This video compares Jupyter Notebooks and Python scripts, explaining when each is the better choice. The presenter uses examples to illustrate the advantages and disadvantages of each approach, focusing on exploratory data analysis and the potential pitfalls of relying solely on notebooks for larger projects.
The speaker suggests two main ways to mitigate the risks:
Avoid using global variables altogether: Instead, pass variables as arguments to functions. This ensures that changes within a function don't affect the global scope, preventing unexpected behavior in other parts of the notebook.
Restart the Jupyter kernel and clear all outputs: This resets the notebook's state, eliminating any lingering effects of previously changed global variables. The speaker demonstrates this within the VSCode Jupyter Notebook environment.
