pokemon_api

This project was generated using fastapi_template.

Project structure

$ tree "pokemon_api"
pokemon_api
├── conftest.py  # Fixtures for all tests.
├── db  # module contains db configurations
│   ├── dao  # Data Access Objects. Contains different classes to interact with database.
│   └── models  # Package contains different models for ORMs.
│       └── pokemon.py  # All the table related to pokemons.
├── __main__.py  # Startup script. Starts uvicorn.
├── services  # Package for different external services such as rabbit or redis etc.
├── settings.py  # Main configuration settings for project.
├── static  # Static content.
├── tests  # Tests for project.
└── web  # Package contains web server. Handlers, startup config.
    ├── api  # Package with all handlers.
    │   └── pokemons  # Endpoints directory for pokemons.
    │   │   └── views.py  # Different routes to get pokemons data.
    │   └── router.py  # Main router.
    ├── application.py  # FastAPI application configuration.
    └── lifetime.py  # Contains actions to perform on startup and shutdown.

Configuration

This application can be configured with environment variables.

You can create .env file in the root directory or rename example.env to .env and place all environment variables here

All environment variables should start with "POKEMON_API_" prefix.

For example if you see in your "pokemon_api/settings.py" a variable named like random_parameter, you should provide the "POKEMON_API_RANDOM_PARAMETER" variable to configure the value. This behaviour can be changed by overriding env_prefix property in pokemon_api.settings.Settings.Config.

An example of .env file:

POKEMON_API_RELOAD="True"
POKEMON_API_PORT="8000"
POKEMON_API_ENVIRONMENT="dev"

You can read more about BaseSettings class here: https://pydantic-docs.helpmanual.io/usage/settings/

Warning

Attention: Please make sure to set up the required environment variables or configuration files before running the application. Failure to provide these settings may result in errors during application startup.

Poetry

This project uses poetry. It's a modern dependency management tool.

To run the project use this set of commands:

Installation

Using virtual environment

Create a virtual environment and install dependencies using Conda

1. Create a New Conda Environment:

   Open your terminal or command prompt and use the following command to create a new Conda environment. Replace myenv with the name you'd like to give to your environment.

   conda create --name pokemon_api python=3.8

   This command will create a new Conda environment named pokemon_api and use Python 3.8.

2. Activate the Conda Environment**:

   Once the environment is created, activate it using the following command:

   conda activate pokemon_api

   Replace pokemon_api with the name of your Conda environment.

After you activated the enviroment install the dependencies using poetry.

pip install poetry
poetry install
poetry run python -m pokemon_api

This will start the server on the configured host.

You can find swagger documentation at /api/docs.

You can read more about poetry here: https://python-poetry.org/

Using Docker

You can start the project with docker using this command:

docker-compose -f deploy/docker-compose.yml --project-directory . up --build

If you want to develop in docker with autoreload add -f deploy/docker-compose.dev.yml to your docker command. Like this:

docker-compose -f deploy/docker-compose.yml -f deploy/docker-compose.dev.yml --project-directory . up --build

This command exposes the web application on port 8000, mounts current directory and enables autoreload.

But you have to rebuild image every time you modify poetry.lock or pyproject.toml with this command:

docker-compose -f deploy/docker-compose.yml --project-directory . build

Pre-commit

To install pre-commit simply run inside the shell:

pre-commit install

pre-commit is very useful to check your code before publishing it. It's configured using .pre-commit-config.yaml file.

By default it runs:

• black (formats your code);
• isort (sorts imports in all files);
• flake8 (spots possible bugs);

You can read more about pre-commit here: https://pre-commit.com/

Using Docker

You can start the project with Docker using the following command:

docker-compose -f deploy/docker-compose.yml -f deploy/docker-compose.dev.yml --project-directory . run --build --rm api pytest -vv .
docker-compose -f deploy/docker-compose.yml -f deploy/docker-compose.dev.yml --project-directory . down

This command will start the server on port 8000.

For running tests on your local machine.

1. you need to start a database.

I prefer doing it with docker:

docker run -p "5432:5432" -e "POSTGRES_PASSWORD=pokemon_api" -e "POSTGRES_USER=pokemon_api" -e "POSTGRES_DB=pokemon_api" postgres:13.8-bullseye

2. Run the pytest.

pytest -vv .