gitgeo 1.0.1

Why use GitGeo?

• Curiosity

• Open source software community management

• Research on open source software ecosystems

• IT security compliance

Installation

pip install gitgeo

Usage

(requires internet connection)

• First, create one or more GitHub personal access tokens.

• Second, run these commands in the command line to set environmental variables:

  export GITHUB_USERNAME='[github_username]'
  export GITHUB_TOKEN='[github_token]'

• Alternatively, to use multiple tokens, create a file called tokens.txt in the code’s directory and enter a GitHub personal access token on each line.

• Third, run these commands in the command line:

gitgeo --package [package_name]

gitgeo --repo [github_repo_url]

For example:

>>> gitgeo --package requests

-----------------
PACKAGE: requests
-----------------
CONTRIBUTOR, LOCATION
* indicates PyPI maintainer
---------------------
kennethreitz42 | Virginia, USA
Lukasa * | London, England
sigmavirus24 | Madison, WI
nateprewitt * | None
slingamn | None
BraulioVM | Malaga & Granada, Spain
dpursehouse | Kawasaki
jgorset | Oslo, Norway
...

Or:

>>> gitgeo --repo www.github.com/psf/requests

-----------------
GITHUB REPO: psf/requests
-----------------
CONTRIBUTOR, LOCATION
---------------------
kennethreitz42 | Virginia, USA | United States
Lukasa | London, England | United Kingdom
sigmavirus24 | Madison, WI | United States
nateprewitt | None | None
...

There are other command line options too:

Add --summary to get the results summarized by country. e.g.

>>> gitgeo --package requests --summary

-----------------
PACKAGE: requests
GITHUB REPO: psf/requests
-----------------
COUNTRY | # OF CONTRIBUTORS
---------------------------
United States 37
None 23
United Kingdom 4
Canada 4
Germany 4
Switzerland 4
Spain 2
Russia 2
...

Add --map when using the --repo option to create an html map saved in the results folder. See image above for static example. Real map includes zooming and tooltip capability.

Add --ouput_csv to output csv of results to results folder.

To create a csv of contributors from many repositories, enter repositories on separate lines in the repos.txt file. Then use the --multirepo flag.

Add multirepo_map and then a filename to create a map of csv ouput. csv output must be located in the results folder.

Add --num and specify a multiple of 100 from 100 (default) to 500 to specify the number of contributors analyzed per repo.

pytest

Roadmap

• Investigate capability of predicting location via a model given only timestamp from commit and commit-related data. (Kinga)

• Investigate GitHub API for examining merges and who has merge rights.

• Add capability of reading through commits and, specifically, (1) determine if GitHub commit rights can be inferred.

• Investigate capability of extracting all users associated with a GitHub group

• Investigate capability to determine authenticity of location information

• Investigate possibility of geographic diversity score for a repo or package

• Investigate possibility of linking emails in commits to email breach lists.

• Investigate possibility of determining whether a project is a “hobby” project (outside of working hours) or a “work” project (within working hours)?

• Investigate possibility of using NLP to determine codebase specialties of each contributor. e.g. This person is the “auth” person.

• Investigate over time commit analysis visualization

• Add dump multirepo results (or similar aggregate scan) to s3 capability

• Investigate diff to tweet capability. Reveal major contributor changes in critical projects to an open feed.

• Investigate switching ownership data. Would be interesting to alert users to this.

• Investigate by user capability. Determine all repo’s a user has contributed to. Do a quick git blame for a user.

Rainy Day Options

• Access commercial API’s to enrich data on GitHub usernames or, if included in GitHub profile, email handles, etc. Perhaps People Data Labs or Explorium. (MK)

Potential Research Questions

• Are there places in the world with unrecognized pockets of software developers?

• Where are maintainers associated with the most critical python packages?

  • Who are the maintainers that are associated with multiple critical python packages?

  • What about contribution-related weighting?

• Where are the maintainers associated with the top GitHub packages by stars? Top data science packages? Quantum computing packages? Blockhcain packages? Etc? (RP)

  • Then do sub-analysis that asks on what repos or types of repos developers of a given country are most active

• What predicts the number of top python packages software developers by country?

  • Total number of coders per country?

  • Total number of python coders per country?

  • GDP per capita per country?

• Is it possible to “verify” user information?

Known bugs

Want to contribute?

• Open a PR. We are glad to accept pull requests. We use black and pylint and pydocstyle, though we are glad to help if you haven’t used those tools before.

• Open an issue. Tell us your problem or a functionality you want.

• Want to help build a community related to GitGeo and similar open source software ecosystem exploration tools? Please send an email to jmeyers@iqt.org.