Skip to main content

github2pandas supports the aggregation of project activities in a GitHub repository and makes them available in pandas dataframes

Project description

Transform GitHub Activities to Pandas Dataframes

General information

This package is being developed by the participating partners (TU Bergakademie Freiberg, OVGU Magdeburg and HU Berlin) as part of the DiP-iT project Website.

The package implements Python functions for

  • aggregating and preprocessing GitHub activities (Commits, Actions, Issues, Pull-Requests) and
  • generating project progress summaries according to different metrics (ratio of changed lines, ratio of aggregated Levenshtein distances e.g.).

github2pandas stores the collected information in a collection of pandas DataFrames starting from a user defined root folder. The structure beyond that (file names, folder names) is defined as a member variable in the corresponding classes and can be overwritten. The default configuration results in the following file structure.

|-- My_Github_Repository_0               <- Repository name
|   |- Repo.json                         <- Json file containing user and repo name
|   |- Repository
|   |   |- Repository.p  
|   |- Issues
|   |   |- pdIssuesComments.p
|   |   |- pdIssuesEvents.p
|   |   |- pdIssues.p
|   |   |- pdIssuesReactions.p
|   |- PullRequests
|   |   |- pdPullRequestsComments.p
|   |   |- pdPullRequestsCommits.p
|   |   |- pdPullRequestsEvents.p
|   |   |- pdPullRequests.p
|   |   |- pdPullRequestsReactions.p
|   |   |- pdPullRequestsReviews.p
|   |- Users.p
|   |- Versions
|   |   |- pdCommits.p
|   |   |- pdEdits.p
|   |   |- pdBranches.p
|   |   |- pVersions.db
|   |   |- repo                         <- Repository clone
|   |   |   |- ..
|   |- Workflows
|       |- pdWorkflows.p
|-- My_Github_Repository_1
...

The internal structure and relations of the data frames are included in the project's wiki.

Installation

github2pandas is available on pypi. Use pip to install the package.

global

On Linux:

sudo pip3 install github2pandas 
sudo pip install github2pandas

On Windows as admin or for one user:

pip install github2pandas
pip install --user github2pandas 

in virtual environment:

pipenv install github2pandas

Usage

GitHub token is required for use, which is used for authentication. The website describes how you can generate this for your GitHub account. Customise the username and project name and explore any public or private repository you have access to with your account!

Access token is to define in .env oder .py (.ipynb) file. The default value of python.envFile setting is ${workspaceFolder}/.env

TOKEN="example_token"

An short example of a python script:

import os
from pathlib import Path
# github2pandas imports
from github2pandas.core import Core
from github2pandas.github2pandas import GitHub2Pandas

git_repo_name = "github2pandas"
git_repo_owner = "TUBAF-IFI-DiPiT"
    
data_root_dir = Path("data")
data_root_dir.mkdir(parents=True, exist_ok=True)
github_token = os.environ['TOKEN']

github2pandas = GitHub2Pandas(github_token,data_root_dir)
repo = github2pandas.get_repo(git_repo_owner, git_repo_name)
# extract complete repository
github2pandas.generate_pandas_tables(repo)

# exports pandas files to one excel file
GitHub2Pandas.save_tables_to_excel(Path(data_root_dir,git_repo_owner,git_repo_name))

Notebook examples

Currently not updated for github2pandas version 2.0.0!! The corresponding github2pandas_notebooks repository illustrates the usage with examplary investigations.

The documentation of the module is available at https://github2pandas.readthedocs.io/.

Working with pipenv

Process Command
Installation pipenv install --dev
Run specific script pipenv run python file.py
Run all Tests pipenv run python -m unittest
Run all tests in a specific folder pipenv run python -m unittest discover -s 'tests'
Run all tests with specific filename pipenv run python -m unittest discover -p 'test_*.py'
Start Jupyter server in virtual environment pipenv run jupyter notebook

For Contributors

Naming conventions: https://namingconvention.org/python/

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

github2pandas-2.0.0.tar.gz (30.0 kB view details)

Uploaded Source

Built Distribution

github2pandas-2.0.0-py3-none-any.whl (36.0 kB view details)

Uploaded Python 3

File details

Details for the file github2pandas-2.0.0.tar.gz.

File metadata

  • Download URL: github2pandas-2.0.0.tar.gz
  • Upload date:
  • Size: 30.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.9.4

File hashes

Hashes for github2pandas-2.0.0.tar.gz
Algorithm Hash digest
SHA256 3bde2cd44bc8dd7d9223816c3bcff14d0aed612158b2ea8fa2a51b1d0f7fa58b
MD5 6fb69c68aa7e6c23f391d24a90b9e7e4
BLAKE2b-256 65256259ab7f03257f845bb5edaffe3ebe2265cdd13af2df6b4c28ff03d9b5b3

See more details on using hashes here.

File details

Details for the file github2pandas-2.0.0-py3-none-any.whl.

File metadata

File hashes

Hashes for github2pandas-2.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 024addf3303f807aa884bff998cecff245d5d52c93b3d2e5f8d69411878710fb
MD5 cddbbdfd91d0681caa82da5ccf0eff0d
BLAKE2b-256 6824153701646b8027285ea93eb3e39dacc5ff3316dfea431615fa4fd77fcad4

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page