Developed and Tested Flask API for Model Predictions

• Day: 2024-04-06
• Time: 18:25 to 19:05
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Flask, API, Machine Learning, Python, Web Development

Description

Session Goal: The primary objective was to develop a Flask API to serve predictions from a machine learning model, ensuring a robust and organized application structure.

Key Activities:

1. Setting Up Flask API: Initiated the setup of a Flask API to handle model predictions, following a structured guide.
2. Organizing Application Structure: Implemented a clean project structure with separate files for API routes and the main entry point.
3. Centralizing Prediction Logic: Refactored code to centralize prediction logic, promoting DRY principles.
4. Testing API: Developed a Python script to test the API, simulating POST requests with JSON data.
5. Troubleshooting Errors: Addressed connection errors and import issues, ensuring the Flask server runs smoothly and all modules are correctly imported.

Achievements: Successfully set up and tested the Flask API, resolving key errors related to connection and imports. The application now follows a clean and organized structure.

Pending Tasks: Further testing with edge cases and deployment considerations for production use.

Evidence

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• event_ids: []