Retrieve analytics for a proxy user on a specific network over a period

import requests
from datetime import datetime, timedelta

# API credentials
API_PUBLIC_KEY = "your_public_key"
API_PRIVATE_KEY = "your_private_key"
BASE_URL = "https://api.pingproxies.com/1.0/public"

# Headers for authentication
headers = {
    "X-API-Public-Key": API_PUBLIC_KEY,
    "X-API-Private-Key": API_PRIVATE_KEY
}

def get_proxy_user_analytics(proxy_user_id, network="residential", days_ago=30, interval="day"):
    """
    Retrieve analytics for a specific proxy user on a given network.
    
    Args:
        proxy_user_id: ID of the proxy user to analyze
        network: Network type to filter (datacenter, isp, residential)
        days_ago: Number of days to look back
        interval: Time interval for data grouping (minute, hour, day, month)
        
    Returns:
        Analytics data for the specified proxy user and parameters
    """
    # Calculate start and end dates
    end_date = datetime.now()
    start_date = end_date - timedelta(days=days_ago)
    
    # Format dates for API
    period_start = start_date.strftime("%Y-%m-%d %H:%M:%S")
    period_end = end_date.strftime("%Y-%m-%d %H:%M:%S")
    
    # Build request URL with query parameters
    url = f"{BASE_URL}/user/analytics/graph"
    params = {
        "proxy_user_id": proxy_user_id,
        "network": network,
        "period_start": period_start,
        "period_end": period_end,
        "interval": interval
    }
    
    # Make the API request
    response = requests.get(url, headers=headers, params=params)
    
    # Check if the request was successful
    if response.status_code == 200:
        return response.json()
    else:
        print(f"Error: {response.status_code}")
        print(response.text)
        return None

def print_analytics_summary(analytics_data):
    """Print a summary of the analytics data"""
    if not analytics_data:
        print("No analytics data available")
        return
    
    data = analytics_data.get("data", {})
    
    # Print overall summary
    print("=== ANALYTICS SUMMARY ===")
    print(f"Total Requests: {data.get('total_requests', 0):,}")
    print(f"Successful Requests: {data.get('total_successful', 0):,}")
    print(f"Failed Requests: {data.get('total_error', 0):,}")
    print(f"Total Bandwidth Used: {data.get('total_bytes', 0) / 1024 / 1024:.2f} MB")
    
    # Print interval data
    print("\n=== DAILY BREAKDOWN ===")
    intervals = data.get("intervals", [])
    
    if not intervals:
        print("No interval data available")
        return
    
    # Print the top 5 days by request volume
    sorted_intervals = sorted(intervals, key=lambda x: x.get("requests", 0), reverse=True)
    for i, interval in enumerate(sorted_intervals[:5]):
        print(f"{i+1}. {interval.get('interval_name', 'Unknown')}")
        print(f"   Requests: {interval.get('requests', 0):,}")
        print(f"   Successful: {interval.get('successful', 0):,}")
        print(f"   Bandwidth: {interval.get('bytes', 0) / 1024 / 1024:.2f} MB")

# Example usage
if __name__ == "__main__":
    # Configure parameters
    PROXY_USER_ID = "your_proxy_user_id"  # Replace with your actual proxy user ID
    NETWORK_TYPE = "residential"          # Options: datacenter, isp, residential
    DAYS_TO_ANALYZE = 30                  # Number of days to look back
    INTERVAL = "day"                      # Options: minute, hour, day, month
    
    # Fetch analytics data
    analytics = get_proxy_user_analytics(
        proxy_user_id=PROXY_USER_ID,
        network=NETWORK_TYPE,
        days_ago=DAYS_TO_ANALYZE,
        interval=INTERVAL
    )
    
    # Print summary
    print_analytics_summary(analytics)