Arca is a library for running Python functions (callables) from git repositories in various states of isolation. Arca can also cache the results of these callables using dogpile.cache.

• Arca - name of the library. When written as Arca, the main interface class is being referenced.
• Task - definition of the function (callable), consists of a reference to the object and arguments.
• Backend - a way of running tasks.

• Python >= 3.6

Requirements for certain backends:

• Docker (for Docker Backend and Vagrant Backend)
• Vagrant (for the Vagrant Backend)

To install the last stable version:

python -m pip install arca

If you want to use the Docker backend:

python -m  pip install arca[docker]

Or if you want to use the Vagrant backend:

python -m pip install arca[vagrant]

Or if you wish to install the upstream version:

python -m pip install git+https://github.com/mikicz/arca.git#egg=arca
python -m pip install git+https://github.com/mikicz/arca.git#egg=arca[docker]
python -m pip install git+https://github.com/mikicz/arca.git#egg=arca[vagrant]

To run a Hello World example you'll only need the arca.Arca and arca.Task classes. Task is used for defining the task that's supposed to be run in the repositories. Arca takes care of all the settings and provides the basic API for running the tasks.

Let's say we have the following file, called hello_world.py, in a repository https://example.com/hello_word.git, on branch master.

def say_hello():
   return "Hello World!"

To call the function using Arca, the following example would do so:

from arca import Arca, Task

task = Task("hello_world:say_hello")
arca = Arca()

result = arca.run("https://example.com/hello_word.git", "master", task)
print(result.output)

The code would print Hello World!. result would be a arca.Result instance which currently only has one attribute, output, with the output of the function call. If the task fails, arca.exceptions.BuildError would be raised.

By default, the Current Environment Backend is used to run tasks, which uses the current Python, launching the code in a subprocess. You can learn about backends here.

You can read the full documentation on Read The Docs.

To run tests you'll need the optional requirements, Docker and Vagrant. Once you have them and they can be used by the current user you just need to run:

python setup.py test

This will launch the tests and a PEP8 check. The tests will take some time since building the custom docker images is also tested and vagrant, in general, takes a long time to set up.

I am developing this library as my bachelor thesis and will be not accepting any PRs at the moment.

• Repository: GitHub
• PyPi package: arca
• CI: Travis
• Test coverage: Codecov
• Documentation: Read The Docs

This project is licensed under the MIT License - see the LICENSE file for details.