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講師的博客:https://www.cnblogs.com/wupeiqi/p/6229292.html
在編寫爬蟲時,性能的消耗主要在IO請求中,當單進程單線程模式下請求URL時必然會引起等待,從而使得請求整體變慢。
比如找10個國外的資源爬取,慢的效果就很明顯。
直接用一個for循環,把所有的請求串起來一次執行。這樣的效率會很低:
import requests
from bs4 import BeautifulSoup
url_list = [
'https://github.com/explore',
'https://www.djangoproject.com/',
'http://www.python-requests.org/en/master/',
'https://jquery.com/',
'https://getbootstrap.com/',
'https://www.solarwinds.com/',
'https://www.zabbix.com/',
'http://open-falcon.org/',
'https://www.python.org/',
'http://www.jetbrains.com/',
]
if __name__ == '__main__':
for url in url_list:
r = requests.get(url)
r.encoding = 'utf-8'
soup = BeautifulSoup(r.text, features='html.parser')
title = soup.find('title')
print(title)
下面是使用線程池(進程池)實現的方式。這里多進程和多線程的效果一樣,但是線程更省資源。
import requests
from bs4 import BeautifulSoup
from concurrent.futures import ThreadPoolExecutor
# from concurrent.futures import ProcessPoolExecutor # 進程池
url_list = [
'https://github.com/explore',
# 省略多個url
'http://www.jetbrains.com/',
]
def fetch_request(url):
r = requests.get(url)
r.encoding = 'utf-8'
soup = BeautifulSoup(r.text, features='html.parser')
title = soup.find('title')
print(title)
if __name__ == '__main__':
pool = ThreadPoolExecutor(10)
# pool = ProcessPoolExecutor(10) # 進程池
for url in url_list:
pool.submit(fetch_request, url)
pool.shutdown(True)
上面的例子用到的模塊,還支持使用回調函數,把代碼稍稍改一下:
import requests
from bs4 import BeautifulSoup
from concurrent.futures import ProcessPoolExecutor
url_list = [
'https://github.com/explore',
# 省略多個url
'http://www.jetbrains.com/',
]
def fetch_request(url):
response = requests.get(url)
response.encoding = 'utf-8'
soup = BeautifulSoup(response.text, features='html.parser')
title = soup.find('title')
return str(title) # 這里返回的,就是下面回調函數的入參。不轉str會報錯
def callback(result):
print(result.result())
if __name__ == '__main__':
pool = ProcessPoolExecutor(10)
for url in url_list:
v = pool.submit(fetch_request, url)
v.add_done_callback(callback)
pool.shutdown(True)
多進程和多線程的回調函數用法也是一樣的。
這里簡單的需求,是不需要用到回調函數。不過作為線程池的一個用法,多一個示例。
多線程和多進程的缺點是在IO阻塞時會造成了線程和進程的浪費,所以異步IO是更好的方式。
異步IO請求的本質則是非阻塞Socket + IO多路復用。這里只需要一個線程,而每一個請求則是一個協程。
下面就是各種Python內置以及第三方提供的異步IO請求模塊。這些模塊,使用簡便,大大提高效率。
這個是內置模塊
先看下模塊是怎么調用的。這里是python3.4版本的用法,到3.5版本有新的 async/await 關鍵字可以用。不過向下兼容,舊的裝飾器的 asyncio/yield from 的用法還是可以使用的。
用法示例:
import asyncio
@asyncio.coroutine
def func(n):
print('before func %s...' % n)
yield from asyncio.sleep(3)
print('end func %s...' % n)
if __name__ == '__main__':
tasks = []
for i in range(5):
tasks.append(func(i))
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.gather(*tasks))
loop.close()
這里注意一下裝飾器和被它裝飾的函數。在tasks.append()里,添加的是函數的調用,添加的是func()而不是func,帶括號的。所以一般情況下是要執行這個函數。當然這里給函數加了裝飾器,就不會直接執行了,而是等到下面在執行的。
通過TCP發送HTTP請求
asyncio模塊只提供了發送tcp的功能,無法直接發送http請求。不過在理解了Web服務的本質的基礎上,http本質上還是tcp。http請求還是通過tcp發送字符串,只是字符串有特定的格式。字符串分為請求頭和請求體,請求頭和請求體之間使用 "/r/n/r/n" 分隔,而請求頭和請求頭之間使用 "/r/n" 分隔。下面就是一個基本的GET請求的格式:
"""
GET /index HTTP/1.0\r\n
HOST: 1.1.1.1
\r\n\r\n
"""
所以只要按上面的方式對字符串進行封裝,然后通過tcp發送,這就是http了。下面這個就是用 asyncio 手動封裝http報頭的示例:
import asyncio
from bs4 import BeautifulSoup
url_list = [
('www.python-requests.org', '/en/master/'),
('open-falcon.org', '/'),
('www.jetbrains.com', '/'),
('www.nga.cn', '/'),
('edu.51cto.com', '/'),
]
@asyncio.coroutine
def fetch_async(host, url):
reader, writer = yield from asyncio.open_connection(host, 80) # 建立tcp連接
request_header_content = "GET %s HTTP/1.0\r\nHost: %s\r\n\r\n" % (url, host) # 這個是GET請求
request_header_content = request_header_content.encode('utf-8') # 最終發送的是bytes類型
writer.write(request_header_content) # 發出請求
yield from writer.drain()
text = yield from reader.read() # 接收到的當然也是bytes類型
text = text.decode('utf-8')
soup = BeautifulSoup(text, features='html.parser')
title = soup.find('title')
print(title)
writer.close()
if __name__ == '__main__':
tasks = []
for host, url in url_list:
tasks.append(fetch_async(host, url))
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.gather(*tasks))
loop.close()
通過TCP發送HTTPS
上面這樣只能發http請求。https主要是2個差別,默認的端口號是443,還有就是需要ssl。好在 asyncio.open_connection
是提供支持ssl的,只需要加上ssl=True的參數(這個參數的默認是False,所以上面不用指定)。下面是支持https的版本:
import asyncio
from bs4 import BeautifulSoup
url_list = [
'https://github.com/explore',
# 省略多個url
'http://www.jetbrains.com/',
]
@asyncio.coroutine
def fetch_async(host, url='/', port=80, ssl=False):
reader, writer = yield from asyncio.open_connection(host, port, ssl=ssl) # 建立tcp連接
request_header_content = "GET %s HTTP/1.0\r\nHost: %s\r\n\r\n" % (url, host) # 這個是GET請求
request_header_content = request_header_content.encode('utf-8') # 最終發送的是bytes類型
writer.write(request_header_content) # 發出請求
yield from writer.drain()
text = yield from reader.read() # 接收到的當然也是bytes類型
text = text.decode('utf-8')
soup = BeautifulSoup(text, features='html.parser')
title = soup.find('title')
print(title)
writer.close()
if __name__ == '__main__':
from urllib.parse import urlparse
tasks = []
for url in url_list:
url_parse = urlparse(url)
if url_parse.scheme == "https":
tasks.append(fetch_async(url_parse.netloc, url_parse.path, 443, True))
else:
tasks.append(fetch_async(url_parse.netloc, url_parse.path))
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.gather(*tasks))
loop.close()
講師博客里的代碼是版本的問題,運行不了會報錯。因為從 python3.5 開始,引入了 async/await 。大概記錄一下原因:
在Python3.5以后,原生協程不能用于迭代,未被裝飾的生成器不能yield from一個原生協程
什么是原生協程?用async關鍵字定義的就是原生線程。asyncio是Python 3.4版本引入的標準庫,是用裝飾器的方式來定義協程的(上面的例子就是)。到了python3.5版本,引入了async關鍵字來定義協程,并且向下兼容,之前的裝飾器的方法也能用。
再來看一下aiohttp模塊。粗略的看一下源碼,舊版本(2.x及之前),用的是 asyncio/yield from 。3.x版本開始,都改用 async/await 了。舊版的 yield from 是不能調用新版的用async關鍵字定義的原生協程的,所以會報錯。
之前的例子用的是 asyncio/yield from ,但是這里的 aishttp 用的是 async/await ,所以無法再用 yield from 了。下面是用 async/await 的例子:
import aiohttp
import asyncio
from bs4 import BeautifulSoup
url_list = [
'https://github.com/explore',
# 省略多個url
'http://www.jetbrains.com/',
]
async def fetch_async(url):
async with aiohttp.request('GET', url) as r:
text = await r.text('utf-8')
soup = BeautifulSoup(text, features='html.parser')
title = soup.find('title')
print(title)
if __name__ == '__main__':
tasks = []
for url in url_list:
tasks.append(fetch_async(url))
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.gather(*tasks))
loop.close()
后面的例子還會繼續用到 asyncio/yield from ,而且這個例子也不好找。
不過 async/await 才是推薦的用法,好在改一下也不難,而且網上例子也多。
import asyncio
import requests
from bs4 import BeautifulSoup
url_list = [
'https://github.com/explore',
# 省略多個url
'http://www.jetbrains.com/',
]
@asyncio.coroutine
def fetch_async(func, *args):
loop = asyncio.get_event_loop()
future = loop.run_in_executor(None, func, *args)
response = yield from future
response.encoding = 'utf-8'
soup = BeautifulSoup(response.text, features='html.parser')
title = soup.find('title')
print(title)
if __name__ == '__main__':
tasks = []
for url in url_list:
tasks.append(fetch_async(requests.get, url))
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.gather(*tasks))
loop.close()
from bs4 import BeautifulSoup
import gevent
from gevent import monkey
monkey.patch_all() # 必須放在requests模塊導入前
import requests
url_list = [
'https://github.com/explore',
# 省略多個url
'http://www.jetbrains.com/',
]
def fetch_request(url):
r = requests.get(url)
r.encoding = 'utf-8'
soup = BeautifulSoup(r.text, features='html.parser')
title = soup.find('title')
print(title)
if __name__ == '__main__':
g_list = []
for url in url_list:
g_list.append(gevent.spawn(fetch_request, url=url))
gevent.joinall(g_list)
grequests 模塊,就是 gevent + requests 。有人用代碼又把這兩個模塊再封裝了一層。就寫個例子:
import grequests
from bs4 import BeautifulSoup
url_list = [
'https://github.com/explore',
# 省略多個url
'http://www.jetbrains.com/',
]
def exception_handler(request, exception):
print(request, exception)
print("Request failed")
def callback(r, *args, **kwargs):
r.encoding = 'utf-8'
soup = BeautifulSoup(r.text, features='html.parser')
title = soup.find('title')
print(title)
if __name__ == '__main__':
request_list = [grequests.get(url, timeout=10, callback=callback) for url in url_list]
response_list = grequests.map(request_list, exception_handler=exception_handler, gtimeout=10)
print(response_list)
之前用for循環寫列表太Low了,這里用列表生成式的寫法。grequests.get里的timeout是單個任務的超時時間,grequests.map里的gtimeout則是整體任務的超時時間。
exception_handler方法是請求有異常時的處理方法。如果單個任務超時,就會拋出異常,如果任務整體超時,則還沒有結束的任務返回None,沒有異常。
直接安裝模塊會報錯,去官網翻了一下 http://twistedmatrix.com 。找到了pip的安裝方法
The recommended way is to run pip install Twisted, preferably inside a virtualenv.
On Linux, and BSDs, you will need a C compiler (such as GCC).
On macOS you will need to run xcode-select --install.
If you are installing on Windows, pip install Twisted[windows_platform] will install the Windows-specific requirements.
所以應該用下面的命令,安裝windwos用的版本:
pip install -i https://mirrors.163.com/pypi/simple Twisted[windows_platform]
但是還是不行,錯誤信息如下:
error: Microsoft Visual C++ 14.0 is required. Get it with "Microsoft Visual C++ Build Tools": http://landinghub.visualstudio.com/visual-cpp-build-tools
Twisted 模塊安裝
最終在網上找到解決方法,就是本地安裝。先去下載這個模塊對應版本的whl文件:
https://www.lfd.uci.edu/~gohlke/pythonlibs/#twisted
然后用 pip 執行本地安裝:
pip install E:/Downloads/Twisted-18.9.0-cp36-cp36m-win_amd64.whl
發GET請求
from bs4 import BeautifulSoup
from twisted.web.client import getPage, defer
from twisted.internet import reactor
url_list = [
'https://github.com/explore',
# 略多個url
'http://www.jetbrains.com/',
]
def all_done(arg):
reactor.stop()
def callback(contents):
soup = BeautifulSoup(contents, features='html.parser')
title = soup.find('title')
print(title)
if __name__ == '__main__':
deferred_list = []
for url in url_list:
deferred = getPage(url.encode('utf-8')) # 發請求
deferred.addCallback(callback) # 請求返回后的回調函數
deferred_list.append(deferred) # 把所有的請求加到列表里,后面要檢測
dlist = defer.DeferredList(deferred_list) # 檢測所有的請求
dlist.addBoth(all_done) # 檢測到所有請求都執行完,執行的方法
reactor.run() # 開啟一個死循環,不停的執行,all_done函數里的stop()方法會停止這個循環
發POST請求
from twisted.internet import reactor
from twisted.web.client import getPage
import urllib.parse
def one_done(arg):
print(arg)
print(arg.decode())
reactor.stop()
post_data = urllib.parse.urlencode({'check_data': 'TEST'})
post_data = post_data.encode('utf-8')
headers = {b'Content-Type': b'application/x-www-form-urlencoded'}
response = getPage(b'http://dig.chouti.com/login',
method=b'POST',
postdata=post_data,
cookies={},
headers=headers)
response.addBoth(one_done)
reactor.run()
這里只有個例子,之后可能還要再學一下:
from bs4 import BeautifulSoup
from tornado.httpclient import AsyncHTTPClient
from tornado.httpclient import HTTPRequest
from tornado import ioloop
url_list = [
'https://github.com/explore',
'https://www.djangoproject.com/',
'http://www.python-requests.org/en/master/',
'https://jquery.com/',
'https://getbootstrap.com/',
'https://www.solarwinds.com/',
'https://www.zabbix.com/',
'http://open-falcon.org/',
'https://www.python.org/',
'http://www.jetbrains.com/',
]
def asynchronous_fetch():
http_client = AsyncHTTPClient()
# 創建一個函數內的函數,來處理返回的結果
def handle_response(response):
"""
處理返回值內容(需要維護計數器,來停止IO循環),調用 ioloop.IOLoop.current().stop()
:param response:
:return:
"""
if response.error:
print("Error:", response.error)
else:
# print(response.headers)
# print(response.body)
soup = BeautifulSoup(response.body, features='html.parser')
title = soup.find('title')
print(title)
# 自己加的停止的方法,實現方法可能不是很正規
# print(response.effective_url)
curr_url = response.effective_url
if curr_url in url_list:
url_list.remove(curr_url)
if not url_list:
ioloop.IOLoop.current().stop()
for url in url_list:
# 異步處理結束后會調用指定的callback的函數
http_client.fetch(HTTPRequest(url), callback=handle_response)
# 下面這句和上面效果一樣,模塊內部會判斷參數的isinstance是否是HTTPRequest
# 如果不是則,HTTPRequest(url, **kwargs)
# 這里的**kwargs,就是如果要給請求加任何參數,就用關鍵參數傳參
# http_client.fetch(url, callback=handle_response)
if __name__ == '__main__':
ioloop.IOLoop.current().add_callback(asynchronous_fetch)
ioloop.IOLoop.current().start()
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