Description
This issue describes how to implement the class-composition
concept exercise for the python track.
Getting started
Please please please read the docs before starting. Posting PRs without reading these docs will be a lot more frustrating for you during the review cycle, and exhaust Exercism's maintainers' time. So, before diving into the implementation, please read up on the following documents:
- Contributing to Exercism | Exercism and GitHub | Contributor Pull Request Guide
- What are those Weird Task Tags about?
- Building Language Tracks: An Overview
- What are Concepts?
- Concept Exercise Specifications
- Concept Specifications
- Exercism Formatting and Style Guide
- Exercism Markdown Specification
- Reputation
Goal
This concept exercise is meant to teach an understanding/use of class-composition
in Python.
Learning objectives
- more fully understand the uses (and possible abuses) of
classes
in Python - understand what
composition
is vsinheritance
inclasses
- learn a bit about the pros and cons of using
composition
inclasses
- learn about the "Composition over inheritance" principle
- learn a bit about
dependency injection
/inversion of control
as acomposition
design pattern
Out of scope
metaclasses
dataclasses
decorators
outside of@property
,@staticmethod
, and@classmethod
(the student should already be exposed to these in the prerequisite exercise)generators
coroutines
descriptors
(these will get their own exercise)- using a
class
as a decorator - performance considerations
Concepts
classes
composition
inOOP
encapsulation
inOOP
inheritance
inOOP
dependency injection
Prerequisites
These are the concepts/concept exercises the student needs to complete/understand before solving this concept exercise.
basics
booleans
classes
class-customization
class-inheritance
comparisons
decorators
dicts
functions
higher-order functions
iteration
lists
numbers
sequences
sets
strings
tuples
Resources to refer to
- classes (Python tutorial)
- Real Python: Object-Oriented Programming in Python 3
- Real Python: Inheritance and Composition: A Python OOP Guide
- What is Composition (OOP in Python)
- What is Composition -- good explanation, but it uses Java
- Inheritance, Composition, and Aggregation in Python
- The Composition over Inheritance Principle
- Pythonic Dependency Injection: A Practical Guide
- Method Delegation in Python
- Python Data Model - Python Docs
- Stack Overflow: Composition and Aggregation in Python
-
Hints
For more information on writing hints see hints
- You can refer to one or more of the resources linked above, or analogous resources from a trusted source. We prefer using links within the Python Docs as the primary go-to, but other resources listed above are also good. Please try to avoid paid or subscription-based links if possible.
-
links.json
For more information, see concept links file
- The same resources listed in this issue can be used as a starting point for the
concepts/links.json
file, if it doesn't already exist. - If there are particularly good/interesting information sources for this concept that extend or supplement the concept exercise material & the resources already listed -- please add them to the
links.json
document.
- The same resources listed in this issue can be used as a starting point for the
Concept Description
Please see the following for more details on these files: concepts & concept exercises
-
Concept
about.md
Concept file/issue: There is currently no issue or files for the concept. They are TBD.
For more information, see Concept
about.md
- This file provides information about this concept for a student who has completed the corresponding concept exercise. It is intended as a reference for continued learning.
-
Concept
introduction.md
For more information, see Concept
introduction.md
- This can also be a summary/paraphrase of the document listed above, and will provide a brief introduction of the concept for a student who has not yet completed the concept exercise. It should contain a good summation of the concept, but not go into lots of detail.
-
Exercise
introduction.md
For more information, see Exercise
introduction.md
- This should also summarize/paraphrase the above document, but with enough information and examples for the student to complete the tasks outlined in this concept exercise.
Test-runner
No changes required to the Python Test Runner at this time.
Representer
No changes required to the Python Representer at this time.
Analyzer
No changes required to the Python Analyzer at this time.
Exercise Metadata - Track
For more information on concept exercises and formatting for the Python track config.json
, please see concept exercise metadata. The track config.json
file can be found in the root of the Python repo.
You can use the below for the exercise UUID. You can also generate a new one via exercism configlet, uuidgenerator.net, or any other favorite method. The UUID must be a valid V4 UUID.
- Exercise UUID :
99088a03-cf0c-41d9-bd98-173459cc1475
- concepts should be filled in from the Concepts section in this issue
- prerequisites should be filled in from the Prerequisites section in this issue
Exercise Metadata Files Under .meta/config.json
For more information on exercise .meta/
files and formatting, see concept exercise metadata files
.meta/config.json
- see this link for the fields and formatting of this file..meta/design.md
- see this link for the formatting of this file. Please use the Goal, Learning Objectives,Concepts, Prerequisites and , Out of Scope sections from this issue.
Implementation Notes
- Code in the
.meta/examplar.py
file should only use syntax & concepts introduced in this exercise or one of its prerequisite exercises. - Please do not use comprehensions, generator expressions, or other syntax not previously covered. Please also follow PEP8 guidelines.
- In General, tests should be written using
unittest.TestCase
and the test file should be named<EXERCISE-NAME>_test.py
. - While we do use PyTest as our test runner and for some implementation tests, please check with a maintainer before using a PyTest test method, fixture, or feature.
- Our markdown and JSON files are checked against prettier . We recommend setting prettier up locally and running it prior to submitting your PR to avoid any CI errors.
Help
If you have any questions while implementing the exercise, please post the questions as comments in this issue, or contact one of the maintainers on our Slack channel.