Plasa Backend

Using Firebase Functions and Firestore.

Table of Contents

• Plasa Backend
  • Table of Contents
  • Firebase Functions Endpoints
    • Endpoint Name: signatures
  • Firestore Collections Structure
    • Collection: {followed_account}
  • Firestore Scripts (@firestore-scripts)
    • push-followers-json.ts
    • push-followers-json-multifile.ts
    • push-followers-csv.ts
    • read-collection.ts

Firebase Functions Endpoints

Endpoint Name: signatures

• HTTP Method: GET

• Description: Generates signatures for follower data, handling both real Instagram usernames and generating fake data when needed.

• Authentication: Required (assumed, as it's a Firebase Function)

• Query Parameters:

  • userAddress (required): Ethereum address of the user
  • instagramUsername (optional): Instagram username of the follower

• Response:

  • Success (200 OK):

    [
      {
        "spaceName": "string",
        "signature": "string",
        "followerSince": number,
        "deadline": number,
        "isReal": boolean,
        "instagramUsername": "string"
      },
      // ... (one object for each space)
    ]

  • Error (400 Bad Request):

    "Missing or invalid userAddress"

    or

    "Invalid instagramUsername"

• Example Usage:

  const userAddress = '0x1234567890123456789012345678901234567890'
  const instagramUsername = 'example_user' // Optional
  
  const url = new URL('https://your-firebase-function-url/signatures')
  url.searchParams.append('userAddress', userAddress)
  if (instagramUsername) {
  	url.searchParams.append('instagramUsername', instagramUsername)
  }
  
  const response = await fetch(url.toString())
  const data = await response.json()
  console.log(data)

Note: If instagramUsername is not provided, the function will generate a single random follower username for all spaces. The isReal field indicates whether the follower data is real (true) or generated (false).

Firestore Collections Structure

Collection: {followed_account}

• Description: Stores information about followers for each followed Instagram account. The collection name is the Instagram username of the followed account.

• Document Structure:

  {
  	"username": "string",
  	"follower_since": "number (timestamp)"
  }

• Document ID: The document ID is the follower's Instagram username.

• Usage Examples:

  // Reading follower data
  const followedAccount = 'example_account'
  const followerUsername = 'follower_user'
  const docRef = db.collection(followedAccount).doc(followerUsername)
  const doc = await docRef.get()
  if (doc.exists) {
  	console.log('Follower data:', doc.data())
  } else {
  	console.log('Follower not found')
  }
  
  // Writing follower data (should be done through Firebase Functions)
  const followedAccount = 'example_account'
  const followerUsername = 'new_follower'
  const followerData = {
  	username: followerUsername,
  	follower_since: firebase.firestore.FieldValue.serverTimestamp()
  }
  await db.collection(followedAccount).doc(followerUsername).set(followerData)

Firestore Scripts (@firestore-scripts)

push-followers-json.ts

• Description: This script reads follower data from a single JSON file and adds it to Firestore.
• Usage:
  1. Set the required environment variables in a .env file:
     • FOLLOWERS_COLLECTION_TO_PUSH: The Firestore collection to push data to
     • SERVICE_ACCOUNT_PATH: Path to the Firebase service account JSON file
     • FOLLOWERS_DATA_PATH: Path to the JSON file containing follower data
  2. Run the script using ts-node push-followers-json.ts
• Key Features:
  • Processes followers in batches of 100 for efficient Firestore writes
  • Handles large datasets by committing in batches
  • Logs progress and any errors encountered

push-followers-json-multifile.ts

• Description: This script processes multiple JSON files containing follower data and adds them to Firestore.
• Usage:
  1. Set the required environment variables in a .env file:
     • FOLLOWERS_COLLECTION_TO_PUSH: The Firestore collection to push data to
     • SERVICE_ACCOUNT_PATH: Path to the Firebase service account JSON file
     • FOLLOWERS_FOLDER_NAME: Name of the folder containing follower JSON files
  2. Run the script using ts-node push-followers-json-multifile.ts
• Key Features:
  • Processes multiple JSON files in a specified folder
  • Handles followers in batches of 500 for efficient Firestore writes
  • Skips reserved usernames (starting and ending with __)
  • Provides detailed logging, including total followers added and skipped for each file and grand totals

push-followers-csv.ts

• Description: This script reads follower data from a CSV file and adds it to Firestore.
• Usage:
  1. Set the required environment variables in a .env file:
     • FOLLOWERS_COLLECTION_TO_PUSH: The Firestore collection to push data to
     • SERVICE_ACCOUNT_PATH: Path to the Firebase service account JSON file
     • CSV_FILE_PATH: Path to the CSV file containing follower data
  2. Run the script using ts-node push-followers-csv.ts
• Key Features:
  • Processes followers from a CSV file
  • Handles followers in batches of 100 for efficient Firestore writes
  • Uses a fixed timestamp for all followers (currently set to '2024-06-12')
  • Provides progress logging, including total records uploaded

read-collection.ts

• Description: This script reads and logs all documents from a specified Firestore collection.
• Usage:
  1. Set the required environment variables in a .env file:
     • COLLECTION_TO_READ: The Firestore collection to read from
     • SERVICE_ACCOUNT_PATH: Path to the Firebase service account JSON file
  2. Run the script using ts-node read-collection.ts
• Key Features:
  • Reads all documents from the specified collection
  • Logs document IDs and data
  • Useful for verifying data after running the push scripts