Purpose: Test GitHub Codespaces + Copilot integration for GIS course assignments
-
Create GitHub Repository
- Push this code to a GitHub repository
- Make sure it's public or you have Codespaces access
-
Launch Codespaces
- Click "Code" → "Create codespace on main"
- Wait for environment to load (~2-3 minutes)
-
Test Copilot Integration
- Open
src/test_pandas.py
- Try typing comments and see if Copilot suggests code
- Use Ctrl+Shift+I (Cmd+Shift+I on Mac) for Copilot Chat
- Open
Try typing this comment in src/test_pandas.py
:
# import pandas and create a dataframe with latitude and longitude columns
Expected: Copilot should suggest pandas import and DataFrame creation
Try typing:
# load a CSV file with spatial coordinates and display basic info about the dataset
Expected: Copilot should suggest reading CSV and showing DataFrame info
Press Ctrl+Shift+I and ask:
"How do I filter a pandas DataFrame to show only rows where temperature > 20?"
Expected: Copilot Chat should provide helpful explanation and code examples
- Codespaces launches without errors
- Python environment loads correctly
- Copilot extension is active and providing suggestions
- Copilot Chat responds to GIS-related questions
- Students can focus on learning concepts instead of setup
If Copilot doesn't work:
- Check if GitHub Copilot Pro is enabled on your account
- Try Ctrl+Shift+P → "GitHub Copilot: Sign In"
- Verify the extensions loaded in VS Code sidebar
If environment fails:
- Check if the base image
aaryno/devcontainer-base-python:fall-2025
exists - Fall back to
mcr.microsoft.com/devcontainers/python:3.11
as base image - Check Codespaces logs for specific errors
This test validates that students will have:
- Zero setup friction - Codespaces "just works"
- AI assistance available - Copilot helps with syntax
- Focus on learning - Time spent on GIS concepts, not debugging
- Professional tools - Same workflow as industry developers
Next Steps: If this test passes, apply the same devcontainer configuration to Module 3 assignments.