将多个文件流式传输到 Python 中的可读对象中

Question

我有一个使用file.read(len)方法处理来自文件的二进制数据的函数。但是，我的文件很大，被切成许多小文件，每个文件 50 MB。是否有一些包装类可以将许多文件馈送到缓冲流中，并提供 read() 方法？

类fileinput.FileInput可以做这样的事情，但它只支持逐行读取（readline()没有参数的方法）并且没有read(len)指定要读取的字节数。

Answer 1

将可迭代对象与 连接起来非常容易itertools.chain：

from itertools import chain

def read_by_chunks(file_objects, block_size=1024):
    readers = (iter(lambda f=f: f.read(block_size), '') for f in file_objects)
    return chain.from_iterable(readers)

然后你可以这样做：

for chunk in read_by_chunks([f1, f2, f3, f4], 4096):
    handle(chunk)

在按4096字节块读取文件的同时按顺序处理文件。

如果您需要为一个对象提供一个read方法，因为其他一些函数希望您可以编写一个非常简单的包装器：

class ConcatFiles(object):
    def __init__(self, files, block_size):
        self._reader = read_by_chunks(files, block_size)

    def __iter__(self):
        return self._reader

    def read(self):
        return next(self._reader, '')

然而，这仅使用固定的块大小。可以通过执行block_size以下操作来支持 的参数read：

def read(self, block_size=None):
    block_size = block_size or self._block_size
    total_read = 0
    chunks = []

    for chunk in self._reader:
        chunks.append(chunk)
        total_read += len(chunk)
        if total_read > block_size:
            contents = ''.join(chunks)
            self._reader = chain([contents[block_size:]], self._reader)
            return contents[:block_size]
    return ''.join(chunks)

注意：如果您以二进制模式阅读，则应''将代码中的空字符串替换为空字节b''。

Answer 2

而不是将流列表转换为生成器 - 正如其他一些答案所做的那样 - 您可以将流链接在一起，然后使用文件接口：

def chain_streams(streams, buffer_size=io.DEFAULT_BUFFER_SIZE):
    """
    Chain an iterable of streams together into a single buffered stream.
    Usage:
        def generate_open_file_streams():
            for file in filenames:
                yield open(file, 'rb')
        f = chain_streams(generate_open_file_streams())
        f.read()
    """

    class ChainStream(io.RawIOBase):
        def __init__(self):
            self.leftover = b''
            self.stream_iter = iter(streams)
            try:
                self.stream = next(self.stream_iter)
            except StopIteration:
                self.stream = None

        def readable(self):
            return True

        def _read_next_chunk(self, max_length):
            # Return 0 or more bytes from the current stream, first returning all
            # leftover bytes. If the stream is closed returns b''
            if self.leftover:
                return self.leftover
            elif self.stream is not None:
                return self.stream.read(max_length)
            else:
                return b''

        def readinto(self, b):
            buffer_length = len(b)
            chunk = self._read_next_chunk(buffer_length)
            while len(chunk) == 0:
                # move to next stream
                if self.stream is not None:
                    self.stream.close()
                try:
                    self.stream = next(self.stream_iter)
                    chunk = self._read_next_chunk(buffer_length)
                except StopIteration:
                    # No more streams to chain together
                    self.stream = None
                    return 0  # indicate EOF
            output, self.leftover = chunk[:buffer_length], chunk[buffer_length:]
            b[:len(output)] = output
            return len(output)

    return io.BufferedReader(ChainStream(), buffer_size=buffer_size)

然后将其用作任何其他文件/流：

f = chain_streams(open_files_or_chunks)
f.read(len)

Answer 3

我不熟悉标准库中执行该功能的任何内容，因此，如果没有：

try:
    from cStringIO import StringIO
except ImportError:
    from StringIO import StringIO

class ConcatenatedFiles( object ):
    def __init__(self, file_objects):
        self.fds= list(reversed(file_objects))

    def read( self, size=None ):
        remaining= size
        data= StringIO()
        while self.fds and (remaining>0 or remaining is None):
            data_read= self.fds[-1].read(remaining or -1)
            if len(data_read)<remaining or remaining is None: #exhausted file
                self.fds.pop()
            if not remaining is None:
                remaining-=len(data_read)
            data.write(data_read)
        return data.getvalue()