def do_register_package():
if not runtime_support.package_exists(pkg_uri):
tmp_path = os.path.join(_pkg_tmp(), "_tmp{}".format(pkg_name))
runtime_support.create_project_package(
working_dir=base_dir, py_modules=[], output_path=tmp_path)
# TODO(ekl) does this get garbage collected correctly with the
# current job id?
runtime_support.push_package(pkg_uri, tmp_path)
if not runtime_support.package_exists(pkg_uri):
raise RuntimeError(
"Failed to upload package {}".format(pkg_uri))
def load_package(config_path: str) -> "_RuntimePackage":
"""Load the code package given its config path.
Args:
config_path (str): The path to the configuration YAML that defines
the package. For documentation on the packaging format, see the
example YAML in ``example_pkg/ray_pkg.yaml``.
Examples:
>>> # Load from local.
>>> my_pkg = load_package("~/path/to/my_pkg.yaml")
>>> # Load from GitHub.
>>> my_pkg = ray.util.load_package(
... "https://raw.githubusercontent.com/user/repo/refspec"
... "/path/to/package/my_pkg.yaml")
>>> # Inspect the package runtime env.
>>> print(my_pkg._runtime_env)
... {"conda": {...},
... "docker": "anyscale-ml/ray-ml:nightly-py38-cpu",
... "files": "https://github.com/demo/foo/blob/v3.0/project/"}
>>> # Run remote functions from the package.
>>> my_pkg.my_func.remote(1, 2)
>>> # Create actors from the package.
>>> actor = my_pkg.MyActor.remote(3, 4)
>>> # Create new remote funcs in the same env as a package.
>>> @ray.remote(runtime_env=my_pkg._runtime_env)
>>> def f(): ...
"""
if not ray.is_initialized():
# TODO(ekl) lift this requirement?
raise RuntimeError("Ray must be initialized first to load packages.")
config_path = _download_from_github_if_needed(config_path)
if not os.path.exists(config_path):
raise ValueError("Config file does not exist: {}".format(config_path))
# TODO(ekl) validate schema?
config = yaml.safe_load(open(config_path).read())
base_dir = os.path.abspath(os.path.dirname(config_path))
runtime_env = config["runtime_env"]
# Autofill working directory by uploading to GCS storage.
if "files" not in runtime_env:
pkg_name = runtime_support.get_project_package_name(
working_dir=base_dir, modules=[])
pkg_uri = runtime_support.Protocol.GCS.value + "://" + pkg_name
if not runtime_support.package_exists(pkg_uri):
tmp_path = os.path.join(_pkg_tmp(), "_tmp{}".format(pkg_name))
runtime_support.create_project_package(
working_dir=base_dir, modules=[], output_path=tmp_path)
# TODO(ekl) does this get garbage collected correctly with the
# current job id?
runtime_support.push_package(pkg_uri, tmp_path)
if not runtime_support.package_exists(pkg_uri):
raise RuntimeError(
"Failed to upload package {}".format(pkg_uri))
runtime_env["files"] = pkg_uri
# Autofill conda config.
conda_yaml = os.path.join(base_dir, "conda.yaml")
if os.path.exists(conda_yaml):
if "conda" in runtime_env:
raise ValueError(
"Both conda.yaml and conda: section found in package")
runtime_env["conda"] = yaml.safe_load(open(conda_yaml).read())
pkg = _RuntimePackage(
name=config["name"],
desc=config["description"],
stub_file=os.path.join(base_dir, config["stub_file"]),
runtime_env=runtime_env)
return pkg