Refactored and Debugged Data Processing Scripts

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📅 2023-12-20 — Session: Refactored and Debugged Data Processing Scripts

🕒 16:20–16:55
🏷️ Labels: Python, Dask, Data Processing, Debugging, Modularization
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The primary goal of this session was to enhance the structure and functionality of data processing scripts, focusing on modularization, debugging, and effective data handling using Python and Dask.

Key Activities

  • Improved Notebook Structure: Strategies were outlined for reorganizing the ‘Extract from database’ notebook to emphasize modularization and clarity.
  • Enhanced Debugging: Detailed logging and error handling were introduced to the get_data and process_price_quantities functions, facilitating easier debugging.
  • Revised Data Processing Script: A linear Python script was provided for processing data, with logging enhancements for debugging.
  • Troubleshooting Dask Issues: A systematic approach was outlined to troubleshoot dd.read_table function issues in Dask.
  • Column Naming in Dask DataFrame: Modified the get_data function to correctly assign column names to a Dask DataFrame.
  • Syntax Error Debugging: Provided insights on resolving SyntaxError: unterminated string literal and debugging strategies for large DataFrames.
  • Modular Script Refactoring: Refactored a Python script for modular data processing, including utility functions for various tasks.

Achievements

  • Achieved a more modular and maintainable structure for data processing scripts.
  • Improved debugging capabilities through enhanced logging and error handling.
  • Clarified strategies for troubleshooting and resolving common Dask issues.

Pending Tasks

  • Further testing of the refactored scripts to ensure robustness and efficiency.
  • Additional documentation for the new modular functions to aid future maintenance and updates.

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