skip to navigation
skip to content

scc 0.5.4

OME tools for managing the git(hub) workflow

Latest Version: 0.9.2


The scc command provides tools for simplifying the Git(Hub) workflow.


Direct dependencies of scc are:


To install scc, run:

$ python install

or using pip, run:

$ pip install scc

To upgrade your pip installation, run:

$ pip install -U scc


The list of available commands can be listed with:

$ scc -h

For each subcommand, additional help can be queried, e.g.:

$ scc merge -h


PyGithub follows PEP 8, the Style Guide for Python Code. Please check your code with pep8 or flake8, the Python style guide checkers, by running flake8 -v . or pep8 -v ..

Running tests

The tests are located under the test directory. To run all the tests, use the test target of

python test

Unit tests

Unit tests are stored under the test/unit folder and can be run by calling:

python test -s test/unit

Unit tests are also run by the Travis build on every Pull Request opened against the main repository.

Integration tests

Integration tests are stored under test/integration. Many integration tests use snoopys-sandbox and snoopys-sandbox2 as sandbox repositories to test the scc commands.

Running the integration test suite requires:

  • a GitHub account

  • a token-based GitHub connection, i.e. a global github.token stored under the global Git configuration file:

    $ git config --global github.token xxxx
  • the user authenticated by the token defined above needs to own forks of snoopys-sandbox and snoopys-sandbox2

Once this is set up, the integration tests can be run by calling:

python -s test/integration

Integration tests are run daily on the OME Continuous Integration infrastructure under the SCC-self-merge job using the token-authenticated snoopycrimecop user


snoopycrimecop is released under the GPL.

File Type Py Version Uploaded on Size
scc-0.5.4.tar.gz (md5) Source 2014-04-07 39KB