Metadata-Version: 2.1
Name: ghga_connector
Version: 0.2.12
Summary: GHGA Connector - A CLI client application for interacting with the GHGA system.
Home-page: https://github.com/ghga-de/ghga-connector
Author: German Human Genome Phenome Archive (GHGA)
Author-email: contact@ghga.de
License: Apache 2.0
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3.9
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Topic :: Internet :: WWW/HTTP :: HTTP Servers
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.9.10
Description-Content-Type: text/markdown; charset=UTF-8
License-File: LICENSE

![tests](https://github.com/ghga-de/ghga-connector/actions/workflows/unit_and_int_tests.yaml/badge.svg)
[![codecov](https://codecov.io/gh/ghga-de/ghga-connector/branch/main/graph/badge.svg?token=GYH99Y71CK)](https://codecov.io/gh/ghga-de/ghga-connector)
# GHGA-Connector

A CLI - Client to perform up- and download operations to and from a local GHGA Node.

## Documentation:

An extensive documentation can be found [here](...) (coming soon).

## Quick Start:
### Installation

This package uses PycURL and thus has curl (https://curl.se/) as a dependency. On Debian-based Linux distributions, you can install cURL using:

```
sudo apt install libcurl4-openssl-dev libssl-dev
```

This package is available at PyPI: https://pypi.org/project/ghga_connector

You can install it from there using:

```
pip install ghga_connector
```

### Using the CLI:

To get help on the command line interface, type:
```
ghga_connector --help
```

## Development
For setting up the development environment, we rely on the
[devcontainer feature](https://code.visualstudio.com/docs/remote/containers) of vscode
in combination with Docker Compose.

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

This will give you a full-fledged, pre-configured development environment including:
- infrastructural dependencies of the service (databases, etc.)
- all relevant vscode extensions pre-installed
- pre-configured linting and auto-formating
- a pre-configured debugger
- automatic license-header insertion

Moreover, inside the devcontainer, there are two convenience commands available
(please type them in the integrated terminal of vscode):
- `dev_install` - install the service with all development dependencies,
installs pre-commit, and applies any migration scripts to the test database
(please run that if you are starting the devcontainer for the first time
or if you added any python dependencies to the [`./setup.cfg`](./setup.cfg))
- `dev_launcher` - starts the service with the development config yaml
(located in the `./.devcontainer/` dir)

If you prefer not to use vscode, you could get a similar setup (without the editor specific features)
by running the following commands:
``` bash
# Execute in the repo's root dir:
cd ./.devcontainer

# build and run the environment with docker-compose
docker-compose up

# attach to the main container:
# (you can open multiple shell sessions like this)
docker exec -it devcontainer_app_1 /bin/bash
```

## License
This repository is free to use and modify according to the [Apache 2.0 License](./LICENSE).
