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[New Concept Exercise] : rich comparisons #2287

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@DavidGerva

Description

@DavidGerva

This issue describes how to implement the rich-comparisons 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:

Watching the following video is also helpful. It is a bit outdated, but is good for describing the general process:

Goal

This concept exercise is meant to teach an understanding/use of rich comparison methods in python. It should also generally explain how to override the behavior of rich comparison operators and methods.

Learning objectives

  • understanding (and using the concept) that the == operator calls the dunder method __eq__() on a specific object, and uses that object's implementation for comparison. Where no implementation is present, the default __eq__() from generic object is used.
  • the same applies for operators <, <=, !=, >=, > and correspondents dunder methods __lt__, __le__, __ne__, __ge__, __gt__
  • overriding the default implementation of the __eq__() dunder method on a specific object to customize comparison behavior.
  • overriding the default implementations of the __lt__, __le__, __ne__, __ge__, __gt__ dunder methods on a specific object to customize comparison behavior.
  • the pros and cons of using functools.total_ordering to "shortcut" defining all rich comparison methods for a class.
  • return the singleton NotImplemented if the called operation is not implemented

Out of scope

  • performance considerations

Concepts

  • __eq__, __lt__, __le__, __ne__, __ge__, __gt__ dunder methods
  • comparison behavior customization
  • operator overload
  • dunder methods override

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
  • class-composition
  • comparisons
  • dicts
  • dict-methods
  • iteration
  • lists
  • list-methods
  • numbers
  • operator-overloading
  • sequences
  • sets
  • strings
  • string-methods
  • tuples

Resources to refer to

  • 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.

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 : 0fc646ac-667e-4fc9-bdee-9be7d5431987
  • 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.

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