SpECTRE  v2024.05.11
GitHub Actions Continuous Integration

Testing SpECTRE with GitHub Actions CI

SpECTRE uses GitHub Actions for testing the code. Multiple build jobs (described below) are launched each time a pull request is submitted or updated. GitHub Actions will also launch these build jobs each time you push to a branch on your fork of SpECTRE if you enable it. GitHub Actions is also used to deploy releases of the code.

For pull requests, you can view the GitHub Actions CI build by clicking on the Checks tab. Near the bottom of the Conversation tab a summary of the CI results are presented. You can view all of the GitHub Actions runs by clicking on the Actions section.

What is tested

The GitHub Actions report lists the build jobs which will each have either a green check mark if it passes, a red X if it has failed, or a yellow dot with a circle if the build is in progress. Clicking on a build job will display the log of the build.

The following build jobs are launched:

  • CHECK_COMMITS runs the script tools/CheckCommits.sh and fails the build if any casing of the words in the list below is the first word of the commit message. This allows developers to flag their commits with these keywords to indicate that a pull request should not be merged in its current state.
    • fixup
    • wip (for work in progress)
    • fixme
    • deleteme
    • rebaseme
    • testing
    • rebase
  • CHECK_FILES runs the script tools/CheckFiles.sh (which also runs the script tools/FileTestDefs.sh). The checks fail if any of the following are true:
    • Any file,
      • contains a line over 80 characters (We allow exceptions for certain file types and inherently long strings like URLs and include lines. See tools/FileTestDefs.sh for the full list of exceptions.)
      • is missing the license line
      • does not end with a newline
      • contains a tab character
      • contains white space at the end of a line
      • contains a carriage return character
    • A c++ header file (i.e., *.hpp or *.tpp) is missing #pragma once
    • A c++ file (i.e., *.hpp, *.tpp, or *.cpp) file,
      • includes <iostream> (useless when running in parallel)
      • includes <lrtslock.h> (use <converse.h> instead)
      • includes "Utilities/TmplDebugging.hpp" (used only for debugging)
      • includes any non-header *.cpp file
      • contains a namespace ending in _details (use _detail)
      • contains a struct TD or class TD (used only for debugging)
      • contains std::enable_if (use Requires instead)
      • contains Ls (use List instead)
      • contains additional text after /*! (does not render correctly in Doxygen)
      • contains the string return Py_None; (bug prone, use Py_RETURN_NONE instead)
      • contains .ckLocal() or .ckLocalBranch() (use Parallel::local or Parallel::local_branch instead)
    • A c++ test,
      • uses TEST_CASE (use SPECTRE_TEST_CASE instead)
      • uses Approx (use approx instead)
    • A CMakeLists.txt file in src, but not in an Executables or Python-binding directory,
      • does not list a C++ file that is present in the directory
      • lists a C++ file that is not present in the directory
    • A c++ or python file contains a TODO (case-insensitive) comment In addition, the CHECK_FILES job tests Python formatting, the release workflow, and other tools in tools/.
  • "Check Python formatting" runs the black and isort formatters over the source code.
  • RUN_CLANG_TIDY runs clang-tidy on the source code. This is done for both Release and Debug builds.
  • TEST_CHECK_FILES runs tools/CheckFiles.sh --test which tests the checks performed in the CHECK_FILES build.
  • The other builds compile the code and run the tests for both Release and Debug builds, for the gcc and clang compilers using a Linux OS, and the AppleClang compiler for OS X.
  • Verify the documentation builds successfully. Builds of develop deploy the documentation to GitHub pages.

How to perform the checks locally

Before pushing to GitHub and waiting for GitHub Actions to perform the checks it is useful to perform at least the following tests locally:

  • Unit tests: Perform a make unit-tests and then execute ctest -L Unit to run all unit tests. As for make you can append a -jN flag to ctest to run in parallel on N cores. To run only a subset of the tests you can use one of the other keywords that the tests are labeled with, such as ctest -L datastructures. To run only particular tests you can also execute ctest -R TEST_NAME instead, where TEST_NAME is a regular expression matching the test identifiers such as Unit.DataStructures.Mesh. Pass the flag --output-on-failure to get output from failed tests. Consult ctest -h for further options.

    To run the input file tests you must build the executables using make test-executables. You can then run ctest -LE unit to run everything except for the unit tests, or ctest to run all tests.

  • clang-tidy: In a clang build directory, run make clang-tidy FILE=SOURCE_FILE where SOURCE_FILE is a relative or absolute path to a .cpp file. To perform this check for all source files that changed in your pull request, make clang-tidy-hash HASH=UPSTREAM_HEAD where UPSTREAM_HEAD is the hash of the commit that your pull request is based on, usually the HEAD of the upstream/develop branch.
  • Python formatting: Run black --check . and isort --check-only . over the repository. You can install these tools with pip3 install -r support/Python/dev_requirements.txt
  • Documentation: To render the documentation for the current state of the source tree the command make doc (or make doc-check to highlight warnings) can be used, placing its result in the docs directory in the build tree. Once code has been made into a pull request to GitHub, the documentation can be rendered locally using the tools/pr-docs script. To view the documentation, simply open the index.html file in the html subdirectory in a browser. Some functionality requires a web server (e.g. citation popovers), so just run a python3 -m http.server in the html directory to enable this.
  • IWYU: We experimented for a time using IWYU (include what you use) as an automated check for correct includes and forward declarations. Unfortunately it gave many incorrect suggestions. We have decided to no longer have a IWYU check with GitHub Actions, but have left support for IWYU so that it can be used locally. To do so just for the changed files in a pull request run make iwyu-hash HASH=UPSTREAM_HEAD. Since IWYU requires USE_PCH=OFF you can create a separate build directory and append -D USE_PCH=OFF to the usual cmake call. Note that it is very easy to incorrectly install IWYU (if not using the Docker container) and generate nonsense errors. Note that we have left IWYU pragmas in the code, but no longer require they be added so that IWYU gives no errors when run. As IWYU is still under development, we plan to investigate using it again in the future.
  • The gcc Debug build runs code coverage for each GitHub Actions build.


  • Occasionally, a build job will fail because of a problem with GitHub Actions (e.g. it times out). On the Checks tab you can restart all or only the failed jobs. In the top right corner there's a Re-run jobs menu, which also has Re-run failed jobs. This button is Cancel workflow during the build process. Note that these buttons are only available if you have write access to the repository (core developer status).
  • GitHub Actions caches some things between builds. Occasionally this may cause a problem leading to strange build failures. For example, inexplicable segfaults on seemingly random tests or Illegal instruction failures. We have to be fairly lax with our caching policies, and so the cache can become stale and outdated when a new container is pushed, among other difficult to understand situations. You can rebuild the ccache by going to Actions, then select the Tests workflow on the left, click the Run workflow drop-down menu, and enter yes in the input field below the ccache discussion.

    If clearing the ccache doesn't help, it could be that a Docker image layer is not being updated. GitHub doesn't (yet) have a way to clear the cache, so instead we clobber it to force GitHub to eject all old caches, both ccache and Docker images, along with anything else. To do this go to Actions, select the Clobber Cache workflow, then run it on develop. This will dump 9.9GB of random data into the cache. The amount is specified in the ClobberCache.yaml workflow file and needs to be updated if GitHub increases their cache size. The current cache size limit is 10GB per repository.

    Note that starting these workflows is only possible if you have write access to the repository (core developer status).

Precompiled Headers and ccache

Getting ccache to work with precompiled headers on GitHub Actions is a little challenging. The header to be precompiled is ${SPECTRE_SOURCE_DIR}/tools/SpectrePch.hpp and is symbolically linked to ${SPECTRE_BUILD_DIR}/SpectrePch.hpp. The configuration that seems to work is specifying the environment variables:


Caching Dependencies on macOS Builds

On macOS builds we cache all of our dependencies, like LIBXSMM and Charm++. These are cached in $HOME/mac_cache. Ultimately this saves about 10-12 minutes even when compared to using ccache to cache the object files from building the dependencies. We also cache $HOME/Library/Caches/Homebrew, which is where Homebrew keeps the downloaded formulas. By caching the Homebrew bottles we are able to avoid brew formulas building from source because a tarball of the package was not available at the time.