我同样需要使用请求下载图像。我首先尝试了Martijn Pieters的答案，效果很好。但是当我对这个简单的函数做了一个概要时，我发现与urllib和urllib2相比，它使用了太多的函数调用。

然后我尝试了请求模块作者推荐的方法:

import requests
from PIL import Image
# python2.x, use this instead  
# from StringIO import StringIO
# for python3.x,
from io import StringIO

r = requests.get('https://example.com/image.jpg')
i = Image.open(StringIO(r.content))

这大大减少了函数调用的数量，从而加快了我的应用程序的速度。 下面是我的分析器的代码和结果。

#!/usr/bin/python
import requests
from StringIO import StringIO
from PIL import Image
import profile

def testRequest():
    image_name = 'test1.jpg'
    url = 'http://example.com/image.jpg'

    r = requests.get(url, stream=True)
    with open(image_name, 'wb') as f:
        for chunk in r.iter_content():
            f.write(chunk)

def testRequest2():
    image_name = 'test2.jpg'
    url = 'http://example.com/image.jpg'

    r = requests.get(url)
    
    i = Image.open(StringIO(r.content))
    i.save(image_name)

if __name__ == '__main__':
    profile.run('testUrllib()')
    profile.run('testUrllib2()')
    profile.run('testRequest()')

testRequest的结果:

343080 function calls (343068 primitive calls) in 2.580 seconds

和testRequest2的结果:

3129 function calls (3105 primitive calls) in 0.024 seconds

你可以使用响应。原始文件对象，或遍历响应。

使用响应。默认情况下，raw类文件对象不会解码压缩后的响应(使用GZIP或deflate)。您可以通过将decode_content属性设置为True(请求将其设置为False以控制解码本身)来强制它为您解压缩。然后，您可以使用shutil.copyfileobj()让Python将数据流传输到文件对象:

import requests
import shutil

r = requests.get(settings.STATICMAP_URL.format(**data), stream=True)
if r.status_code == 200:
    with open(path, 'wb') as f:
        r.raw.decode_content = True
        shutil.copyfileobj(r.raw, f)        

要遍历响应，请使用循环;这样的迭代确保数据在此阶段解压缩:

r = requests.get(settings.STATICMAP_URL.format(**data), stream=True)
if r.status_code == 200:
    with open(path, 'wb') as f:
        for chunk in r:
            f.write(chunk)

这将读取128字节的数据块;如果你觉得另一个块大小更好，使用Response.iter_content()方法自定义块大小:

r = requests.get(settings.STATICMAP_URL.format(**data), stream=True)
if r.status_code == 200:
    with open(path, 'wb') as f:
        for chunk in r.iter_content(1024):
            f.write(chunk)

注意，您需要以二进制模式打开目标文件，以确保python不会尝试为您翻译换行符。我们还设置stream=True，这样请求就不会先把整个图像下载到内存中。

从请求中获取一个类似文件的对象，并将其复制到文件中。这也将避免将整个内容一次性读入内存。

import shutil

import requests

url = 'http://example.com/img.png'
response = requests.get(url, stream=True)
with open('img.png', 'wb') as out_file:
    shutil.copyfileobj(response.raw, out_file)
del response

你可以这样做:

import requests
import random

url = "https://images.pexels.com/photos/1308881/pexels-photo-1308881.jpeg? auto=compress&cs=tinysrgb&dpr=1&w=500"
name=random.randrange(1,1000)
filename=str(name)+".jpg"
response = requests.get(url)
if response.status_code.ok:
   with open(filename,'w') as f:
    f.write(response.content)

我同样需要使用请求下载图像。我首先尝试了Martijn Pieters的答案，效果很好。但是当我对这个简单的函数做了一个概要时，我发现与urllib和urllib2相比，它使用了太多的函数调用。

然后我尝试了请求模块作者推荐的方法:

import requests
from PIL import Image
# python2.x, use this instead  
# from StringIO import StringIO
# for python3.x,
from io import StringIO

r = requests.get('https://example.com/image.jpg')
i = Image.open(StringIO(r.content))

这大大减少了函数调用的数量，从而加快了我的应用程序的速度。 下面是我的分析器的代码和结果。

#!/usr/bin/python
import requests
from StringIO import StringIO
from PIL import Image
import profile

def testRequest():
    image_name = 'test1.jpg'
    url = 'http://example.com/image.jpg'

    r = requests.get(url, stream=True)
    with open(image_name, 'wb') as f:
        for chunk in r.iter_content():
            f.write(chunk)

def testRequest2():
    image_name = 'test2.jpg'
    url = 'http://example.com/image.jpg'

    r = requests.get(url)
    
    i = Image.open(StringIO(r.content))
    i.save(image_name)

if __name__ == '__main__':
    profile.run('testUrllib()')
    profile.run('testUrllib2()')
    profile.run('testRequest()')

testRequest的结果:

343080 function calls (343068 primitive calls) in 2.580 seconds

和testRequest2的结果:

3129 function calls (3105 primitive calls) in 0.024 seconds

主要有两种方式:

Using .content (simplest/official) (see Zhenyi Zhang's answer): import io # Note: io.BytesIO is StringIO.StringIO on Python2. import requests r = requests.get('http://lorempixel.com/400/200') r.raise_for_status() with io.BytesIO(r.content) as f: with Image.open(f) as img: img.show() Using .raw (see Martijn Pieters's answer): import requests r = requests.get('http://lorempixel.com/400/200', stream=True) r.raise_for_status() r.raw.decode_content = True # Required to decompress gzip/deflate compressed responses. with PIL.Image.open(r.raw) as img: img.show() r.close() # Safety when stream=True ensure the connection is released.

计时两者无明显差异。