Enhanced Data Pipeline with Pandas and Promptflow

• Day: 2025-08-31
• Time: 00:10 to 00:35
• Project: Dev
• Workspace: WP 2: Operational
• Status: In Progress
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Data Processing, Pandas, Automation, Promptflow

Description

Session Goal: The goal of this session was to enhance the data processing pipeline by implementing robust data handling and automation scripts using Python and Pandas.

Key Activities:

• Developed a master index update script to validate input data, manage directory structures, and write to CSV files. Implemented error handling by quarantining bad rows and logging updates for database consistency.
• Created a helper for row serialization and column preseeding to prevent KeyErrors during data operations.
• Updated and optimized code for merging DataFrames in Pandas, ensuring proper handling of missing values and timestamp columns to avoid errors.
• Implemented the 03_headlines_digests.py script for processing and validating data, generating JSONL outputs for Promptflow.
• Developed a contract-compliant PromptFlow runner script with comprehensive input/output management and error handling.

Achievements:

• Successfully enhanced the data processing pipeline with improved error handling and automation capabilities.
• Ensured data integrity and efficient processing through updated scripts and robust error management.

Pending Tasks:

• Further testing and validation of the PromptFlow runner script to ensure contract compliance and output accuracy.

Evidence

• source_file=2025-08-31.sessions.jsonl, line_number=1, event_count=0, session_id=b97495fd44a2c9dc80e80cfe12319c2133b129a8bb0322a8d61614241427fd7a
• event_ids: []