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tests Coverage Status

$title

$summary

Description

$description

Installation

We recommend using the provided Docker container.

A pre-build version is available at docker hub:

docker pull ghga/$name:$version

Or you can build the container yourself from the ./Dockerfile:

# Execute in the repo's root dir:
docker build -t ghga/$name:$version .

For production-ready deployment, we recommend using Kubernetes, however, for simple use cases, you could execute the service using docker on a single server:

# The entrypoint is preconfigured:
docker run -p 8080:8080 ghga/$name:$version --help

If you prefer not to use containers, you may install the service from source:

# Execute in the repo's root dir:
pip install .

# To run the service:
$shortname --help

Configuration

Parameters

The service requires the following configuration parameters: $config_description

Usage:

A template YAML for configurating the service can be found at ./example-config.yaml. Please adapt it, rename it to .$shortname.yaml, and place it into one of the following locations:

  • in the current working directory were you are execute the service (on unix: ./.$shortname.yaml)
  • in your home directory (on unix: ~/.$shortname.yaml)

The config yaml will be automatically parsed by the service.

Important: If you are using containers, the locations refer to paths within the container.

All parameters mentioned in the ./example-config.yaml could also be set using environment variables or file secrets.

For naming the environment variables, just prefix the parameter name with ${shortname}_, e.g. for the host set an environment variable named ${shortname}_host (you may use both upper or lower cases, however, it is standard to define all env variables in upper cases).

To using file secrets please refer to the corresponding section of the pydantic documentation.

$openapi_doc

Architecture and Design:

$design_description

Development

For setting up the development environment, we rely on the devcontainer feature of VS Code in combination with Docker Compose.

To use it, you have to have Docker Compose as well as VS Code with its "Remote - Containers" extension (ms-vscode-remote.remote-containers) installed. Then open this repository in VS Code and run the command Remote-Containers: Reopen in Container from the VS Code "Command Palette".

This will give you a full-fledged, pre-configured development environment including:

  • infrastructural dependencies of the service (databases, etc.)
  • all relevant VS Code extensions pre-installed
  • pre-configured linting and auto-formatting
  • a pre-configured debugger
  • automatic license-header insertion

Moreover, inside the devcontainer, a convenience commands dev_install is available. It installs the service with all development dependencies, installs pre-commit.

The installation is performed automatically when you build the devcontainer. However, if you update dependencies in the ./pyproject.toml or the ./requirements-dev.txt, please run it again.

License

This repository is free to use and modify according to the Apache 2.0 License.

README Generation

This README file is auto-generated, please see readme_generation.md for details.