In the process of Python Weibo crawling, proxy IP plays a vital role. It can help us break through many limitations and successfully obtain Weibo data. The following will introduce in detail the relevant skills of using proxy IP in Python Weibo crawling.
1. Setting proxy IP in Python
(I) Setting proxy IP using requests library
In Python's requests library, you can use proxy IP by setting the proxies parameter. For example, if we get an HTTP proxy IP of "123.45.67.89" and port of "8080", we can set it like this:
import requests
proxy = {
"http": "http://123.45.67.89:8080",
"https": "https://123.45.67.89:8080"
}
response = requests.get("https://weibo.com", proxies=proxy)
It should be noted here that if the proxy IP requires a username and password for verification, the username and password information must also be added to the proxy URL in the format of "http:// username: password @ proxy IP: port".
(II) Using proxy IP in Scrapy framework
If you use the Scrapy framework to crawl Weibo, it is also convenient to set the proxy IP. In Scrapy's settings.py file, you can set it as follows:
DOWNLOADER_MIDDLEWARES = {
'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware': 110,
'myproject.middlewares.ProxyMiddleware': 100,
}
PROXY_LIST = [
"http://123.45.67.89:8080",
"http://98.76.54.32:8888"
]
Then you need to create a middleware class called ProxyMiddleware, in which you can implement the logic of randomly selecting a proxy IP from PROXY_LIST and setting it to the request. The example is as follows:
import random
from scrapy.downloadermiddlewares.httpproxy import HttpProxyMiddleware
class ProxyMiddleware(HttpProxyMiddleware):
def __init__(self, proxy_list):
self.proxy_list = proxy_list
@classmethod
def from_crawler(cls, crawler):
return cls(
proxy_list=crawler.settings.get('PROXY_LIST')
)
def process_request(self, request, spider):
proxy = random.choice(self.proxy_list)
request.meta['proxy'] = proxy
With this setting, Scrapy will automatically use a randomly selected proxy IP when sending a request.
2. Management and maintenance of proxy IP
(I) Construction and update of IP pool
In order to ensure the continuous crawling of Weibo, it is very necessary to build a proxy IP pool. The obtained multiple proxy IPs can be stored in a list or other data structure to form an IP pool. During the crawling process, when a proxy IP fails (such as being blocked or the connection timed out), remove the IP from the IP pool and add a new available proxy IP in time. You can regularly obtain new IP resources from the proxy IP provider to update the IP pool, for example, every 1-2 hours, to ensure that there are enough available IPs in the IP pool.
(II) Error handling and IP switching
When using proxy IP to crawl Weibo data, it is inevitable to encounter various errors, such as connection rejection, timeout, etc. When these errors occur, it is necessary to perform reasonable error handling and switch the proxy IP in time. You can use the try-except block in the code to capture exceptions during the request process. When an exception is captured, mark the currently used proxy IP as unavailable, and select a new proxy IP from the IP pool to resend the request. For example:
while True:
try:
# Use the current proxy IP to send a Weibo crawling request
response = requests.get("https://weibo.com", proxies=proxy)
# If the request succeeds, process the response data
break
except requests.exceptions.RequestException as e:
# If the request fails, mark the current proxy IP as unavailable and switch the proxy IP
print(f"Request failed: {e}")
# Remove the current proxy IP from the IP pool
proxy_pool.remove(proxy)
# Select a new proxy IP
if proxy_pool:
proxy = random.choice(proxy_pool)
else:
print("IP pool exhausted, waiting for new IP to be added")
# Here you can add the logic of adding new IP, such as pausing for a period of time and then reacquiring new IP resources
time.sleep(3600)
Through the above application of various techniques on the selection, setting, management and maintenance of proxy IP, you can better utilize the proxy IP in the process of Python Weibo crawling To break through the limitations, improve the success rate and efficiency of crawling, so as to smoothly obtain the required Weibo data, and lay a solid foundation for subsequent data analysis, public opinion monitoring, etc. But at the same time, it should also be noted that when crawling Weibo, it is necessary to comply with relevant laws and regulations and the provisions of the Weibo platform, and carry out data crawling activities legally and compliantly.
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