# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"). You # may not use this file except in compliance with the License. A copy of # the License is located at # # http://aws.amazon.com/apache2.0/ # # or in the "license" file accompanying this file. This file is # distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF # ANY KIND, either express or implied. See the License for the specific # language governing permissions and limitations under the License. """Utilities to support workflow.""" from __future__ import absolute_import import inspect import logging from functools import wraps from pathlib import Path from typing import List, Sequence, Union, Set, TYPE_CHECKING import hashlib from urllib.parse import unquote, urlparse from _hashlib import HASH as Hash from sagemaker.workflow.parameters import Parameter from sagemaker.workflow.pipeline_context import _StepArguments from sagemaker.workflow.entities import ( Entity, RequestType, ) logger = logging.getLogger(__name__) if TYPE_CHECKING: from sagemaker.workflow.step_collections import StepCollection BUF_SIZE = 65536 # 64KiB def list_to_request(entities: Sequence[Union[Entity, "StepCollection"]]) -> List[RequestType]: """Get the request structure for list of entities. Args: entities (Sequence[Entity]): A list of entities. Returns: list: A request structure for a workflow service call. """ from sagemaker.workflow.step_collections import StepCollection request_dicts = [] for entity in entities: if isinstance(entity, Entity): request_dicts.append(entity.to_request()) elif isinstance(entity, StepCollection): request_dicts.extend(entity.request_dicts()) return request_dicts def hash_file(path: str) -> str: """Get the MD5 hash of a file. Args: path (str): The local path for the file. Returns: str: The MD5 hash of the file. """ return _hash_file(path, hashlib.md5()).hexdigest() def hash_files_or_dirs(paths: List[str]) -> str: """Get the MD5 hash of the contents of a list of files or directories. Hash is changed if: * input list is changed * new nested directories/files are added to any directory in the input list * nested directory/file names are changed for any of the inputted directories * content of files is edited Args: paths: List of file or directory paths Returns: str: The MD5 hash of the list of files or directories. """ md5 = hashlib.md5() for path in sorted(paths): md5 = _hash_file_or_dir(path, md5) return md5.hexdigest() def _hash_file_or_dir(path: str, md5: Hash) -> Hash: """Updates the inputted Hash with the contents of the current path. Args: path: path of file or directory Returns: str: The MD5 hash of the file or directory """ if isinstance(path, str) and path.lower().startswith("file://"): path = unquote(urlparse(path).path) md5.update(path.encode()) if Path(path).is_dir(): md5 = _hash_dir(path, md5) elif Path(path).is_file(): md5 = _hash_file(path, md5) return md5 def _hash_dir(directory: Union[str, Path], md5: Hash) -> Hash: """Updates the inputted Hash with the contents of the current path. Args: directory: path of the directory Returns: str: The MD5 hash of the directory """ if not Path(directory).is_dir(): raise ValueError(str(directory) + " is not a valid directory") for path in sorted(Path(directory).iterdir()): md5.update(path.name.encode()) if path.is_file(): md5 = _hash_file(path, md5) elif path.is_dir(): md5 = _hash_dir(path, md5) return md5 def _hash_file(file: Union[str, Path], md5: Hash) -> Hash: """Updates the inputted Hash with the contents of the current path. Args: file: path of the file Returns: str: The MD5 hash of the file """ if isinstance(file, str) and file.lower().startswith("file://"): file = unquote(urlparse(file).path) if not Path(file).is_file(): raise ValueError(str(file) + " is not a valid file") with open(file, "rb") as f: while True: data = f.read(BUF_SIZE) if not data: break md5.update(data) return md5 def validate_step_args_input( step_args: _StepArguments, expected_caller: Set[str], error_message: str ): """Validate the `_StepArguments` object which is passed into a pipeline step Args: step_args (_StepArguments): A `_StepArguments` object to be used for composing a pipeline step. expected_caller (Set[str]): The expected name of the caller function which is intercepted by the PipelineSession to get the step arguments. error_message (str): The error message to be thrown if the validation fails. """ if not isinstance(step_args, _StepArguments): raise TypeError(error_message) if step_args.caller_name not in expected_caller: raise ValueError(error_message) def override_pipeline_parameter_var(func): """A decorator to override pipeline Parameters passed into a function This is a temporary decorator to override pipeline Parameter objects with their default value and display warning information to instruct users to update their code. This decorator can help to give a grace period for users to update their code when we make changes to explicitly prevent passing any pipeline variables to a function. We should remove this decorator after the grace period. """ warning_msg_template = ( "The input argument %s of function (%s) is a pipeline variable (%s), which is not allowed. " "The default_value of this Parameter object will be used to override it. " "Please make sure the default_value is valid." ) @wraps(func) def wrapper(*args, **kwargs): func_name = "{}.{}".format(func.__module__, func.__name__) params = inspect.signature(func).parameters args = list(args) for i, (arg_name, _) in enumerate(params.items()): if i >= len(args): break if isinstance(args[i], Parameter): logger.warning(warning_msg_template, arg_name, func_name, type(args[i])) args[i] = args[i].default_value args = tuple(args) for arg_name, value in kwargs.items(): if isinstance(value, Parameter): logger.warning(warning_msg_template, arg_name, func_name, type(value)) kwargs[arg_name] = value.default_value return func(*args, **kwargs) return wrapper