爬蟲3 request3高階 代理操作、模擬登入、單執行緒+多工非同步協程
- HttpConnectinPool:
- 原因:
- 1.短時間內發起了高頻的請求導致ip被禁
- 2.http連線池中的連線資源被耗盡
- 解決:
- 1.代理
- 2.headers中加入Conection:“close”
- 代理:代理伺服器,可以接受請求然後將其轉發。
- 匿名度
- 高匿:啥也不知道
- 匿名:知道你使用了代理,但是不知道你的真實ip
- 透明:知道你使用了代理並且知道你的真實ip
- 型別:
- http
- https
- 免費代理:
- www.goubanjia.com
- 西祠代理
- http://http.zhiliandaili.cn/ 智聯HTTP的代理精靈
- cookie的處理
代理的寫法示例:
import requests headers = { 'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/76.0.3809.132 Safari/537.36' } url = 'https://www.baidu.com/s?wd=ip' page_text1 = requests.get(url,headers=headers,proxies={'https':'183.166.171.51:8888'}).text with open('ip.html','w',encoding='utf-8') as fp: fp.write(page_text1)
一個代理很容易被封,這時候我們要構造一個代理池
#代理池:列表 import random proxy_list = [ {'https':'121.231.94.44:8888'}, {'https':'131.231.94.44:8888'}, {'https':'141.231.94.44:8888'} ] url = 'https://www.baidu.com/s?wd=ip' page_text = requests.get(url,headers=headers,proxies=random.choice(proxy_list)).text with open('ip.html','w',encoding='utf-8') as fp: fp.write(page_text)
如何構造代理池呢?其中一個方法如下
from lxml import etree ip_url = 'http://t.11jsq.com/index.php/api/entry?method=proxyServer.generate_api_url&packid=1&fa=0&fetch_key=&groupid=0&qty=4&time=1&pro=&city=&port=1&format=html&ss=5&css=&dt=1&specialTxt=3&specialJson=&usertype=2' page_text = requests.get(ip_url,headers=headers).text tree = etree.HTML(page_text) ip_list = tree.xpath('//body//text()') print(ip_list)#從代理精靈中提取代理ip
然後
import random headers = { 'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/76.0.3809.132 Safari/537.36', 'Connection':"close" } url = 'https://www.xicidaili.com/nn/%d' proxy_list_http = [] proxy_list_https = [] for page in range(1,20): new_url = format(url%page) ip_port = random.choice(ip_list) page_text = requests.get(new_url,headers=headers,proxies={'https':ip_port}).text tree = etree.HTML(page_text) #tbody不可以出現在xpath表示式中 tr_list = tree.xpath('//*[@id="ip_list"]//tr')[1:] for tr in tr_list: ip = tr.xpath('./td[2]/text()')[0] port = tr.xpath('./td[3]/text()')[0] t_type = tr.xpath('./td[6]/text()')[0] ips = ip+':'+port if t_type == 'HTTP': dic = { t_type: ips } proxy_list_http.append(dic) else: dic = { t_type:ips } proxy_list_https.append(dic) print(len(proxy_list_http),len(proxy_list_https))#爬取西祠代理
#檢測 for ip in proxy_list_http: response = requests.get('https://www/sogou.com',headers=headers,proxies={'https':ip}) if response.status_code == '200': print('檢測到了可用ip')
模擬登入!!!
cookie的處理
- 手動處理:將cookie封裝到headers中
- 自動處理:session物件。可以建立一個session物件,改物件可以像requests一樣進行請求傳送。不同之處在於如果在使用session進行請求傳送的過程中產生了cookie,則cookie會被自動儲存在session物件中。
手動加上cookie:
#對雪球網中的新聞資料進行爬取https://xueqiu.com/ headers = { 'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/76.0.3809.132 Safari/537.36', # 'Cookie':'aliyungf_tc=AQAAAAl2aA+kKgkAtxdwe3JmsY226Y+n; acw_tc=2760822915681668126047128e605abf3a5518432dc7f074b2c9cb26d0aa94; xq_a_token=75661393f1556aa7f900df4dc91059df49b83145; xq_r_token=29fe5e93ec0b24974bdd382ffb61d026d8350d7d; u=121568166816578; device_id=24700f9f1986800ab4fcc880530dd0ed' } url = 'https://xueqiu.com/v4/statuses/public_timeline_by_category.json?since_id=-1&max_id=20349203&count=15&category=-1' page_text = requests.get(url=url,headers=headers).json() page_text
自動新增cookie:
#建立session物件 session = requests.Session() session.get('https://xueqiu.com',headers=headers) url = 'https://xueqiu.com/v4/statuses/public_timeline_by_category.json?since_id=-1&max_id=20349203&count=15&category=-1' page_text = session.get(url=url,headers=headers).json() page_text
- 驗證碼的識別
- 超級鷹:
- 註冊:(使用者中心身份)
- 登陸:
- 建立一個軟體:899370
- 下載示例程式碼
- 打碼兔
- 雲打碼
超級鷹示例
import requests from hashlib import md5 class Chaojiying_Client(object): def __init__(self, username, password, soft_id): self.username = username password = password.encode('utf8') self.password = md5(password).hexdigest() self.soft_id = soft_id self.base_params = { 'user': self.username, 'pass2': self.password, 'softid': self.soft_id, } self.headers = { 'Connection': 'Keep-Alive', 'User-Agent': 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 5.1; Trident/4.0)', } def PostPic(self, im, codetype): """ im: 圖片位元組 codetype: 題目型別 參考 http://www.chaojiying.com/price.html """ params = { 'codetype': codetype, } params.update(self.base_params) files = {'userfile': ('ccc.jpg', im)} r = requests.post('http://upload.chaojiying.net/Upload/Processing.php', data=params, files=files, headers=self.headers) return r.json() def ReportError(self, im_id): """ im_id:報錯題目的圖片ID """ params = { 'id': im_id, } params.update(self.base_params) r = requests.post('http://upload.chaojiying.net/Upload/ReportError.php', data=params, headers=self.headers) return r.json() #識別古詩文網中的驗證碼 def tranformImgData(imgPath,t_type): chaojiying = Chaojiying_Client('bobo328410948', 'bobo328410948', '899370') im = open(imgPath, 'rb').read() return chaojiying.PostPic(im, t_type)['pic_str'] url = 'https://so.gushiwen.org/user/login.aspx?from=http://so.gushiwen.org/user/collect.aspx' page_text = requests.get(url,headers=headers).text tree = etree.HTML(page_text) img_src = 'https://so.gushiwen.org'+tree.xpath('//*[@id="imgCode"]/@src')[0] img_data = requests.get(img_src,headers=headers).content with open('./code.jpg','wb') as fp: fp.write(img_data) tranformImgData('./code.jpg',1004)超級鷹
然後就可以輕鬆登入古詩文 網站啦!(注意驗證碼的重新整理的機制和動態變化的請求引數)
- 動態變化的請求引數
- 通常情況下動態變化的請求引數都會被隱藏在前臺頁面原始碼中
(這裡直接在頁面搜__VIEWSTATE值,然後抓下來用它)
(用session 傳送請求,保持驗證碼的一致性!)
s = requests.Session() url = 'https://so.gushiwen.org/user/login.aspx?from=http://so.gushiwen.org/user/collect.aspx' page_text = s.get(url,headers=headers).text tree = etree.HTML(page_text) img_src = 'https://so.gushiwen.org'+tree.xpath('//*[@id="imgCode"]/@src')[0] img_data = s.get(img_src,headers=headers).content with open('./code.jpg','wb') as fp: fp.write(img_data) #動態獲取變化的請求引數 __VIEWSTATE = tree.xpath('//*[@id="__VIEWSTATE"]/@value')[0] __VIEWSTATEGENERATOR = tree.xpath('//*[@id="__VIEWSTATEGENERATOR"]/@value')[0] code_text = tranformImgData('./code.jpg',1004) print(code_text) login_url = 'https://so.gushiwen.org/user/login.aspx?from=http%3a%2f%2fso.gushiwen.org%2fuser%2fcollect.aspx' data = { '__VIEWSTATE': __VIEWSTATE, '__VIEWSTATEGENERATOR': __VIEWSTATEGENERATOR, 'from':'http://so.gushiwen.org/user/collect.aspx', 'email': '[email protected]', 'pwd': 'bobo328410948', 'code': code_text, 'denglu': '登入', } page_text = s.post(url=login_url,headers=headers,data=data).text with open('login.html','w',encoding='utf-8') as fp: fp.write(page_text)
# 普通單執行緒 和執行緒池的速度對比
from time import sleep
import time
from multiprocessing.dummy import Pool
start = time.time()
urls = [
'http://www.baidu.com',
'http://www.sougou.com',
'http://www.qq.com',
'https://www.iqiyi.com/'
]
def get_request(url):
print('正在下載',url)
time.sleep(2)
print('OK了',url)
# pool = Pool(3)
# pool.map(get_request,urls)
for url in urls:
get_request(url)
print('總耗時:',time.time()-start)
單執行緒+多工非同步協程
- 協程
- 在函式(特殊的函式)定義的時候,如果使用了async修飾的話,則改函式呼叫後會返回一個協程物件,並且函式內部的實現語句不會被立即執行
- 任務物件
- 任務物件就是對協程物件的進一步封裝。任務物件==高階的協程物件==特殊的函式
- 任務物件時必須要註冊到事件迴圈物件中
- 給任務物件繫結回撥:爬蟲的資料解析中
- 事件迴圈
- 當做是一個容器,容器中必須存放任務物件。
- 當啟動事件迴圈物件後,則事件迴圈物件會對其內部儲存任務物件進行非同步的執行。
- aiohttp:支援非同步網路請求的模組
模板如下 import asyncio def callback(task): #作為任務物件的回撥函式 print('i am callback and ',task.result()) # task.result()就是非同步函式的返回值 async def test(): print('i am test()') return 'bobo' c = test() #封裝了一個任務物件 task = asyncio.ensure_future(c) task.add_done_callback(callback) # 繫結回撥 #建立一個事件迴圈的物件 loop = asyncio.get_event_loop() loop.run_until_complete(task)
非同步 I/O
asyncio 是用來編寫併發程式碼的庫,使用async/await語法。
asyncio 被用作多個提供高效能 Python 非同步框架的基礎,包括網路和網站服務,資料庫連線庫,分散式任務佇列等等。
asyncio 往往是構建 IO 密集型和高層級結構化網路程式碼的最佳選擇。
import asyncio import time start = time.time() #在特殊函式內部的實現中不可以出現不支援非同步的模組程式碼 async def get_request(url): await asyncio.sleep(2) print('下載成功:',url) urls = [ 'www.1.com', 'www.2.com' ] tasks = [] for url in urls: c = get_request(url) task = asyncio.ensure_future(c) tasks.append(task) loop = asyncio.get_event_loop() #注意:掛起操作需要手動處理 loop.run_until_complete(asyncio.wait(tasks)) print(time.time()-start)
爬蟲應用:
import requests import aiohttp import time import asyncio s = time.time() urls = [ 'http://127.0.0.1:5000/bobo', 'http://127.0.0.1:5000/jay' ] # async def get_request(url): # page_text = requests.get(url).text # return page_text async def get_request(url): async with aiohttp.ClientSession() as s: #這邊不能用不支援非同步的requests async with await s.get(url=url) as response: page_text = await response.text() print(page_text) return page_text tasks = [] for url in urls: c = get_request(url) task = asyncio.ensure_future(c) tasks.append(task) loop = asyncio.get_event_loop() loop.run_until_complete(asyncio.wait(tasks)) print(time.time()-s)
multiprocessing包是Python中的多程序管理包。
1、示例:
爬蟲指令碼:
from time import sleep import time from multiprocessing.dummy import Pool start = time.time() urls = [ 'http://127.0.0.1:5000/bobo', 'http://127.0.0.1:5000/jay' ] def get_request(url): page_text = requests.get(url).text print(page_text) pool = Pool(3) pool.map(get_request,urls) print('總耗時:',time.time()-start)
示例伺服器:
from flask import Flask from time import sleep app = Flask(__name__) @app.route('/index') def index(): sleep(2) return 'hello' @app.route('/index1') def index1(): sleep(2) return 'hello1' if __name__ == '__main__': app.run()