# Copyright 2022 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License 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. """Concurrent media operations.""" import concurrent.futures import io import inspect import os import warnings import pickle import copyreg import struct import base64 import functools from google.api_core import exceptions from google.cloud.storage import Client from google.cloud.storage import Blob from google.cloud.storage.blob import _get_host_name from google.cloud.storage.blob import _quote from google.cloud.storage.constants import _DEFAULT_TIMEOUT from google.cloud.storage.retry import DEFAULT_RETRY import google_crc32c from google.cloud.storage._media.requests.upload import XMLMPUContainer from google.cloud.storage._media.requests.upload import XMLMPUPart from google.cloud.storage.exceptions import DataCorruption TM_DEFAULT_CHUNK_SIZE = 32 * 1024 * 1024 DEFAULT_MAX_WORKERS = 8 MAX_CRC32C_ZERO_ARRAY_SIZE = 4 * 1024 * 1024 METADATA_HEADER_TRANSLATION = { "cacheControl": "Cache-Control", "contentDisposition": "Content-Disposition", "contentEncoding": "Content-Encoding", "contentLanguage": "Content-Language", "customTime": "x-goog-custom-time", "storageClass": "x-goog-storage-class", } # Constants to be passed in as `worker_type`. PROCESS = "process" THREAD = "thread" DOWNLOAD_CRC32C_MISMATCH_TEMPLATE = """\ Checksum mismatch while downloading: {} The object metadata indicated a crc32c checksum of: {} but the actual crc32c checksum of the downloaded contents was: {} """ _cached_clients = {} def _deprecate_threads_param(func): @functools.wraps(func) def convert_threads_or_raise(*args, **kwargs): binding = inspect.signature(func).bind(*args, **kwargs) threads = binding.arguments.get("threads") if threads: worker_type = binding.arguments.get("worker_type") max_workers = binding.arguments.get("max_workers") if worker_type or max_workers: # Parameter conflict raise ValueError( "The `threads` parameter is deprecated and conflicts with its replacement parameters, `worker_type` and `max_workers`." ) # No conflict, so issue a warning and set worker_type and max_workers. warnings.warn( "The `threads` parameter is deprecated. Please use `worker_type` and `max_workers` parameters instead." ) args = binding.args kwargs = binding.kwargs kwargs["worker_type"] = THREAD kwargs["max_workers"] = threads return func(*args, **kwargs) else: return func(*args, **kwargs) return convert_threads_or_raise @_deprecate_threads_param def upload_many( file_blob_pairs, skip_if_exists=False, upload_kwargs=None, threads=None, deadline=None, raise_exception=False, worker_type=PROCESS, max_workers=DEFAULT_MAX_WORKERS, ): """Upload many files concurrently via a worker pool. :type file_blob_pairs: List(Tuple(IOBase or str, 'google.cloud.storage.blob.Blob')) :param file_blob_pairs: A list of tuples of a file or filename and a blob. Each file will be uploaded to the corresponding blob by using APIs identical to `blob.upload_from_file()` or `blob.upload_from_filename()` as appropriate. File handlers are only supported if worker_type is set to THREAD. If worker_type is set to PROCESS, please use filenames only. :type skip_if_exists: bool :param skip_if_exists: If True, blobs that already have a live version will not be overwritten. This is accomplished by setting `if_generation_match = 0` on uploads. Uploads so skipped will result in a 412 Precondition Failed response code, which will be included in the return value but not raised as an exception regardless of the value of raise_exception. :type upload_kwargs: dict :param upload_kwargs: A dictionary of keyword arguments to pass to the upload method. Refer to the documentation for `blob.upload_from_file()` or `blob.upload_from_filename()` for more information. The dict is directly passed into the upload methods and is not validated by this function. :type threads: int :param threads: ***DEPRECATED*** Sets `worker_type` to THREAD and `max_workers` to the number specified. If `worker_type` or `max_workers` are set explicitly, this parameter should be set to None. Please use `worker_type` and `max_workers` instead of this parameter. :type deadline: int :param deadline: The number of seconds to wait for all threads to resolve. If the deadline is reached, all threads will be terminated regardless of their progress and `concurrent.futures.TimeoutError` will be raised. This can be left as the default of `None` (no deadline) for most use cases. :type raise_exception: bool :param raise_exception: If True, instead of adding exceptions to the list of return values, instead they will be raised. Note that encountering an exception on one operation will not prevent other operations from starting. Exceptions are only processed and potentially raised after all operations are complete in success or failure. If skip_if_exists is True, 412 Precondition Failed responses are considered part of normal operation and are not raised as an exception. :type worker_type: str :param worker_type: The worker type to use; one of `google.cloud.storage.transfer_manager.PROCESS` or `google.cloud.storage.transfer_manager.THREAD`. Although the exact performance impact depends on the use case, in most situations the PROCESS worker type will use more system resources (both memory and CPU) and result in faster operations than THREAD workers. Because the subprocesses of the PROCESS worker type can't access memory from the main process, Client objects have to be serialized and then recreated in each subprocess. The serialization of the Client object for use in subprocesses is an approximation and may not capture every detail of the Client object, especially if the Client was modified after its initial creation or if `Client._http` was modified in any way. THREAD worker types are observed to be relatively efficient for operations with many small files, but not for operations with large files. PROCESS workers are recommended for large file operations. PROCESS workers do not support writing to file handlers. Please refer to files by filename only when using PROCESS workers. :type max_workers: int :param max_workers: The maximum number of workers to create to handle the workload. With PROCESS workers, a larger number of workers will consume more system resources (memory and CPU) at once. How many workers is optimal depends heavily on the specific use case, and the default is a conservative number that should work okay in most cases without consuming excessive resources. :raises: :exc:`concurrent.futures.TimeoutError` if deadline is exceeded. :rtype: list :returns: A list of results corresponding to, in order, each item in the input list. If an exception was received, it will be the result for that operation. Otherwise, the return value from the successful upload method is used (which will be None). """ if upload_kwargs is None: upload_kwargs = {} if skip_if_exists: upload_kwargs = upload_kwargs.copy() upload_kwargs["if_generation_match"] = 0 upload_kwargs["command"] = "tm.upload_many" pool_class, needs_pickling = _get_pool_class_and_requirements(worker_type) with pool_class(max_workers=max_workers) as executor: futures = [] for path_or_file, blob in file_blob_pairs: # File objects are only supported by the THREAD worker because they can't # be pickled. if needs_pickling and not isinstance(path_or_file, str): raise ValueError( "Passing in a file object is only supported by the THREAD worker type. Please either select THREAD workers, or pass in filenames only." ) futures.append( executor.submit( _call_method_on_maybe_pickled_blob, _pickle_client(blob) if needs_pickling else blob, "_handle_filename_and_upload" if isinstance(path_or_file, str) else "_prep_and_do_upload", path_or_file, **upload_kwargs, ) ) concurrent.futures.wait( futures, timeout=deadline, return_when=concurrent.futures.ALL_COMPLETED ) results = [] for future in futures: exp = future.exception() # If raise_exception is False, don't call future.result() if exp and not raise_exception: results.append(exp) # If skip_if_exists and the exception is PreconditionFailed, do same. elif exp and skip_if_exists and isinstance(exp, exceptions.PreconditionFailed): results.append(exp) # Get the real result. If there was an exception not handled above, # this will raise it. else: results.append(future.result()) return results @_deprecate_threads_param def download_many( blob_file_pairs, download_kwargs=None, threads=None, deadline=None, raise_exception=False, worker_type=PROCESS, max_workers=DEFAULT_MAX_WORKERS, *, skip_if_exists=False, ): """Download many blobs concurrently via a worker pool. :type blob_file_pairs: List(Tuple('google.cloud.storage.blob.Blob', IOBase or str)) :param blob_file_pairs: A list of tuples of blob and a file or filename. Each blob will be downloaded to the corresponding blob by using APIs identical to blob.download_to_file() or blob.download_to_filename() as appropriate. Note that blob.download_to_filename() does not delete the destination file if the download fails. File handlers are only supported if worker_type is set to THREAD. If worker_type is set to PROCESS, please use filenames only. :type download_kwargs: dict :param download_kwargs: A dictionary of keyword arguments to pass to the download method. Refer to the documentation for `blob.download_to_file()` or `blob.download_to_filename()` for more information. The dict is directly passed into the download methods and is not validated by this function. :type threads: int :param threads: ***DEPRECATED*** Sets `worker_type` to THREAD and `max_workers` to the number specified. If `worker_type` or `max_workers` are set explicitly, this parameter should be set to None. Please use `worker_type` and `max_workers` instead of this parameter. :type deadline: int :param deadline: The number of seconds to wait for all threads to resolve. If the deadline is reached, all threads will be terminated regardless of their progress and `concurrent.futures.TimeoutError` will be raised. This can be left as the default of `None` (no deadline) for most use cases. :type raise_exception: bool :param raise_exception: If True, instead of adding exceptions to the list of return values, instead they will be raised. Note that encountering an exception on one operation will not prevent other operations from starting. Exceptions are only processed and potentially raised after all operations are complete in success or failure. :type worker_type: str :param worker_type: The worker type to use; one of `google.cloud.storage.transfer_manager.PROCESS` or `google.cloud.storage.transfer_manager.THREAD`. Although the exact performance impact depends on the use case, in most situations the PROCESS worker type will use more system resources (both memory and CPU) and result in faster operations than THREAD workers. Because the subprocesses of the PROCESS worker type can't access memory from the main process, Client objects have to be serialized and then recreated in each subprocess. The serialization of the Client object for use in subprocesses is an approximation and may not capture every detail of the Client object, especially if the Client was modified after its initial creation or if `Client._http` was modified in any way. THREAD worker types are observed to be relatively efficient for operations with many small files, but not for operations with large files. PROCESS workers are recommended for large file operations. PROCESS workers do not support writing to file handlers. Please refer to files by filename only when using PROCESS workers. :type max_workers: int :param max_workers: The maximum number of workers to create to handle the workload. With PROCESS workers, a larger number of workers will consume more system resources (memory and CPU) at once. How many workers is optimal depends heavily on the specific use case, and the default is a conservative number that should work okay in most cases without consuming excessive resources. :type skip_if_exists: bool :param skip_if_exists: Before downloading each blob, check if the file for the filename exists; if it does, skip that blob. :raises: :exc:`concurrent.futures.TimeoutError` if deadline is exceeded. :rtype: list :returns: A list of results corresponding to, in order, each item in the input list. If an exception was received, it will be the result for that operation. Otherwise, the return value from the successful download method is used (which will be None). """ if download_kwargs is None: download_kwargs = {} download_kwargs["command"] = "tm.download_many" pool_class, needs_pickling = _get_pool_class_and_requirements(worker_type) with pool_class(max_workers=max_workers) as executor: futures = [] for blob, path_or_file in blob_file_pairs: # File objects are only supported by the THREAD worker because they can't # be pickled. if needs_pickling and not isinstance(path_or_file, str): raise ValueError( "Passing in a file object is only supported by the THREAD worker type. Please either select THREAD workers, or pass in filenames only." ) if skip_if_exists and isinstance(path_or_file, str): if os.path.isfile(path_or_file): continue futures.append( executor.submit( _call_method_on_maybe_pickled_blob, _pickle_client(blob) if needs_pickling else blob, "_handle_filename_and_download" if isinstance(path_or_file, str) else "_prep_and_do_download", path_or_file, **download_kwargs, ) ) concurrent.futures.wait( futures, timeout=deadline, return_when=concurrent.futures.ALL_COMPLETED ) results = [] for future in futures: # If raise_exception is False, don't call future.result() if not raise_exception: exp = future.exception() if exp: results.append(exp) continue # Get the real result. If there was an exception, this will raise it. results.append(future.result()) return results @_deprecate_threads_param def upload_many_from_filenames( bucket, filenames, source_directory="", blob_name_prefix="", skip_if_exists=False, blob_constructor_kwargs=None, upload_kwargs=None, threads=None, deadline=None, raise_exception=False, worker_type=PROCESS, max_workers=DEFAULT_MAX_WORKERS, *, additional_blob_attributes=None, ): """Upload many files concurrently by their filenames. The destination blobs are automatically created, with blob names based on the source filenames and the blob_name_prefix. For example, if the `filenames` include "images/icon.jpg", `source_directory` is "/home/myuser/", and `blob_name_prefix` is "myfiles/", then the file at "/home/myuser/images/icon.jpg" will be uploaded to a blob named "myfiles/images/icon.jpg". :type bucket: :class:`google.cloud.storage.bucket.Bucket` :param bucket: The bucket which will contain the uploaded blobs. :type filenames: list(str) :param filenames: A list of filenames to be uploaded. This may include part of the path. The file will be accessed at the full path of `source_directory` + `filename`. :type source_directory: str :param source_directory: A string that will be prepended (with `os.path.join()`) to each filename in the input list, in order to find the source file for each blob. Unlike the filename itself, the source_directory does not affect the name of the uploaded blob. For instance, if the source_directory is "/tmp/img/" and a filename is "0001.jpg", with an empty blob_name_prefix, then the file uploaded will be "/tmp/img/0001.jpg" and the destination blob will be "0001.jpg". This parameter can be an empty string. Note that this parameter allows directory traversal (e.g. "/", "../") and is not intended for unsanitized end user input. :type blob_name_prefix: str :param blob_name_prefix: A string that will be prepended to each filename in the input list, in order to determine the name of the destination blob. Unlike the filename itself, the prefix string does not affect the location the library will look for the source data on the local filesystem. For instance, if the source_directory is "/tmp/img/", the blob_name_prefix is "myuser/mystuff-" and a filename is "0001.jpg" then the file uploaded will be "/tmp/img/0001.jpg" and the destination blob will be "myuser/mystuff-0001.jpg". The blob_name_prefix can be blank (an empty string). :type skip_if_exists: bool :param skip_if_exists: If True, blobs that already have a live version will not be overwritten. This is accomplished by setting `if_generation_match = 0` on uploads. Uploads so skipped will result in a 412 Precondition Failed response code, which will be included in the return value, but not raised as an exception regardless of the value of raise_exception. :type blob_constructor_kwargs: dict :param blob_constructor_kwargs: A dictionary of keyword arguments to pass to the blob constructor. Refer to the documentation for `blob.Blob()` for more information. The dict is directly passed into the constructor and is not validated by this function. `name` and `bucket` keyword arguments are reserved by this function and will result in an error if passed in here. :type upload_kwargs: dict :param upload_kwargs: A dictionary of keyword arguments to pass to the upload method. Refer to the documentation for `blob.upload_from_file()` or `blob.upload_from_filename()` for more information. The dict is directly passed into the upload methods and is not validated by this function. :type threads: int :param threads: ***DEPRECATED*** Sets `worker_type` to THREAD and `max_workers` to the number specified. If `worker_type` or `max_workers` are set explicitly, this parameter should be set to None. Please use `worker_type` and `max_workers` instead of this parameter. :type deadline: int :param deadline: The number of seconds to wait for all threads to resolve. If the deadline is reached, all threads will be terminated regardless of their progress and `concurrent.futures.TimeoutError` will be raised. This can be left as the default of `None` (no deadline) for most use cases. :type raise_exception: bool :param raise_exception: If True, instead of adding exceptions to the list of return values, instead they will be raised. Note that encountering an exception on one operation will not prevent other operations from starting. Exceptions are only processed and potentially raised after all operations are complete in success or failure. If skip_if_exists is True, 412 Precondition Failed responses are considered part of normal operation and are not raised as an exception. :type worker_type: str :param worker_type: The worker type to use; one of `google.cloud.storage.transfer_manager.PROCESS` or `google.cloud.storage.transfer_manager.THREAD`. Although the exact performance impact depends on the use case, in most situations the PROCESS worker type will use more system resources (both memory and CPU) and result in faster operations than THREAD workers. Because the subprocesses of the PROCESS worker type can't access memory from the main process, Client objects have to be serialized and then recreated in each subprocess. The serialization of the Client object for use in subprocesses is an approximation and may not capture every detail of the Client object, especially if the Client was modified after its initial creation or if `Client._http` was modified in any way. THREAD worker types are observed to be relatively efficient for operations with many small files, but not for operations with large files. PROCESS workers are recommended for large file operations. :type max_workers: int :param max_workers: The maximum number of workers to create to handle the workload. With PROCESS workers, a larger number of workers will consume more system resources (memory and CPU) at once. How many workers is optimal depends heavily on the specific use case, and the default is a conservative number that should work okay in most cases without consuming excessive resources. :type additional_blob_attributes: dict :param additional_blob_attributes: A dictionary of blob attribute names and values. This allows the configuration of blobs beyond what is possible with blob_constructor_kwargs. For instance, {"cache_control": "no-cache"} would set the cache_control attribute of each blob to "no-cache". As with blob_constructor_kwargs, this affects the creation of every blob identically. To fine-tune each blob individually, use `upload_many` and create the blobs as desired before passing them in. :raises: :exc:`concurrent.futures.TimeoutError` if deadline is exceeded. :rtype: list :returns: A list of results corresponding to, in order, each item in the input list. If an exception was received, it will be the result for that operation. Otherwise, the return value from the successful upload method is used (which will be None). """ if blob_constructor_kwargs is None: blob_constructor_kwargs = {} if additional_blob_attributes is None: additional_blob_attributes = {} file_blob_pairs = [] for filename in filenames: path = os.path.join(source_directory, filename) blob_name = blob_name_prefix + filename blob = bucket.blob(blob_name, **blob_constructor_kwargs) for prop, value in additional_blob_attributes.items(): setattr(blob, prop, value) file_blob_pairs.append((path, blob)) return upload_many( file_blob_pairs, skip_if_exists=skip_if_exists, upload_kwargs=upload_kwargs, deadline=deadline, raise_exception=raise_exception, worker_type=worker_type, max_workers=max_workers, ) @_deprecate_threads_param def download_many_to_path( bucket, blob_names, destination_directory="", blob_name_prefix="", download_kwargs=None, threads=None, deadline=None, create_directories=True, raise_exception=False, worker_type=PROCESS, max_workers=DEFAULT_MAX_WORKERS, *, skip_if_exists=False, ): """Download many files concurrently by their blob names. The destination files are automatically created, with paths based on the source blob_names and the destination_directory. The destination files are not automatically deleted if their downloads fail, so please check the return value of this function for any exceptions, or enable `raise_exception=True`, and process the files accordingly. For example, if the `blob_names` include "icon.jpg", `destination_directory` is "/home/myuser/", and `blob_name_prefix` is "images/", then the blob named "images/icon.jpg" will be downloaded to a file named "/home/myuser/icon.jpg". :type bucket: :class:`google.cloud.storage.bucket.Bucket` :param bucket: The bucket which contains the blobs to be downloaded :type blob_names: list(str) :param blob_names: A list of blobs to be downloaded. The blob name in this string will be used to determine the destination file path as well. The full name to the blob must be blob_name_prefix + blob_name. The blob_name is separate from the blob_name_prefix because the blob_name will also determine the name of the destination blob. Any shared part of the blob names that need not be part of the destination path should be included in the blob_name_prefix. :type destination_directory: str :param destination_directory: A string that will be prepended (with os.path.join()) to each blob_name in the input list, in order to determine the destination path for that blob. For instance, if the destination_directory string is "/tmp/img" and a blob_name is "0001.jpg", with an empty blob_name_prefix, then the source blob "0001.jpg" will be downloaded to destination "/tmp/img/0001.jpg" . This parameter can be an empty string. Note that this parameter allows directory traversal (e.g. "/", "../") and is not intended for unsanitized end user input. :type blob_name_prefix: str :param blob_name_prefix: A string that will be prepended to each blob_name in the input list, in order to determine the name of the source blob. Unlike the blob_name itself, the prefix string does not affect the destination path on the local filesystem. For instance, if the destination_directory is "/tmp/img/", the blob_name_prefix is "myuser/mystuff-" and a blob_name is "0001.jpg" then the source blob "myuser/mystuff-0001.jpg" will be downloaded to "/tmp/img/0001.jpg". The blob_name_prefix can be blank (an empty string). :type download_kwargs: dict :param download_kwargs: A dictionary of keyword arguments to pass to the download method. Refer to the documentation for `blob.download_to_file()` or `blob.download_to_filename()` for more information. The dict is directly passed into the download methods and is not validated by this function. :type threads: int :param threads: ***DEPRECATED*** Sets `worker_type` to THREAD and `max_workers` to the number specified. If `worker_type` or `max_workers` are set explicitly, this parameter should be set to None. Please use `worker_type` and `max_workers` instead of this parameter. :type deadline: int :param deadline: The number of seconds to wait for all threads to resolve. If the deadline is reached, all threads will be terminated regardless of their progress and `concurrent.futures.TimeoutError` will be raised. This can be left as the default of `None` (no deadline) for most use cases. :type create_directories: bool :param create_directories: If True, recursively create any directories that do not exist. For instance, if downloading object "images/img001.png", create the directory "images" before downloading. :type raise_exception: bool :param raise_exception: If True, instead of adding exceptions to the list of return values, instead they will be raised. Note that encountering an exception on one operation will not prevent other operations from starting. Exceptions are only processed and potentially raised after all operations are complete in success or failure. If skip_if_exists is True, 412 Precondition Failed responses are considered part of normal operation and are not raised as an exception. :type worker_type: str :param worker_type: The worker type to use; one of `google.cloud.storage.transfer_manager.PROCESS` or `google.cloud.storage.transfer_manager.THREAD`. Although the exact performance impact depends on the use case, in most situations the PROCESS worker type will use more system resources (both memory and CPU) and result in faster operations than THREAD workers. Because the subprocesses of the PROCESS worker type can't access memory from the main process, Client objects have to be serialized and then recreated in each subprocess. The serialization of the Client object for use in subprocesses is an approximation and may not capture every detail of the Client object, especially if the Client was modified after its initial creation or if `Client._http` was modified in any way. THREAD worker types are observed to be relatively efficient for operations with many small files, but not for operations with large files. PROCESS workers are recommended for large file operations. :type max_workers: int :param max_workers: The maximum number of workers to create to handle the workload. With PROCESS workers, a larger number of workers will consume more system resources (memory and CPU) at once. How many workers is optimal depends heavily on the specific use case, and the default is a conservative number that should work okay in most cases without consuming excessive resources. :type skip_if_exists: bool :param skip_if_exists: Before downloading each blob, check if the file for the filename exists; if it does, skip that blob. This only works for filenames. :raises: :exc:`concurrent.futures.TimeoutError` if deadline is exceeded. :rtype: list :returns: A list of results corresponding to, in order, each item in the input list. If an exception was received, it will be the result for that operation. Otherwise, the return value from the successful download method is used (which will be None). """ blob_file_pairs = [] for blob_name in blob_names: full_blob_name = blob_name_prefix + blob_name path = os.path.join(destination_directory, blob_name) if create_directories: directory, _ = os.path.split(path) os.makedirs(directory, exist_ok=True) blob_file_pairs.append((bucket.blob(full_blob_name), path)) return download_many( blob_file_pairs, download_kwargs=download_kwargs, deadline=deadline, raise_exception=raise_exception, worker_type=worker_type, max_workers=max_workers, skip_if_exists=skip_if_exists, ) def download_chunks_concurrently( blob, filename, chunk_size=TM_DEFAULT_CHUNK_SIZE, download_kwargs=None, deadline=None, worker_type=PROCESS, max_workers=DEFAULT_MAX_WORKERS, *, crc32c_checksum=True, ): """Download a single file in chunks, concurrently. In some environments, using this feature with mutiple processes will result in faster downloads of large files. Using this feature with multiple threads is unlikely to improve download performance under normal circumstances due to Python interpreter threading behavior. The default is therefore to use processes instead of threads. :type blob: :class:`google.cloud.storage.blob.Blob` :param blob: The blob to be downloaded. :type filename: str :param filename: The destination filename or path. :type chunk_size: int :param chunk_size: The size in bytes of each chunk to send. The optimal chunk size for maximum throughput may vary depending on the exact network environment and size of the blob. :type download_kwargs: dict :param download_kwargs: A dictionary of keyword arguments to pass to the download method. Refer to the documentation for `blob.download_to_file()` or `blob.download_to_filename()` for more information. The dict is directly passed into the download methods and is not validated by this function. Keyword arguments "start" and "end" which are not supported and will cause a ValueError if present. The key "checksum" is also not supported in `download_kwargs`, but see the argument `crc32c_checksum` (which does not go in `download_kwargs`) below. :type deadline: int :param deadline: The number of seconds to wait for all threads to resolve. If the deadline is reached, all threads will be terminated regardless of their progress and `concurrent.futures.TimeoutError` will be raised. This can be left as the default of `None` (no deadline) for most use cases. :type worker_type: str :param worker_type: The worker type to use; one of `google.cloud.storage.transfer_manager.PROCESS` or `google.cloud.storage.transfer_manager.THREAD`. Although the exact performance impact depends on the use case, in most situations the PROCESS worker type will use more system resources (both memory and CPU) and result in faster operations than THREAD workers. Because the subprocesses of the PROCESS worker type can't access memory from the main process, Client objects have to be serialized and then recreated in each subprocess. The serialization of the Client object for use in subprocesses is an approximation and may not capture every detail of the Client object, especially if the Client was modified after its initial creation or if `Client._http` was modified in any way. THREAD worker types are observed to be relatively efficient for operations with many small files, but not for operations with large files. PROCESS workers are recommended for large file operations. :type max_workers: int :param max_workers: The maximum number of workers to create to handle the workload. With PROCESS workers, a larger number of workers will consume more system resources (memory and CPU) at once. How many workers is optimal depends heavily on the specific use case, and the default is a conservative number that should work okay in most cases without consuming excessive resources. :type crc32c_checksum: bool :param crc32c_checksum: Whether to compute a checksum for the resulting object, using the crc32c algorithm. As the checksums for each chunk must be combined using a feature of crc32c that is not available for md5, md5 is not supported. :raises: :exc:`concurrent.futures.TimeoutError` if deadline is exceeded. :exc:`google.cloud.storage._media.common.DataCorruption` if the download's checksum doesn't agree with server-computed checksum. The `google.cloud.storage._media` exception is used here for consistency with other download methods despite the exception originating elsewhere. """ client = blob.client if download_kwargs is None: download_kwargs = {} if "start" in download_kwargs or "end" in download_kwargs: raise ValueError( "Download arguments 'start' and 'end' are not supported by download_chunks_concurrently." ) if "checksum" in download_kwargs: raise ValueError( "'checksum' is in download_kwargs, but is not supported because sliced downloads have a different checksum mechanism from regular downloads. Use the 'crc32c_checksum' argument on download_chunks_concurrently instead." ) download_kwargs = download_kwargs.copy() download_kwargs["checksum"] = None download_kwargs["command"] = "tm.download_sharded" # We must know the size and the generation of the blob. if not blob.size or not blob.generation: blob.reload() pool_class, needs_pickling = _get_pool_class_and_requirements(worker_type) # Pickle the blob ahead of time (just once, not once per chunk) if needed. maybe_pickled_blob = _pickle_client(blob) if needs_pickling else blob futures = [] # Create and/or truncate the destination file to prepare for sparse writing. with open(filename, "wb") as _: pass with pool_class(max_workers=max_workers) as executor: cursor = 0 end = blob.size while cursor < end: start = cursor cursor = min(cursor + chunk_size, end) futures.append( executor.submit( _download_and_write_chunk_in_place, maybe_pickled_blob, filename, start=start, end=cursor - 1, download_kwargs=download_kwargs, crc32c_checksum=crc32c_checksum, ) ) concurrent.futures.wait( futures, timeout=deadline, return_when=concurrent.futures.ALL_COMPLETED ) # Raise any exceptions; combine checksums. results = [] for future in futures: results.append(future.result()) if crc32c_checksum and results: crc_digest = _digest_ordered_checksum_and_size_pairs(results) actual_checksum = base64.b64encode(crc_digest).decode("utf-8") expected_checksum = blob.crc32c if actual_checksum != expected_checksum: # For consistency with other download methods we will use # "google.cloud.storage._media.common.DataCorruption" despite the error # not originating inside google.cloud.storage._media. download_url = blob._get_download_url( client, if_generation_match=download_kwargs.get("if_generation_match"), if_generation_not_match=download_kwargs.get("if_generation_not_match"), if_metageneration_match=download_kwargs.get("if_metageneration_match"), if_metageneration_not_match=download_kwargs.get( "if_metageneration_not_match" ), ) raise DataCorruption( None, DOWNLOAD_CRC32C_MISMATCH_TEMPLATE.format( download_url, expected_checksum, actual_checksum ), ) return None def upload_chunks_concurrently( filename, blob, content_type=None, chunk_size=TM_DEFAULT_CHUNK_SIZE, deadline=None, worker_type=PROCESS, max_workers=DEFAULT_MAX_WORKERS, *, checksum="auto", timeout=_DEFAULT_TIMEOUT, retry=DEFAULT_RETRY, ): """Upload a single file in chunks, concurrently. This function uses the XML MPU API to initialize an upload and upload a file in chunks, concurrently with a worker pool. The XML MPU API is significantly different from other uploads; please review the documentation at `https://cloud.google.com/storage/docs/multipart-uploads` before using this feature. The library will attempt to cancel uploads that fail due to an exception. If the upload fails in a way that precludes cancellation, such as a hardware failure, process termination, or power outage, then the incomplete upload may persist indefinitely. To mitigate this, set the `AbortIncompleteMultipartUpload` with a nonzero `Age` in bucket lifecycle rules, or refer to the XML API documentation linked above to learn more about how to list and delete individual downloads. Using this feature with multiple threads is unlikely to improve upload performance under normal circumstances due to Python interpreter threading behavior. The default is therefore to use processes instead of threads. ACL information cannot be sent with this function and should be set separately with :class:`ObjectACL` methods. :type filename: str :param filename: The path to the file to upload. File-like objects are not supported. :type blob: :class:`google.cloud.storage.blob.Blob` :param blob: The blob to which to upload. :type content_type: str :param content_type: (Optional) Type of content being uploaded. :type chunk_size: int :param chunk_size: The size in bytes of each chunk to send. The optimal chunk size for maximum throughput may vary depending on the exact network environment and size of the blob. The remote API has restrictions on the minimum and maximum size allowable, see: `https://cloud.google.com/storage/quotas#requests` :type deadline: int :param deadline: The number of seconds to wait for all threads to resolve. If the deadline is reached, all threads will be terminated regardless of their progress and `concurrent.futures.TimeoutError` will be raised. This can be left as the default of `None` (no deadline) for most use cases. :type worker_type: str :param worker_type: The worker type to use; one of `google.cloud.storage.transfer_manager.PROCESS` or `google.cloud.storage.transfer_manager.THREAD`. Although the exact performance impact depends on the use case, in most situations the PROCESS worker type will use more system resources (both memory and CPU) and result in faster operations than THREAD workers. Because the subprocesses of the PROCESS worker type can't access memory from the main process, Client objects have to be serialized and then recreated in each subprocess. The serialization of the Client object for use in subprocesses is an approximation and may not capture every detail of the Client object, especially if the Client was modified after its initial creation or if `Client._http` was modified in any way. THREAD worker types are observed to be relatively efficient for operations with many small files, but not for operations with large files. PROCESS workers are recommended for large file operations. :type max_workers: int :param max_workers: The maximum number of workers to create to handle the workload. With PROCESS workers, a larger number of workers will consume more system resources (memory and CPU) at once. How many workers is optimal depends heavily on the specific use case, and the default is a conservative number that should work okay in most cases without consuming excessive resources. :type checksum: str :param checksum: (Optional) The checksum scheme to use: either "md5", "crc32c", "auto" or None. The default is "auto", which will try to detect if the C extension for crc32c is installed and fall back to md5 otherwise. Each individual part is checksummed. At present, the selected checksum rule is only applied to parts and a separate checksum of the entire resulting blob is not computed. Please compute and compare the checksum of the file to the resulting blob separately if needed, using the "crc32c" algorithm as per the XML MPU documentation. :type timeout: float or tuple :param timeout: (Optional) The amount of time, in seconds, to wait for the server response. See: :ref:`configuring_timeouts` :type retry: google.api_core.retry.Retry :param retry: (Optional) How to retry the RPC. A None value will disable retries. A `google.api_core.retry.Retry` value will enable retries, and the object will configure backoff and timeout options. Custom predicates (customizable error codes) are not supported for media operations such as this one. This function does not accept `ConditionalRetryPolicy` values because preconditions are not supported by the underlying API call. See the retry.py source code and docstrings in this package (`google.cloud.storage.retry`) for information on retry types and how to configure them. :raises: :exc:`concurrent.futures.TimeoutError` if deadline is exceeded. """ bucket = blob.bucket client = blob.client transport = blob._get_transport(client) hostname = _get_host_name(client._connection) url = "{hostname}/{bucket}/{blob}".format( hostname=hostname, bucket=bucket.name, blob=_quote(blob.name) ) base_headers, object_metadata, content_type = blob._get_upload_arguments( client, content_type, filename=filename, command="tm.upload_sharded" ) headers = {**base_headers, **_headers_from_metadata(object_metadata)} if blob.user_project is not None: headers["x-goog-user-project"] = blob.user_project # When a Customer Managed Encryption Key is used to encrypt Cloud Storage object # at rest, object resource metadata will store the version of the Key Management # Service cryptographic material. If a Blob instance with KMS Key metadata set is # used to upload a new version of the object then the existing kmsKeyName version # value can't be used in the upload request and the client instead ignores it. if blob.kms_key_name is not None and "cryptoKeyVersions" not in blob.kms_key_name: headers["x-goog-encryption-kms-key-name"] = blob.kms_key_name container = XMLMPUContainer(url, filename, headers=headers, retry=retry) container.initiate(transport=transport, content_type=content_type) upload_id = container.upload_id size = os.path.getsize(filename) num_of_parts = -(size // -chunk_size) # Ceiling division pool_class, needs_pickling = _get_pool_class_and_requirements(worker_type) # Pickle the blob ahead of time (just once, not once per chunk) if needed. maybe_pickled_client = _pickle_client(client) if needs_pickling else client futures = [] with pool_class(max_workers=max_workers) as executor: for part_number in range(1, num_of_parts + 1): start = (part_number - 1) * chunk_size end = min(part_number * chunk_size, size) futures.append( executor.submit( _upload_part, maybe_pickled_client, url, upload_id, filename, start=start, end=end, part_number=part_number, checksum=checksum, headers=headers, retry=retry, ) ) concurrent.futures.wait( futures, timeout=deadline, return_when=concurrent.futures.ALL_COMPLETED ) try: # Harvest results and raise exceptions. for future in futures: part_number, etag = future.result() container.register_part(part_number, etag) container.finalize(blob._get_transport(client)) except Exception: container.cancel(blob._get_transport(client)) raise def _upload_part( maybe_pickled_client, url, upload_id, filename, start, end, part_number, checksum, headers, retry, ): """Helper function that runs inside a thread or subprocess to upload a part. `maybe_pickled_client` is either a Client (for threads) or a specially pickled Client (for processes) because the default pickling mangles Client objects.""" if isinstance(maybe_pickled_client, Client): client = maybe_pickled_client else: client = pickle.loads(maybe_pickled_client) part = XMLMPUPart( url, upload_id, filename, start=start, end=end, part_number=part_number, checksum=checksum, headers=headers, retry=retry, ) part.upload(client._http) return (part_number, part.etag) def _headers_from_metadata(metadata): """Helper function to translate object metadata into a header dictionary.""" headers = {} # Handle standard writable metadata for key, value in metadata.items(): if key in METADATA_HEADER_TRANSLATION: headers[METADATA_HEADER_TRANSLATION[key]] = value # Handle custom metadata if "metadata" in metadata: for key, value in metadata["metadata"].items(): headers["x-goog-meta-" + key] = value return headers def _download_and_write_chunk_in_place( maybe_pickled_blob, filename, start, end, download_kwargs, crc32c_checksum ): """Helper function that runs inside a thread or subprocess. `maybe_pickled_blob` is either a Blob (for threads) or a specially pickled Blob (for processes) because the default pickling mangles Client objects which are attached to Blobs. Returns a crc if configured (or None) and the size written. """ if isinstance(maybe_pickled_blob, Blob): blob = maybe_pickled_blob else: blob = pickle.loads(maybe_pickled_blob) with _ChecksummingSparseFileWrapper(filename, start, crc32c_checksum) as f: blob._prep_and_do_download(f, start=start, end=end, **download_kwargs) return (f.crc, (end - start) + 1) class _ChecksummingSparseFileWrapper: """A file wrapper that writes to a sparse file and optionally checksums. This wrapper only implements write() and does not inherit from `io` module base classes. """ def __init__(self, filename, start_position, crc32c_enabled): # Open in mixed read/write mode to avoid truncating or appending self.f = open(filename, "rb+") self.f.seek(start_position) self._crc = None self._crc32c_enabled = crc32c_enabled def write(self, chunk): if self._crc32c_enabled: if self._crc is None: self._crc = google_crc32c.value(chunk) else: self._crc = google_crc32c.extend(self._crc, chunk) self.f.write(chunk) @property def crc(self): return self._crc def __enter__(self): return self def __exit__(self, exc_type, exc_value, tb): self.f.close() def _call_method_on_maybe_pickled_blob( maybe_pickled_blob, method_name, *args, **kwargs ): """Helper function that runs inside a thread or subprocess. `maybe_pickled_blob` is either a Blob (for threads) or a specially pickled Blob (for processes) because the default pickling mangles Client objects which are attached to Blobs.""" if isinstance(maybe_pickled_blob, Blob): blob = maybe_pickled_blob else: blob = pickle.loads(maybe_pickled_blob) return getattr(blob, method_name)(*args, **kwargs) def _reduce_client(cl): """Replicate a Client by constructing a new one with the same params. LazyClient performs transparent caching for when the same client is needed on the same process multiple times.""" client_object_id = id(cl) project = cl.project credentials = cl._credentials _http = None # Can't carry this over client_info = cl._initial_client_info client_options = cl._initial_client_options extra_headers = cl._extra_headers return _LazyClient, ( client_object_id, project, credentials, _http, client_info, client_options, extra_headers, ) def _pickle_client(obj): """Pickle a Client or an object that owns a Client (like a Blob)""" # We need a custom pickler to process Client objects, which are attached to # Buckets (and therefore to Blobs in turn). Unfortunately, the Python # multiprocessing library doesn't seem to have a good way to use a custom # pickler, and using copyreg will mutate global state and affect code # outside of the client library. Instead, we'll pre-pickle the object and # pass the bytestring in. f = io.BytesIO() p = pickle.Pickler(f) p.dispatch_table = copyreg.dispatch_table.copy() p.dispatch_table[Client] = _reduce_client p.dump(obj) return f.getvalue() def _get_pool_class_and_requirements(worker_type): """Returns the pool class, and whether the pool requires pickled Blobs.""" if worker_type == PROCESS: # Use processes. Pickle blobs with custom logic to handle the client. return (concurrent.futures.ProcessPoolExecutor, True) elif worker_type == THREAD: # Use threads. Pass blobs through unpickled. return (concurrent.futures.ThreadPoolExecutor, False) else: raise ValueError( "The worker_type must be google.cloud.storage.transfer_manager.PROCESS or google.cloud.storage.transfer_manager.THREAD" ) def _digest_ordered_checksum_and_size_pairs(checksum_and_size_pairs): base_crc = None zeroes = bytes(MAX_CRC32C_ZERO_ARRAY_SIZE) for part_crc, size in checksum_and_size_pairs: if not base_crc: base_crc = part_crc else: base_crc ^= 0xFFFFFFFF # precondition # Zero pad base_crc32c. To conserve memory, do so with only # MAX_CRC32C_ZERO_ARRAY_SIZE at a time. Reuse the zeroes array where # possible. padded = 0 while padded < size: desired_zeroes_size = min((size - padded), MAX_CRC32C_ZERO_ARRAY_SIZE) base_crc = google_crc32c.extend(base_crc, zeroes[:desired_zeroes_size]) padded += desired_zeroes_size base_crc ^= 0xFFFFFFFF # postcondition base_crc ^= part_crc crc_digest = struct.pack( ">L", base_crc ) # https://cloud.google.com/storage/docs/json_api/v1/objects#crc32c return crc_digest class _LazyClient: """An object that will transform into either a cached or a new Client""" def __new__(cls, id, *args, **kwargs): cached_client = _cached_clients.get(id) if cached_client: return cached_client else: cached_client = Client(*args, **kwargs) _cached_clients[id] = cached_client return cached_client