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Rate Limiting System

FlavumHive implements a sophisticated rate limiting system to ensure responsible platform usage and prevent abuse. This document explains the rate limiting concepts and implementation.

Overview​

The rate limiting system:

  • Prevents platform API abuse
  • Maintains natural interaction patterns
  • Ensures compliance with platform limits
  • Manages resource utilization

Implementation​

Rate Limit Configuration​

{
  "platforms": {
    "twitter": {
      "rate_limits": {
        "tweets_per_hour": 5,
        "likes_per_hour": 20,
        "follows_per_day": 50,
        "min_delay_between_actions": 30
      }
    },
    "reddit": {
      "rate_limits": {
        "posts_per_hour": 2,
        "comments_per_hour": 10,
        "min_delay_between_actions": 60
      }
    }
  }
}

Database Schema​

CREATE TABLE rate_limits (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    platform TEXT NOT NULL,
    action_type TEXT NOT NULL,
    timestamp DATETIME DEFAULT CURRENT_TIMESTAMP,
    window_start DATETIME NOT NULL,
    window_end DATETIME NOT NULL,
    count INTEGER DEFAULT 1
);

Rate Limit Types​

Time-Based Limits​

  • Actions per minute
  • Actions per hour
  • Actions per day
  • Minimum delay between actions

Platform-Specific Limits​

  • Twitter API limits
  • Reddit API limits
  • Platform-specific cooldowns
  • Action-specific quotas

Resource-Based Limits​

  • CPU usage limits
  • Memory constraints
  • Network bandwidth
  • Storage quotas

Implementation Details​

Rate Limit Checking​

async def check_rate_limit(
    platform: str,
    action_type: str,
    window_seconds: int
) -> bool:
    """
    Check if action is within rate limits.
    
    Args:
        platform: Platform name
        action_type: Type of action
        window_seconds: Time window
        
    Returns:
        bool: True if action is allowed
    """

Rate Limit Recording​

async def record_action(
    platform: str,
    action_type: str
) -> None:
    """
    Record an action for rate limiting.
    
    Args:
        platform: Platform name
        action_type: Type of action
    """

Best Practices​

  1. Configuration

    • Set conservative limits
    • Account for platform rules
    • Include safety margins
    • Regular limit reviews

  2. Monitoring

    • Track limit usage
    • Monitor violations
    • Alert on threshold
    • Log all actions

  3. Error Handling

    • Graceful backoff
    • Retry mechanisms
    • Error notifications
    • Violation handling

Next Steps​