Main content:
First, the principle of reptiles
two, Requests library request
First, the principle reptile
1. What is the Internet?
It refers to a stack of a network device, to the computer station to the Internet together with a called Internet.
2. The purpose of the establishment of the Internet?
The purpose is to establish the Internet transfer and data sharing data.
3. What is the data?
For example ... Taobao, Jingdong product information such as
number of securities investment information East Fortune, snowball network ...
the chain of home, such as availability of information freely ....
12306 ticket information ...
4. Internet whole process:
- Common User:
Open Browser -> sending a request to a target site -> the fetch response data -> renderer to the browser
- crawlers:
Analog Browser -> sending a request to a target site -> the fetch response data -> extract valuable data -> persisted to the data
5. What is the browser sends a request?
request http protocol.
- Client:
the browser is a software -> Client IP and port
- server
https://www.jd.com/
www.jd.com (Jingdong domain name) -> DNS parsing -> Jingdong server IP and port
Client ip and port ------> IP and port to send the request to the server can establish a link to obtain the corresponding data.
6. The crawler whole process
- the transmission request (request requires libraries: Requests database request, requesting the Selenium library)
- fetch response data (as long as the transmission request to the server, the request returns response data)
- parses and extracts data (requires parsing library : Re, BeautifulSoup4, Xpath ...)
- save to a local (file processing, database, MongoDB repository)
Two, Requests library request
1. Installation and Use
- open cmd
- Input: pip3 install requests
import requests # import request requests Library # Baidu home page to send a request to obtain the response object response = requests.get(url='https://www.baidu.com/') # Set the character encoding to utf-8 response.encoding = 'utf-8' # Print the response text print(response.text) # The text is written in response to local with open('baidu.html', 'w', encoding='utf-8') as f: f.write(response.text)
2. crawling video
Pear video crawling example:
'''''' ''' Video Options: 1. Pears video ''' # import requests # ## to the source address of the video transmission request # response = requests.get( # 'https://video.pearvideo.com/mp4/adshort/20190625/cont-1570302-14057031_adpkg-ad_hd.mp4') # # # Print binary stream, such as pictures, video and other data # print(response.content) # # # Save the video to your local # with open('视频.mp4', 'wb') as f: # f.write(response.content) ''' 1, first send a request to the pear Video Home https://www.pearvideo.com/ Id get resolved for all videos: video_1570302 re.findall() 2, access to video details page url: Thrilling! Man robbed on the subway slip, go on foot https://www.pearvideo.com/video_1570302 Secret Karez https://www.pearvideo.com/video_1570107 ''' import requests import re # regularization, for parsing text data # 1, first send a request to the pear Video Home response = requests.get('https://www.pearvideo.com/') # print(response.text) # Re regular matches to get all video id Parameter # 1: Regular matching rules Parameter # 2: parse text Parameter # 3: Match mode res_list = re.findall('<a href="video_(.*?)"', response.text, re.S) # print(res_list) # Stitching each video detail page url for v_id in res_list: detail_url = 'https://www.pearvideo.com/video_' + v_id # print(detail_url) # Sending a request to obtain the video source url for each video detail page response = requests.get(url=detail_url) # print(response.text) # Parse and extract details page video url # Video url video_url = re.findall('srcUrl="(.*?)"', response.text, re.S)[0] print(video_url) # Name video video_name = re.findall( '<h1 class="video-tt">(.*?)</h1>', response.text, re.S)[0] print(video_name) # Binary stream to acquire a video transmission request video url v_response = requests.get(video_url) with open('%s.mp4' % video_name, 'wb') as f: f.write(v_response.content) print (video_name, 'video crawling Complete')
3. packet capture analysis
Open developer mode browser (check) ----> select the network
to find pages visited suffix xxx.html (response text)
1) the request url (website address access)
2) request method:
GET:
direct sending a request to obtain data
https://www.cnblogs.com/kermitjam/articles/9692597.html
POST:
need to carry user information to the target address to send a request
https://www.cnblogs.com/login
3) response status codes:
2xx: Success
3xx: Redirection
4xx: Can not find resource
5xx: Server Error
4) request header information:
the User-Agent: User Agent (proved to be a request sent by computer equipment and browser)
Cookies: login user real information (to prove users of your target site)
Referer: a url to access the (prove you are Jump from the target sites on the web)
5) Request body:
POST request will have the request body.
The Data Form1
{
'User': 'Tank',
'pwd': '123'
}
4. crawling IMDb
. : Starting from the current position
* : Find all
? : Find the first not to look
. *? : Non-greedy matching
* : greedy match
(. *?): Extract data in brackets
'''''' ''' https://movie.douban.com/top250?start=0&filter= https://movie.douban.com/top250?start=25&filter= https://movie.douban.com/top250?start=50&filter= 1. The transmission request 2. Parse the data 3. Save data ''' import requests import re # Reptile three-part song # 1 sends a request def get_page(base_url): response = requests.get(base_url) return response # 2. parse text def parse_index(text): res = re.findall('<div class="item">.*?<em class="">(.*?)</em>.*?<a href="(.*?)">.*?<span class="title">(.*?)</span>.*?导演:(.*?)</p>.*?<span class="rating_num".*?>(.*?)</span>.*?<span>(.*?)人评价</span>.*?<span class="inq">(.*?)</span>', text, re.S) # print(res) return res # 3. Save data def save_data(data): with open('douban.txt', 'a', encoding='utf-8') as f: f.write(data) # Main + Enter key if __name__ == '__main__': # A = 10 # base_url = 'https://movie.douban.com/top250?start={}&filter='.format(num) a = 0 for line in range(10): base_url = f'https://movie.douban.com/top250?start={num}&filter=' a = + 25 print(base_url) # 1 sends a request, the calling function response = get_page(base_url) # 2. parse text movie_list = parse_index(response.text) # 3. Save data # Formatted data for movie in movie_list: # print(movie) # Decompression assignment Ranked # movie, movies url, film name, director - starring - the type of movie scores, number of reviews, film synopsis v_top, v_url, v_name, v_daoyan, v_point, v_num, v_desc = movie # v_top = movie[0] # v_url = movie[1] moive_content = f''' Movie Ranking: {v_top} Film url: {v_url} Movie Name: {v_name} Director Starring: {v_daoyan} Movie rating: {v_point} Number of Evaluation: {v_num} Movie Synopsis: {v_desc} \n ''' print(moive_content) # save data save_data(moive_content)
Movie rankings, movies url, film name, director - starring - the type of movie scores, number of reviews, film synopsis
.? <Div class = "item "> * <em class = ""> </ em> (*.?)
.?.? * <a href="(.*?)"> * <span class = "title"> </ span> (*.?)
* director:.? (.? *) </ p>. *? <span class = "rating_num." *?> (. *?) </ span>
. *? <span> (. *?) people commented </ span>. *? < span class = "inq"> (. *?) </ span >
<div class="item">
<div class="pic">
<em class="">226</em>
<a href="https://movie.douban.com/subject/1300374/">
<img width="100" alt="绿里奇迹" src="https://img3.doubanio.com/view/photo/s_ratio_poster/public/p767586451.webp" class="">
</a>
</div>
<div class="info">
<div class="hd">
<a href="https://movie.douban.com/subject/1300374/" class="">
<span class="title">绿里奇迹</span>
<span class="title"> / The Green Mile</span>
<span class="other"> / The Green Mile (units) / green mile </ span>
</a>
<span class = "playable"> [ play] </ span>
</ div>
<div class = "bd">
< "the p-class =">
Director: Frank Darabont & nbsp; & nbsp ; & nbsp; Starring: Tom Hanks Adams Tom Hanks / David Morse M ... <br> David
1999 & nbsp; / & nbsp; USA & nbsp; / & nbsp; crime Drama Fantasy Mystery
</ p>
<div class="star">
<span class="rating45-t"></span>
<span class="rating_num" property="v:average">8.7</span>
<span property="v:best" content="10.0"></span>
<span>141370人评价</span>
</div>
<P class = "quote">
<span class = "INQ"> Angel temporarily leave. </ span>
</ P>
</ div>
</ div>
</ div>