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CI helps make sure that we never accidentally break something when we merge in new code. At the very least, it checks that the package can be installed on all of the different python versions and platforms (Windows/Mac/Linux) that we choose to support.
But ultimately it will also run our full suite of unit tests, once we create that, to check not only that the install works but also that all of our tests run and pass on all python versions/platforms.
We can+should also configure it with a linter to make sure that all code adheres to standard style and formatting rules. E.g. flake8.
CI helps make sure that we never accidentally break something when we merge in new code. At the very least, it checks that the package can be installed on all of the different python versions and platforms (Windows/Mac/Linux) that we choose to support.
But ultimately it will also run our full suite of unit tests, once we create that, to check not only that the install works but also that all of our tests run and pass on all python versions/platforms.
We can+should also configure it with a linter to make sure that all code adheres to standard style and formatting rules. E.g. flake8.
Azure Pipelines is a good option, see e.g. https://github.com/spencerahill/aospy/tree/master/ci. It takes some configuring to get all working, which is true of any CI tool, but it's well worth it.
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