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scc 0.5.4

OME tools for managing the git(hub) workflow

Latest Version: 0.6.5

Introduction

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

Dependencies

Direct dependencies of scc are:

Installation

To install scc, run:

$ python setup.py install

or using pip, run:

$ pip install scc

To upgrade your pip installation, run:

$ pip install -U scc

Usage

The list of available commands can be listed with:

$ scc -h

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

$ scc merge -h

Contributing

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 setup.py:

python setup.py test

Unit tests

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

python setup.py 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 setupy.py -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

License

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
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