Documentation hub for Spyder users

First launch checklist

1. Select the interpreter that matches your Conda or virtual environment.
2. Confirm the working directory points at your repository root so relative data paths resolve.
3. Open the IPython console and run a smoke import for NumPy, SciPy, and pandas.
4. Dock the plots pane where it will not obscure breakpoints in the editor gutter.

Environment management

Keep teaching environments separate from production stacks. Export environment definitions alongside assignment repositories so students can reproduce the exact package set you used while recording screencasts.

Pinning dependencies

Record major and minor versions of scientific libraries when a paper goes under review. Spyder itself upgrades on its own cadence, so treat the IDE version as part of your reproducibility statement.

Debugging scientific code

Use conditional breakpoints when loops iterate over thousands of records. Combine the variable explorer with the debugger watch window to inspect slices without dumping entire tensors to the console.

Plotting and publication quality

Set matplotlib rcParams early in your session script so font sizes and dpi match journal requirements. Spyder keeps figures attached to the session that generated them, which simplifies tracing aesthetics back to code.