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31 changes: 31 additions & 0 deletions perfect-numbers/.exercism/config.json
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{
"authors": [
"behrtam"
],
"contributors": [
"cmccandless",
"Dog",
"emerali",
"ikhadykin",
"N-Parsons",
"olufotebig",
"pheanex",
"saurabhchalke",
"smalley",
"tqa236"
],
"files": {
"solution": [
"perfect_numbers.py"
],
"test": [
"perfect_numbers_test.py"
],
"example": [
".meta/example.py"
]
},
"blurb": "Determine if a number is perfect, abundant, or deficient based on Nicomachus' (60 - 120 CE) classification scheme for positive integers.",
"source": "Taken from Chapter 2 of Functional Thinking by Neal Ford.",
"source_url": "https://www.oreilly.com/library/view/functional-thinking/9781449365509/"
}
1 change: 1 addition & 0 deletions perfect-numbers/.exercism/metadata.json
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{"track":"python","exercise":"perfect-numbers","id":"21824e00793945d38db7a58a68bb9360","url":"https://exercism.org/tracks/python/exercises/perfect-numbers","handle":"myFirstCode","is_requester":true,"auto_approve":false}
130 changes: 130 additions & 0 deletions perfect-numbers/HELP.md
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# Help

## Running the tests

We use [pytest][pytest: Getting Started Guide] as our website test runner.
You will need to install `pytest` on your development machine if you want to run tests for the Python track locally.
You should also install the following `pytest` plugins:

- [pytest-cache][pytest-cache]
- [pytest-subtests][pytest-subtests]

Extended information can be found in our website [Python testing guide][Python track tests page].


### Running Tests

To run the included tests, navigate to the folder where the exercise is stored using `cd` in your terminal (_replace `{exercise-folder-location}` below with your path_).
Test files usually end in `_test.py`, and are the same tests that run on the website when a solution is uploaded.

Linux/MacOS
```bash
$ cd {path/to/exercise-folder-location}
```

Windows
```powershell
PS C:\Users\foobar> cd {path\to\exercise-folder-location}
```

<br>

Next, run the `pytest` command in your terminal, replacing `{exercise_test.py}` with the name of the test file:

Linux/MacOS
```bash
$ python3 -m pytest -o markers=task {exercise_test.py}
==================== 7 passed in 0.08s ====================
```

Windows
```powershell
PS C:\Users\foobar> py -m pytest -o markers=task {exercise_test.py}
==================== 7 passed in 0.08s ====================
```


### Common options
- `-o` : override default `pytest.ini` (_you can use this to avoid marker warnings_)
- `-v` : enable verbose output.
- `-x` : stop running tests on first failure.
- `--ff` : run failures from previous test before running other test cases.

For additional options, use `python3 -m pytest -h` or `py -m pytest -h`.


### Fixing warnings

If you do not use `pytest -o markers=task` when invoking `pytest`, you might receive a `PytestUnknownMarkWarning` for tests that use our new syntax:

```bash
PytestUnknownMarkWarning: Unknown pytest.mark.task - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/mark.html
```

To avoid typing `pytest -o markers=task` for every test you run, you can use a `pytest.ini` configuration file.
We have made one that can be downloaded from the top level of the Python track directory: [pytest.ini][pytest.ini].

You can also create your own `pytest.ini` file with the following content:

```ini
[pytest]
markers =
task: A concept exercise task.
```

Placing the `pytest.ini` file in the _root_ or _working_ directory for your Python track exercises will register the marks and stop the warnings.
More information on pytest marks can be found in the `pytest` documentation on [marking test functions][pytest: marking test functions with attributes] and the `pytest` documentation on [working with custom markers][pytest: working with custom markers].

Information on customizing pytest configurations can be found in the `pytest` documentation on [configuration file formats][pytest: configuration file formats].


### Extending your IDE or Code Editor

Many IDEs and code editors have built-in support for using `pytest` and other code quality tools.
Some community-sourced options can be found on our [Python track tools page][Python track tools page].

[Pytest: Getting Started Guide]: https://docs.pytest.org/en/latest/getting-started.html
[Python track tools page]: https://exercism.org/docs/tracks/python/tools
[Python track tests page]: https://exercism.org/docs/tracks/python/tests
[pytest-cache]:http://pythonhosted.org/pytest-cache/
[pytest-subtests]:https://github.com/pytest-dev/pytest-subtests
[pytest.ini]: https://github.com/exercism/python/blob/main/pytest.ini
[pytest: configuration file formats]: https://docs.pytest.org/en/6.2.x/customize.html#configuration-file-formats
[pytest: marking test functions with attributes]: https://docs.pytest.org/en/6.2.x/mark.html#raising-errors-on-unknown-marks
[pytest: working with custom markers]: https://docs.pytest.org/en/6.2.x/example/markers.html#working-with-custom-markers

## Submitting your solution

You can submit your solution using the `exercism submit perfect_numbers.py` command.
This command will upload your solution to the Exercism website and print the solution page's URL.

It's possible to submit an incomplete solution which allows you to:

- See how others have completed the exercise
- Request help from a mentor

## Need to get help?

If you'd like help solving the exercise, check the following pages:

- The [Python track's documentation](https://exercism.org/docs/tracks/python)
- The [Python track's programming category on the forum](https://forum.exercism.org/c/programming/python)
- [Exercism's programming category on the forum](https://forum.exercism.org/c/programming/5)
- The [Frequently Asked Questions](https://exercism.org/docs/using/faqs)

Should those resources not suffice, you could submit your (incomplete) solution to request mentoring.

Below are some resources for getting help if you run into trouble:

- [The PSF](https://www.python.org) hosts Python downloads, documentation, and community resources.
- [The Exercism Community on Discord](https://exercism.org/r/discord)
- [Python Community on Discord](https://pythondiscord.com/) is a very helpful and active community.
- [/r/learnpython/](https://www.reddit.com/r/learnpython/) is a subreddit designed for Python learners.
- [#python on Libera.chat](https://www.python.org/community/irc/) this is where the core developers for the language hang out and get work done.
- [Python Community Forums](https://discuss.python.org/)
- [Free Code Camp Community Forums](https://forum.freecodecamp.org/)
- [CodeNewbie Community Help Tag](https://community.codenewbie.org/t/help)
- [Pythontutor](http://pythontutor.com/) for stepping through small code snippets visually.

Additionally, [StackOverflow](http://stackoverflow.com/questions/tagged/python) is a good spot to search for your problem/question to see if it has been answered already.
If not - you can always [ask](https://stackoverflow.com/help/how-to-ask) or [answer](https://stackoverflow.com/help/how-to-answer) someone else's question.
80 changes: 80 additions & 0 deletions perfect-numbers/README.md
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# Perfect Numbers

Welcome to Perfect Numbers on Exercism's Python Track.
If you need help running the tests or submitting your code, check out `HELP.md`.

## Instructions

Determine if a number is perfect, abundant, or deficient based on Nicomachus' (60 - 120 CE) classification scheme for positive integers.

The Greek mathematician [Nicomachus][nicomachus] devised a classification scheme for positive integers, identifying each as belonging uniquely to the categories of [perfect](#perfect), [abundant](#abundant), or [deficient](#deficient) based on their [aliquot sum][aliquot-sum].
The _aliquot sum_ is defined as the sum of the factors of a number not including the number itself.
For example, the aliquot sum of `15` is `1 + 3 + 5 = 9`.

## Perfect

A number is perfect when it equals its aliquot sum.
For example:

- `6` is a perfect number because `1 + 2 + 3 = 6`
- `28` is a perfect number because `1 + 2 + 4 + 7 + 14 = 28`

## Abundant

A number is abundant when it is less than its aliquot sum.
For example:

- `12` is an abundant number because `1 + 2 + 3 + 4 + 6 = 16`
- `24` is an abundant number because `1 + 2 + 3 + 4 + 6 + 8 + 12 = 36`

## Deficient

A number is deficient when it is greater than its aliquot sum.
For example:

- `8` is a deficient number because `1 + 2 + 4 = 7`
- Prime numbers are deficient

## Task

Implement a way to determine whether a given number is [perfect](#perfect).
Depending on your language track, you may also need to implement a way to determine whether a given number is [abundant](#abundant) or [deficient](#deficient).

[nicomachus]: https://en.wikipedia.org/wiki/Nicomachus
[aliquot-sum]: https://en.wikipedia.org/wiki/Aliquot_sum

## Exception messages

Sometimes it is necessary to [raise an exception](https://docs.python.org/3/tutorial/errors.html#raising-exceptions). When you do this, you should always include a **meaningful error message** to indicate what the source of the error is. This makes your code more readable and helps significantly with debugging. For situations where you know that the error source will be a certain type, you can choose to raise one of the [built in error types](https://docs.python.org/3/library/exceptions.html#base-classes), but should still include a meaningful message.

This particular exercise requires that you use the [raise statement](https://docs.python.org/3/reference/simple_stmts.html#the-raise-statement) to "throw" a `ValueError` if the `classify()` function is passed a number that is not a _positive integer_. The tests will only pass if you both `raise` the `exception` and include a message with it.

To raise a `ValueError` with a message, write the message as an argument to the `exception` type:

```python
# if a number to be classified is less than 1.
raise ValueError("Classification is only possible for positive integers.")
```

## Source

### Created by

- @behrtam

### Contributed to by

- @cmccandless
- @Dog
- @emerali
- @ikhadykin
- @N-Parsons
- @olufotebig
- @pheanex
- @saurabhchalke
- @smalley
- @tqa236

### Based on

Taken from Chapter 2 of Functional Thinking by Neal Ford. - https://www.oreilly.com/library/view/functional-thinking/9781449365509/
35 changes: 35 additions & 0 deletions perfect-numbers/perfect_numbers.py
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"""
Determine if a number is perfect, abundant, or deficient based on
Nicomachus' (60 - 120 CE) classification scheme for positive integers.
"""

import math


def classify(number: int) -> str:
"""
A perfect number equals the sum of its positive divisors.

:param number: int a positive integer
:return: str the classification of the input integer
"""
if number < 1:
raise ValueError(
"Classification is only possible for positive integers."
)

total_divisors: int = 1

for n in range(2, int(math.sqrt(number)) + 1):
if number % n == 0:
total_divisors += n
if n != number // n:
total_divisors += number // n

if number == 1 or number > total_divisors:
return "deficient"

if total_divisors == number:
return "perfect"

return "abundant"
69 changes: 69 additions & 0 deletions perfect-numbers/perfect_numbers_test.py
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# pylint: disable=C0114, C0115, C0116, R0904
# These tests are auto-generated with test data from:
# https://github.com/exercism/problem-specifications/tree/main/exercises/perfect-numbers/canonical-data.json
# File last updated on 2023-07-19

import unittest

from perfect_numbers import (
classify,
)


class PerfectNumbersTest(unittest.TestCase):
def test_smallest_perfect_number_is_classified_correctly(self):
self.assertEqual(classify(6), "perfect")

def test_medium_perfect_number_is_classified_correctly(self):
self.assertEqual(classify(28), "perfect")

def test_large_perfect_number_is_classified_correctly(self):
self.assertEqual(classify(33550336), "perfect")


class AbundantNumbersTest(unittest.TestCase):
def test_smallest_abundant_number_is_classified_correctly(self):
self.assertEqual(classify(12), "abundant")

def test_medium_abundant_number_is_classified_correctly(self):
self.assertEqual(classify(30), "abundant")

def test_large_abundant_number_is_classified_correctly(self):
self.assertEqual(classify(33550335), "abundant")


class DeficientNumbersTest(unittest.TestCase):
def test_smallest_prime_deficient_number_is_classified_correctly(self):
self.assertEqual(classify(2), "deficient")

def test_smallest_non_prime_deficient_number_is_classified_correctly(self):
self.assertEqual(classify(4), "deficient")

def test_medium_deficient_number_is_classified_correctly(self):
self.assertEqual(classify(32), "deficient")

def test_large_deficient_number_is_classified_correctly(self):
self.assertEqual(classify(33550337), "deficient")

def test_edge_case_no_factors_other_than_itself_is_classified_correctly(self):
self.assertEqual(classify(1), "deficient")


class InvalidInputsTest(unittest.TestCase):
def test_zero_is_rejected_as_it_is_not_a_positive_integer(self):
with self.assertRaises(ValueError) as err:
classify(0)
self.assertEqual(type(err.exception), ValueError)
self.assertEqual(
err.exception.args[0],
"Classification is only possible for positive integers.",
)

def test_negative_integer_is_rejected_as_it_is_not_a_positive_integer(self):
with self.assertRaises(ValueError) as err:
classify(-1)
self.assertEqual(type(err.exception), ValueError)
self.assertEqual(
err.exception.args[0],
"Classification is only possible for positive integers.",
)
26 changes: 26 additions & 0 deletions solutions/python/perfect-numbers/1/perfect_numbers.py
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"""
Determine if a number is perfect, abundant, or deficient based on
Nicomachus' (60 - 120 CE) classification scheme for positive integers.
"""


def classify(number: int) -> str:
"""
A perfect number equals the sum of its positive divisors.

:param number: int a positive integer
:return: str the classification of the input integer
"""
if number < 1:
raise ValueError(
"Classification is only possible for positive integers."
)

total_divisors: int = sum(i for i in range(1, number) if number % i == 0)

if total_divisors == number:
return "perfect"
if number < total_divisors:
return "abundant"

return "deficient"