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How to scrape data from GitHub using rotation proxy
by jack
2024-02-02

In today's data-driven era, obtaining data is a key step for data analysis and mining. As the world's largest open source code hosting platform, GitHub has a large number of data resources that can provide us with valuable information.


However, due to GitHub's access restrictions, we may encounter IP restrictions, resulting in the inability to crawl data normally. At this time, using a rotating proxy becomes an essential tool. This article will introduce how to use rotation proxy to scrape data from GitHub


Why rotating proxies are good for scraping data


Rotating proxies have the following advantages in crawling data:


Improve stability: Using rotating proxies can spread requests and reduce the risk of a single proxy being accessed frequently. When an proxy is unavailable, it can automatically switch to the next proxy to ensure the continuity of the crawling task. 


By using multiple proxies, the request load can be evenly distributed, reducing the pressure on a single proxy and thus improving overall stability.


Improved speed: Using rotating proxies allows you to send requests in parallel, resulting in faster web crawling. By using multiple proxies at the same time, you can send multiple requests at the same time, reducing the time you wait for a response. This is very helpful for tasks that require crawling a large number of pages or are response time sensitive.


Support geographical location positioning: Use rotation proxy to simulate visits from different geographical locations to obtain data in specific areas. This is useful if you need to perform analysis based on geographic location or crawl information for a specific area. By using proxy servers with different geographical locations, data from all over the world can be easily obtained.


Multi-source data collection: By using rotation proxy, data can be collected from different data sources simultaneously. This is very helpful for the task of comparing and integrating multiple data sources. 


You can set up different proxies to crawl different websites, and then integrate and analyze the data to get more comprehensive and accurate results.


How to scrape data from GitHub using rotation proxy


First, we need to install a Python library called "requests". This library can help us send HTTP requests and obtain web content. Enter the following command on the command line to install:


```

pip install requests

```


Next, we need to prepare a proxy pool. The proxy pool is a collection of multiple proxy IPs from which we can randomly select an available IP to send requests. You can purchase a proxy IP or obtain it for free. Here we recommend a free proxy pool [https://github.com/jhao104/proxy_pool](https://github.com/jhao104/proxy_pool).


Then, we need to define a function to implement the function of rotating proxy. This function needs to receive a URL parameter, and an optional headers parameter. The code looks like this:


```

import requests


def get_page(url, headers=None):

# Get proxy IP

proxy = get_proxy()

# Construct request header

If headers:

response = requests.get(url, headers=headers, proxies={'http': proxy})

else:

response = requests.get(url, proxies={'http': proxy})

# If the request fails, re-obtain the proxy IP and resend the request

If response.status_code != 200:

proxy = get_proxy()

                          if headers:

           response = requests.get(url, headers=headers, proxies={'http': proxy})

          else:

            response = requests.get(url, proxies={'http': proxy})

# Return to web page content

Return response.text

```


In the above code, we use the "get_proxy()" function to obtain an available proxy IP. This function randomly selects an IP from the proxy pool and checks its availability. If the current IP cannot access the web page, a new IP will be obtained and the request will be sent again. This can avoid data capture failures caused by IP being blocked.


Finally, we can grab the data by calling the "get_page()" function. For example, if we want to get a list of files from a GitHub repository, we can use the following code:


```

url = 'https://github.com/username/repositoryname'

html = get_page(url)

print(html)

```


Through the above steps, we can use the rotation proxy to crawl data from GitHub. Of course, there are many other ways to implement rotation proxy, but here is just a simple example. 


It is worth noting that using a rotating proxy does not guarantee 100% success, because the quality and availability of the proxy IP will also affect the data crawling effect. Therefore, it is recommended to use multi-threading or asynchronous requests to improve efficiency when capturing large amounts of data.


In general, using a rotating proxy can effectively solve the problem of IP restrictions and allow us to smoothly obtain the data we want from GitHub. I hope this article can help readers who need to crawl GitHub data.



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