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Generates a text-based statistical analysis report from session data and saves it to the configured reports folder.

Purpose

This function creates a formatted text report containing session information, analysis summary statistics, and detailed results. It serves as a placeholder implementation for report generation that can be extended to support multiple output formats. The report includes session metadata, step counts, plot information, and serialized results, saved with a timestamped filename.

Source Code

def generate_report(session_id: str, summary: Dict[str, Any], format_type: str) -> str:
    """Generate analysis report (placeholder implementation)"""
    # This would implement the actual report generation
    # For now, just create a simple text file
    
    report_content = f"""
Statistical Analysis Report
Session ID: {session_id}
Generated: {datetime.now().isoformat()}

Session Information:
- Title: {summary['session'].get('title', 'Untitled')}
- Description: {summary['session'].get('description', 'No description')}
- Status: {summary['session'].get('status', 'Unknown')}

Summary:
- Total Steps: {summary['summary']['total_steps']}
- Successful Steps: {summary['summary']['successful_steps']}
- Plots Generated: {summary['summary']['plots_generated']}

Results:
{json.dumps(summary['results'], indent=2, default=str)}
"""
    
    # Save report
    report_filename = f"analysis_report_{session_id}_{datetime.now().strftime('%Y%m%d_%H%M%S')}.txt"
    report_path = app_config.REPORTS_FOLDER / report_filename
    
    with open(report_path, 'w') as f:
        f.write(report_content)
    
    return report_path

Parameters

Parameter Details

session_id: Unique identifier string for the analysis session. Used to label the report and track which session the report belongs to.

summary: Dictionary containing session data with expected keys: 'session' (dict with title, description, status), 'summary' (dict with total_steps, successful_steps, plots_generated), and 'results' (any serializable data structure containing analysis results).

format_type: String specifying the desired report format (e.g., 'txt', 'pdf', 'html'). Currently not used in the placeholder implementation but intended for future format selection.

Return Value

Type: str

Returns a Path object (or string representation of path) pointing to the generated report file. The filename follows the pattern 'analysis_report_{session_id}_{timestamp}.txt' where timestamp is in YYYYMMDD_HHMMSS format. The file is saved in the app_config.REPORTS_FOLDER directory.

Dependencies

• json
• datetime
• pathlib
• typing

Required Imports

import json
from datetime import datetime
from typing import Dict, Any
from pathlib import Path

Usage Example

from datetime import datetime
import json
from typing import Dict, Any
from pathlib import Path

# Assume app_config is configured with REPORTS_FOLDER
# from config import app_config

summary_data = {
    'session': {
        'title': 'Sales Analysis Q4',
        'description': 'Quarterly sales performance analysis',
        'status': 'completed'
    },
    'summary': {
        'total_steps': 5,
        'successful_steps': 4,
        'plots_generated': 2
    },
    'results': {
        'mean_sales': 15000.50,
        'total_revenue': 450000,
        'top_product': 'Widget A'
    }
}

report_path = generate_report(
    session_id='abc123',
    summary=summary_data,
    format_type='txt'
)

print(f'Report generated at: {report_path}')

Best Practices

• Ensure app_config.REPORTS_FOLDER exists and is writable before calling this function
• The summary dictionary should contain all expected keys ('session', 'summary', 'results') to avoid KeyError exceptions
• Consider implementing error handling for file write operations in production use
• The format_type parameter is currently unused; implement format-specific logic when extending this function
• Use json.dumps with default=str to handle non-serializable objects in results
• Consider adding file size limits or cleanup mechanisms for old reports to prevent disk space issues
• The function overwrites files with the same timestamp if called multiple times in the same second; consider adding microseconds or UUID to filename for uniqueness

Tags

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