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A Python library and tools for the DaSCH Service Platform

Project description

PyPI version

DSP-TOOLS - DaSCH Service Platform Tools

dsp-tools is a command line tool that helps you interacting with the DaSCH Service Platform API.
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Information for developers

There is a Makefile for all the following tasks (and more). Type make to print the available targets.

For a quick start, use:

pip install pipenv
pipenv install --dev
pipenv run make install

This creates a pipenv-environment, installs all dependencies, and installs dsp-tools from source.

If you prefer getting around pipenv, use instead:

make install-requirements
make install

Pipenv

We use pipenv for our dependency management. There are two ways to get started:

  • pipenv install --dev installs all dependencies, while giving them the opportunity to update themselves
  • pipenv install --ignore-pipfile is used to get a deterministic build in production

This works because there are two files defining the dependencies:

  • Pipfile replaces requirements.txt, but lists only the core dependencies, ordered in two sections:
    • [packages] lists the dependencies used to run the software.
    • [dev-packages] lists additional dependencies used for tests and deployment.
  • Pipfile.lock enables deterministic builds, by exactly pinning the version of all (sub-) dependencies. This is done automatically, you must not edit Pipfile.lock.

The diverse requirements.txt files in this repo are only present for backwards compatibility and for GitHub CI.

If you want to install a new package, install it with pipenv install package. This

  • installs the package (incl. sub-dependencies) in your virtual environment
  • adds the package to the section [packages] of Pipfile. By default, no versions are pinned
  • adds the pinned versions of package and all sub-dependencies to Pipfile.lock

If a package is only needed for development, please install it with pipenv install package --dev, so it gets added to the [dev-packages] section of Pipfile.

For security reasons, the maintainer regularly executes

  • pipenv check to get informed about vulnerabilities
  • pipenv update to update Pipfile.lock with the latest version of every package
  • make freeze-requirements to update the requirement files and setup.py

make freeze-requirements must also be executed after adding a new dependency. If you prefer working without pipenv, you can freeze your requirements with pip3 freeze > requirements.txt and update setup.py manually.

Pipenv setup in PyCharm

  • Go to Add Interpreter > Pipenv Environment
  • Base Interpreter: PyCarm auto-detects one of your system-wide installed Pythons as base interpreter.
  • Pipenv executable: auto-detected
  • After hitting OK, PyCharm creates a new pipenv environment and installs the dependencies from Pipfile

If you already initialized a pipenv-environment via command line, you can add its interpreter in PyCharm, but this will create the pipenv-environment again.

Testing

Please note that testing requires launching the complete DSP API stack which is based on docker images. Therefore, we recommend installing the docker desktop client.
To run the complete test suite:

make test

Code style

When contributing to the project please make sure you use the same code style rules as we do. We use autopep8 and mypy. The configuration is defined in pyproject.toml in the root directory of the project.

You can use the configuration with autopep8 --global-config pyproject.toml [file path] and mypy --config-file pyproject.toml [file path].

If you are using PyCharm we recommend installing autopep8 as external tool. You can then use it with right-click on the file > External Tools > autopep8 to reformat files in-place. Due to compatibility issues with VSCode, the argument --in-place=true can not be declared in the pyproject.toml and needs to be passed to the external tool in the PyCharm settings.
mypy is available as plugin.

In VSCode, both mypy and autopep8 can be set up as default linter and formatter through the python extension.

For formatting Markdown files (*.md) we use the default styling configuration provided by PyCharm.

Publishing

Publishing is automated with GitHub Actions and should not be done manually. Please follow the Pull Request Guidelines. If done correctly, when merging a pull request into main, the release-please action will create or update a pull request for a release. This pull request will follow semantic versioning and update the change log. Once all desired features are merged, the release can be executed by merging this release pull request into main. This will trigger actions that create a release on GitHub, on PyPI and the docs.

Please ensure you have only one pull request per feature.

Publishing manually

Publishing is automated with GitHub Actions and should not be done manually. If you still need to do it, follow the steps below.

Generate the distribution package. Make sure you have the latest versions of setuptools and wheel installed:

python3 -m pip install --upgrade pip setuptools wheel
python3 setup.py sdist bdist_wheel

You can install the package locally from the dist:

python3 -m pip ./dist/some_name.whl

Upload package works also with make:

make dist
make upload

For local development:

python3 setup.py develop

Contributing to the documentation

The documentation is a collection of markdown files in the docs folder.
After updates of the files, build and check the result with the following command:

make docs-serve 

The documentation is published on https://docs.dasch.swiss/latest/DSP-TOOLS. During the centralized release process of all components of the DSP software stack, the docs of dsp-tools get built from the main branch to https://docs.dasch.swiss.

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