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"""Custom rules for gRPC Python"""
# Adapted with modifications from
# tensorflow/tensorflow/core/platform/default/build_config.bzl
# Native Bazel rules don't exist yet to compile Cython code, but rules have
# been written at cython/cython and tensorflow/tensorflow. We branch from
# Tensorflow's version as it is more actively maintained and works for gRPC
# Python's needs.
def pyx_library(name, deps=[], py_deps=[], srcs=[], **kwargs):
"""Compiles a group of .pyx / .pxd / .py files.
First runs Cython to create .cpp files for each input .pyx or .py + .pxd
pair. Then builds a shared object for each, passing "deps" to each cc_binary
rule (includes Python headers by default). Finally, creates a py_library rule
with the shared objects and any pure Python "srcs", with py_deps as its
dependencies; the shared objects can be imported like normal Python files.
Args:
name: Name for the rule.
deps: C/C++ dependencies of the Cython (e.g. Numpy headers).
py_deps: Pure Python dependencies of the final library.
srcs: .py, .pyx, or .pxd files to either compile or pass through.
**kwargs: Extra keyword arguments passed to the py_library.
"""
# First filter out files that should be run compiled vs. passed through.
py_srcs = []
pyx_srcs = []
pxd_srcs = []
for src in srcs:
if src.endswith(".pyx") or (src.endswith(".py") and
src[:-3] + ".pxd" in srcs):
pyx_srcs.append(src)
elif src.endswith(".py"):
py_srcs.append(src)
else:
pxd_srcs.append(src)
if src.endswith("__init__.py"):
pxd_srcs.append(src)
# Invoke cython to produce the shared object libraries.
for filename in pyx_srcs:
native.genrule(
name=filename + "_cython_translation",
srcs=[filename],
outs=[filename.split(".")[0] + ".cpp"],
# Optionally use PYTHON_BIN_PATH on Linux platforms so that python 3
# works. Windows has issues with cython_binary so skip PYTHON_BIN_PATH.
cmd=
"PYTHONHASHSEED=0 $(location @cython//:cython_binary) --cplus $(SRCS) --output-file $(OUTS)",
tools=["@cython//:cython_binary"] + pxd_srcs,
)
shared_objects = []
for src in pyx_srcs:
stem = src.split(".")[0]
shared_object_name = stem + ".so"
native.cc_binary(
name=shared_object_name,
srcs=[stem + ".cpp"],
deps=deps + ["@local_config_python//:python_headers"],
linkshared=1,
)
shared_objects.append(shared_object_name)
# Now create a py_library with these shared objects as data.
native.py_library(
name=name,
srcs=py_srcs,
deps=py_deps,
srcs_version="PY2AND3",
data=shared_objects,
**kwargs)
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