from itertools import chain import os import re import shutil import subprocess import sys from setuptools import setup, find_packages, Distribution import setuptools.command.build_ext as _build_ext # Ideally, we could include these files by putting them in a # MANIFEST.in or using the package_data argument to setup, but the # MANIFEST.in gets applied at the very beginning when setup.py runs # before these files have been created, so we have to move the files # manually. # NOTE: The lists below must be kept in sync with ray/BUILD.bazel. ray_files = [ "ray/core/src/ray/thirdparty/redis/src/redis-server", "ray/core/src/ray/gcs/redis_module/libray_redis_module.so", "ray/core/src/plasma/plasma_store_server", "ray/_raylet.so", "ray/core/src/ray/raylet/raylet_monitor", "ray/core/src/ray/gcs/gcs_server", "ray/core/src/ray/raylet/raylet", "ray/streaming/_streaming.so", ] build_java = os.getenv("RAY_INSTALL_JAVA") == "1" if build_java: ray_files.append("ray/jars/ray_dist.jar") # These are the directories where automatically generated Python protobuf # bindings are created. generated_python_directories = [ "ray/core/generated", "ray/streaming/generated", ] optional_ray_files = [] ray_autoscaler_files = [ "ray/autoscaler/aws/example-full.yaml", "ray/autoscaler/azure/example-full.yaml", "ray/autoscaler/azure/azure-vm-template.json", "ray/autoscaler/azure/azure-config-template.json", "ray/autoscaler/gcp/example-full.yaml", "ray/autoscaler/local/example-full.yaml", "ray/autoscaler/kubernetes/example-full.yaml", "ray/autoscaler/kubernetes/kubectl-rsync.sh", "ray/autoscaler/ray-schema.json" ] ray_project_files = [ "ray/projects/schema.json", "ray/projects/templates/cluster_template.yaml", "ray/projects/templates/project_template.yaml", "ray/projects/templates/requirements.txt" ] ray_dashboard_files = [ os.path.join(dirpath, filename) for dirpath, dirnames, filenames in os.walk("ray/dashboard/client/build") for filename in filenames ] optional_ray_files += ray_autoscaler_files optional_ray_files += ray_project_files optional_ray_files += ray_dashboard_files if "RAY_USE_NEW_GCS" in os.environ and os.environ["RAY_USE_NEW_GCS"] == "on": ray_files += [ "ray/core/src/credis/build/src/libmember.so", "ray/core/src/credis/build/src/libmaster.so", "ray/core/src/credis/redis/src/redis-server" ] extras = { "debug": [], "dashboard": ["requests"], "serve": ["uvicorn", "pygments", "werkzeug", "flask", "pandas", "blist"], "tune": ["tabulate", "tensorboardX", "pandas"] } extras["rllib"] = extras["tune"] + [ "atari_py", "dm_tree", "gym[atari]", "lz4", "opencv-python-headless", "pyyaml", "scipy", ] extras["streaming"] = ["msgpack >= 0.6.2"] extras["all"] = list(set(chain.from_iterable(extras.values()))) class build_ext(_build_ext.build_ext): def run(self): # Note: We are passing in sys.executable so that we use the same # version of Python to build packages inside the build.sh script. Note # that certain flags will not be passed along such as --user or sudo. # TODO(rkn): Fix this. command = ["../build.sh", "-p", sys.executable] if build_java: # Also build binaries for Java if the above env variable exists. command += ["-l", "python,java"] subprocess.check_call(command) # We also need to install pickle5 along with Ray, so make sure that the # relevant non-Python pickle5 files get copied. pickle5_files = self.walk_directory("./ray/pickle5_files/pickle5") thirdparty_files = self.walk_directory("./ray/thirdparty_files") files_to_include = ray_files + pickle5_files + thirdparty_files # Copy over the autogenerated protobuf Python bindings. for directory in generated_python_directories: for filename in os.listdir(directory): if filename[-3:] == ".py": files_to_include.append(os.path.join(directory, filename)) for filename in files_to_include: self.move_file(filename) # Try to copy over the optional files. for filename in optional_ray_files: try: self.move_file(filename) except Exception: print("Failed to copy optional file {}. This is ok." .format(filename)) def walk_directory(self, directory): file_list = [] for (root, dirs, filenames) in os.walk(directory): for name in filenames: file_list.append(os.path.join(root, name)) return file_list def move_file(self, filename): # TODO(rkn): This feels very brittle. It may not handle all cases. See # https://github.com/apache/arrow/blob/master/python/setup.py for an # example. source = filename destination = os.path.join(self.build_lib, filename) # Create the target directory if it doesn't already exist. parent_directory = os.path.dirname(destination) if not os.path.exists(parent_directory): os.makedirs(parent_directory) if not os.path.exists(destination): print("Copying {} to {}.".format(source, destination)) shutil.copy(source, destination, follow_symlinks=True) class BinaryDistribution(Distribution): def has_ext_modules(self): return True def find_version(*filepath): # Extract version information from filepath here = os.path.abspath(os.path.dirname(__file__)) with open(os.path.join(here, *filepath)) as fp: version_match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]", fp.read(), re.M) if version_match: return version_match.group(1) raise RuntimeError("Unable to find version string.") requires = [ "aiohttp", "click", "colorama", "filelock", "google", "grpcio", "jsonschema", "msgpack >= 0.6.0, < 1.0.0", "numpy >= 1.16", "protobuf >= 3.8.0", "py-spy >= 0.2.0", "pyyaml", "redis >= 3.3.2", ] setup( name="ray", version=find_version("ray", "__init__.py"), author="Ray Team", author_email="ray-dev@googlegroups.com", description=("A system for parallel and distributed Python that unifies " "the ML ecosystem."), long_description=open("../README.rst").read(), url="https://github.com/ray-project/ray", keywords=("ray distributed parallel machine-learning " "reinforcement-learning deep-learning python"), packages=find_packages(), cmdclass={"build_ext": build_ext}, # The BinaryDistribution argument triggers build_ext. distclass=BinaryDistribution, install_requires=requires, setup_requires=["cython >= 0.29.14", "wheel"], extras_require=extras, entry_points={ "console_scripts": [ "ray=ray.scripts.scripts:main", "rllib=ray.rllib.scripts:cli [rllib]", "tune=ray.tune.scripts:cli" ] }, include_package_data=True, zip_safe=False, license="Apache 2.0")