This issue describes how to implement the functional tools 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:
Goal
This concept exercise is meant to teach an understanding/use of functional tools (e.g, map(), filter(), and functools.reduce() in Python.
Learning objectives
- Understand/use the
built-in map() function.
- constructing a
lambda or callback function used as the argument.
- comparisons to
set, dict or list comprehensions
- when and when not to use - considering performance & readability
- Understand/use the
built-in filter() function.
- constructing a
lambda or callback function used as the argument.
- comparisons to
set, dict or list comprehensions
- when and when not to use - considering performance & readability
- Understand/use the
functools.reduce() function
- constructing a
lambda or callback function used as the argument.
- using
initializer as a "first call" or to guard against TypeErrors when the passed iterable is empty.
- comparisons to
sum(), min(), max(), any(), all(), math.prod() and to intertools.accumulate()
- when and when not to use - considering performance & readability
Out of scope
comprehensions
comprehensions in lambdas
map(), filter() or functools.reduce() in a comprehension
functools beyond functools.reduce()(this will get its own exercise)
generators
- using an
assignment expression or "walrus" operator (:=) in a lambda
Concepts
- functional tools in python
built-ins
any() & all()
sum()
min() & max()
map()
filter()
functools.reduce()
itertools.accumulate()
Prerequisites
These are the concepts/concept exercises the student needs to complete/understand before solving this concept exercise.
basics
bools
comparisons
dicts
dict-methods
functions
function-arguments
higher-order-functions
iteration
lists
list-methods
numbers
sequences
sets
strings
string-methods
tuples
Resources to refer to
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.
- 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.
This issue describes how to implement the
functional toolsconcept 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:
Goal
This concept exercise is meant to teach an understanding/use of
functional tools(e.g,map(), filter(), and functools.reduce()in Python.Learning objectives
built-in map()function.lambdaor callback function used as the argument.set,dictorlistcomprehensionsbuilt-in filter()function.lambdaor callback function used as the argument.set,dictorlistcomprehensionsfunctools.reduce()functionlambdaor callback function used as the argument.initializeras a "first call" or to guard against TypeErrors when the passediterableis empty.sum(),min(),max(),any(),all(),math.prod()and tointertools.accumulate()Out of scope
comprehensionscomprehensionsinlambdasmap(),filter()orfunctools.reduce()in acomprehensionfunctoolsbeyondfunctools.reduce()(this will get its own exercise)generatorsassignment expressionor "walrus" operator (:=) in alambdaConcepts
built-insany()&all()sum()min()&max()map()filter()functools.reduce()itertools.accumulate()Prerequisites
These are the concepts/concept exercises the student needs to complete/understand before solving this concept exercise.
basicsboolscomparisonsdictsdict-methodsfunctionsfunction-argumentshigher-order-functionsiterationlistslist-methodsnumberssequencessetsstringsstring-methodstuplesResources to refer to
map()&filter()any()&all()min()&max()sum()itertools.accumulate()functools.reduce()Hints
For more information on writing hints see hints
links.jsonFor more information, see concept links file
concepts/links.jsonfile, if it doesn't already exist.links.jsondocument.Concept Description
Please see the following for more details on these files: concepts & concept exercises
Concept
about.mdConcept file/issue: There is currently no issue or files for the concept. They are TBD.
For more information, see Concept
about.mdConcept
introduction.mdFor more information, see Concept
introduction.mdExercise
introduction.mdFor more information, see Exercise
introduction.mdTest-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 trackconfig.jsonfile 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 Metadata Files Under
.meta/config.jsonFor 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
.meta/examplar.pyfile should only use syntax & concepts introduced in this exercise or one of its prerequisite exercises.unittest.TestCaseand the test file should be named<EXERCISE-NAME>_test.py.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.