NBA injury dataset acquisition: a hands-on guide to crawling sports data via proxies

For projects like NBA injury data crawling, if the request volume is very large and covers a wide range of teams and players, it is recommended to prioritize theDynamic Residential Proxy IP, because it effectively circumvents blocking. If only a few specific pages are targeted for low-frequency, long-term monitoring, theStatic Residential Proxy IPIt will be more economically stable.

Hands-on: crawling data with Python and the ipipgo proxy

Below we demonstrate how to crawl data through ipipgo's dynamic residential proxy using a simple Python example. Here we take the example of crawling hypothetical-example-nba-injuries.com, a hypothetical example website.

You need to registeripipgoservice and get the proxy information. Assuming you choose the Dynamic Residential (Standard) package, you will be given a proxy server address, port, username and password.

import requests
from bs4 import BeautifulSoup

 Your ipipgo proxy information (please replace with your own)
proxy_username = "your-ipipgo-username"
proxy_password = "your-ipipgo-password"
proxy_host = "gateway.ipipgo.com"
proxy_port = "10000"

 Build the proxy format
proxies = {
    'http': f'http://{proxy_username}:{proxy_password}@{proxy_host}:{proxy_port}',
    'https': f'http://{proxy_username}:{proxy_password}@{proxy_host}:{proxy_port}'
}

 Target URL (this is an example, please replace it with a real and allowed to crawl URL)
target_url = "http://hypothetical-example-nba-injuries.com/today"

 Set request headers to simulate browser access
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
}

try.
     Initiate the request and use the proxy with the proxies parameter
    response = requests.get(target_url, headers=headers, proxies=proxies, timeout=10)
    response.raise_for_status() check if the request was successful or not

     Parsing the content of the page
    soup = BeautifulSoup(response.text, 'html.parser')
     Here you need to locate the injury data based on the actual page structure
     For example, suppose the injury information is in a div with the class 'injury-list'.
    injury_list = soup.find('div', class_='injury-list')
    if injury_list.
        print("Successfully fetched injury data:")
        print(injury_list.get_text())
    print(injury_list.get_text())
        print("Injury data not found, may need to check page structure or selector.")

except requests.exceptions.RequestException as e:: print(f "Injury_list.get_text()")
    RequestException as e: print(f "Request error: {e}")

Code Key Points Explained:

1. Proxy Settings: Fill in your ipipgo account information into the proxy string so that all your requests are sent through ipipgo's proxy server.

2. Request header (User-Agent): This is an important step in reducing your chances of being recognized by anti-crawler systems by making your requests look more like they are coming from a regular browser.

3. error handling: Usetry... . exceptThe block catches possible exceptions to network requests, making the program more robust.

In practice, you'll need to replace the example URL with a real, crawl-permitted target URL, and adjust BeautifulSoup's parsing logic to the HTML structure of that site.

Crawling Strategies and Considerations

Even if you use a high-quality proxy IP, you need to follow good crawler etiquette, which not only protects the target site, but also makes your data collection efforts last longer.

1. Setting reasonable request delays: Dormant for a random period of time, say 1 to 3 seconds, between successive requests. This mimics human reading speed and avoids stressing the server.

import time
import random

 Insert a random delay into the loop request
time.sleep(random.uniform(1, 3))

2. Handling of CAPTCHAs: Sometimes CAPTCHA can be triggered even if a proxy is used. For small-scale crawling, this can be handled manually. If the scale is large, you may need to integrate a third-party CAPTCHA recognition service.

3. Compliance with robots.txt: Before crawling, check the robots.txt file of the target website (usually located in the root directory of the website, e.g.:www.example.com/robots.txt), understand the directories that the site allows and prohibits crawling.

4. Data storage: The crawled data is recommended to be stored immediately in a file (e.g., CSV, JSON) or a database to avoid loss due to unexpected program interruptions.

Why do you recommend ipipgo?

When crawling targets like NBA injury data that have anti-crawl measures in place, the quality of the proxy IP directly determines the success or failure of the project.ipipgoThe agency service has a clear advantage in this regard:

ipipgos Dynamic Residential Proxy IP resource is huge, covering more than 220 countries and regions around the world. This means that your requests can simulate real users from all over the world, greatly reducing the risk of centralized IP blocking. Its IPs are all from real home networks.Anonymity is extremely highThe target site has a hard time distinguishing them from the average user.

For data crawling projects, theipipgoIt supports per-traffic billing, how much you use is counted, and the cost is controllable. It supports rotating sessions and sticky sessions, and you can choose flexibly according to whether the crawler needs to maintain the login status. Whether it is high-frequency fast crawling or low-frequency long-term monitoring, you can find the right configuration.

Frequently Asked Questions QA

Q1: I'm just starting to learn about crawlers, is it ok to use free proxies?

A1:Not recommended. Free proxies are usually unstable, slow, insecure, and easily recognized and blocked by the target site. It may be okay to use it for learning tests once or twice, but for official projects like crawling NBA data, using free proxies is almost doomed to fail, and waste a lot of time instead.

Q2: How can I tell if my crawler is blocked by the site?

A2:Common signs include: continuously receiving HTTP error codes such as 403 (Access Forbidden), 429 (Too Many Requests), or 503 (Service Unavailable); returning page content that is not expected data but an anti-crawler warning message; or simply being unable to establish a connection. If any of these situations occur, you should pause the crawler, check your policies (e.g. latency settings, User-Agent), and consider changing the proxy IP.

Q3: How is the proxy IP speed of ipipgo? Will it affect the crawling efficiency?

A3:ipipgoWhat is provided is a high quality network channel with low latency and high speed. As long as you set a reasonable request latency (1-3 seconds as mentioned above), the speed impact from the proxy IP itself is minimal for data crawling. The bottleneck in crawling efficiency usually lies in how well you circumvent the anti-crawling strategy of the target website, not the speed of the proxy IP.

Q4: What else can ipipgo crawl besides NBA stats?

A4:The application scenarios are very wide. Almost all publicly available Internet data can be attempted to crawl, for example: product information and prices on e-commerce sites (e.g. Amazon, eBay), public posts in social media (e.g. Twitter, Reddit), search engine results, news site content, flight fare information, etc. The key is to comply with the rules of the website and use the right technical means.