Best Practices for Using GitHub Co-Pilot in Python Coding

Introduction

• GitHub Co-Pilot integration with popular code editors like VS Code.
• Provides coding recommendations, useful for average to below-average coders.
• Includes a chat interface for deep questions, enhancing coding efficiency.

Personal Experience

• Developed a Python web app with GitHub Co-Pilot aid.
• Faced challenges integrating with a live SQL database; Co-Pilot provided solutions.
• Studies show increased task completion speed among Co-Pilot users.

Drawbacks and Concerns

• Potential decline in code quality due to AI assistance.
• Increase in code churn rate, indicating quick code edits post-creation.
• White papers suggest these trends might worsen by 2024.

Using GitHub Co-Pilot

Setup

1. Subscription:

   • Annual $100 fee, free for students.
   • Business account recommended for work involving secure data.

2. Installation:

   • Enable via extensions in VS Code: main extension for integration, chat extension for interaction.

Project Building

• Data Analytics Project:

  1. Data set selection: integrating a personal dataset of job postings.
  2. Python notebook creation for data analysis.
  3. Generate a README file summarizing results.

• Analysis Process:

  • Code generation for exploratory data analysis.
  • Error troubleshooting strategies, including regeneration of code and manual corrections.
  • Visualization issues and attempted solutions.

Improvements and Alternatives

• Co-Pilot chat sometimes uses GPT-3.5 turbo instead of GPT-4, impacting accuracy.
• Despite challenges, industry surveys show it's the leading AI coding assistant.

Final Project Steps

1. Title Analysis:

   • Extracting job title frequencies via Python comments.

2. README Generation:

   • Automating README content creation detailing notebook contents, requirements, and usage.

Conclusion

• GitHub Co-Pilot significantly reduces coding time and aids in troubleshooting.
• Highly beneficial for newcomers and experienced developers alike.
• Recognized as a leader among AI coding tools, despite some performance limitations.