https://github.com/sylhare/git-processor

📊Process and parse through git log statistic
https://github.com/sylhare/git-processor

data-science git graph pandas plot python

Last synced: about 2 months ago
JSON representation

📊Process and parse through git log statistic

• Host: GitHub
• URL: https://github.com/sylhare/git-processor
• Owner: sylhare
• Created: 2019-11-21T21:34:29.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2020-11-25T18:19:17.000Z (over 5 years ago)
• Last Synced: 2025-06-14T12:05:30.551Z (about 1 year ago)
• Topics: data-science, git, graph, pandas, plot, python
• Language: Python
• Homepage: https://sylhare.github.io/git-processor/
• Size: 979 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst

Awesome Lists containing this project

README

          
Git Processor

=============

A git log processor for better stats.

Made to be used on one or multiple Git repositories

View the demo `git processor demo `_.

Setup

-----

Install the library with:

.. code:: bash

    # From pypi

    python3 -m pip install git_processor

To use it, run the ``generate_git_logs.sh`` in where you have all your repository.

It will create a ``stats.txt`` file.

.. code:: python

    import os

    from git_processor.data import Projects

    p = Projects(os.path.abspath("stats.txt"))  # Process the git log stats

    p.clean_up_names()                          # Get all similar names as one

    p.df                                        # Get the created dataframe

    p.total()                                   # Total commits per user

Let's use jupyter to display the information.

.. code:: bash

    pyhton3 -m pip install jupyter

    cd jupyter/

    jupyter notebook

Once you are in the jupyter notebook, you can display the data and plot the stats.

Check in the ``jupyter/`` folder, you can reuse the demo and get your stats in one go.

Just click on ``Run All Cell``, or go along with [shift] + [enter] to run them individually.

Testing

-------

To find out more info about the testing configuration, check out the

``tox.ini`` file.

.. code:: bash

   # Run the test suite

   tox

   # Run the linter:

   tox -e lint

Local Installation

------------------

Using a virtual environment:

.. code:: bash

    # From pypi

    python3 -m pip install virtualenv

Then set it up and install the package locally

.. code:: bash

   # Create the virtual environment

   python3 -m venv `pwd`/env

   # Activate it

   source env/bin/activate

   # Install from local

   (env) python3 -m pip install .

   

   

Other Git Processors

--------------------

Here is a list of other python git processors. (Usually meant for one repository)

- `hercules `_

- `git-of-theseus `_