data_source_plan.md

Data Source Integration Plan

Current Data Sources

1. BindingDB

• Core binding data
• Target patterns for psychoactive compounds
• Activity classification
• Structure validation

2. Web Enrichment

• Swiss* services integration
• Community data sources
• Social media monitoring

Missing Data Sources

1. ChEMBL Integration

class ChEMBLSource:
    """ChEMBL data source handler."""
    
    # Core functionality
    - Target-based compound retrieval
    - Activity data processing
    - Structure standardization
    
    # Enhanced features
    - Assay data integration
    - Document linking
    - Target relationships

2. PubChem Integration

class PubChemSource:
    """PubChem data source handler."""
    
    # Core functionality
    - Compound lookup
    - Bioassay data
    - Literature links
    
    # Enhanced features
    - Patent integration
    - Structure clustering
    - Similar compound search

3. Community Sources

class CommunityDataSource:
    """Community data integration."""
    
    # Data sources
    - PsychonautWiki API
    - Erowid Experience Vaults
    - TripSit Factsheets
    - Reddit Data Analysis
    
    # Features
    - Experience report parsing
    - Effect profiling
    - Safety information
    - Usage patterns

4. Social Media

class SocialMediaMonitor:
    """Social media data harvesting."""
    
    # Platforms
    - Reddit (r/researchchemicals, r/nootropics)
    - Twitter API
    - Bluesky API
    - Discord monitoring
    
    # Features
    - New compound detection
    - Trend analysis
    - Safety monitoring
    - Community insights

Integration Plan

Phase 1: Core Chemical DBs (2 weeks)

1. ChEMBL Integration

   • Implement ChEMBL client
   • Add target mapping
   • Process activity data

2. PubChem Integration

   • Implement PubChem client
   • Add compound lookup
   • Process bioassay data

Phase 2: Community Sources (2 weeks)

1. PsychonautWiki

   • Implement API client
   • Parse effect data
   • Extract safety info

2. Erowid

   • Implement scraping
   • Parse experience reports
   • Extract compound data

3. TripSit

   • Implement API client
   • Get factsheet data
   • Process combinations

Phase 3: Social Media (2 weeks)

1. Reddit Integration

   • Implement PRAW client
   • Monitor key subreddits
   • Extract compound mentions

2. Twitter Integration

   • Implement Twitter API v2
   • Track relevant hashtags
   • Monitor key accounts

3. Bluesky/Discord

   • Implement API clients
   • Set up monitoring
   • Process messages

Phase 4: Data Enrichment (2 weeks)

1. Cross-referencing

   • Link identifiers
   • Merge activity data
   • Combine references

2. Data Validation

   • Structure checking
   • Activity validation
   • Reference verification

3. Export Enhancement

   • Flexible columns
   • Multiple formats
   • Data completeness

Implementation Details

1. Base Client

class DataSourceClient:
    """Base class for data source clients."""
    
    def __init__(self):
        self.http_client = None
        self.rate_limiter = None
        self.cache = None
    
    def get_compound(self, identifier: str) -> CompoundData:
        """Get compound by identifier."""
        pass
    
    def search_compounds(self, query: str) -> List[CompoundData]:
        """Search for compounds."""
        pass
    
    def get_activity_data(self, compound: CompoundData) -> None:
        """Get activity data for compound."""
        pass

2. Integration Manager

class DataSourceManager:
    """Manages multiple data sources."""
    
    def __init__(self):
        self.sources = {}
        self.cache = None
        self.logger = None
    
    def register_source(self, name: str, source: DataSourceClient) -> None:
        """Register a data source."""
        pass
    
    def get_compound_data(self, identifier: str) -> CompoundData:
        """Get compound data from all sources."""
        pass
    
    def enrich_compound(self, compound: CompoundData) -> None:
        """Enrich compound with data from all sources."""
        pass

3. Cache Management

class DataSourceCache:
    """Cache for data source results."""
    
    def __init__(self):
        self.cache_dir = None
        self.max_age = None
        self.compression = None
    
    def get(self, key: str) -> Optional[Any]:
        """Get cached data."""
        pass
    
    def set(self, key: str, value: Any) -> None:
        """Cache data."""
        pass

Next Steps

1. Immediate Actions

• Create ChEMBL client
• Implement base client
• Set up caching

2. Short-term Goals

• Add all chemical DBs
• Implement community sources
• Add social monitoring

3. Long-term Goals

• Full data integration
• Enhanced validation
• Comprehensive export

Success Metrics

1. Coverage

• Number of compounds
• Data completeness
• Source coverage

2. Quality

• Structure validation
• Activity validation
• Reference verification

3. Performance

• Response times
• Cache hit rates
• Resource usage

4. Usability

• API simplicity
• Documentation
• Error handling