Developed Instagram Data Processing Playbook

• Day: 2025-09-30
• Time: 18:50 to 19:10
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Instagram, Data Processing, Python, Automation, Jupyter

Description

Session Goal

The session aimed to develop a comprehensive playbook for processing and ingesting Instagram data, focusing on automation and data parsing techniques.

Key Activities

• Instagram Message Retrieval: Analyzed 25 messages to extract key steps, dependencies, and configurations.
• Data Parsing Pipeline: Set up a data extraction pipeline using Python and BeautifulSoup to parse Instagram HTML exports, focusing on messages, profiles, and chat indices.
• Data Ingestion Playbook: Structured a playbook for ingesting Instagram data into a unified format, detailing parsers and enhancements for compatibility.
• Jupyter Notebook Management: Developed Python scripts to check for notebook existence, extract and print code and markdown cells, and analyze cell structures.

Achievements

• Created a distilled playbook for Instagram message retrieval and data ingestion.
• Established a robust data parsing pipeline with validation checks.
• Enhanced Jupyter notebook management with code extraction and analysis tools.

Pending Tasks

• Further refine the data ingestion playbook for broader compatibility with other platforms.
• Address potential issues in the data_parser.ipynb for improved stability.

Evidence

• source_file=2025-09-30.sessions.jsonl, line_number=2, event_count=0, session_id=5e3e17db672ccc1b678d8b7741425af438f355b910a47b741200067332b62ba2
• event_ids: []