📅 2024-04-06 — Session: Developed and Tested Flask API for Model Predictions
🕒 18:25–19:05
🏷️ Labels: Flask, API, Machine Learning, Python, Web Development
📂 Project: Dev
⭐ Priority: MEDIUM
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:
- Setting Up Flask API: Initiated the setup of a Flask API to handle model predictions, following a structured guide.
- Organizing Application Structure: Implemented a clean project structure with separate files for API routes and the main entry point.
- Centralizing Prediction Logic: Refactored code to centralize prediction logic, promoting DRY principles.
- Testing API: Developed a Python script to test the API, simulating POST requests with JSON data.
- 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.