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Coding in Python/VSCode and LLMs

Field Details
Date 29 October 2025
Time 14:00 - 15:30
Location House of Prominence, Attic (Top floor), Luxemburger Str. 299, Cologne
Speaker Job Schepens, Project S, CRC 1252
Prerequisites No formal prerequisites listed on this page.
Materials status Slides and repository resources are available below.
Slides / recording Slides are linked below; no recording is listed.

Overview

Set up a productive Python development environment with VSCode, essential research libraries, and modern AI-assisted coding practices with LLMs. Includes Git integration and code quality tips.

This workshop covers practical Python development for linguistic research, with hands-on examples, statistical analysis, and LLM-assisted coding workflows.

Learning Objectives

  • Configure Python and VSCode for research workflows
  • Use pandas, numpy, matplotlib effectively
  • Integrate Git and version control with VSCode
  • Apply AI-assisted coding patterns responsibly
  • Improve code quality and documentation
  • Build reproducible data analysis pipelines

Topics Covered

  • Python + VSCode environment setup (Windows, macOS, Linux)
  • Core libraries: pandas, numpy, scipy, matplotlib, seaborn
  • Git integration and collaborative workflows
  • LLM-assisted coding tools (GitHub Copilot, Continue, Cline)
  • Statistical analysis for linguistic data
  • Code quality, testing, and documentation
  • Virtual environments and dependency management

Materials

Slides & Resources

  • Workshop Presentation (Quarto) - Full workshop slides source code
  • Python environment setup
  • LLM configuration and best practices
  • Code examples and async agents

Further GWDG courses: - Effectively Utilize AI Tools in Research - AI Competence Training

View Slides: - HTML Version on GIT.NRW - Slides hosted on GIT.NRW (looks better in some browsers) - HTML Version - Slides hosted on GitHub - PDF Version - Printable PDF format

Code Repository

Quick Start

# Clone the repository
git clone https://github.com/jobschepens/py-rdm.git
cd py-rdm

# Set up Python environment
python -m venv .venv
source .venv/bin/activate  # macOS/Linux
# or: .venv\Scripts\Activate.ps1  # Windows PowerShell

# Install dependencies
pip install -r requirements.txt

# Explore examples
python head-nods-example/job-testanalysis2/code/sample_size_analysis.py
python clause-mates-example/job-testanalysis/code/analyze_pronoun_thematic_roles.py

Example Projects

The repository includes an example analysis:

Head Nods Analysis

  • Statistical comparison of head nod characteristics across languages
  • Sample size assessment and power analysis
  • Normality testing and Mann-Whitney U tests

Tools & Setup

  • Python: 3.9+ (3.11+ recommended)
  • Editor: Visual Studio Code
  • Terminal: PowerShell (Windows), Bash (macOS/Linux)
  • Version Control: Git with GitHub

Essential VS Code Extensions

  • Python (Microsoft) - Language support
  • Jupyter (Microsoft) - Notebook support
  • Pylance (Microsoft) - Type checking

LLM Integration (Optional)

  • GitHub Copilot Chat - Code completion and chat
  • Continue - LLM integration with multiple providers
  • Cline - Autonomous coding agent

Repository Structure

py-rdm/
├── head-nods-example/          # Head nods analysis
├── example-scripts/             # Helper scripts (env loading, etc.)
├── slides.qmd                   # Workshop presentation
├── requirements.txt             # Python dependencies
├── .gitignore                   # Git ignore rules
└── README.md                    # Full documentation

For Participants

Folder Organization Template

analyses-your-name/
├── code/
│   ├── data_cleaning.py
│   ├── analysis.py
│   └── visualization.py
├── processed_data/
│   └── cleaned_data.csv
├── results/
│   ├── plots/
│   ├── summary.csv
│   └── report.md
└── README.md

Last updated: October 2025