Blog backend

Backend for blog.didgibot.com

Prerequisites: (Also see requirements.txt in the project's root):

1. Python >= 3.12
2. FastAPI
3. MongoDB
4. Strawberry (GraphQL)
5. Docker and Docker Compose (optional)

Development

Installation

Docker and docker compose are recommended for development purposes.

1. Open your terminal and clone repository.
2. In the root of the cloned project copy cicd/.env.dist to cicd/.env.
3. Set up your own env vars in the cicd/.env file and/or accept defaults.
4. Run docker build --progress=plain --no-cache -t <your tag here> -f cicd/Dockerfile .. It will build FastAPI docker container.
5. Switch to cicd directory.
6. Run docker compose up and wait until application starts.
7. Run docker compose ps to make sure all containers have started.
8. Run docker compose logs -f and make sure all is running as expected.
9. Open browser at http://localhost:<your mongo express port from .env> and see if you successfully connected to MongoDB.
10. Open browser at http://localhost:<your backend port from .env>/docs and see if it serves you the API documentation (OAS 3.1).
11. Check if the data folder in the root of the project now contains the MongoDB files.
12. You should be all set.

Development procedures

This app should be started in Docker. The code would reload automatically with every saved change (thanks to uvicorn's --reload flag).

The minimum requirement is to start Mongo DB, which is also configured in a docker compose environment (see docker-compose.yaml in the root of the project). For this you can run docker compose up -d in the root of this project. Create, however, .env file first - clone it from the .env.dist and modify accordingly.

I also recommend to start this and other apps by running docker compose up -d in the parent folder instead. Most probably the folder's name is didgibot. There other applications, such as Blog FE and Blog Admin FE, among others, reside. This way all applications necessary for Blog project will be started (Blog, for example, also needs the MinIO).

Since this repo uses DevContainers (which can be configured in .devcontainer/devcontainer.json), next step is to open it as a devcontainer. This way the correct python version is ensured, among other benefits. In VS Code use Dev Containers extension.

The GraphQL schema is available in the Graphql IDE (Apollo Sandbox) form at http://:/graphql path (most probably http://localhost:8888/graphql).

Migrations

In the dev environment run following terminal command from the project's root: python -m app.migrations.cli run to run all pending migrations. To go back one step, run python -m app.migrations.cli rollback. It will roll back one migration at a time. Note: The migrations will be run automatically when the app is deployed to main branch using the init pod.

If you want

Debugging

For debugging purposes do not forget to install necessary extension, such as Python Debugger (if using VS Code).

The codebase ships with .vscode folder that contains the launch.json file. The file contains the "Python Debugger: Remote Attach" configuration that would allow to set breakpoints and debug the application inside VSCode. For any other IDE's - please find an appropriate documentation.

Please note that docker has opened a debug port (which you should have set up in the .env file) - please consult .env, docker-compose.yml. If you accepted defaults while setting up the .env, the debug port should be 5690.