numpy：gzip 压缩文件的 fromfile

我在用numpy.fromfile构造一个数组，我可以将其传递给pandas.DataFrame构造函数

import numpy as np
import pandas as pd

def read_best_file(file, **kwargs):
    '''
    Loads best price data into a dataframe
    '''
    names   = [ 'time', 'bid_size', 'bid_price', 'ask_size', 'ask_price' ]
    formats = [ 'u8',   'i4',       'f8',        'i4',       'f8'        ]
    offsets = [  0,      8,          12,          20,         24         ]

    dt = np.dtype({
            'names': names, 
            'formats': formats,
            'offsets': offsets 
        })
    return pd.DataFrame(np.fromfile(file, dt))

我想扩展此方法以处理 gzip 压缩文件。

根据numpy.fromfile http://docs.scipy.org/doc/numpy/reference/generated/numpy.fromfile.html文档，第一个参数是文件：

file : file or str
Open file object or filename

因此，我添加了以下内容来检查 gzip 文件路径：

if isinstance(file, str) and file.endswith(".gz"):
    file = gzip.open(file, "r")

但是，当我尝试将其传递给fromfile构造函数我得到一个IOError:

IOError: first argument must be an open file

问题：

我怎样才能打电话numpy.fromfile使用 gzip 压缩文件？

Edit:

根据评论中的请求，显示检查 gzip 压缩文件的实现：

def read_best_file(file, **kwargs):
    '''
    Loads best price data into a dataframe
    '''
    names   = [ 'time', 'bid_size', 'bid_price', 'ask_size', 'ask_price' ]
    formats = [ 'u8',   'i4',       'f8',        'i4',       'f8'        ]
    offsets = [  0,      8,          12,          20,         24         ]

    dt = np.dtype({
            'names': names, 
            'formats': formats,
            'offsets': offsets 
        })

    if isinstance(file, str) and file.endswith(".gz"):
        file = gzip.open(file, "r")

    return pd.DataFrame(np.fromfile(file, dt))

我通过 numpy.frombuffer() 提供 read() 结果，成功地从 gzipped 文件中读取原始二进制数据数组。此代码适用于 Python 3.7.3，也许也适用于早期版本。

# Example: read short integers (signed) from gzipped raw binary file

import gzip
import numpy as np

fname_gzipped = 'my_binary_data.dat.gz'
raw_dtype = np.int16
with gzip.open(fname_gzipped, 'rb') as f:
    from_gzipped = np.frombuffer(f.read(), dtype=raw_dtype)

# Demonstrate equivalence with direct np.fromfile()
fname_raw = 'my_binary_data.dat'
from_raw = np.fromfile(fname_raw, dtype=raw_dtype)

# True
print('raw binary and gunzipped are the same: {}'.format(
    np.array_equiv(from_gzipped, from_raw)))

# False
wrong_dtype = np.uint8
binary_as_wrong_dtype = np.fromfile(fname_raw, dtype=wrong_dtype)
print('wrong dtype and gunzipped are the same: {}'.format(
    np.array_equiv(from_gzipped, binary_as_wrong_dtype)))