包装C++ FileSystem API的文件IO方法

2018-10-18 17:15 更新

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""包装 C ++ FileSystem API的文件IO方法.""

""C ++ FileSystem API是 SWIG 包装在 file_io.i 中.这些功能称之为 完成基本的文件 IO 操作.""

from __future__ import absolute_import from __future__ import division from __future__ import print_function import os import uuid import six from tensorflow.python import pywrap_tensorflow from tensorflow.python.framework import errors from tensorflow.python.util import compat from tensorflow.python.util import deprecation class FileIO(object): """FileIO class that exposes methods to read / write to / from files. The constructor takes the following arguments: name: name of the file mode: one of 'r', 'w', 'a', 'r+', 'w+', 'a+'. Append 'b' for bytes mode. Can be used as an iterator to iterate over lines in the file. The default buffer size used for the BufferedInputStream used for reading the file line by line is 1024 * 512 bytes. """ def __init__(self, name, mode): self.__name = name self.__mode = mode self._read_buf = None self._writable_file = None self._binary_mode = "b" in mode mode = mode.replace("b", "") if mode not in ("r", "w", "a", "r+", "w+", "a+"): raise errors.InvalidArgumentError( None, None, "mode is not 'r' or 'w' or 'a' or 'r+' or 'w+' or 'a+'") self._read_check_passed = mode in ("r", "r+", "a+", "w+") self._write_check_passed = mode in ("a", "w", "r+", "a+", "w+") @property def name(self): """Returns the file name.""" return self.__name @property def mode(self): """Returns the mode in which the file was opened.""" return self.__mode def _preread_check(self): if not self._read_buf: if not self._read_check_passed: raise errors.PermissionDeniedError(None, None, "File isn't open for reading") with errors.raise_exception_on_not_ok_status() as status: self._read_buf = pywrap_tensorflow.CreateBufferedInputStream( compat.as_bytes(self.__name), 1024 * 512, status) def _prewrite_check(self): if not self._writable_file: if not self._write_check_passed: raise errors.PermissionDeniedError(None, None, "File isn't open for writing") with errors.raise_exception_on_not_ok_status() as status: self._writable_file = pywrap_tensorflow.CreateWritableFile( compat.as_bytes(self.__name), compat.as_bytes(self.__mode), status) def _prepare_value(self, val): if self._binary_mode: return compat.as_bytes(val) else: return compat.as_str_any(val) def size(self): """Returns the size of the file.""" return stat(self.__name).length def write(self, file_content): """Writes file_content to the file. Appends to the end of the file.""" self._prewrite_check() with errors.raise_exception_on_not_ok_status() as status: pywrap_tensorflow.AppendToFile( compat.as_bytes(file_content), self._writable_file, status) def read(self, n=-1): """Returns the contents of a file as a string. Starts reading from current position in file. Args: n: Read 'n' bytes if n != -1. If n = -1, reads to end of file. Returns: 'n' bytes of the file (or whole file) in bytes mode or 'n' bytes of the string if in string (regular) mode. """ self._preread_check() with errors.raise_exception_on_not_ok_status() as status: if n == -1: length = self.size() - self.tell() else: length = n return self._prepare_value( pywrap_tensorflow.ReadFromStream(self._read_buf, length, status)) @deprecation.deprecated_args( None, "position is deprecated in favor of the offset argument.", "position") def seek(self, offset=None, whence=0, position=None): # TODO(jhseu): Delete later. Used to omit `position` from docs. # pylint: disable=g-doc-args """Seeks to the offset in the file. Args: offset: The byte count relative to the whence argument. whence: Valid values for whence are: 0: start of the file (default) 1: relative to the current position of the file 2: relative to the end of file. offset is usually negative. """ # pylint: enable=g-doc-args self._preread_check() # We needed to make offset a keyword argument for backwards-compatibility. # This check exists so that we can convert back to having offset be a # positional argument. # TODO(jhseu): Make `offset` a positional argument after `position` is # deleted. if offset is None and position is None: raise TypeError("seek(): offset argument required") if offset is not None and position is not None: raise TypeError("seek(): offset and position may not be set " "simultaneously.") if position is not None: offset = position with errors.raise_exception_on_not_ok_status() as status: if whence == 0: pass elif whence == 1: offset += self.tell() elif whence == 2: offset += self.size() else: raise errors.InvalidArgumentError( None, None, "Invalid whence argument: {}. Valid values are 0, 1, or 2." .format(whence)) ret_status = self._read_buf.Seek(offset) pywrap_tensorflow.Set_TF_Status_from_Status(status, ret_status) def readline(self): r"""Reads the next line from the file. Leaves the '\n' at the end.""" self._preread_check() return self._prepare_value(self._read_buf.ReadLineAsString()) def readlines(self): """Returns all lines from the file in a list.""" self._preread_check() lines = [] while True: s = self.readline() if not s: break lines.append(s) return lines def tell(self): """Returns the current position in the file.""" self._preread_check() return self._read_buf.Tell() def __enter__(self): """Make usable with "with" statement.""" return self def __exit__(self, unused_type, unused_value, unused_traceback): """Make usable with "with" statement.""" self.close() def __iter__(self): return self def next(self): retval = self.readline() if not retval: raise StopIteration() return retval def __next__(self): return self.next() def flush(self): """Flushes the Writable file. This only ensures that the data has made its way out of the process without any guarantees on whether it's written to disk. This means that the data would survive an application crash but not necessarily an OS crash. """ if self._writable_file: with errors.raise_exception_on_not_ok_status() as status: ret_status = self._writable_file.Flush() pywrap_tensorflow.Set_TF_Status_from_Status(status, ret_status) def close(self): """Closes FileIO. Should be called for the WritableFile to be flushed.""" self._read_buf = None if self._writable_file: with errors.raise_exception_on_not_ok_status() as status: ret_status = self._writable_file.Close() pywrap_tensorflow.Set_TF_Status_from_Status(status, ret_status) self._writable_file = None def file_exists(filename): """Determines whether a path exists or not. Args: filename: string, a path Returns: True if the path exists, whether its a file or a directory. False if the path does not exist and there are no filesystem errors. Raises: errors.OpError: Propagates any errors reported by the FileSystem API. """ try: with errors.raise_exception_on_not_ok_status() as status: pywrap_tensorflow.FileExists(compat.as_bytes(filename), status) except errors.NotFoundError: return False return True def delete_file(filename): """Deletes the file located at 'filename'. Args: filename: string, a filename Raises: errors.OpError: Propagates any errors reported by the FileSystem API. E.g., NotFoundError if the file does not exist. """ with errors.raise_exception_on_not_ok_status() as status: pywrap_tensorflow.DeleteFile(compat.as_bytes(filename), status) def read_file_to_string(filename, binary_mode=False): """Reads the entire contents of a file to a string. Args: filename: string, path to a file binary_mode: whether to open the file in binary mode or not. This changes the type of the object returned. Returns: contents of the file as a string or bytes. Raises: errors.OpError: Raises variety of errors that are subtypes e.g. NotFoundError etc. """ if binary_mode: f = FileIO(filename, mode="rb") else: f = FileIO(filename, mode="r") return f.read() def write_string_to_file(filename, file_content): """Writes a string to a given file. Args: filename: string, path to a file file_content: string, contents that need to be written to the file Raises: errors.OpError: If there are errors during the operation. """ with FileIO(filename, mode="w") as f: f.write(file_content) def get_matching_files(filename): """Returns a list of files that match the given pattern(s). Args: filename: string or iterable of strings. The glob pattern(s). Returns: A list of strings containing filenames that match the given pattern(s). Raises: errors.OpError: If there are filesystem / directory listing errors. """ with errors.raise_exception_on_not_ok_status() as status: if isinstance(filename, six.string_types): return [ # Convert the filenames to string from bytes. compat.as_str_any(matching_filename) for matching_filename in pywrap_tensorflow.GetMatchingFiles( compat.as_bytes(filename), status) ] else: return [ # Convert the filenames to string from bytes. compat.as_str_any(matching_filename) for single_filename in filename for matching_filename in pywrap_tensorflow.GetMatchingFiles( compat.as_bytes(single_filename), status) ] def create_dir(dirname): """Creates a directory with the name 'dirname'. Args: dirname: string, name of the directory to be created Notes: The parent directories need to exist. Use recursive_create_dir instead if there is the possibility that the parent dirs don't exist. Raises: errors.OpError: If the operation fails. """ with errors.raise_exception_on_not_ok_status() as status: pywrap_tensorflow.CreateDir(compat.as_bytes(dirname), status) def recursive_create_dir(dirname): """Creates a directory and all parent/intermediate directories. It succeeds if dirname already exists and is writable. Args: dirname: string, name of the directory to be created Raises: errors.OpError: If the operation fails. """ with errors.raise_exception_on_not_ok_status() as status: pywrap_tensorflow.RecursivelyCreateDir(compat.as_bytes(dirname), status) def copy(oldpath, newpath, overwrite=False): """Copies data from oldpath to newpath. Args: oldpath: string, name of the file who's contents need to be copied newpath: string, name of the file to which to copy to overwrite: boolean, if false its an error for newpath to be occupied by an existing file. Raises: errors.OpError: If the operation fails. """ with errors.raise_exception_on_not_ok_status() as status: pywrap_tensorflow.CopyFile( compat.as_bytes(oldpath), compat.as_bytes(newpath), overwrite, status) def rename(oldname, newname, overwrite=False): """Rename or move a file / directory. Args: oldname: string, pathname for a file newname: string, pathname to which the file needs to be moved overwrite: boolean, if false its an error for newpath to be occupied by an existing file. Raises: errors.OpError: If the operation fails. """ with errors.raise_exception_on_not_ok_status() as status: pywrap_tensorflow.RenameFile( compat.as_bytes(oldname), compat.as_bytes(newname), overwrite, status) def atomic_write_string_to_file(filename, contents): """Writes to `filename` atomically. This means that when `filename` appears in the filesystem, it will contain all of `contents`. With write_string_to_file, it is possible for the file to appear in the filesystem with `contents` only partially written. Accomplished by writing to a temp file and then renaming it. Args: filename: string, pathname for a file contents: string, contents that need to be written to the file """ temp_pathname = filename + ".tmp" + uuid.uuid4().hex write_string_to_file(temp_pathname, contents) rename(temp_pathname, filename, overwrite=True) def delete_recursively(dirname): """Deletes everything under dirname recursively. Args: dirname: string, a path to a directory Raises: errors.OpError: If the operation fails. """ with errors.raise_exception_on_not_ok_status() as status: pywrap_tensorflow.DeleteRecursively(compat.as_bytes(dirname), status) def is_directory(dirname): """Returns whether the path is a directory or not. Args: dirname: string, path to a potential directory Returns: True, if the path is a directory; False otherwise """ try: status = pywrap_tensorflow.TF_NewStatus() return pywrap_tensorflow.IsDirectory(compat.as_bytes(dirname), status) finally: pywrap_tensorflow.TF_DeleteStatus(status) def list_directory(dirname): """Returns a list of entries contained within a directory. The list is in arbitrary order. It does not contain the special entries "." and "..". Args: dirname: string, path to a directory Returns: [filename1, filename2, ... filenameN] as strings Raises: errors.NotFoundError if directory doesn't exist """ if not is_directory(dirname): raise errors.NotFoundError(None, None, "Could not find directory") with errors.raise_exception_on_not_ok_status() as status: # Convert each element to string, since the return values of the # vector of string should be interpreted as strings, not bytes. return [ compat.as_str_any(filename) for filename in pywrap_tensorflow.GetChildren( compat.as_bytes(dirname), status) ] def walk(top, in_order=True): """Recursive directory tree generator for directories. Args: top: string, a Directory name in_order: bool, Traverse in order if True, post order if False. Errors that happen while listing directories are ignored. Yields: Each yield is a 3-tuple: the pathname of a directory, followed by lists of all its subdirectories and leaf files. (dirname, [subdirname, subdirname, ...], [filename, filename, ...]) as strings """ top = compat.as_str_any(top) try: listing = list_directory(top) except errors.NotFoundError: return files = [] subdirs = [] for item in listing: full_path = os.path.join(top, item) if is_directory(full_path): subdirs.append(item) else: files.append(item) here = (top, subdirs, files) if in_order: yield here for subdir in subdirs: for subitem in walk(os.path.join(top, subdir), in_order): yield subitem if not in_order: yield here def stat(filename): """Returns file statistics for a given path. Args: filename: string, path to a file Returns: FileStatistics struct that contains information about the path Raises: errors.OpError: If the operation fails. """ file_statistics = pywrap_tensorflow.FileStatistics() with errors.raise_exception_on_not_ok_status() as status: pywrap_tensorflow.Stat(compat.as_bytes(filename), file_statistics, status) return file_statistics
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