primeiro commit com exercicios de Exercism realizados até esta data
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{
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"authors": [
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"behrtam"
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],
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"contributors": [
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"cmccandless",
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"Dog",
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"emerali",
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"ikhadykin",
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"N-Parsons",
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"olufotebig",
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"pheanex",
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"saurabhchalke",
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"smalley",
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"tqa236"
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],
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"files": {
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"solution": [
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"perfect_numbers.py"
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],
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"test": [
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"perfect_numbers_test.py"
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],
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"example": [
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".meta/example.py"
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]
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},
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"blurb": "Determine if a number is perfect, abundant, or deficient based on Nicomachus' (60 - 120 CE) classification scheme for positive integers.",
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"source": "Taken from Chapter 2 of Functional Thinking by Neal Ford.",
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"source_url": "https://www.oreilly.com/library/view/functional-thinking/9781449365509/"
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}
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{"track":"python","exercise":"perfect-numbers","id":"effeada50c8449bb9bdda35ab14b2a88","url":"https://exercism.org/tracks/python/exercises/perfect-numbers","handle":"sanctushck","is_requester":true,"auto_approve":false}
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# Help
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## Running the tests
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We use [pytest][pytest: Getting Started Guide] as our website test runner.
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You will need to install `pytest` on your development machine if you want to run tests for the Python track locally.
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You should also install the following `pytest` plugins:
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- [pytest-cache][pytest-cache]
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- [pytest-subtests][pytest-subtests]
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Extended information can be found in our website [Python testing guide][Python track tests page].
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### Running Tests
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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_).
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Test files usually end in `_test.py`, and are the same tests that run on the website when a solution is uploaded.
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Linux/MacOS
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```bash
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$ cd {path/to/exercise-folder-location}
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```
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Windows
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```powershell
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PS C:\Users\foobar> cd {path\to\exercise-folder-location}
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```
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<br>
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Next, run the `pytest` command in your terminal, replacing `{exercise_test.py}` with the name of the test file:
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Linux/MacOS
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```bash
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$ python3 -m pytest -o markers=task {exercise_test.py}
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==================== 7 passed in 0.08s ====================
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```
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Windows
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```powershell
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PS C:\Users\foobar> py -m pytest -o markers=task {exercise_test.py}
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==================== 7 passed in 0.08s ====================
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```
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### Common options
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- `-o` : override default `pytest.ini` (_you can use this to avoid marker warnings_)
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- `-v` : enable verbose output.
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- `-x` : stop running tests on first failure.
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- `--ff` : run failures from previous test before running other test cases.
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For additional options, use `python3 -m pytest -h` or `py -m pytest -h`.
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### Fixing warnings
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If you do not use `pytest -o markers=task` when invoking `pytest`, you might receive a `PytestUnknownMarkWarning` for tests that use our new syntax:
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```bash
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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
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```
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To avoid typing `pytest -o markers=task` for every test you run, you can use a `pytest.ini` configuration file.
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We have made one that can be downloaded from the top level of the Python track directory: [pytest.ini][pytest.ini].
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You can also create your own `pytest.ini` file with the following content:
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```ini
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[pytest]
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markers =
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task: A concept exercise task.
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```
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Placing the `pytest.ini` file in the _root_ or _working_ directory for your Python track exercises will register the marks and stop the warnings.
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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].
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Information on customizing pytest configurations can be found in the `pytest` documentation on [configuration file formats][pytest: configuration file formats].
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### Extending your IDE or Code Editor
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Many IDEs and code editors have built-in support for using `pytest` and other code quality tools.
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Some community-sourced options can be found on our [Python track tools page][Python track tools page].
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[Pytest: Getting Started Guide]: https://docs.pytest.org/en/latest/getting-started.html
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[Python track tools page]: https://exercism.org/docs/tracks/python/tools
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[Python track tests page]: https://exercism.org/docs/tracks/python/tests
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[pytest-cache]:http://pythonhosted.org/pytest-cache/
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[pytest-subtests]:https://github.com/pytest-dev/pytest-subtests
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[pytest.ini]: https://github.com/exercism/python/blob/main/pytest.ini
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[pytest: configuration file formats]: https://docs.pytest.org/en/6.2.x/customize.html#configuration-file-formats
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[pytest: marking test functions with attributes]: https://docs.pytest.org/en/6.2.x/mark.html#raising-errors-on-unknown-marks
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[pytest: working with custom markers]: https://docs.pytest.org/en/6.2.x/example/markers.html#working-with-custom-markers
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## Submitting your solution
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You can submit your solution using the `exercism submit perfect_numbers.py` command.
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This command will upload your solution to the Exercism website and print the solution page's URL.
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It's possible to submit an incomplete solution which allows you to:
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- See how others have completed the exercise
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- Request help from a mentor
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## Need to get help?
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If you'd like help solving the exercise, check the following pages:
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- The [Python track's documentation](https://exercism.org/docs/tracks/python)
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- The [Python track's programming category on the forum](https://forum.exercism.org/c/programming/python)
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- [Exercism's programming category on the forum](https://forum.exercism.org/c/programming/5)
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- The [Frequently Asked Questions](https://exercism.org/docs/using/faqs)
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Should those resources not suffice, you could submit your (incomplete) solution to request mentoring.
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Below are some resources for getting help if you run into trouble:
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- [The PSF](https://www.python.org) hosts Python downloads, documentation, and community resources.
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- [The Exercism Community on Discord](https://exercism.org/r/discord)
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- [Python Community on Discord](https://pythondiscord.com/) is a very helpful and active community.
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- [/r/learnpython/](https://www.reddit.com/r/learnpython/) is a subreddit designed for Python learners.
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- [#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.
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- [Python Community Forums](https://discuss.python.org/)
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- [Free Code Camp Community Forums](https://forum.freecodecamp.org/)
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- [CodeNewbie Community Help Tag](https://community.codenewbie.org/t/help)
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- [Pythontutor](http://pythontutor.com/) for stepping through small code snippets visually.
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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.
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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.
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# Perfect Numbers
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Welcome to Perfect Numbers on Exercism's Python Track.
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If you need help running the tests or submitting your code, check out `HELP.md`.
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## Instructions
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Determine if a number is perfect, abundant, or deficient based on Nicomachus' (60 - 120 CE) classification scheme for positive integers.
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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].
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The _aliquot sum_ is defined as the sum of the factors of a number not including the number itself.
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For example, the aliquot sum of `15` is `1 + 3 + 5 = 9`.
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## Perfect
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A number is perfect when it equals its aliquot sum.
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For example:
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- `6` is a perfect number because `1 + 2 + 3 = 6`
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- `28` is a perfect number because `1 + 2 + 4 + 7 + 14 = 28`
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## Abundant
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A number is abundant when it is less than its aliquot sum.
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For example:
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- `12` is an abundant number because `1 + 2 + 3 + 4 + 6 = 16`
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- `24` is an abundant number because `1 + 2 + 3 + 4 + 6 + 8 + 12 = 36`
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## Deficient
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A number is deficient when it is greater than its aliquot sum.
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For example:
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- `8` is a deficient number because `1 + 2 + 4 = 7`
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- Prime numbers are deficient
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## Task
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Implement a way to determine whether a given number is [perfect](#perfect).
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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).
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[nicomachus]: https://en.wikipedia.org/wiki/Nicomachus
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[aliquot-sum]: https://en.wikipedia.org/wiki/Aliquot_sum
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## Exception messages
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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.
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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.
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To raise a `ValueError` with a message, write the message as an argument to the `exception` type:
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```python
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# if a number to be classified is less than 1.
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raise ValueError("Classification is only possible for positive integers.")
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```
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## Source
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### Created by
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- @behrtam
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### Contributed to by
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- @cmccandless
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- @Dog
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- @emerali
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- @ikhadykin
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- @N-Parsons
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- @olufotebig
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- @pheanex
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- @saurabhchalke
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- @smalley
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- @tqa236
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### Based on
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Taken from Chapter 2 of Functional Thinking by Neal Ford. - https://www.oreilly.com/library/view/functional-thinking/9781449365509/
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def classify(number):
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"""A perfect number equals the sum of its positive divisors.
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:param number: int a positive integer
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:return: str the classification of the input integer
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"""
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if number <= 0:
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raise ValueError(
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"Classification is only possible for positive integers.")
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aliquot_sum: int = 0
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# find divisors and store them in a list
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for divisor in range(1, (number // 2) + 1):
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if not number % divisor:
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aliquot_sum += divisor
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if aliquot_sum == number:
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return "perfect"
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elif aliquot_sum > number:
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return "abundant"
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else:
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return "deficient"
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# These tests are auto-generated with test data from:
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# https://github.com/exercism/problem-specifications/tree/main/exercises/perfect-numbers/canonical-data.json
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# File last updated on 2023-07-19
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import unittest
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from perfect_numbers import (
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classify,
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)
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class PerfectNumbersTest(unittest.TestCase):
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def test_smallest_perfect_number_is_classified_correctly(self):
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self.assertEqual(classify(6), "perfect")
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def test_medium_perfect_number_is_classified_correctly(self):
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self.assertEqual(classify(28), "perfect")
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def test_large_perfect_number_is_classified_correctly(self):
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self.assertEqual(classify(33550336), "perfect")
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class AbundantNumbersTest(unittest.TestCase):
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def test_smallest_abundant_number_is_classified_correctly(self):
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self.assertEqual(classify(12), "abundant")
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def test_medium_abundant_number_is_classified_correctly(self):
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self.assertEqual(classify(30), "abundant")
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def test_large_abundant_number_is_classified_correctly(self):
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self.assertEqual(classify(33550335), "abundant")
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class DeficientNumbersTest(unittest.TestCase):
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def test_smallest_prime_deficient_number_is_classified_correctly(self):
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self.assertEqual(classify(2), "deficient")
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def test_smallest_non_prime_deficient_number_is_classified_correctly(self):
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self.assertEqual(classify(4), "deficient")
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def test_medium_deficient_number_is_classified_correctly(self):
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self.assertEqual(classify(32), "deficient")
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def test_large_deficient_number_is_classified_correctly(self):
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self.assertEqual(classify(33550337), "deficient")
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def test_edge_case_no_factors_other_than_itself_is_classified_correctly(self):
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self.assertEqual(classify(1), "deficient")
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class InvalidInputsTest(unittest.TestCase):
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def test_zero_is_rejected_as_it_is_not_a_positive_integer(self):
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with self.assertRaises(ValueError) as err:
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classify(0)
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self.assertEqual(type(err.exception), ValueError)
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self.assertEqual(
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err.exception.args[0],
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"Classification is only possible for positive integers.",
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)
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def test_negative_integer_is_rejected_as_it_is_not_a_positive_integer(self):
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with self.assertRaises(ValueError) as err:
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classify(-1)
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self.assertEqual(type(err.exception), ValueError)
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self.assertEqual(
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err.exception.args[0],
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"Classification is only possible for positive integers.",
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)
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