[New Concept Exercise]: Functions in Python

This issue describes how to implement the functions concept exercise for the Python track. There is an outdated issue for this exercise with some discussion. It can be found here The related concept documents can be found here.

✅ Getting started

If you have not yet created or contributed to a concept exercise, this issue will require some upfront reading to give you the needed background knowledge. Some good example exercises to look at in the repo:

💡Example Exercises💡 (click to expand)

1. Little Sister’s Vocabulary
2. Meltdown Mitigation
3. Making the Grade
4. Ellen’s Alien Game

We also recommend completing one or more of the concept exercises (they’re called “learning exercises”) on the website.

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 go through the following documents:

General Contributing Docs:

• Contributing to Exercism | Exercism and GitHub | - Contributor Pull Request Guide
• What are those Weird Task Tags about?
• Exercism Formatting and Style Guide
• Exercism Markdown Specification
• Reputation

Documents on Language Tracks and Concept Exercises

• Building Language Tracks: An Overview
• What are Concept Exercises?
• Concept Exercise Specifications
• Concept Exercise Stories

🎯 Goal

This functions concept exercise is meant to teach a deeper understanding and use of functions in Python. It should also explain how Python treats/views functions (as callable objects), and dig into some of the features that make Python functions unique.

💡Learning objectives

• Understand more about Python scopes and namespaces
  • understand the difference between the global and nonlocal keywords and when to use them
• Get familiar with the special attributes of Python functions
• Get familiar with best practices when using return, and the difference between explicit and implicit return
  • functions without an explicit return will return the singleton object None
• Understand what is meant by “functions are first class objects in Python”.
  • understand that functions are objects in Python, and that they have types
  • understand that functions can be assigned to variables, used in expressions, and stored in various data structures such as dicts or lists
  • create functons that are assigned to variables, used in expressions, and stored in different data structures.
  • understand and create functions that are/can be nested inside one another
• Understand that Python considers a function a form of callable object.
• Understand that a user-defined function object is created by a function definition.

🤔 Concepts

• callable objects
• first-class functions
• global
• nested functions
• nonlocal
• return, implicit return, explicit return
• scope
• special function attributes

🚫 Topics that are Out of scope

Concepts & Subjects that are Out of Scope (click to expand)

• named parameters (these can be touched on if needed)
• default parameters (these can be touched on, if needed)
• arbitrary parameters
• *args & **kwargs
• keyword-only arguments
• / and * for requiring parameter types
• functions-as-arguments (this can be mentioned, but shouldn’t be required for the exercise)
• functions-as-returns(_this can be mentioned, but will be covered in-depth in higher-order functions)
• closures (these will be covered in a different exercise)
• decorators (these will be covered in a different exercise)
• functools.wraps (this is used mostly for decorators)
• functools (this will get its own exercise)
• comprehensions
• generators
• lambda, anonymous functions (these will be covered in a different exercise)
• recursion

↩️ Prerequisites

These are the concepts/concept exercises the student needs to complete/understand before solving this concept exercise. Since functions is a “meta” topic, these will probably need to be adjusted to fit the parameters of the exercise.

Prereqs (click to expand)

• basics
• bools
• comparisons
• lists
• list-methods
• loops
• numbers
• strings
• string-methods

📚 Resources for Writing and Reference

Resources (click to expand)

• Python Docs: Naming and Binding
• Python Docs: Python Scopes and Namespaces
• Python Docs: Defining Functions
• Function definitions (Python Library Reference)
• Dan Bader: Python s Functions are First-Class
• Real Python: Python Scope & the LEGB Rule
• Stack Overflow: Short Description of Python’s Scoping Rules?
• Real Python: Python Inner Functions: What are they Good For?
• Stack Abuse: How to Use global and nonlocal variables in Python
• The nonlocal Statement (Python Docs)
• The global Statement (Python Docs)
• Real Python: The Python return Statement: Usage and Best Practices
• Calls (Python Library Reference)
• Is it a Class or a Function? It’s a Callable! (Trey Hunner)
• Callables in Python (Vimal A.R Blog)
• Functions as Objects in Python – this is a subscription-based medium blog, so not good for hints or links
• Python Datamodel: Types

Exercise Ideas & Stories

Should you need inspiration for an exercise story, you can find a collection here. You can also port an exercise from another track, but please make sure to only to include tasks that actually make sense in Python and that add value for a student. Remove/replace/add tasks as needed to make the concept clear/workable.

📁 Exercise Files to Be Created

File Detail for this Exercise (click to collapse)

Exercise introduction.md For more information, see Exercise introduction.md This can summarize/paraphrase the linked concept documents if they have already been created (either the about or the introduction). The summary does need to have enough information and examples for the student to complete all the tasks outlined for this concept exercise. Exercise instructions.md For more information, see instructions.md Instructions for an exercise usually center on a story that sets up the code challenge to be solved. You can create your own story, or fork one from the ones listed here. Please make sure to give credit to the original authors if you use a story or fork an exercise. Exercise Exemplar.py Solution For more information, see exemplar implementation. This file should not use syntax or datas structures not introduced in this exercise or in this exercise’s prerequisites. It will be used as an “ideal” solution for the challenge, so make sure it conforms to PEP8 and other formatting conventions, and does not use single letter variable names. It should also include proper module and function-level docstrings. However, it should NOT include typehinting or type aliases. <Exercise>.py (Stub) for Implementation For more information, see stub implementation. This file should provide the expected function names imported for testing, and optionally TODO comments and or docstrings to aid the student in their implementation. TODOs and docstrings are not required. <Exercise>_Test.py Files For more information, see Tests. Additionally, please note that Python associates exercise tasks to tests via a Pytest Marker, and uses unittest subtests as a form of test paramaterization. See the test file for Little Sisters Vocab for examples of how these techniques work. Exercise Hints.md For more information on writing hints see hints.md Hints should provide enough information to get most students “un-stuck” and moving toward a solution. They should not provide a student with a direct solution. You can refer to one or more of the resources linked in this issue 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. 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.

♾️ Exercise Metadata - Track

For more information on concept exercises and formatting for the Python track config.json , please see config.json. 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 : 9f38f70d-48f4-4934-ae6e-d8277ede8edc
• concepts should be filled in from the Concepts section in this issue
• prerequisites should be filled in from the Prerequisites section in this issue

🎶 Implementation Notes

• As a reminder, code in the .meta/examplar.py file should only use syntax & concepts introduced in this exercise or one of its prerequisite exercises. We run all our examplar.py files through PyLint, but do not strictly require module docstrings. We do require function docstrings similar to PEP257. See this concept exercise exemplar.py for an example.

• Please do not use comprehensions, generator expressions, or other syntax not previously covered either in the introduction to this exercise, or to one of its prerequisites. 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.

  • All asserts should contain a “user friendly” failure message (these will display on the webiste to students, so be as clear as you can).
  • We use a PyTest custom mark to link test cases to exercise task numbers.
  • We also use unittest.subtest to parameterize test input where/when needed. Here is an example testfile that shows all three of these in action.

• While we do use PyTest as our test runner and for some implementation tests, please check with a maintainer before using a PyTest-specific 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.

🆘 Next Steps & Getting Help

1. If you'd like to work on this issue, comment saying "I'd like to work on this" (there is no real need to wait for a response, just go ahead, we’ll assign you and put a [claimed] label on the issue).
2. If you have any questions while implementing, please post the questions as comments in here, or contact one of the maintainers on our Slack channel.

[BethanyG]

I won’t have time before this weekend I don’t think - but I am going to PR turning off the stale bot, since none of us on the track are moving very fast these days (which is OK!). Right now, if we comment on anything and 22 days pass, the critter wakes up and flags things as abandoned. It’s starting to not be useful, so. 😀

[BethanyG]

Apologies. Had some things to take care of this afternoon, so am late with replying to things.

I just looked over the learning objectives and concepts and I winced a bit at global and nonlocal. Is it okay to include them in a way that shows how they can be problematical?

I think for the exercise, it’s important to provide students the opportunity to practice using both global and nonlocal in an appropriate or “safe” fashion (heavy guardrails). It doesn’t have to be elaborate, and it doesn’t have to be much more than a basic mimic (I am thinking of something similar to how we set up error handling messaging in a lot of practice exercises ).

And I think for the instructions/introduction, it would be great to put cautions in, and examples of why it can be a bad idea. Although my thinking here is that if the task or tasks set up a “proper” or “good” use case, the students will more than likely find the foot-gun, and that will convey a really good lesson, about scope, using the keywords, AND about how the Python ethos is to say “we are all adults here, so you need to think through your choices, Python’s not going to do that for you.”

It does seem somewhat “unfair” to set up students like that … but I don’t know that we teach them fluency by hiding the warts of the language. While we do do that to some extent early on, by the time students are getting ready to feed functions to other functions, use recursion, nest functions, and all the other goodness that comes along with FP paradigms in Python, they should have a working sense of caution, and be building a sense of why endless mutability can be problematic.

So my thought is that maybe there is a task that has them reach out and modify/update a global constant. Or create a global in a function that other functions could read/access (and modify at peril). I’m less clear on the nonlocal, although that could be done with an inner function – and would be a quite legitimate (if minority) use-case.

…and thinking out loud here… I don’t know if we want to consider a mutability topic, or if we want to (like we have with error handling) insert messages and reminders about the dangers of mutability as we build out the exercises in the functions and higher order functions cluster … as well as the classes, class-customization, class-interfaces cluster.