Optimizing Memory and Data Processing in Python

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📅 2023-04-25 — Session: Optimizing Memory and Data Processing in Python

🕒 20:15–22:46
🏷️ Labels: Python, Vs Code, Memory Optimization, Data Processing, Pandas
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to explore tools and techniques for optimizing memory usage in Python applications, particularly within the Visual Studio Code environment, and to enhance data processing workflows using Python.

Key Activities

  • Memory Monitoring in VS Code: Reviewed and listed several Visual Studio Code extensions for real-time memory monitoring, including alternatives for the unavailable Memory Monitor extension.
  • Pylance Setup: Provided instructions for installing and configuring Pylance in VS Code to improve Python development with type checking and code analysis.
  • Data Normalization and Processing: Summarized an algorithm for data normalization and implemented Python functions for decomposing dataframes into CSV files, modifying file paths, and harmonizing names across datasets.
  • Performance Measurement: Explained the use of Jupyter magic commands %%time and %timeit for performance measurement of code execution.
  • Process Management in Linux: Offered guidance on using the kill command to terminate processes in Linux.

Achievements

  • Identified and documented key VS Code extensions for memory optimization.
  • Successfully set up and utilized Pylance for Python development.
  • Implemented and tested various data processing functions in Python, enhancing data management capabilities.

Pending Tasks

  • Further exploration of memory optimization techniques and tools for Python applications.
  • Continued refinement and testing of data processing scripts to ensure robustness and efficiency.

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