Welcome to OpenTransit! We're passionate about using open data to improve public transit systems around the world, starting with San Francisco.
This app uses historical transit data to help riders understand the quality of SF Muni bus and subway lines. Check out the app!
If you're visiting this repo and looking to contribute, check out our onboarding doc!
To start, you'll need to get Docker. Install Docker Desktop or another Docker distribution for your platform.
Build and run the Docker containers:
docker-compose up
This will run the React frontend in development mode at http://localhost:3000, and the Flask backend in development mode at http://localhost:5000.
Your local directory will be shared within the Docker container at /app
.
When you edit files in your local directory, the React and Flask containers should automatically update with the new code.
To start a shell within the Flask Docker container, run ./docker-shell.sh
(Linux/Mac) or docker-shell
(Windows).
You can run command line scripts like backend/compute_arrivals.py
and backend/headways.py
from the shell in the Docker container.
If you need to install some new dependencies in the Docker images, you can rebuild them via docker-compose build
.
By default, the app shows statistics for San Francisco Muni. You can configure the transit agency displayed in the web app by setting the OPENTRANSIT_AGENCY_IDS environment variable.
Other available agency IDs include:
trimet
(TriMet in Portland, Oregon)portland-sc
(Portland Streetcar)
To set this environment variable in development when using Docker, create a file named docker-compose.override.yml file in the root directory of this repository, like so:
version: "3.7"
services:
flask-dev:
environment:
OPENTRANSIT_AGENCY_IDS: trimet
After changing docker-compose.override.yml, you will need to re-run docker-compose up
for the changes to take effect.
Make sure you've been added to the trynmaps organization on GitHub. Join the Code for SF Slack and join the #opentransit channel, then you'll see a guide to get in.
To get started, see the Issues page. You may want to identify good first issues.
When you make a Pull Request, we would suggest you deploy your branch to Heroku so that other team members can try out your feature.
First, create an account at heroku.com and create an app. Follow the instructions to deploy using Heroku Git with an existing Git repository.
The first time you deploy to Heroku, you'll need to tell it to build Docker containers using heroku.yml:
heroku stack:set container
You then need to set up a remote called heroku
. Then run this to deploy your local branch:
git push heroku local-branch-name:master
Then copy the link to this app and paste it in the PR.
Once a PR is merged into master, Google Cloud Build will automatically build
the latest code and deploy it to a cluster on Google Kubernetes Engine (GKE).
The build steps are defined in cloudbuild.yaml
.
- Docker - to ensure a consistent environment across machines.
- Docker Compose - to run multiple containers at once.
- NPM - for package management. We explicitly decided to not use Yarn, because both package managers offer similar performance, we were already using NPM for backend package management, and the Yarn roadmap did not offer compelling improvements going forward.
- React - Selected for popularity, simple view, and speedy virutal DOM. Code lives in the
/frontend
directory. It was built using Create React App. - Material UI - which we use over Bootstrap since MUI doesn't rely on jQuery. It has a popular React framework and looks great on mobile.
- Redux - for state management and to simplify our application and component interaction.
- Redux Thunk - as middleware for Redux.
- React Hooks - to manage interactions with state management.
- Functional Components - We migrated away from ES6 React Components and toward React Functional Components due to the simpler component logic and the ability to use React Hooks that Functional Components offer.
- ESLint - Linting set in the format of AirBNB Style.
- Prettier - Code formatter to maintain standard code format for the frontend code.
- Husky - Pre-commit hook to trigger Prettier auto formatting before pushing to Github.
- Flask - because our data science work was already done in iPython and using Python for the backend would ease the migration from experimentation to production.
If you ever need to use a new pip library, make sure you run pip freeze > requirements.txt
so other contributors have the latest versions of required packages.
If you're developing within Docker on Windows, by default, React does not automatically recompile the frontend code when you make changes.
In order to allow React to automatically recompile the frontend code within the Docker container when you edit files shared from your
Windows host computer, you can create a docker-compose.override.yml
to enable CHOKIDAR_USEPOLLING like this:
version: "3.7"
services:
react-dev:
environment:
CHOKIDAR_USEPOLLING: "true"
CHOKIDAR_INTERVAL: "2500"
This setting is not in the main docker-compose.yml file because CHOKIDAR_USEPOLLING causes high CPU/battery usage for developers using Mac OS X, and CHOKIDAR_USEPOLLING is not necessary on Mac OS X to automatically recompile the frontend code when it changes.
Please see ADVANCED_DEV.md for advanced information like computing arrival times and deploying to AWS.
See agencies.md for configuring for different agencies, and how the front end gets the configuration information. Important for testing with other devices against your dev machine.