;\n // /* wait 100ms before rescheduling the action */\n // setTimeout(function () {\n // originalAction.schedule(counter + 1);\n // }, 100);\n // }, 1000);\n // ```\n this.id = this.recycleAsyncId(this.scheduler, this.id, null);\n }\n }\n\n protected _execute(state: T, _delay: number): any {\n let errored: boolean = false;\n let errorValue: any;\n try {\n this.work(state);\n } catch (e) {\n errored = true;\n // HACK: Since code elsewhere is relying on the \"truthiness\" of the\n // return here, we can't have it return \"\" or 0 or false.\n // TODO: Clean this up when we refactor schedulers mid-version-8 or so.\n errorValue = e ? e : new Error('Scheduled action threw falsy error');\n }\n if (errored) {\n this.unsubscribe();\n return errorValue;\n }\n }\n\n unsubscribe() {\n if (!this.closed) {\n const { id, scheduler } = this;\n const { actions } = scheduler;\n\n this.work = this.state = this.scheduler = null!;\n this.pending = false;\n\n arrRemove(actions, this);\n if (id != null) {\n this.id = this.recycleAsyncId(scheduler, id, null);\n }\n\n this.delay = null!;\n super.unsubscribe();\n }\n }\n}\n", "import { Action } from './scheduler/Action';\nimport { Subscription } from './Subscription';\nimport { SchedulerLike, SchedulerAction } from './types';\nimport { dateTimestampProvider } from './scheduler/dateTimestampProvider';\n\n/**\n * An execution context and a data structure to order tasks and schedule their\n * execution. Provides a notion of (potentially virtual) time, through the\n * `now()` getter method.\n *\n * Each unit of work in a Scheduler is called an `Action`.\n *\n * ```ts\n * class Scheduler {\n * now(): number;\n * schedule(work, delay?, state?): Subscription;\n * }\n * ```\n *\n * @class Scheduler\n * @deprecated Scheduler is an internal implementation detail of RxJS, and\n * should not be used directly. Rather, create your own class and implement\n * {@link SchedulerLike}. Will be made internal in v8.\n */\nexport class Scheduler implements SchedulerLike {\n public static now: () => number = dateTimestampProvider.now;\n\n constructor(private schedulerActionCtor: typeof Action, now: () => number = Scheduler.now) {\n this.now = now;\n }\n\n /**\n * A getter method that returns a number representing the current time\n * (at the time this function was called) according to the scheduler's own\n * internal clock.\n * @return {number} A number that represents the current time. May or may not\n * have a relation to wall-clock time. May or may not refer to a time unit\n * (e.g. milliseconds).\n */\n public now: () => number;\n\n /**\n * Schedules a function, `work`, for execution. May happen at some point in\n * the future, according to the `delay` parameter, if specified. May be passed\n * some context object, `state`, which will be passed to the `work` function.\n *\n * The given arguments will be processed an stored as an Action object in a\n * queue of actions.\n *\n * @param {function(state: ?T): ?Subscription} work A function representing a\n * task, or some unit of work to be executed by the Scheduler.\n * @param {number} [delay] Time to wait before executing the work, where the\n * time unit is implicit and defined by the Scheduler itself.\n * @param {T} [state] Some contextual data that the `work` function uses when\n * called by the Scheduler.\n * @return {Subscription} A subscription in order to be able to unsubscribe\n * the scheduled work.\n */\n public schedule(work: (this: SchedulerAction, state?: T) => void, delay: number = 0, state?: T): Subscription {\n return new this.schedulerActionCtor(this, work).schedule(state, delay);\n }\n}\n", "import { Scheduler } from '../Scheduler';\nimport { Action } from './Action';\nimport { AsyncAction } from './AsyncAction';\nimport { TimerHandle } from './timerHandle';\n\nexport class AsyncScheduler extends Scheduler {\n public actions: Array> = [];\n /**\n * A flag to indicate whether the Scheduler is currently executing a batch of\n * queued actions.\n * @type {boolean}\n * @internal\n */\n public _active: boolean = false;\n /**\n * An internal ID used to track the latest asynchronous task such as those\n * coming from `setTimeout`, `setInterval`, `requestAnimationFrame`, and\n * others.\n * @type {any}\n * @internal\n */\n public _scheduled: TimerHandle | undefined;\n\n constructor(SchedulerAction: typeof Action, now: () => number = Scheduler.now) {\n super(SchedulerAction, now);\n }\n\n public flush(action: AsyncAction): void {\n const { actions } = this;\n\n if (this._active) {\n actions.push(action);\n return;\n }\n\n let error: any;\n this._active = true;\n\n do {\n if ((error = action.execute(action.state, action.delay))) {\n break;\n }\n } while ((action = actions.shift()!)); // exhaust the scheduler queue\n\n this._active = false;\n\n if (error) {\n while ((action = actions.shift()!)) {\n action.unsubscribe();\n }\n throw error;\n }\n }\n}\n", "import { AsyncAction } from './AsyncAction';\nimport { AsyncScheduler } from './AsyncScheduler';\n\n/**\n *\n * Async Scheduler\n *\n * Schedule task as if you used setTimeout(task, duration)\n *\n * `async` scheduler schedules tasks asynchronously, by putting them on the JavaScript\n * event loop queue. It is best used to delay tasks in time or to schedule tasks repeating\n * in intervals.\n *\n * If you just want to \"defer\" task, that is to perform it right after currently\n * executing synchronous code ends (commonly achieved by `setTimeout(deferredTask, 0)`),\n * better choice will be the {@link asapScheduler} scheduler.\n *\n * ## Examples\n * Use async scheduler to delay task\n * ```ts\n * import { asyncScheduler } from 'rxjs';\n *\n * const task = () => console.log('it works!');\n *\n * asyncScheduler.schedule(task, 2000);\n *\n * // After 2 seconds logs:\n * // \"it works!\"\n * ```\n *\n * Use async scheduler to repeat task in intervals\n * ```ts\n * import { asyncScheduler } from 'rxjs';\n *\n * function task(state) {\n * console.log(state);\n * this.schedule(state + 1, 1000); // `this` references currently executing Action,\n * // which we reschedule with new state and delay\n * }\n *\n * asyncScheduler.schedule(task, 3000, 0);\n *\n * // Logs:\n * // 0 after 3s\n * // 1 after 4s\n * // 2 after 5s\n * // 3 after 6s\n * ```\n */\n\nexport const asyncScheduler = new AsyncScheduler(AsyncAction);\n\n/**\n * @deprecated Renamed to {@link asyncScheduler}. Will be removed in v8.\n */\nexport const async = asyncScheduler;\n", "import { AsyncAction } from './AsyncAction';\nimport { Subscription } from '../Subscription';\nimport { QueueScheduler } from './QueueScheduler';\nimport { SchedulerAction } from '../types';\nimport { TimerHandle } from './timerHandle';\n\nexport class QueueAction extends AsyncAction {\n constructor(protected scheduler: QueueScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n public schedule(state?: T, delay: number = 0): Subscription {\n if (delay > 0) {\n return super.schedule(state, delay);\n }\n this.delay = delay;\n this.state = state;\n this.scheduler.flush(this);\n return this;\n }\n\n public execute(state: T, delay: number): any {\n return delay > 0 || this.closed ? super.execute(state, delay) : this._execute(state, delay);\n }\n\n protected requestAsyncId(scheduler: QueueScheduler, id?: TimerHandle, delay: number = 0): TimerHandle {\n // If delay exists and is greater than 0, or if the delay is null (the\n // action wasn't rescheduled) but was originally scheduled as an async\n // action, then recycle as an async action.\n\n if ((delay != null && delay > 0) || (delay == null && this.delay > 0)) {\n return super.requestAsyncId(scheduler, id, delay);\n }\n\n // Otherwise flush the scheduler starting with this action.\n scheduler.flush(this);\n\n // HACK: In the past, this was returning `void`. However, `void` isn't a valid\n // `TimerHandle`, and generally the return value here isn't really used. So the\n // compromise is to return `0` which is both \"falsy\" and a valid `TimerHandle`,\n // as opposed to refactoring every other instanceo of `requestAsyncId`.\n return 0;\n }\n}\n", "import { AsyncScheduler } from './AsyncScheduler';\n\nexport class QueueScheduler extends AsyncScheduler {\n}\n", "import { QueueAction } from './QueueAction';\nimport { QueueScheduler } from './QueueScheduler';\n\n/**\n *\n * Queue Scheduler\n *\n * Put every next task on a queue, instead of executing it immediately\n *\n * `queue` scheduler, when used with delay, behaves the same as {@link asyncScheduler} scheduler.\n *\n * When used without delay, it schedules given task synchronously - executes it right when\n * it is scheduled. However when called recursively, that is when inside the scheduled task,\n * another task is scheduled with queue scheduler, instead of executing immediately as well,\n * that task will be put on a queue and wait for current one to finish.\n *\n * This means that when you execute task with `queue` scheduler, you are sure it will end\n * before any other task scheduled with that scheduler will start.\n *\n * ## Examples\n * Schedule recursively first, then do something\n * ```ts\n * import { queueScheduler } from 'rxjs';\n *\n * queueScheduler.schedule(() => {\n * queueScheduler.schedule(() => console.log('second')); // will not happen now, but will be put on a queue\n *\n * console.log('first');\n * });\n *\n * // Logs:\n * // \"first\"\n * // \"second\"\n * ```\n *\n * Reschedule itself recursively\n * ```ts\n * import { queueScheduler } from 'rxjs';\n *\n * queueScheduler.schedule(function(state) {\n * if (state !== 0) {\n * console.log('before', state);\n * this.schedule(state - 1); // `this` references currently executing Action,\n * // which we reschedule with new state\n * console.log('after', state);\n * }\n * }, 0, 3);\n *\n * // In scheduler that runs recursively, you would expect:\n * // \"before\", 3\n * // \"before\", 2\n * // \"before\", 1\n * // \"after\", 1\n * // \"after\", 2\n * // \"after\", 3\n *\n * // But with queue it logs:\n * // \"before\", 3\n * // \"after\", 3\n * // \"before\", 2\n * // \"after\", 2\n * // \"before\", 1\n * // \"after\", 1\n * ```\n */\n\nexport const queueScheduler = new QueueScheduler(QueueAction);\n\n/**\n * @deprecated Renamed to {@link queueScheduler}. Will be removed in v8.\n */\nexport const queue = queueScheduler;\n", "import { AsyncAction } from './AsyncAction';\nimport { AnimationFrameScheduler } from './AnimationFrameScheduler';\nimport { SchedulerAction } from '../types';\nimport { animationFrameProvider } from './animationFrameProvider';\nimport { TimerHandle } from './timerHandle';\n\nexport class AnimationFrameAction extends AsyncAction {\n constructor(protected scheduler: AnimationFrameScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n protected requestAsyncId(scheduler: AnimationFrameScheduler, id?: TimerHandle, delay: number = 0): TimerHandle {\n // If delay is greater than 0, request as an async action.\n if (delay !== null && delay > 0) {\n return super.requestAsyncId(scheduler, id, delay);\n }\n // Push the action to the end of the scheduler queue.\n scheduler.actions.push(this);\n // If an animation frame has already been requested, don't request another\n // one. If an animation frame hasn't been requested yet, request one. Return\n // the current animation frame request id.\n return scheduler._scheduled || (scheduler._scheduled = animationFrameProvider.requestAnimationFrame(() => scheduler.flush(undefined)));\n }\n\n protected recycleAsyncId(scheduler: AnimationFrameScheduler, id?: TimerHandle, delay: number = 0): TimerHandle | undefined {\n // If delay exists and is greater than 0, or if the delay is null (the\n // action wasn't rescheduled) but was originally scheduled as an async\n // action, then recycle as an async action.\n if (delay != null ? delay > 0 : this.delay > 0) {\n return super.recycleAsyncId(scheduler, id, delay);\n }\n // If the scheduler queue has no remaining actions with the same async id,\n // cancel the requested animation frame and set the scheduled flag to\n // undefined so the next AnimationFrameAction will request its own.\n const { actions } = scheduler;\n if (id != null && actions[actions.length - 1]?.id !== id) {\n animationFrameProvider.cancelAnimationFrame(id as number);\n scheduler._scheduled = undefined;\n }\n // Return undefined so the action knows to request a new async id if it's rescheduled.\n return undefined;\n }\n}\n", "import { AsyncAction } from './AsyncAction';\nimport { AsyncScheduler } from './AsyncScheduler';\n\nexport class AnimationFrameScheduler extends AsyncScheduler {\n public flush(action?: AsyncAction): void {\n this._active = true;\n // The async id that effects a call to flush is stored in _scheduled.\n // Before executing an action, it's necessary to check the action's async\n // id to determine whether it's supposed to be executed in the current\n // flush.\n // Previous implementations of this method used a count to determine this,\n // but that was unsound, as actions that are unsubscribed - i.e. cancelled -\n // are removed from the actions array and that can shift actions that are\n // scheduled to be executed in a subsequent flush into positions at which\n // they are executed within the current flush.\n const flushId = this._scheduled;\n this._scheduled = undefined;\n\n const { actions } = this;\n let error: any;\n action = action || actions.shift()!;\n\n do {\n if ((error = action.execute(action.state, action.delay))) {\n break;\n }\n } while ((action = actions[0]) && action.id === flushId && actions.shift());\n\n this._active = false;\n\n if (error) {\n while ((action = actions[0]) && action.id === flushId && actions.shift()) {\n action.unsubscribe();\n }\n throw error;\n }\n }\n}\n", "import { AnimationFrameAction } from './AnimationFrameAction';\nimport { AnimationFrameScheduler } from './AnimationFrameScheduler';\n\n/**\n *\n * Animation Frame Scheduler\n *\n * Perform task when `window.requestAnimationFrame` would fire\n *\n * When `animationFrame` scheduler is used with delay, it will fall back to {@link asyncScheduler} scheduler\n * behaviour.\n *\n * Without delay, `animationFrame` scheduler can be used to create smooth browser animations.\n * It makes sure scheduled task will happen just before next browser content repaint,\n * thus performing animations as efficiently as possible.\n *\n * ## Example\n * Schedule div height animation\n * ```ts\n * // html:
\n * import { animationFrameScheduler } from 'rxjs';\n *\n * const div = document.querySelector('div');\n *\n * animationFrameScheduler.schedule(function(height) {\n * div.style.height = height + \"px\";\n *\n * this.schedule(height + 1); // `this` references currently executing Action,\n * // which we reschedule with new state\n * }, 0, 0);\n *\n * // You will see a div element growing in height\n * ```\n */\n\nexport const animationFrameScheduler = new AnimationFrameScheduler(AnimationFrameAction);\n\n/**\n * @deprecated Renamed to {@link animationFrameScheduler}. Will be removed in v8.\n */\nexport const animationFrame = animationFrameScheduler;\n", "import { Observable } from '../Observable';\nimport { SchedulerLike } from '../types';\n\n/**\n * A simple Observable that emits no items to the Observer and immediately\n * emits a complete notification.\n *\n * Just emits 'complete', and nothing else.\n *\n * ![](empty.png)\n *\n * A simple Observable that only emits the complete notification. It can be used\n * for composing with other Observables, such as in a {@link mergeMap}.\n *\n * ## Examples\n *\n * Log complete notification\n *\n * ```ts\n * import { EMPTY } from 'rxjs';\n *\n * EMPTY.subscribe({\n * next: () => console.log('Next'),\n * complete: () => console.log('Complete!')\n * });\n *\n * // Outputs\n * // Complete!\n * ```\n *\n * Emit the number 7, then complete\n *\n * ```ts\n * import { EMPTY, startWith } from 'rxjs';\n *\n * const result = EMPTY.pipe(startWith(7));\n * result.subscribe(x => console.log(x));\n *\n * // Outputs\n * // 7\n * ```\n *\n * Map and flatten only odd numbers to the sequence `'a'`, `'b'`, `'c'`\n *\n * ```ts\n * import { interval, mergeMap, of, EMPTY } from 'rxjs';\n *\n * const interval$ = interval(1000);\n * const result = interval$.pipe(\n * mergeMap(x => x % 2 === 1 ? of('a', 'b', 'c') : EMPTY),\n * );\n * result.subscribe(x => console.log(x));\n *\n * // Results in the following to the console:\n * // x is equal to the count on the interval, e.g. (0, 1, 2, 3, ...)\n * // x will occur every 1000ms\n * // if x % 2 is equal to 1, print a, b, c (each on its own)\n * // if x % 2 is not equal to 1, nothing will be output\n * ```\n *\n * @see {@link Observable}\n * @see {@link NEVER}\n * @see {@link of}\n * @see {@link throwError}\n */\nexport const EMPTY = new Observable((subscriber) => subscriber.complete());\n\n/**\n * @param scheduler A {@link SchedulerLike} to use for scheduling\n * the emission of the complete notification.\n * @deprecated Replaced with the {@link EMPTY} constant or {@link scheduled} (e.g. `scheduled([], scheduler)`). Will be removed in v8.\n */\nexport function empty(scheduler?: SchedulerLike) {\n return scheduler ? emptyScheduled(scheduler) : EMPTY;\n}\n\nfunction emptyScheduled(scheduler: SchedulerLike) {\n return new Observable((subscriber) => scheduler.schedule(() => subscriber.complete()));\n}\n", "import { SchedulerLike } from '../types';\nimport { isFunction } from './isFunction';\n\nexport function isScheduler(value: any): value is SchedulerLike {\n return value && isFunction(value.schedule);\n}\n", "import { SchedulerLike } from '../types';\nimport { isFunction } from './isFunction';\nimport { isScheduler } from './isScheduler';\n\nfunction last(arr: T[]): T | undefined {\n return arr[arr.length - 1];\n}\n\nexport function popResultSelector(args: any[]): ((...args: unknown[]) => unknown) | undefined {\n return isFunction(last(args)) ? args.pop() : undefined;\n}\n\nexport function popScheduler(args: any[]): SchedulerLike | undefined {\n return isScheduler(last(args)) ? args.pop() : undefined;\n}\n\nexport function popNumber(args: any[], defaultValue: number): number {\n return typeof last(args) === 'number' ? args.pop()! : defaultValue;\n}\n", "export const isArrayLike = ((x: any): x is ArrayLike => x && typeof x.length === 'number' && typeof x !== 'function');", "import { isFunction } from \"./isFunction\";\n\n/**\n * Tests to see if the object is \"thennable\".\n * @param value the object to test\n */\nexport function isPromise(value: any): value is PromiseLike {\n return isFunction(value?.then);\n}\n", "import { InteropObservable } from '../types';\nimport { observable as Symbol_observable } from '../symbol/observable';\nimport { isFunction } from './isFunction';\n\n/** Identifies an input as being Observable (but not necessary an Rx Observable) */\nexport function isInteropObservable(input: any): input is InteropObservable {\n return isFunction(input[Symbol_observable]);\n}\n", "import { isFunction } from './isFunction';\n\nexport function isAsyncIterable(obj: any): obj is AsyncIterable {\n return Symbol.asyncIterator && isFunction(obj?.[Symbol.asyncIterator]);\n}\n", "/**\n * Creates the TypeError to throw if an invalid object is passed to `from` or `scheduled`.\n * @param input The object that was passed.\n */\nexport function createInvalidObservableTypeError(input: any) {\n // TODO: We should create error codes that can be looked up, so this can be less verbose.\n return new TypeError(\n `You provided ${\n input !== null && typeof input === 'object' ? 'an invalid object' : `'${input}'`\n } where a stream was expected. You can provide an Observable, Promise, ReadableStream, Array, AsyncIterable, or Iterable.`\n );\n}\n", "export function getSymbolIterator(): symbol {\n if (typeof Symbol !== 'function' || !Symbol.iterator) {\n return '@@iterator' as any;\n }\n\n return Symbol.iterator;\n}\n\nexport const iterator = getSymbolIterator();\n", "import { iterator as Symbol_iterator } from '../symbol/iterator';\nimport { isFunction } from './isFunction';\n\n/** Identifies an input as being an Iterable */\nexport function isIterable(input: any): input is Iterable {\n return isFunction(input?.[Symbol_iterator]);\n}\n", "import { ReadableStreamLike } from '../types';\nimport { isFunction } from './isFunction';\n\nexport async function* readableStreamLikeToAsyncGenerator(readableStream: ReadableStreamLike): AsyncGenerator {\n const reader = readableStream.getReader();\n try {\n while (true) {\n const { value, done } = await reader.read();\n if (done) {\n return;\n }\n yield value!;\n }\n } finally {\n reader.releaseLock();\n }\n}\n\nexport function isReadableStreamLike(obj: any): obj is ReadableStreamLike {\n // We don't want to use instanceof checks because they would return\n // false for instances from another Realm, like an