Enhanced MongoDB Data Processing and Error Handling

📅 2025-01-24 — Session: Enhanced MongoDB Data Processing and Error Handling

🕒 16:10–17:29
🏷️ Labels: Python, Mongodb, Logging, Error Handling, Data Processing
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal:

The session aimed to enhance the robustness and logging capabilities of Python scripts interacting with MongoDB and Google Sheets, focusing on error handling and data integrity.

Key Activities:

• Enhanced a Python script to include detailed logging for MongoDB and Google Sheets operations, facilitating effective debugging and monitoring.
• Improved the flatten_records function with robust error handling and fallback mechanisms for processing MongoDB records into a DataFrame.
• Updated the flatten_records method to handle missing fields by logging warnings and providing default values.
• Implemented workflow improvements by reintroducing a query limit in MongoDB, ensuring unique email ID generation, and enforcing string data types for key columns.
• Developed a strategy for consistent email_id management in MongoDB workflows.
• Provided Python commands for MongoDB connection and data retrieval, aiding in debugging.
• Suggested a structured approach for debugging and validating data quality in email processing.
• Outlined message ID tracking and triage workflows for email processing.
• Provided guides and scripts for MongoDB database queries and cleanup operations.

Achievements:

• Successfully integrated comprehensive logging and error handling into data processing scripts.
• Enhanced data integrity and workflow robustness in MongoDB operations.

Pending Tasks:

• Further refine the email ID management strategy to address any remaining inconsistencies.
• Continue monitoring and improving data quality validation processes.