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https://github.com/manas1820/fantastic-waffle
https://github.com/manas1820/fantastic-waffle
Last synced: 1 day ago
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- Host: GitHub
- URL: https://github.com/manas1820/fantastic-waffle
- Owner: Manas1820
- Created: 2024-10-28T19:25:23.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-10-28T20:14:42.000Z (3 months ago)
- Last Synced: 2024-10-28T20:35:26.666Z (3 months ago)
- Language: Python
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# upload_service
#### Sample Curl Request
```
curl -X POST "http://localhost:8000/api/upload-file" -F "[email protected]"
```
## Poetry
This project uses poetry. It's a modern dependency management
tool.
To run the project use this set of commands:
```bash
poetry install
poetry run python -m upload_service
```
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/
## Docker
You can start the project with docker using this command:
```bash
docker-compose up --build
```
If you want to develop in docker with autoreload and exposed ports add `-f deploy/docker-compose.dev.yml` to your docker command.
Like this:
```bash
docker-compose -f 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:
```bash
docker-compose build
```
## Project structure
```bash
$ tree "upload_service"
upload_service
├── 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.
├── __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.
│ └── router.py # Main router.
├── application.py # FastAPI application configuration.
└── lifespan.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 and place all
environment variables here.
All environment variables should start with "UPLOAD_SERVICE_" prefix.
For example if you see in your "upload_service/settings.py" a variable named like
`random_parameter`, you should provide the "UPLOAD_SERVICE_RANDOM_PARAMETER"
variable to configure the value. This behaviour can be changed by overriding `env_prefix` property
in `upload_service.settings.Settings.Config`.
An example of .env file:
```bash
UPLOAD_SERVICE_RELOAD="True"
UPLOAD_SERVICE_PORT="8000"
UPLOAD_SERVICE_ENVIRONMENT="dev"
```
You can read more about BaseSettings class here: https://pydantic-docs.helpmanual.io/usage/settings/
## Pre-commit
To install pre-commit simply run inside the shell:
```bash
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);
* mypy (validates types);
* ruff (spots possible bugs);
You can read more about pre-commit here: https://pre-commit.com/
## Running tests
If you want to run it in docker, simply run:
```bash
docker-compose run --build --rm api pytest -vv .
docker-compose down
```
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=upload_service" -e "POSTGRES_USER=upload_service" -e "POSTGRES_DB=upload_service" postgres:16.3-bullseye
```
2. Run the pytest.
```bash
pytest -vv .
```