一、首先，认识下文件

进行个总结：

计算机内的文件广义上来说，只有二进制文件

狭义上来讲分为两大类：二进制文件和文本文件。

先说数据的产生（即写操作）

文本文件的所有数据都是固定长度的，每条数据（也就是每个字符）都是1个字节。文本文件的“编/解码器”会将每条数据转换成ASCII码或者Unicode，然后以二进制的形式存到硬盘；

而二进制文件每条数据不固定，如short占2个字节，int占5个字节，float占8个字节（不一定，只是举个例子），这是二进制文件的写操作是将内存里的数据直接写入文件。

再说数据的读取：

文件的读过程是这样的：磁盘 》》 文件缓冲区》》应用程序内存空间。

我们说“文本文件和二进制文件没有区别”，实际上针对的是第一个过程；既然没有区别，那么打开方式不同，为何显示内容就不同呢？这个区别实际上是第二个过程造成的。

文件实际上包括两部分，控制信息和内容信息。纯文本文件仅仅是没有控制格式信息罢了；

 

 

 

1.以Numpy的multiarray.fromfile为例

numpy.fromfile()

def fromfile(file, dtype=None, count=-1, sep=''): # real signature unknown; restored from __doc__    """    fromfile(file, dtype=float, count=-1, sep='')            Construct an array from data in a text or binary file.            A highly efficient way of reading binary data with a known data-type,        as well as parsing simply formatted text files.  Data written using the        `tofile` method can be read using this function.            Parameters        ----------        file : file or str            Open file object or filename.        dtype : data-type            Data type of the returned array.            For binary files, it is used to determine the size and byte-order            of the items in the file.        count : int            Number of items to read. ``-1`` means all items (i.e., the complete            file).        sep : str            Separator between items if file is a text file.            Empty ("") separator means the file should be treated as binary.            Spaces (" ") in the separator match zero or more whitespace characters.            A separator consisting only of spaces must match at least one            whitespace.            See also        --------        load, save        ndarray.tofile        loadtxt : More flexible way of loading data from a text file.            Notes        -----        Do not rely on the combination of `tofile` and `fromfile` for        data storage, as the binary files generated are are not platform        independent.  In particular, no byte-order or data-type information is        saved.  Data can be stored in the platform independent ``.npy`` format        using `save` and `load` instead.            Examples        --------        Construct an ndarray:            >>> dt = np.dtype([('time', [('min', int), ('sec', int)]),        ...                ('temp', float)])        >>> x = np.zeros((1,), dtype=dt)        >>> x['time']['min'] = 10; x['temp'] = 98.25        >>> x        array([((10, 0), 98.25)],              dtype=[('time', [('min', '
     
      >> import os        >>> fname = os.tmpnam()        >>> x.tofile(fname)            Read the raw data from disk:            >>> np.fromfile(fname, dtype=dt)        array([((10, 0), 98.25)],              dtype=[('time', [('min', '
      
       >> np.save(fname, x)        >>> np.load(fname + '.npy')        array([((10, 0), 98.25)],              dtype=[('time', [('min', '
      
     

 　值得注意的是，

Empty ("") separator means the file should be treated as binary.

　也就是说，default情况下，是将文件按照二进制文件读取的，加上separator参数后会将二进制转换后的ASCII码或者unicode再解码为文本数据，

以test.txt文件为例(1对应的ASCII码十进制为49，","为44)

test.txt

1,1,1,1,1

(1)使用默认sep参数读取：

filepath = "D://Documents/temp/testForPyStruct.txt"data= np.fromfile(filepath , dtype=np.uint8, sep="")print(data)

输出

[49 44 49 44 49 44 49 44 49]

(2)使用sep=","读取：

filepath = "D://Documents/temp/testForPyStruct.txt"data= np.fromfile(filepath , dtype=np.uint8, sep=",")print(data)

输出

[1 1 1 1 1]

 

 

2.

See also        --------        load, save        ndarray.tofile        loadtxt : More flexible way of loading data from a text file.