Quickstart

Get your first Bet365 scraper running in minutes with this step-by-step guide

This quickstart guide will walk you through setting up the Bet365 Scraper SDK and running your first successful data extraction in under 5 minutes.

Prerequisites

• Python 3.8 or higher installed
• API key for the X-Net header generation service
• Basic terminal/command line knowledge

If you don’t have an API key yet, contact the developer via Discord to request access.

Getting Started

1. Install Dependencies

   First, install the required Python packages:

   pip3 install -r requirements.txt
   

   This installs three core dependencies:

   • curl_cffi: Low-level HTTP client with TLS fingerprinting support
   • tls_client: Additional TLS client for API communication
   • prettytable: Table formatting for displaying scraped data
2. Configure API Credentials

   Create or edit the config.json file in your project root:

   {
     "api_url": "https://vercel-android-server-three.vercel.app/get_x_net_android",
     "api_key": "your_api_key_here",
     "proxy": "",
     "email": "",
     "password": ""
   }
   

   Required Configuration:

   • api_url: The endpoint for X-Net header generation (provided by the service)
   • api_key: Your authentication key for the API service

   Optional Configuration:

   • proxy: Add a proxy URL (format: http://user:pass@host:port) for enhanced reliability
   • email and password: Reserved for future authentication features
3. Initialize the Session

   Create a new Python file or use the provided main.py:

   import json
   from bet365 import Bet365AndroidSession
   
   # Load configuration
   with open("config.json", encoding="utf8") as fp:
       config = json.load(fp)
   
   # Initialize the session
   session = Bet365AndroidSession(
       config["api_url"],
       config["api_key"],
       proxy=config["proxy"] or None,
       verify=False,
       host="www.bet365.com",
   )
   

   The Bet365AndroidSession handles:

   • TLS fingerprinting to match Android devices
   • Cookie management and device ID generation
   • Anti-bot protection headers
4. Navigate to Homepage

   Establish a session by visiting the Bet365 homepage:

   print("Going to homepage...")
   session.go_homepage()
   

   This critical step:

   • Establishes cookies and session tokens
   • Extracts the SST (Session State Token) for subsequent requests
   • Initializes device fingerprinting

   The homepage navigation may take longer than expected due to curl_cffi initialization. This is normal behavior.

5. Extract Available Sports

   Retrieve the list of all available sports from Bet365:

   sports = session.extract_available_sports()
   
   # Display available sports
   for sport in sports:
       print(f"Sport: {sport.name}, PD: {sport.PD}")
   

   Each Sport object contains:

   • name: Human-readable sport name (e.g., “Soccer”, “Tennis”)
   • PD: Bet365’s internal page descriptor identifier
6. Scrape Sport Homepage Data

   Extract odds and match data from a specific sport:

   # Find Soccer sport
   soccer = next(filter(lambda m: m.name == "Soccer", sports))
   
   # Get Soccer homepage with matches and odds
   session.get_sport_homepage(soccer)
   

   This method:

   • Fetches splash pods containing match data
   • Parses tables with odds, teams, and market information
   • Pretty-prints the data to console
   • Saves raw response to response.txt for debugging
7. Run the Complete Example

   Execute the complete script:

   python3 main.py
   

   Expected output:

   Fetching soccer page using android api
   Going to homepage started taking longer than it should because of curl_cffi.
   False  # ZAP connection availability
   Sport: Soccer, PD: #AS#B1#...
   Sport: Tennis, PD: #AS#B2#...
   # ... (match tables with odds data)
   

   The scraper will:

   1. Navigate to Bet365 homepage
   2. List all available sports
   3. Extract Soccer matches and odds
   4. Display formatted tables in the console

Complete Working Example

Here’s the full main.py implementation:

import json
from bet365 import Bet365AndroidSession

with open("config.json", encoding="utf8") as fp:
    config = json.load(fp)

print("Fetching soccer page using android api")

session = Bet365AndroidSession(
    config["api_url"],
    config["api_key"],
    proxy=config["proxy"] or None,
    verify=False,
    host="www.bet365.com",
)

print("Going to homepage started taking longer than it should because of curl_cffi.")
session.go_homepage()

sports = session.extract_available_sports()
soccer = next(filter(lambda m: m.name == "Soccer", sports))
session.get_sport_homepage(soccer)

if session.zap_thread is not None:
    session.zap_thread.join()

Understanding the Output

The SDK will display:

• Pretty-printed tables: Match data formatted using prettytable
• Raw response file: response.txt contains the full API response for debugging
• Console logs: Progress indicators and error messages

Troubleshooting

403 Forbidden Error: If you receive a 403 status code, this typically means:

• Your IP address is blocked by Cloudflare
• Headers need updating (contact support)
• Proxy configuration required

500 Internal Error: Usually indicates:

• Bad IP address or proxy
• Configuration endpoint is unavailable
• Rate limiting triggered

Common Issues

API Key Invalid

An error occured while generating token: Invalid API key

→ Verify your api_key in config.json is correct

Assertion Error During Homepage

AssertionError: Blocked by Cloudflare...

→ Try using a residential proxy or contact support for header updates

Import Error

ModuleNotFoundError: No module named 'curl_cffi'

→ Run pip3 install -r requirements.txt to install dependencies

Next Steps

Now that you have a working scraper:

API Reference

Explore all available methods and parameters

Core Concepts

Learn about anti-bot protection and TLS fingerprinting

Message Parsing

Understand Bet365’s message format and parsing

Error Handling

Best practices for handling errors and edge cases