Method get_available_values

xtop/core/data_source.py:210–250

Get distinct values for a column with optional filters. Useful for drill-down suggestions.

(self, column: str, csv_type: str = 'samples', 
                           where_clause: str = "1=1", limit: int = 100)

        return validated
    
    def get_available_values(self, column: str, csv_type: str = 'samples', 
                           where_clause: str = "1=1", limit: int = 100) -> List[Any]:
        """
        Get distinct values for a column with optional filters.
        Useful for drill-down suggestions.
        """
        conn = self.connect()
        
        # Get the CSV pattern
        patterns = {
            'samples': 'xcapture_samples_*.csv',
            'syscend': 'xcapture_syscend_*.csv',
            'iorqend': 'xcapture_iorqend_*.csv',
            'kstacks': 'xcapture_kstacks_*.csv',
            'ustacks': 'xcapture_ustacks_*.csv'
        }
        
        pattern = patterns.get(csv_type, 'xcapture_samples_*.csv')
        csv_path = str(self.datadir / pattern)
        
        # Validate column name
        validated_cols = self.validate_columns([column], csv_type)
        if validated_cols:
            column = validated_cols[0]
        
        try:
            query = f"""
            SELECT DISTINCT {column} as value, COUNT(*) as count
            FROM read_csv_auto('{csv_path}')
            WHERE ({where_clause})
            AND {column} IS NOT NULL
            GROUP BY {column}
            ORDER BY count DESC
            LIMIT {limit}
            """
            
            result = conn.execute(query).fetchall()
            return [row[0] for row in result]
        except Exception as e:
            print(f"Error getting values for {column}: {e}", file=sys.stderr)
            return []
    
    def get_partitions_info(self) -> Dict[str, str]:
        """