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

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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.

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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

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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()

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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

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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

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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

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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

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