pySohila’s learning labPYTHON / FIELD GUIDE 01

Choose your next depth / OPTIONAL DEPTH

OOP, composition & data classes

Use objects to express a useful boundary, with functions for transformation logic.

3h planning budget · Sohila Khaled Abbas · Reviewed 2026-11-01

Apply this to your Python data tools, PixelFed quality work, n8n integrations or BI delivery when the project needs it.

Understand the idea

A class is useful when related state and behavior form a stable concept. A dataclass reduces repetitive initialization and representation code, but it does not validate every input automatically. Keep boundary parsing separate from the trusted object.

Composition means a service receives the collaborator it needs: for example, a reader or a clock. This makes fixture tests possible without making HTTP calls. Inheritance is appropriate for a genuine substitutable relationship, not simply for sharing two helper methods.

What to learn

A small original example

from dataclasses import dataclass

@dataclass(frozen=True)
class Order:
    order_id: str
    total_piastres: int

order = Order("O001", 12550)
print(order.total_piastres)

Practice on your own data

Create an Order dataclass and a report service that accepts a fixture reader.

Practice this lesson in the Python lab →

EXIT CHECK

A second reader can be substituted without rewriting the aggregation; invalid input is rejected before creating the domain record.

Common pitfalls

Prerequisites

Modules, typing & data classes

Video and playlist companions

Choose one explanation for the concept, then attempt the practice. These are topic mappings, not a claim that every linked lesson covers every outcome.

Python Object Oriented Programming - شرح للبرمجة كائنية التوجه في بايثون

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Sources and further reading

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