Coding in Python/VSCode and LLMs
Date: 29. Oktober 2025
Time: 14:00 - 15:30
Speaker: Job Schepens (Project S, CRC 1252)
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
View Slides: - HTML Version - Interactive slides (best for viewing) - PDF Version - Printable PDF format
Code Repository
- py-rdm GitHub Repository - Complete workshop materials
- Example analyses (head nods, clause mates)
- Starter scripts and templates
- Requirements and setup instructions
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
Recommended Environment
- 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