Automated YouTube Video Data Backfill and Markdown Generation

• Day: 2025-08-04
• Time: 18:10 to 19:55
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Python, Youtube, CSV, Markdown, Automation

Description

Session Goal: The session aimed to automate the process of backfilling YouTube video data into CSV files and generating Markdown files from these CSVs for further processing.

Key Activities:

1. Developed a Python CLI script to backfill YouTube video uploads into a CSV file based on specified dates. Utilized argparse for command-line arguments and integrated with an existing API to fetch video data.
2. Created a batch Markdown renderer script to process CSV files of video data, slicing them into batches and generating Markdown files with metadata and links.
3. Implemented a patch to inject date information into CSV filenames, ensuring unique and timestamped outputs.
4. Updated command-line interface options for enhanced usability, changing positional arguments to required options.
5. Curated political video content for the PoliticalSpeeches.app, establishing criteria for selecting genuine political speeches and interviews.
6. Adapted YAML configurations for JSONL processing in Azure ML, improving functionality by detailing changes in flow and run files.
7. Developed a Python script to convert Markdown stubs into JSONL format for data processing pipelines.

Achievements:

• Successfully automated the backfilling of YouTube video data and the generation of Markdown files, streamlining data processing workflows.
• Enhanced usability of scripts through improved command-line interfaces and file management.
• Established a structured workflow for curating political content, ensuring relevance and quality.

Pending Tasks:

• Validate the JSONL outputs in the PromptFlow pipeline to ensure data integrity.
• Further refine the criteria for political content selection to improve accuracy and relevance.

Evidence

• source_file=2025-08-04.sessions.jsonl, line_number=1, event_count=0, session_id=559710e47f06b79dfbf2e522bcfb5fa8d138cfab82cba7f03d336ce27d836a91
• event_ids: []