A History Lesson - Deepstash
Machine Learning With Google

Learn more about computerscience with this collection

Understanding machine learning models

Improving data analysis and decision-making

How Google uses logic in machine learning

Machine Learning With Google

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A History Lesson

A History Lesson

In the beginning there where:

  • dicts for look-ups
  • tuples for structures
  • hand-written classes for more functionality

Later Named Tuples where added as a code generator with the goal of adding names to the fields of a tuple. This was limited by design, hence its name

ORMs appeared and pioneered using class attributes to specify rich data structures

In Python 3.6, it became possible to supply type annotations

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MORE IDEAS ON THIS

Dataclasses & What are they for

Dataclasses & What are they for

Dataclasses are an implementation of a code generator, similar to a Named Tuple.

The idea of using a code generator is to save time and reduce wordiness.

There are two views about the purpose of Dataclasses:

  1. It makes a mutable da...

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A Complex Example of using Dataclasses

A Complex Example of using Dataclasses

In the image example, the generated code includes:

  • typed attributes
  • hidden attributes from __repr__ response
  • custom __hash__ dunder with the selected fields
  • attribute with default factory value in __init__ constructor

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Generated Code Includes

  • Dunder methods like init, repr, eq, lt, le, etc.
  • Frozen nature by generating dunder methods for __setattr__ and __delattr__
  • Class variables for the provided attributes

The code generation can be configured by providing keyword a...

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RAYMOND HETTINGER

If you have an immutable mind get out!

RAYMOND HETTINGER

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Comparison with Named Tuples

Comparison with Named Tuples

  • Dataclasses are by default mutable
  • Named Tuples have methods which start with an underscore which can be confusing. Ex: obj._replace...

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CURATED FROM

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pvl

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I started using Dataclasses and I think you should too

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