fastcore: An Underrated Python Library

2020-09-01 · Source: Hamel Husain's Blog · Field: Technology & Digital — Software Development & Engineering, Artificial Intelligence & Machine Learning, Data Science & Analytics · Depth: Advanced, long

Summary

fastcore is a Python library that extends the language, providing utilities to enhance developer productivity and eliminate boilerplate. It serves as a foundational library for many fast.ai projects. The library introduces patterns from other languages like Julia, Ruby, and Haskell, offering tools such as the `@delegates` decorator for transparent `**kwargs` handling, `store_attr()` to simplify instance attribute assignment in `__init__`, and `PrePostInitMeta` for avoiding `super().__init__()` boilerplate in subclassing. fastcore also includes `@typedispatch` for multiple dispatch based on type hints, `partialler` for `functools.partial` with preserved docstrings, and `compose` for functional programming. Additionally, it offers `basic_repr` for clearer object representations, `@patch` for monkey patching, extensions to `pathlib.Path`, the `Self` object for concise lambdas, and the `L` class as a more powerful list replacement.

Key takeaway

For Python developers seeking to write more concise and expressive code, exploring fastcore can significantly streamline development. Its features, like `@delegates` and `store_attr()`, directly address common pain points such as `**kwargs` obfuscation and `__init__` boilerplate. Consider integrating fastcore utilities to adopt advanced programming patterns and reduce repetitive code, potentially improving code readability and maintainability in your projects.

Key insights

fastcore extends Python with advanced patterns and utilities to reduce boilerplate and enhance code expressiveness.

Principles

• Minimize boilerplate code.
• Enhance Python with multi-language patterns.
• Improve API transparency.

Method

fastcore employs decorators like `@delegates` and `@typedispatch`, and utility functions such as `store_attr()` and `compose`, to modify Python's behavior and streamline common programming tasks.

In practice

• Use `@delegates` to clarify `**kwargs` APIs.
• Employ `store_attr()` for concise `__init__` attribute assignment.
• Apply `@typedispatch` for type-dependent function behavior.

Topics

• fastcore Library
• Python Utilities
• Boilerplate Reduction
• Multiple Dispatch
• Functional Programming

Code references

• mrocklin/multipledispatch
• fastai/fastcore
• fastai/fastpages

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Editorial summary, takeaway, and curation by AIssential. Original article published by Hamel Husain's Blog.