Museum Visit Planner

Welcome to the Museum Visit Planner (named since this is an MVP minimal viable product :) ). This application will let you plan a trip to a museum exhibition, including weather forecast information for the exhibition location.

Deployed frontend: link

Deployed backend API: link

This repo contains two projects:

1. A serverless backend application, written in Python, that includes:

   1. An AWS Lambda to retrieve Exhbition data from the Harvard Art Museum API and store in DynamoDB.
   2. An AWS Lambda to retrieve weather data for each Exhbition venue from Open Meteo, and enrich the items in DynamoDB.
   3. An AWS Lambda running FastAPI to expose rest based API, via an AWS API Gateway.

2. A frontend application, written using React + Vite template, that queries the Rest API backend.

Archictecture Diagram

Technologies Used

1. Backend: Cloud Native Services
   1. AWS Lambda
   2. AWS DynamoDB (via boto3 client)
   3. AWS Api Gateway
   4. AWS Secrets Manager
   5. AWS Event Bridge Rules
2. Infrastructure as Code
   1. AWS CDK
3. Frontend:
   1. React + Vite
   2. AWS Amplify for deployment and hosting

Developer Environment Setup

Prerequisites

1. An AWS Account with credentials configured locally.
2. aws cli installed locally link.
3. Python installed locally (recommend using pyenv).
4. Node v22 installed locally (recommend using nvm).
5. CDK installed locally link.

Manual Steps in AWS console (could be automated with more time)

1. Create a Secret for the Harvard Art Museum API key to avoid committing it to GitHub.
2. Set up AWS Amplify to deploy frontend app on push to main branch in GitHub repo. Follow the steps here
3. Create an IAM User for credentials to use when pushing from CDK locally.

Quick Instructions

Backend

Build and deploy the backend using the Makefile commands, found in the backend directory.

Run the FastAPI locally

make run

Deploy to AWS using CDK

make full-clean-deploy

Clean up

make clean

Frontend

Run locally, in frontend directory:

npm run dev

Detailed instructions

Note: this instructions are for mac os local environment.

Pyenv Install

  brew update
  brew install pyenv

Configure pyenv for your choice of terminal e.g. for ksh

  echo 'export PYENV_ROOT="$HOME/.pyenv"' >> ~/.zshrc
  echo '[[ -d $PYENV_ROOT/bin ]] && export PATH="$PYENV_ROOT/bin:$PATH"' >> ~/.zshrc
  echo 'eval "$(pyenv init - zsh)"' >> ~/.zshrc

Use pyenv to download 3.12 version of Python.

pyenv install 3.12

Set this version of Python to be used:

pyenv local 3.12

Check that it's set

python --version

should output something like:

julianleonard@Julians-Laptop  museum-visit-planner % python --version
Python 3.12.8

To use CDK you will need to install Node. I recommend using nvm (https://github.com/nvm-sh/nvm) to install and manage your node version (similar to pyenv above). For this case study I am using node v.22.11.0.

CDK Install Instructions

Also, this readme assumes you have an AWS account and the aws cli installed already: https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html

Install the CDK:

npm install -g aws-cdk

Check the version that is installed:

(myenv) julianleonard@Julians-Laptop  museum-visit-planner % cdk version
2.177.0 (build b396961)

Boostrap your CDK environment

If you working in an AWS environment which has not been bootstrapped for CDK, you'll need to run this command: cdk bootstrap aws://<aws-account-id>/<region> e.g.

cdk bootstrap aws://1234567890/eu-central-1