OME tools for managing the git(hub) workflow
Project description
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 -t 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-sandbox-2 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-sandbox-2
Once this is set up, the integration tests can be run by calling:
python setupy.py test -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.
Copyright
2012-2016, The Open Microscopy Environment
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