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Attribute

As explained in Python Workout, Second Edition

An attribute is a named value associated with a Python object and accessed through attribute lookup.

An attribute is a named value associated with an object. Attribute lookup exposes data and behavior through objects, classes, and built-in types. section 10.6

Create an instance attribute

Assign an argument to self.flavor inside __init__. Calling Scoop('chocolate') creates an instance whose flavor attribute contains 'chocolate'. section 10.6 section 10.8

Use attributes while practicing these object-oriented patterns:

  • Store instance state such as a beverage's name and temperature, including a default temperature. section 10.8
  • Attach an opened file to a LogFile instance through its file attribute. section 10.8
  • Combine attributes with composition by giving a Shelf books and width, then checking capacity. section 10.12
  • Use class-level declarations and annotations with dataclasses, while recognizing that type checking remains external. section 10.12
from dataclasses import dataclass

@dataclass
class Scoop():
    flavor : str

A minimal dataclass declaration shows an annotated flavor attribute without writing __init__ manually. section 10.12

How Python Workout, Second Edition covers it

How deep it goes
Explains instance assignment through self, class-level declarations, dunder attributes, and __new__/__init__ sequencing; defers runtime type enforcement.
Examples
Practices Scoop, Beverage, LogFile, Book, Shelf, and dataclass examples with state, defaults, files, composition, and capacity checks.
What it assumes
Assumes introductory Python experience and teaches object attributes, self, __init__, and related object mechanics through practice.
What you can do after
Build instance and class attributes, then apply them in small Python classes and composed object models.
How it connects
Connects attributes to objects, classes, methods, inheritance, composition, dataclasses, type annotations, and object initialization.

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This explainer was generated by Manning's knowledge graph from the text of Python Workout, Second Edition. The section links point to the parts of the book it draws on.