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Stephen Macke - Python as a Hackable Language for Interactive Data Science | PyData Global 2023
Python as a hackable language enables interactive data science workflows, reactive execution, and extensibility with AST transformations, Piccolo, and optional chaining.
- Python is a hackable language, allowing for interactive and reactive data science workflows.
- AST (Abstract Syntax Tree) transformations can be used to optimize code execution, making it appear instantaneous.
- Piccolo, an instrumentation library, allows for composable AST transformations and reactive execution.
- Optional chaining in Python can be used to safely navigate null values.
- Reactive execution can be used to refresh widgets and plots in real-time.
- AST visitors can be used to leverage Python’s extensibility and expose an API for AST transformers.
- Interactive features can be enabled, such as sliders and plots, using reactive execution.
- Python’s ability to expose an API for AST transformers makes it possible to extend Python’s behavior.
- Memoization can be used to cache expensive computations and reduce execution time.
- AST transformations can be used to skip code that has no dependencies on previous executions.
- Piccolo’s instrumentation allows for dynamic registration of transformers, enabling more complex reactive execution scenarios.