Reddit Integration

FlavumHive's Reddit integration leverages the PRAW (Python Reddit API Wrapper) library to enable sophisticated interactions with Reddit communities while maintaining personality-driven engagement.

Overview

The Reddit integration includes:

• Subreddit monitoring
• Post creation
• Comment management
• Community engagement
• Analytics tracking

Setup

Prerequisites

1. Reddit account
2. Reddit API credentials
3. Environment variables
4. Platform configuration

Environment Configuration

# Required in .env
REDDIT_USERNAME="your_username"
REDDIT_PASSWORD="your_password"
REDDIT_CLIENT_ID="your_client_id"
REDDIT_CLIENT_SECRET="your_client_secret"
REDDIT_USER_AGENT="FlavumHive Bot v1.0"

# Rate Limits
REDDIT_POSTS_PER_HOUR=2
REDDIT_COMMENTS_PER_HOUR=5

Platform Configuration

{
  "platforms": {
    "reddit": {
      "enabled": true,
      "personality": {
        "active": "crypto_researcher",
        "settings": {
          "add_signature": true,
          "auto_reply": true
        }
      },
      "target_subreddits": ["RedHarmonyAI"],
      "rate_limits": {
        "posts_per_hour": 2,
        "comments_per_hour": 5,
        "min_delay_between_actions": 20
      }
    }
  }
}

Core Features

1. Post Creation

async def create_post(self, subreddit: str, title: str, content: str) -> bool:
    """
    Create a new Reddit post.
    
    Args:
        subreddit: Target subreddit
        title: Post title
        content: Post content
        
    Returns:
        bool: Success status
    """

2. Comment Management

async def add_comment(self, post_id: str, content: str) -> bool:
    """
    Add a comment to a post.
    
    Args:
        post_id: Target post ID
        content: Comment content
        
    Returns:
        bool: Success status
    """

3. Subreddit Monitoring

async def monitor_subreddit(self, subreddit: str, keywords: List[str]):
    """
    Monitor subreddit for relevant posts.
    
    Args:
        subreddit: Subreddit to monitor
        keywords: Keywords to track
    """

Authentication

PRAW Setup

def initialize_reddit(self):
    self.reddit = praw.Reddit(
        client_id=self.client_id,
        client_secret=self.client_secret,
        username=self.username,
        password=self.password,
        user_agent=self.user_agent
    )

Validation

def validate_auth(self):
    try:
        self.reddit.user.me()
        return True
    except Exception as e:
        self.logger.error(f"Authentication failed: {e}")
        return False

Rate Limiting

Configuration

{
  "rate_limits": {
    "posts_per_hour": 2,
    "comments_per_hour": 5,
    "min_delay_between_actions": 20,
    "max_daily_posts": 48,
    "max_daily_comments": 100
  }
}

Implementation

class RedditRateLimiter:
    def __init__(self, config: dict):
        self.limits = config["rate_limits"]
        self.action_history = {}
        
    async def can_perform_action(self, action_type: str) -> bool:
        return await self._check_limits(action_type)

Error Handling

Common Errors

1. API rate limits
2. Authentication issues
3. Subreddit restrictions
4. Content filters

Error Recovery

async def handle_error(self, error: Exception):
    if isinstance(error, praw.exceptions.APIException):
        await self._handle_api_error(error)
    elif isinstance(error, praw.exceptions.ClientException):
        await self._handle_client_error(error)
    else:
        await self._handle_general_error(error)

Monitoring

Metrics Tracking

class RedditMetrics:
    def __init__(self):
        self.post_count = 0
        self.comment_count = 0
        self.karma_earned = 0
        self.error_count = 0

Health Checks

async def health_check(self):
    return {
        "status": "healthy" if self.is_authenticated else "error",
        "rate_limit_status": await self.rate_limiter.status(),
        "recent_errors": self.recent_errors,
        "karma_status": await self._get_karma_status()
    }

Best Practices

1. Content Guidelines

• Follow subreddit rules
• Maintain quality standards
• Use appropriate formatting
• Include relevant links

2. Rate Limiting

• Respect Reddit's limits
• Implement backoff strategy
• Monitor karma scores
• Track API usage

3. Error Management

• Handle rate limits gracefully
• Log all errors
• Monitor for bans
• Implement recovery strategies

4. Community Engagement

• Follow reddiquette
• Engage meaningfully
• Build reputation
• Monitor feedback

Advanced Features

1. Karma Monitoring

async def monitor_karma(self):
    """
    Track karma changes and adjust behavior.
    """
    karma = await self._get_karma()
    await self._adjust_posting_strategy(karma)

2. Content Analysis

async def analyze_post_performance(self, post_id: str) -> dict:
    """
    Analyze post performance metrics.
    
    Args:
        post_id: Post to analyze
        
    Returns:
        dict: Performance metrics
    """

3. Community Analysis

async def analyze_subreddit(self, subreddit: str) -> dict:
    """
    Analyze subreddit characteristics.
    
    Args:
        subreddit: Subreddit to analyze
        
    Returns:
        dict: Subreddit metrics
    """

Troubleshooting

Common Issues

1. API Rate Limits

   # Check rate limit status
   limits = await self.rate_limiter.status()
   
   # Implement backoff
   await self.backoff_strategy.execute()

2. Content Filtering

   # Validate content
   await self.content_validator.check(content)
   
   # Format for Reddit
   content = await self.formatter.format_for_reddit(content)

3. Karma Issues

   # Check karma status
   karma = await self._get_karma()
   
   # Adjust strategy if needed
   await self._adjust_posting_strategy(karma)

Security Considerations

1. API Credentials

• Use environment variables
• Rotate credentials
• Monitor usage
• Implement access controls

2. Content Security

• Validate all content
• Check for prohibited content
• Monitor for spam flags
• Implement content filters

3. Account Protection

• Monitor for suspicious activity
• Track karma changes
• Implement rate limiting
• Handle bans appropriately

Next Steps

• Twitter Integration
• Personality System
• Rate Limiting
• API Reference