pyodide/pyodide-build/pyodide_build/__main__.py

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#!/usr/bin/env python3
import argparse
import os
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import pathlib
import sys
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from . import buildall, buildpkg, mkpkg, serve
from .common import get_make_environment_vars
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def make_parser() -> argparse.ArgumentParser:
"""Create an argument parser with argparse"""
main_parser = argparse.ArgumentParser(prog="pyodide")
main_parser.description = "A command line interface (CLI) for pyodide_build"
subparsers = main_parser.add_subparsers(help="action")
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for command_name, module in (
("buildpkg", buildpkg),
("buildall", buildall),
("serve", serve),
("mkpkg", mkpkg),
):
if "sphinx" in sys.modules and command_name in [
"buildpkg",
"buildall",
"pywasmcross",
]:
# Likely building documentation, skip private API
continue
parser = module.make_parser(subparsers.add_parser(command_name))
parser.set_defaults(func=module.main)
return main_parser
def main():
if not os.environ.get("__LOADED_PYODIDE_ENV"):
Use pypa/build (#2272) This resolves #2189. > build isolation would be a bit difficult to use in our case, as for instance > when building scipy we need the patched numpy on the host and not the numpy > version specified in pyproject.toml (which would be unpatched) This is indeed the case, certain packages cannot be isolated. My strategy is to make a list of packages that shouldn't be isolated and add symlinks from the isolated build environment into the `.artifacts` directory to "unisolate" them. Then we remove the unisolated package requirements from the list of packages to install, in case pesky constraints aren't satisfied. In particular, packages that expect to be used with `pypa/build` often feel free to put very specific constraints on their build dependencies (often asking them to be == to a particular version). Specific version constraints is good for build reproducibility and with build isolation doesn't cost anything. So we just ignore the constraints. Hopefully nothing goes wrong. In particular, any package that does stuff both at build time and at runtime and requires synchronization between the build time and run time environments needs the unisolation. This includes cffi with `_cffi_backend.so`, and of course numpy and scipy. pycparser needs to be unisolated because it is a dependency of cffi. Currently I have also unisolated pythran and cython, though these are build time only tools and do not really need to be unisolated. Cython I unisolated specifically because numcodecs needs it but it isn't in the numcodecs build dependencies. Pythran I unisolated because of a problem with the scipy build which I don't fully understand (some problem with long double feature detection).
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from .common import get_hostsitepackages
PYODIDE_ROOT = str(pathlib.Path(__file__).parents[2].resolve())
os.environ["PYODIDE_ROOT"] = PYODIDE_ROOT
os.environ.update(get_make_environment_vars())
Use pypa/build (#2272) This resolves #2189. > build isolation would be a bit difficult to use in our case, as for instance > when building scipy we need the patched numpy on the host and not the numpy > version specified in pyproject.toml (which would be unpatched) This is indeed the case, certain packages cannot be isolated. My strategy is to make a list of packages that shouldn't be isolated and add symlinks from the isolated build environment into the `.artifacts` directory to "unisolate" them. Then we remove the unisolated package requirements from the list of packages to install, in case pesky constraints aren't satisfied. In particular, packages that expect to be used with `pypa/build` often feel free to put very specific constraints on their build dependencies (often asking them to be == to a particular version). Specific version constraints is good for build reproducibility and with build isolation doesn't cost anything. So we just ignore the constraints. Hopefully nothing goes wrong. In particular, any package that does stuff both at build time and at runtime and requires synchronization between the build time and run time environments needs the unisolation. This includes cffi with `_cffi_backend.so`, and of course numpy and scipy. pycparser needs to be unisolated because it is a dependency of cffi. Currently I have also unisolated pythran and cython, though these are build time only tools and do not really need to be unisolated. Cython I unisolated specifically because numcodecs needs it but it isn't in the numcodecs build dependencies. Pythran I unisolated because of a problem with the scipy build which I don't fully understand (some problem with long double feature detection).
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hostsitepackages = get_hostsitepackages()
pythonpath = [
Use pypa/build (#2272) This resolves #2189. > build isolation would be a bit difficult to use in our case, as for instance > when building scipy we need the patched numpy on the host and not the numpy > version specified in pyproject.toml (which would be unpatched) This is indeed the case, certain packages cannot be isolated. My strategy is to make a list of packages that shouldn't be isolated and add symlinks from the isolated build environment into the `.artifacts` directory to "unisolate" them. Then we remove the unisolated package requirements from the list of packages to install, in case pesky constraints aren't satisfied. In particular, packages that expect to be used with `pypa/build` often feel free to put very specific constraints on their build dependencies (often asking them to be == to a particular version). Specific version constraints is good for build reproducibility and with build isolation doesn't cost anything. So we just ignore the constraints. Hopefully nothing goes wrong. In particular, any package that does stuff both at build time and at runtime and requires synchronization between the build time and run time environments needs the unisolation. This includes cffi with `_cffi_backend.so`, and of course numpy and scipy. pycparser needs to be unisolated because it is a dependency of cffi. Currently I have also unisolated pythran and cython, though these are build time only tools and do not really need to be unisolated. Cython I unisolated specifically because numcodecs needs it but it isn't in the numcodecs build dependencies. Pythran I unisolated because of a problem with the scipy build which I don't fully understand (some problem with long double feature detection).
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hostsitepackages,
f"{PYODIDE_ROOT}/pyodide-build/",
]
os.environ["PYTHONPATH"] = ":".join(pythonpath)
os.environ["BASH_ENV"] = ""
os.environ["__LOADED_PYODIDE_ENV"] = "1"
main_parser = make_parser()
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args = main_parser.parse_args()
if hasattr(args, "func"):
# run the selected action
args.func(args)
else:
main_parser.print_help()
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if __name__ == "__main__":
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main()