要编写惰性函数，只需使用yield:

def read_in_chunks(file_object, chunk_size=1024):
    """Lazy function (generator) to read a file piece by piece.
    Default chunk size: 1k."""
    while True:
        data = file_object.read(chunk_size)
        if not data:
            break
        yield data


with open('really_big_file.dat') as f:
    for piece in read_in_chunks(f):
        process_data(piece)

另一种选择是使用iter和helper函数:

f = open('really_big_file.dat')
def read1k():
    return f.read(1024)

for piece in iter(read1k, ''):
    process_data(piece)

如果文件是基于行的，那么文件对象已经是一个惰性的行生成器:

for line in open('really_big_file.dat'):
    process_data(line)

由于我的低声誉，我不允许评论，但SilentGhosts解决方案应该更容易与file.readlines([sizehint])

Python文件方法

编辑:SilentGhost是对的，但这应该比:

s = "" 
for i in xrange(100): 
   s += file.next()

f = ... # file-like object, i.e. supporting read(size) function and 
        # returning empty string '' when there is nothing to read

def chunked(file, chunk_size):
    return iter(lambda: file.read(chunk_size), '')

for data in chunked(f, 65536):
    # process the data

更新:该方法最好在https://stackoverflow.com/a/4566523/38592中解释

您可以使用以下代码。

file_obj = open('big_file') 

Open()返回一个文件对象

然后使用os。获取大小的数据

file_size = os.stat('big_file').st_size

for i in range( file_size/1024):
    print file_obj.read(1024)

要编写惰性函数，只需使用yield:

def read_in_chunks(file_object, chunk_size=1024):
    """Lazy function (generator) to read a file piece by piece.
    Default chunk size: 1k."""
    while True:
        data = file_object.read(chunk_size)
        if not data:
            break
        yield data


with open('really_big_file.dat') as f:
    for piece in read_in_chunks(f):
        process_data(piece)

另一种选择是使用iter和helper函数:

f = open('really_big_file.dat')
def read1k():
    return f.read(1024)

for piece in iter(read1k, ''):
    process_data(piece)

如果文件是基于行的，那么文件对象已经是一个惰性的行生成器:

for line in open('really_big_file.dat'):
    process_data(line)

参考python的官方文档https://docs.python.org/3/library/functions.html#iter

也许这个方法更python化:

"""A file object returned by open() is a iterator with
read method which could specify current read's block size
"""
with open('mydata.db', 'r') as f_in:
    block_read = partial(f_in.read, 1024 * 1024)
    block_iterator = iter(block_read, '')

    for index, block in enumerate(block_iterator, start=1):
        block = process_block(block)  # process your block data

        with open(f'{index}.txt', 'w') as f_out:
            f_out.write(block)