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This introduces tooling and enforcement for formatting bazel files. The tooling is provided as a bazel run target from [keith/buildifier-prebuilt](https://github.com/keith/buildifier-prebuilt). This is used in a [`pre-commit`](https://pre-commit.com/) hook for those having that installed. In turn this is used in a CI check. Relying on a `pre-commit` action gives us easy checking that buildifying did not change anything in the files and printing the diff, without having to hand-roll the check ourselves. This enforcement will make usage of gazelle easier, as gazelle itself might reformat files, even outside of `go`. Having them properly formatted will allow gazelle to leave them unchanged, without needing to configure awkward exclude directives.
Code generation suite
This directory contains the code generation suite used by the Swift extractor and the QL library. This suite will use
the abstract class specification of schema.py to generate:
- the
dbschemefile (seedbschemegen.py) - the QL generated code and when appropriate the corresponding stubs (see
qlgen.py) - C++ tags and trap entries (see
trapgen.py) - C++ structured classes (see
cppgen.py)
An example schema.py can be found in the Swift package.
Usage
By default bazel run //misc/codegen -- -c your-codegen.conf will load options from your-codegen.conf. See
the Swift configuration for an example. Calling misc/codegen/codegen.py directly (provided
you installed dependencies via pip3 install -r misc/codegen/requirements.txt) will use a file named codegen.conf
contained in an ancestor directory if any exists.
See bazel run //misc/codegen -- --help for a list of all options. In particular --generate can be used with a comma
separated list to select what to generate (choosing among dbscheme, ql, trap and cpp).
Implementation notes
The suite uses mustache templating for generation. Templates are
in the templates directory, prefixed with the generation target they are used for.
Rather than passing dictionaries to the templating engine, python dataclasses are used as defined
in the lib directory. For each of the four generation targets the entry point for the implementation is
specified as the generate function in the modules within the generators directory.
Finally, codegen.py is the driver script gluing everything together and specifying the command line
options.
Unit tests are in the test directory and can be run via bazel test //misc/codegen/test.
For more details about each specific generation target, please refer to the module docstrings
in the generators directory.