| =============================== | |
| MEP19: Continuous Integration | |
| =============================== | |
| Status | |
| ====== | |
| **Completed** | |
| Branches and Pull requests | |
| ========================== | |
| Abstract | |
| ======== | |
| matplotlib could benefit from better and more reliable continuous | |
| integration, both for testing and building installers and | |
| documentation. | |
| Detailed description | |
| ==================== | |
| Current state-of-the-art | |
| ------------------------ | |
| **Testing** | |
| matplotlib currently uses Travis-CI for automated tests. While | |
| Travis-CI should be praised for how much it does as a free service, it | |
| has a number of shortcomings: | |
| - It often fails due to network timeouts when installing dependencies. | |
| - It often fails for inexplicable reasons. | |
| - build or test products can only be saved from build off of branches | |
| on the main repo, not pull requests, so it is often difficult to | |
| "post mortem" analyse what went wrong. This is particularly | |
| frustrating when the failure cannot be subsequently reproduced | |
| locally. | |
| - It is not extremely fast. matplotlib's cpu and memory requirements | |
| for testing are much higher than the average Python project. | |
| - It only tests on Ubuntu Linux, and we have only minimal control over | |
| the specifics of the platform. It can be upgraded at any time | |
| outside of our control, causing unexpected delays at times that may | |
| not be convenient in our release schedule. | |
| On the plus side, Travis-CI's integration with github -- automatically | |
| testing all pending pull requests -- is exceptional. | |
| **Builds** | |
| There is no centralized effort for automated binary builds for | |
| matplotlib. However, the following disparate things are being done | |
| [If the authors mentioned here could fill in detail, that would be | |
| great!]: | |
| - @sandrotosi: builds Debian packages | |
| - @takluyver: Has automated Ubuntu builds on Launchpad | |
| - @cgohlke: Makes Windows builds (don't know how automated that is) | |
| - @r-owen: Makes OS-X builds (don't know how automated that is) | |
| **Documentation** | |
| Documentation of main is now built by travis and uploaded to https://matplotlib.org/devdocs/index.html | |
| @NelleV, I believe, generates the docs automatically and posts them on | |
| the web to chart MEP10 progress. | |
| Peculiarities of matplotlib | |
| --------------------------- | |
| matplotlib has complex requirements that make testing and building | |
| more taxing than many other Python projects. | |
| - The CPU time to run the tests is quite high. It puts us beyond the | |
| free accounts of many CI services (e.g. ShiningPanda) | |
| - It has a large number of dependencies, and testing the full matrix | |
| of all combinations is impractical. We need to be clever about what | |
| space we test and guarantee to support. | |
| Requirements | |
| ------------ | |
| This section outlines the requirements that we would like to have. | |
| #. Testing all pull requests by hooking into the GitHub API, as | |
| Travis-CI does | |
| #. Testing on all major platforms: Linux, Mac OS-X, MS Windows (in | |
| that order of priority, based on user survey) | |
| #. Retain the last n days worth of build and test products, to aid in | |
| post-mortem debugging. | |
| #. Automated nightly binary builds, so that users can test the | |
| bleeding edge without installing a complete compilation | |
| environment. | |
| #. Automated benchmarking. It would be nice to have a standard | |
| benchmark suite (separate from the tests) whose performance could | |
| be tracked over time, in different backends and platforms. While | |
| this is separate from building and testing, ideally it would run on | |
| the same infrastructure. | |
| #. Automated nightly building and publishing of documentation (or as | |
| part of testing, to ensure PRs don't introduce documentation bugs). | |
| (This would not replace the static documentation for stable | |
| releases as a default). | |
| #. The test systems should be manageable by multiple developers, so | |
| that no single person becomes a bottleneck. (Travis-CI's design | |
| does this well -- storing build configuration in the git | |
| repository, rather than elsewhere, is a very good design.) | |
| #. Make it easy to test a large but sparse matrix of different | |
| versions of matplotlib's dependencies. The matplotlib user survey | |
| provides some good data as to where to focus our efforts: | |
| https://docs.google.com/spreadsheets/d/1jbK0J4cIkyBNncnS-gP7pINSliNy9lI-N4JHwxlNSXE/edit | |
| #. Nice to have: A decentralized design so that those with more | |
| obscure platforms can publish build results to a central dashboard. | |
| Implementation | |
| ============== | |
| This part is yet-to-be-written. | |
| However, ideally, the implementation would be a third-party service, | |
| to avoid adding system administration to our already stretched time. | |
| As we have some donated funds, this service may be a paid one if it | |
| offers significant time-saving advantages over free offerings. | |
| Backward compatibility | |
| ====================== | |
| Backward compatibility is not a major concern for this MEP. We will | |
| replace current tools and procedures with something better and throw | |
| out the old. | |
| Alternatives | |
| ============ | |
| Hangout Notes | |
| ============= | |
| CI Infrastructure | |
| ----------------- | |
| - We like Travis and it will probably remain part of our arsenal in | |
| any event. The reliability issues are being looked into. | |
| - Enable Amazon S3 uploads of testing products on Travis. This will | |
| help with post-mortem of failures (@mdboom is looking into this | |
| now). | |
| - We want Mac coverage. The best bet is probably to push Travis to | |
| enable it for our project by paying them for a Pro account (since | |
| they don't otherwise allow testing on both Linux and Mac). | |
| - We want Windows coverage. Shining Panda is an option there. | |
| - Investigate finding or building a tool that would collect and | |
| synthesize test results from a number of sources and post it to | |
| GitHub using the GitHub API. This may be of general use to the | |
| Scipy community. | |
| - For both Windows and Mac, we should document (or better yet, script) | |
| the process of setting up the machine for a build, and how to build | |
| binaries and installers. This may require getting information from | |
| Russel Owen and Christoph Gohlke. This is a necessary step for | |
| doing automated builds, but would also be valuable for a number of | |
| other reasons. | |
| The test framework itself | |
| ------------------------- | |
| - We should investigate ways to make it take less time | |
| - Eliminating redundant tests, if possible | |
| - General performance improvements to matplotlib will help | |
| - We should be covering more things, particularly more backends | |
| - We should have more unit tests, fewer integration tests, if possible | |