Python: completed Meltdown Mitigation

python/card-games/.exercism/config.json

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+{
+  "authors": [
+    "itamargal",
+    "isaacg",
+    "bethanyg"
+  ],
+  "contributors": [
+    "valentin-p",
+    "pranasziaukas"
+  ],
+  "files": {
+    "solution": [
+      "lists.py"
+    ],
+    "test": [
+      "lists_test.py"
+    ],
+    "exemplar": [
+      ".meta/exemplar.py"
+    ]
+  },
+  "icon": "poker",
+  "blurb": "Learn about lists by tracking hands in card games."
+}

python/card-games/.exercism/metadata.json

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+{"track":"python","exercise":"card-games","id":"47aa83e6f3eb45219f2ef38dc238d4e2","url":"https://exercism.org/tracks/python/exercises/card-games","handle":"Chomp1295","is_requester":true,"auto_approve":false}

python/card-games/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 lists.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.

python/card-games/HINTS.md

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+# Hints
+
+## General
+
+## 1. Tracking Poker Rounds
+
+- Lists in Python may be [constructed][constructed] in multiple ways.
+- This function should [return][return] a `list`.
+
+## 2. Keeping all Rounds in the Same Place
+
+- Sequence types such as `list` support [common operations][common sequence operations].
+- This function should [return][return] a `list`.
+
+## 3. Finding Prior Rounds
+
+- Sequence types such as `list` support a few [common operations][common sequence operations].
+- This function should [return][return] a `bool`.
+
+## 4. Averaging Card Values
+
+- To get the average, this function should count how many items are in the `list` and sum up their values. Then, return the sum divided by the count.
+
+## 5. Alternate Averages
+
+- Sequence types such as `list` support a few [common operations][common sequence operations].
+- To access an element, use the square brackets (`<list>[]`) notation.
+- Remember that the first element of the `list` is at index 0 from the **left-hand** side.
+- In Python, negative indexing starts at -1 from the **right-hand** side. This means that you can find the last element of a `list` by using `<list>[-1]`.
+- Think about how you could reuse the code from the functions that you have already implemented.
+
+## 6. More Averaging Techniques
+
+- Sequence types such as `list` already support a few [common operations][common sequence operations].
+- Think about reusing the code from the functions that you just implemented.
+- The slice syntax supports a _step value_ (`<list>[<start>:<stop>:<step>]`).
+
+## 7. Bonus Round Rules
+
+- Lists are _mutable_. Once a `list` is created, you can modify, delete or add any type of element you wish.
+- Python provides a wide range of [ways to modify `lists`][ways to modify `lists`].
+
+
+[common sequence operations]: https://docs.python.org/3/library/stdtypes.html#sequence-types-list-tuple-range
+[constructed]: https://docs.python.org/3/library/stdtypes.html#list
+[return]: https://www.w3schools.com/python/ref_keyword_return.asp
+[ways to modify `lists`]: https://realpython.com/python-lists-tuples/#lists-are-mutable

python/card-games/README.md

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+# Card Games
+
+Welcome to Card Games on Exercism's Python Track.
+If you need help running the tests or submitting your code, check out `HELP.md`.
+If you get stuck on the exercise, check out `HINTS.md`, but try and solve it without using those first :)
+
+## Introduction
+
+A [`list`][list] is a mutable collection of items in _sequence_.
+Like most collections (_see the built-ins [`tuple`][tuple], [`dict`][dict] and [`set`][set]_), lists can hold reference to any (or multiple) data type(s) - including other lists.
+Like any [sequence][sequence type], items can be accessed via `0-based index` number from the left and `-1-based index` from the right.
+Lists can be copied in whole or in part via [slice notation][slice notation] or `<list>.copy()`.
+
+Lists support both [common][common sequence operations] and [mutable][mutable sequence operations] sequence operations such as `min()`/`max()`, `<list>.index()`, `<list>.append()` and `<list>.reverse()`.
+List elements can be iterated over using the `for item in <list>` construct.
+ `for index, item in enumerate(<list>)` can be used when both the element index and the element value are needed.
+
+Under the hood, `lists` are implemented as [dynamic arrays][dynamic array] -- similar to Java's [`ArrayList`][arraylist] type, and are most often used to store groups of similar data (_strings, numbers, sets etc._) of unknown length.
+Lists are an extremely flexible and useful data structure and many built-in methods and operations in Python produce lists as their output.
+
+
+## Construction
+
+A `list` can be declared as a _literal_ with square `[]` brackets and commas between elements:
+
+
+```python
+>>> no_elements = []
+
+>>> no_elements
+[]
+
+>>> one_element = ["Guava"]
+
+>>> one_element
+['Guava']
+
+>>> elements_separated_with_commas = ["Parrot", "Bird", 334782]
+
+>>> elements_separated_with_commas
+['Parrot', 'Bird', 334782]
+```
+
+For readability, line breaks can be used when there are many elements or nested data structures within a `list`:
+
+
+```python
+>>> lots_of_entries = [
+      "Rose",
+      "Sunflower",
+      "Poppy",
+      "Pansy",
+      "Tulip",
+      "Fuchsia",
+      "Cyclamen",
+      "Lavender"
+   ]
+   
+>>> lots_of_entries
+['Rose', 'Sunflower', 'Poppy', 'Pansy', 'Tulip', 'Fuchsia', 'Cyclamen', 'Lavender']
+
+# Each data structure is on its own line to help clarify what they are.
+>>> nested_data_structures = [
+      {"fish": "gold", "monkey": "brown", "parrot": "grey"},
+      ("fish", "mammal", "bird"),
+      ['water', 'jungle', 'sky']
+   ]
+   
+>>> nested_data_structures
+[{'fish': 'gold', 'monkey': 'brown', 'parrot': 'grey'}, ('fish', 'mammal', 'bird'), ['water', 'jungle', 'sky']]
+```
+
+The `list()` constructor can be used empty or with an _iterable_ as an argument.
+ Elements in the iterable are cycled through by the constructor and added to the `list` in order:
+
+
+```python
+>>> no_elements = list()
+
+>>> no_elements
+[]
+
+# The tuple is unpacked and each element is added.
+>>> multiple_elements_from_tuple = list(("Parrot", "Bird", 334782))
+
+>>> multiple_elements_from_tuple
+['Parrot', 'Bird', 334782]
+
+# The set is unpacked and each element is added.
+>>> multiple_elements_from_set = list({2, 3, 5, 7, 11})
+
+>>> multiple_elements_from_set
+[2, 3, 5, 7, 11]
+```
+
+Results when using a `list` constructor with a `string` or a `dict` may be surprising:
+
+
+```python
+# String elements (Unicode code points) are iterated through and added *individually*.
+>>> multiple_elements_string = list("Timbuktu")
+
+>>> multiple_elements_string
+['T', 'i', 'm', 'b', 'u', 'k', 't', 'u']
+
+# Unicode separators and positioning code points are also added *individually*.
+>>> multiple_code_points_string = list('अभ्यास')
+
+>>> multiple_code_points_string
+['अ', 'भ', '्', 'य', 'ा', 'स']
+
+# The iteration default for dictionaries is over the keys, so only key data is inserted into the list.
+>>> source_data = {"fish": "gold", "monkey": "brown"}
+
+>>> multiple_elements_dict_1 = list(source_data)
+['fish', 'monkey']
+```
+
+Because the `list` constructor will only take _iterables_ (or nothing) as arguments, objects that are _not_ iterable will throw a type error.
+ Consequently, it is much easier to create a one-item `list` via the literal method.
+
+```python
+# Numbers are not iterable, and so attempting to create a list with a number passed to the constructor fails.
+>>> one_element = list(16)
+Traceback (most recent call last):
+  File "<stdin>", line 1, in <module>
+TypeError: 'int' object is not iterable
+
+# Tuples *are* iterable, so passing a one-element tuple to the constructor does work, but it's awkward
+>>> one_element_from_iterable = list((16,))
+
+>>> one_element_from_iterable
+[16]
+```
+
+## Accessing elements
+
+Items inside lists (_as well as items in other sequence types `str` & `tuple`_) can be accessed via `0-based index` and _bracket notation_.
+ Indexes can be from **`left`** --> **`right`** (_starting at zero_) or **`right`** --> **`left`** (_starting at -1_).
+
+
+<table>
+<tr>
+  <td style="vertical-align: top"> index from left ⟹<br><br><br><br><br><br><br></td><td style="vertical-align: middle">
+
+|  0<br>👇🏾 	|  1<br>👇🏾 	|  2<br>👇🏾 	|  3<br>👇🏾 	|  4<br>👇🏾 	|  5<br>👇🏾 	|
+|:--------:	|:--------:	|:--------:	|:--------:	|:--------:	|:--------:	|
+|     P    	|     y    	|     t    	|     h    	|     o    	|     n    	|
+| 👆🏾<br>-6 	| 👆🏾<br>-5 	| 👆🏾<br>-4 	| 👆🏾<br>-3 	| 👆🏾<br>-2 	| 👆🏾<br>-1 	|
+</td><td style="vertical-align: bottom"><br><br><br><br><br>⟸ index from right</td>
+</tr>
+</table>
+
+
+```python
+>>> breakfast_foods = ["Oatmeal", "Fruit Salad", "Eggs", "Toast"]
+
+# Oatmeal is at index 0 or index -4.
+>>> breakfast_foods[0]
+'Oatmeal'
+
+>>> breakfast_foods[-4]
+'Oatmeal'
+
+# Eggs are at index -2 or 2
+>>> breakfast_foods[-2]
+'Eggs'
+
+>>> breakfast_foods[2]
+'Eggs'
+
+# Toast is at -1
+>>> breakfast_foods[-1]
+'Toast'
+```
+
+A section of the elements inside a `list` can be accessed via _slice notation_ (`<list>[start:stop]`).
+ A _slice_ is defined as an element sequence at position `index`, such that `start <= index < stop`.
+ _Slicing_ returns a copy of the "sliced" items and does not modify the original `list`.
+
+
+A `step` parameter can also be used `[start:stop:step]` to "skip over" or filter the `list` elements (_for example, a `step` of 2 will select every other element in the range_):
+
+
+```python
+>>> colors = ["Red", "Purple", "Green", "Yellow", "Orange", "Pink", "Blue", "Grey"]
+
+# If there is no step parameter, the step is assumed to be 1.
+>>> middle_colors = colors[2:6]
+
+>>> middle_colors
+['Green', 'Yellow', 'Orange', 'Pink']
+
+# If the start or stop parameters are omitted, the slice will
+# start at index zero, and will stop at the end of the list.
+>>> primary_colors = colors[::3]
+
+>>> primary_colors
+['Red', 'Yellow', 'Blue']
+```
+
+## Working with lists
+
+The usage of the built-in `sum()` function on a list will return the sum of all the numbers in the list:
+
+```python
+>>> number_list = [1, 2, 3, 4]
+>>> sum(number_list)
+10
+```
+
+You can also get the _length_ of a list by using the `len()` function:
+
+```python
+>>> long_list = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J"]
+>>> len(long_list)
+10
+```
+
+Lists can be also combined in various ways:
+
+```python
+# Using the plus + operator unpacks each list and creates a new list, but it is not efficient.
+>>> new_via_concatenate = ["George", 5] + ["cat", "Tabby"]
+
+>>> new_via_concatenate
+['George', 5, 'cat', 'Tabby']
+
+# Likewise, using the multiplication operator * is the equivalent of using + n times.
+>>> first_group = ["cat", "dog", "elephant"]
+>>> multiplied_group = first_group * 3
+
+>>> multiplied_group
+['cat', 'dog', 'elephant', 'cat', 'dog', 'elephant', 'cat', 'dog', 'elephant']
+```
+
+Lists supply an _iterator_, and can be looped through/over in the same manner as other _sequence types_.
+
+```python
+#  Looping through the list and printing out each element.
+>>> colors = ["Orange", "Green", "Grey", "Blue"]
+
+>>> for item in colors:
+...     print(item)
+...
+Orange
+Green
+Grey
+Blue
+```
+
+_For a more in-depth explanation, of `loops` and `iterators`, complete the `loops` concept._
+
+[arraylist]: https://beginnersbook.com/2013/12/java-arraylist/
+[common sequence operations]: https://docs.python.org/3/library/stdtypes.html#common-sequence-operations
+[dict]: https://docs.python.org/3/library/stdtypes.html#dict
+[dynamic array]: https://en.wikipedia.org/wiki/Dynamic_array
+[list]: https://docs.python.org/3/library/stdtypes.html#list
+[mutable sequence operations]: https://docs.python.org/3/library/stdtypes.html#typesseq-mutable
+[sequence type]: https://docs.python.org/3/library/stdtypes.html#sequence-types-list-tuple-range
+[set]: https://docs.python.org/3/library/stdtypes.html#set
+[slice notation]: https://docs.python.org/3/reference/expressions.html#slicings
+[tuple]: https://docs.python.org/3/library/stdtypes.html#tuple
+
+## Instructions
+
+Elyse is really looking forward to playing some poker (and other card games) during her upcoming trip to Vegas.
+ Being a big fan of "self-tracking" she wants to put together some small functions that will help her with tracking tasks and has asked for your help thinking them through.
+
+## 1. Tracking Poker Rounds
+
+Elyse is especially fond of poker, and wants to track how many rounds she plays - and _which rounds_ those are.
+ Every round has its own number, and every table shows the round number currently being played.
+ Elyse chooses a table and sits down to play her first round. She plans on playing three rounds.
+
+Implement a function `get_rounds(<round_number>)` that takes the current round number and returns a single `list` with that round and the _next two_ that are coming up:
+
+```python
+>>> get_rounds(27)
+[27, 28, 29]
+```
+
+## 2. Keeping all Rounds in the Same Place
+
+Elyse played a few rounds at the first table, then took a break and played some more rounds at a second table ... but ended up with a different list for each table!
+ She wants to put the two lists together, so she can track all of the poker rounds in the same place.
+
+Implement a function `concatenate_rounds(<rounds_1>, <rounds_2>)` that takes two lists and returns a single `list` consisting of all the rounds in the first `list`, followed by all the rounds in the second `list`:
+
+```python
+>>> concatenate_rounds([27, 28, 29], [35, 36])
+[27, 28, 29, 35, 36]
+```
+
+## 3. Finding Prior Rounds
+
+Talking about some of the prior Poker rounds, another player remarks how similarly two of them played out.
+ Elyse is not sure if she played those rounds or not.
+
+Implement a function `list_contains_round(<rounds>, <round_number>)` that takes two arguments, a list of rounds played and a round number.
+ The function will return `True` if the round is in the list of rounds played, `False` if not:
+
+```python
+>>> list_contains_round([27, 28, 29, 35, 36], 29)
+True
+
+>>> list_contains_round([27, 28, 29, 35, 36], 30)
+False
+```
+
+## 4. Averaging Card Values
+
+Elyse wants to try out a new game called Black Joe.
+ It's similar to Black Jack - where your goal is to have the cards in your hand add up to a target value - but in Black Joe the goal is to get the _average_ of the card values to be 7.
+ The average can be found by summing up all the card values and then dividing that sum by the number of cards in the hand.
+
+Implement a function `card_average(<hand>)` that will return the average value of a hand of Black Joe.
+
+```python
+>>> card_average([5, 6, 7])
+6.0
+```
+
+## 5. Alternate Averages
+
+In Black Joe, speed is important. Elyse is going to try and find a faster way of finding the average.
+
+She has thought of two ways of getting an _average-like_ number:
+
+- Take the average of the _first_ and _last_ number in the hand.
+- Using the median (middle card) of the hand.
+  
+Implement the function `approx_average_is_average(<hand>)`, given `hand`, a list containing the values of the cards in your hand.
+
+Return `True` if either _one_ `or` _both_ of the, above named, strategies result in a number _equal_ to the _actual average_.
+
+Note: _The length of all hands are odd, to make finding a median easier._
+
+```python
+>>> approx_average_is_average([1, 2, 3])
+True
+
+>>> approx_average_is_average([2, 3, 4, 8, 8])
+True
+
+>>> approx_average_is_average([1, 2, 3, 5, 9])
+False
+```
+
+## 6. More Averaging Techniques
+
+Intrigued by the results of her averaging experiment, Elyse is wondering if taking the average of the cards at the _even_ positions versus the average of the cards at the _odd_ positions would give the same results.
+ Time for another test function!
+
+Implement a function `average_even_is_average_odd(<hand>)` that returns a Boolean indicating if the average of the cards at even indexes is the same as the average of the cards at odd indexes.
+
+```python
+>>> average_even_is_average_odd([1, 2, 3])
+True
+
+>>> average_even_is_average_odd([1, 2, 3, 4])
+False
+```
+
+## 7. Bonus Round Rules
+
+Every 11th hand in Black Joe is a bonus hand with a bonus rule: if the last card you draw is a Jack, you double its value.
+
+Implement a function `maybe_double_last(<hand>)` that takes a hand and checks if the last card is a Jack (11).
+ If the last card **is** a Jack (11), double its value before returning the hand.
+
+```python
+>>> hand = [5, 9, 11]
+>>> maybe_double_last(hand)
+[5, 9, 22]
+
+>>> hand = [5, 9, 10]
+>>> maybe_double_last(hand)
+[5, 9, 10]
+```
+
+## Source
+
+### Created by
+
+- @itamargal
+- @isaacg
+- @bethanyg
+
+### Contributed to by
+
+- @valentin-p
+- @pranasziaukas

python/card-games/lists.py

@@ -0,0 +1,81 @@
+"""Functions for tracking poker hands and assorted card tasks.
+
+Python list documentation: https://docs.python.org/3/tutorial/datastructures.html
+"""
+
+
+def get_rounds(number):
+    """Create a list containing the current and next two round numbers.
+
+    :param number: int - current round number.
+    :return: list - current round and the two that follow.
+    """
+
+    return [number, number + 1, number + 2]
+
+
+def concatenate_rounds(rounds_1, rounds_2):
+    """Concatenate two lists of round numbers.
+
+    :param rounds_1: list - first rounds played.
+    :param rounds_2: list - second set of rounds played.
+    :return: list - all rounds played.
+    """
+
+    return rounds_1 + rounds_2
+
+
+def list_contains_round(rounds, number):
+    """Check if the list of rounds contains the specified number.
+
+    :param rounds: list - rounds played.
+    :param number: int - round number.
+    :return: bool - was the round played?
+    """
+    return number in rounds
+
+
+def card_average(hand):
+    """Calculate and returns the average card value from the list.
+
+    :param hand: list - cards in hand.
+    :return: float - average value of the cards in the hand.
+    """
+    return sum(hand) / len(hand)
+
+
+def approx_average_is_average(hand):
+    """Return if the (average of first and last card values) OR ('middle' card) == calculated average.
+
+    :param hand: list - cards in hand.
+    :return: bool - does one of the approximate averages equal the `true average`?
+    """
+
+    size = len(hand)
+    actual_avg = card_average(hand)
+    first_last = (hand[0] + hand[size - 1]) / 2
+    median = hand[size // 2]
+
+    return actual_avg in (first_last, median)
+
+
+def average_even_is_average_odd(hand):
+    """Return if the (average of even indexed card values) == (average of odd indexed card values).
+
+    :param hand: list - cards in hand.
+    :return: bool - are even and odd averages equal?
+    """
+    return card_average(hand[::2]) == card_average(hand[1::2])
+
+
+def maybe_double_last(hand):
+    """Multiply a Jack card value in the last index position by 2.
+
+    :param hand: list - cards in hand.
+    :return: list - hand with Jacks (if present) value doubled.
+    """
+
+    if hand[-1] == 11:
+        hand[-1] *= 2
+
+    return hand

python/card-games/lists_test.py

@@ -0,0 +1,137 @@
+import unittest
+import pytest
+
+from lists import (
+    get_rounds,
+    concatenate_rounds,
+    list_contains_round,
+    card_average,
+    approx_average_is_average,
+    average_even_is_average_odd,
+    maybe_double_last,
+)
+
+
+class CardGamesTest(unittest.TestCase):
+
+    @pytest.mark.task(taskno=1)
+    def test_get_rounds(self):
+
+        input_data = [0, 1, 10, 27, 99, 666]
+        result_data = [[0, 1, 2], [1, 2, 3],
+                       [10, 11, 12], [27, 28, 29],
+                       [99, 100, 101], [666, 667, 668]]
+
+        for variant, (number, expected) in enumerate(zip(input_data, result_data), start=1):
+            with self.subTest(f'variation #{variant}', number=number, expected=expected):
+                actual_result = get_rounds(number)
+                error_message = (f'Called get_rounds({number}). '
+                                 f'The function returned {actual_result}, '
+                                 f'but the tests expected rounds {expected} '
+                                 f'given the current round {number}.')
+
+                self.assertEqual(actual_result, expected, msg=error_message)
+
+    @pytest.mark.task(taskno=2)
+    def test_concatenate_rounds(self):
+
+        input_data = [([], []), ([0, 1], []), ([], [1, 2]),
+                      ([1], [2]), ([27, 28, 29], [35, 36]),
+                      ([1, 2, 3], [4, 5, 6])]
+
+        result_data = [[], [0, 1], [1, 2], [1, 2],
+                       [27, 28, 29, 35, 36],
+                       [1, 2, 3, 4, 5, 6]]
+
+        for variant, ((rounds_1, rounds_2), expected) in enumerate(zip(input_data, result_data), start=1):
+            with self.subTest(f'variation #{variant}', rounds_1=rounds_1, rounds_2=rounds_2, expected=expected):
+                actual_result = concatenate_rounds(rounds_1, rounds_2)
+                error_message = (f'Called concatenate_rounds({rounds_1}, {rounds_2}). '
+                                 f'The function returned {actual_result}, but the tests '
+                                 f'expected {expected} as the concatenation '
+                                 f'of {rounds_1} and {rounds_2}.')
+
+                self.assertEqual(actual_result, expected, msg=error_message)
+
+    @pytest.mark.task(taskno=3)
+    def test_list_contains_round(self):
+
+        input_data = [([], 1), ([1, 2, 3], 0),
+                      ([27, 28, 29, 35, 36], 30),
+                      ([1], 1), ([1, 2, 3], 1),
+                      ([27, 28, 29, 35, 36], 29)]
+        result_data = [False, False, False, True, True, True]
+
+        for variant, ((rounds, round_number), expected) in enumerate(zip(input_data, result_data), start=1):
+            with self.subTest(f'variation #{variant}', rounds=rounds, round_number=round_number, expected=expected):
+                actual_result = list_contains_round(rounds, round_number)
+                error_message = (f'Called list_contains_round({rounds}, {round_number}). '
+                                 f'The function returned {actual_result}, but round {round_number} '
+                                 f'{"is" if expected else "is not"} in {rounds}.')
+
+                self.assertEqual(actual_result, expected, msg=error_message)
+
+    @pytest.mark.task(taskno=4)
+    def test_card_average(self):
+
+        input_data = [[1], [5, 6, 7], [1, 2, 3, 4], [1, 10, 100]]
+        result_data = [1.0, 6.0, 2.5, 37.0]
+
+        for variant, (hand, expected) in enumerate(zip(input_data, result_data), start=1):
+            with self.subTest(f'variation #{variant}', hand=hand, expected=expected):
+                actual_result = card_average(hand)
+                error_message = (f'Called card_average({hand}). '
+                                 f'The function returned {actual_result}, but '
+                                 f'the tests expected {expected} as the average of {hand}.')
+
+                self.assertEqual(actual_result, expected, msg=error_message)
+
+    @pytest.mark.task(taskno=5)
+    def test_approx_average_is_average(self):
+
+        input_data = [[0, 1, 5], [3, 6, 9, 12, 150], [1, 2, 3, 5, 9],
+                      [2, 3, 4, 7, 8], [1, 2, 3], [2, 3, 4],
+                      [2, 3, 4, 8, 8], [1, 2, 4, 5, 8]]
+
+        result_data = [False, False, False, False, True, True, True, True]
+
+        for variant, (hand, expected) in enumerate(zip(input_data, result_data), start=1):
+            with self.subTest(f'variation #{variant}', hand=hand, expected=expected):
+                actual_result = approx_average_is_average(hand)
+                error_message = (f'Called approx_average_is_average({hand}). '
+                                 f'The function returned {actual_result}, but '
+                                 f'the hand {hand} {"does" if expected else "does not"} '
+                                 f'yield the same approximate average.')
+
+                self.assertEqual(actual_result, expected, msg=error_message)
+
+    @pytest.mark.task(taskno=6)
+    def test_average_even_is_average_odd(self):
+
+        input_data = [[5, 6, 8], [1, 2, 3, 4], [1, 2, 3], [5, 6, 7], [1, 3, 5, 7, 9]]
+        result_data = [False, False, True, True, True]
+
+        for variant, (input_hand, expected) in enumerate(zip(input_data, result_data), start=1):
+            with self.subTest(f'variation #{variant}', input_hand=input_hand, expected=expected):
+                actual_result = average_even_is_average_odd(input_hand)
+                error_message = (f'Called average_even_is_average_odd({input_hand}). '
+                                 f'The function returned {actual_result}, but '
+                                 f'the hand {"does" if expected else "does not"} '
+                                 f'yield the same odd-even average.')
+
+                self.assertEqual(actual_result, expected, msg=error_message)
+
+    @pytest.mark.task(taskno=7)
+    def test_maybe_double_last(self):
+
+        input_data = [(1, 2, 11), (5, 9, 11), (5, 9, 10), (1, 2, 3), (1, 11, 8)]
+        result_data = [[1, 2, 22], [5, 9, 22], [5, 9, 10], [1, 2, 3], [1, 11, 8]]
+
+        for variant, (hand, expected) in enumerate(zip(input_data, result_data), start=1):
+            with self.subTest(f'variation #{variant}', hand=list(hand), expected=expected):
+                actual_result = maybe_double_last(list(hand))
+                error_message = (f'Called maybe_double_last({list(hand)}). '
+                                 f'The function returned {actual_result}, but '
+                                 f'the tests expected {expected} as the maybe-doubled version of {list(hand)}.')
+
+                self.assertEqual(actual_result, expected, msg=error_message)

python/meltdown-mitigation/.exercism/config.json

@@ -0,0 +1,22 @@
+{
+  "authors": [
+    "sachsom95",
+    "BethanyG"
+  ],
+  "contributors": [
+    "kbuc"
+  ],
+  "files": {
+    "solution": [
+      "conditionals.py"
+    ],
+    "test": [
+      "conditionals_test.py"
+    ],
+    "exemplar": [
+      ".meta/exemplar.py"
+    ]
+  },
+  "icon": "circular-buffer",
+  "blurb": "Learn about conditionals and avoid a meltdown by developing a simple control system for a Nuclear Reactor."
+}

python/meltdown-mitigation/.exercism/metadata.json

@@ -0,0 +1 @@
+{"track":"python","exercise":"meltdown-mitigation","id":"b1c401666a194150aa374afe91089205","url":"https://exercism.org/tracks/python/exercises/meltdown-mitigation","handle":"Chomp1295","is_requester":true,"auto_approve":false}

python/meltdown-mitigation/HELP.md

@@ -0,0 +1,130 @@
+# 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 conditionals.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.

python/meltdown-mitigation/HINTS.md

@@ -0,0 +1,50 @@
+# Hints
+
+## General
+
+- The Python Docs on [Control Flow Tools][control flow tools] and the Real Python tutorial on [conditionals][real python conditionals] are great places to start.
+- The Python Docs on [Boolean Operations][boolean operations] can be a great refresher on `bools`, as can the Real Python tutorial on [booleans][python booleans].
+- The Python Docs on [Comparisons][comparisons] and [comparisons examples][python comparisons examples] can be a great refresher for comparisons.
+
+## 1. Check for criticality
+
+- Comparison operators ([comparisons][comparisons review]) and boolean operations ([concept:python/bools]()) can be combined and used with conditionals.
+- Conditional expressions must evaluate to `True` or `False`.
+- `else` can be used for a code block that will execute when all conditional tests return `False`.
+
+  ```python
+     >>> item = 'blue'
+     >>> item_2 = 'green'
+     
+     >>>  if len(item) >= 3 and len(item_2) < 5:
+            print('Both pass the test!')
+          elif len(item) >= 3 or len(item_2) < 5:
+            print('One passes the test!')
+          else:
+            print('None pass the test!')
+    ...
+    One passes the test!
+  ```
+
+## 2. Determine the Power output range
+
+- Comparison operators can be combined and used with conditionals.
+- Any number of `elif` statements can be used as decision "branches".
+- Each "branch" can have a separate `return`, although it might be considered "bad form" by linting tools.
+- If the linter complains, consider assigning the output of a branch to a common variable, and then `return`ing that variable.
+
+## 3. Fail Safe Mechanism
+
+- Comparison operators can be combined and used with conditionals.
+- Any number of `elif` statements can be used as decision "branches".
+- Each "branch" can have a separate `return`, although it might be considered "bad form" by linting tools.
+- If the linter complains, consider assigning the output of a branch to a common variable, and then `return`ing that variable.
+
+
+[boolean operations]: https://docs.python.org/3/library/stdtypes.html#boolean-operations-and-or-not
+[comparisons review]: https://www.learnpython.dev/02-introduction-to-python/090-boolean-logic/20-comparisons/
+[comparisons]: https://docs.python.org/3/library/stdtypes.html#comparisons
+[control flow tools]: https://docs.python.org/3/tutorial/controlflow.html
+[python booleans]: https://realpython.com/python-boolean/
+[python comparisons examples]: https://www.tutorialspoint.com/python/comparison_operators_example.htm
+[real python conditionals]: https://realpython.com/python-conditional-statements/

python/meltdown-mitigation/README.md

@@ -0,0 +1,172 @@
+# Meltdown Mitigation
+
+Welcome to Meltdown Mitigation on Exercism's Python Track.
+If you need help running the tests or submitting your code, check out `HELP.md`.
+If you get stuck on the exercise, check out `HINTS.md`, but try and solve it without using those first :)
+
+## Introduction
+
+In Python, [`if`][if statement], `elif` (_a contraction of 'else and if'_) and `else` statements are used to [control the flow][control flow tools] of execution and make decisions in a program.
+Unlike many other programming languages, Python versions 3.9 and below do not offer a formal case-switch statement, instead using multiple `elif` statements to serve a similar purpose.
+
+Python 3.10 introduces a variant case-switch statement called `structural pattern matching`, which will be covered separately in another concept.
+
+Conditional statements use expressions that must resolve to `True` or `False` -- either by returning a `bool` type directly, or by evaluating as ["truthy" or "falsy"][truth value testing].
+
+```python
+x = 10
+y = 5
+
+# The comparison '>' returns the bool 'True',
+# so the statement is printed.
+if x > y:
+    print("x is greater than y")
+...
+>>> x is greater than y
+```
+
+When paired with `if`, an optional `else` code block will execute when the original `if` condition evaluates to `False`:
+
+```python
+x = 5
+y = 10
+
+# The comparison '>' here returns the bool 'False',
+# so the 'else' block is executed instead of the 'if' block.
+if x > y:
+    print("x is greater than y")
+else:
+    print("y is greater than x")
+...
+>>> y is greater than x
+```
+
+`elif` allows for multiple evaluations/branches.
+
+```python
+x = 5
+y = 10
+z = 20
+
+# The 'elif' statement allows for the checking of more conditions.
+if x > y:
+    print("x is greater than y and z")
+elif y > z:
+    print("y is greater than x and z")
+else:
+    print("z is greater than x and y")
+...
+>>> z is greater than x and y
+```
+
+[Boolean operations][boolean operations] and [comparisons][comparisons] can be combined with conditionals for more complex testing:
+
+```python
+>>> def classic_fizzbuzz(number):
+        if number % 3 == 0 and number % 5 == 0:
+            say = 'FizzBuzz!'
+        elif number % 5 == 0:
+            say = 'Buzz!'
+        elif number % 3 == 0:
+            say = 'Fizz!'
+        else:
+            say = str(number)
+        
+        return say
+
+>>> classic_fizzbuzz(15)
+'FizzBuzz!'
+
+>>> classic_fizzbuzz(13)
+'13'
+```
+
+[boolean operations]: https://docs.python.org/3/library/stdtypes.html#boolean-operations-and-or-not
+[comparisons]: https://docs.python.org/3/library/stdtypes.html#comparisons
+[control flow tools]: https://docs.python.org/3/tutorial/controlflow.html#more-control-flow-tools
+[if statement]: https://docs.python.org/3/reference/compound_stmts.html#the-if-statement
+[truth value testing]: https://docs.python.org/3/library/stdtypes.html#truth-value-testing
+
+## Instructions
+
+In this exercise, we'll develop a simple control system for a nuclear reactor.
+
+For a reactor to produce the power it must be in a state of _criticality_.
+If the reactor is in a state less than criticality, it can become damaged.
+If the reactor state goes beyond criticality, it can overload and result in a meltdown.
+We want to mitigate the chances of meltdown and correctly manage reactor state.
+
+The following three tasks are all related to writing code for maintaining ideal reactor state.
+
+## 1. Check for criticality
+
+The first thing a control system has to do is check if the reactor is balanced in criticality.
+A reactor is said to be critical if it satisfies the following conditions:
+
+- The temperature is less than 800 K.
+- The number of neutrons emitted per second is greater than 500.
+- The product of temperature and neutrons emitted per second is less than 500000.
+
+Implement the function `is_criticality_balanced()` that takes `temperature` measured in kelvin and `neutrons_emitted` as parameters, and returns `True` if the criticality conditions are met, `False` if not.
+
+```python
+>>> is_criticality_balanced(750, 600)
+True
+```
+
+## 2. Determine the Power output range
+
+Once the reactor has started producing power its efficiency needs to be determined.
+Efficiency can be grouped into 4 bands:
+
+1. `green` -> efficiency of 80% or more,
+2. `orange` -> efficiency of less than 80% but at least 60%,
+3. `red` -> efficiency below 60%, but still 30% or more,
+4. `black` ->  less than 30% efficient.
+
+The percentage value can be calculated as `(generated_power/theoretical_max_power)*100`
+where `generated_power` = `voltage` * `current`.
+Note that the percentage value is usually not an integer number, so make sure to consider the
+proper use of the `<` and `<=` comparisons.
+
+Implement the function `reactor_efficiency(<voltage>, <current>, <theoretical_max_power>)`, with three parameters: `voltage`,
+`current`, and `theoretical_max_power`.
+This function should return the efficiency band of the reactor : 'green', 'orange', 'red', or 'black'.
+
+```python
+>>> reactor_efficiency(200,50,15000)
+'orange'
+```
+
+## 3. Fail Safe Mechanism
+
+Your final task involves creating a fail-safe mechanism to avoid overload and meltdown.
+This mechanism will determine if the reactor is below, at, or above the ideal criticality threshold.
+Criticality can then be increased, decreased, or stopped by inserting (or removing) control rods into the reactor.
+
+Implement the function called `fail_safe()`, which takes 3 parameters: `temperature` measured in kelvin,
+`neutrons_produced_per_second`, and `threshold`, and outputs a status code for the reactor.
+
+- If `temperature * neutrons_produced_per_second` < 90% of `threshold`, output a status code of 'LOW'
+  indicating that control rods must be removed to produce power.
+
+- If the value `temperature * neutrons_produced_per_second` is within 10% of the `threshold` (so either 0-10% less than the threshold, at the threshold, or 0-10% greater than the threshold), the reactor is in _criticality_ and the status code of 'NORMAL' should be output, indicating that the reactor is in optimum condition and control rods are in an ideal position.
+
+- If `temperature * neutrons_produced_per_second` is not in the above-stated ranges, the reactor is
+  going into meltdown and a status code of 'DANGER' must be passed to immediately shut down the reactor.
+
+```python
+>>> fail_safe(temperature=1000, neutrons_produced_per_second=30, threshold=5000)
+'DANGER'
+```
+
+## Source
+
+### Created by
+
+- @sachsom95
+- @BethanyG
+
+### Contributed to by
+
+- @kbuc

python/meltdown-mitigation/conditionals.py

@@ -0,0 +1,79 @@
+"""Functions to prevent a nuclear meltdown."""
+
+
+def is_criticality_balanced(temperature, neutrons_emitted):
+    """Verify criticality is balanced.
+
+    :param temperature: int or float - temperature value in kelvin.
+    :param neutrons_emitted: int or float - number of neutrons emitted per second.
+    :return: bool - is criticality balanced?
+
+    A reactor is said to be critical if it satisfies the following conditions:
+    - The temperature is less than 800 K.
+    - The number of neutrons emitted per second is greater than 500.
+    - The product of temperature and neutrons emitted per second is less than 500000.
+    """
+
+    if (
+        temperature < 800
+        and neutrons_emitted > 500
+        and temperature * neutrons_emitted < 500000
+    ):
+        return True
+
+    return False
+
+
+def reactor_efficiency(voltage, current, theoretical_max_power):
+    """Assess reactor efficiency zone.
+
+    :param voltage: int or float - voltage value.
+    :param current: int or float - current value.
+    :param theoretical_max_power: int or float - power that corresponds to a 100% efficiency.
+    :return: str - one of ('green', 'orange', 'red', or 'black').
+
+    Efficiency can be grouped into 4 bands:
+
+    1. green -> efficiency of 80% or more,
+    2. orange -> efficiency of less than 80% but at least 60%,
+    3. red -> efficiency below 60%, but still 30% or more,
+    4. black ->  less than 30% efficient.
+
+    The percentage value is calculated as
+    (generated power/ theoretical max power)*100
+    where generated power = voltage * current
+    """
+
+    efficiency = ((voltage * current) / theoretical_max_power) * 100
+
+    if efficiency >= 80:
+        return "green"
+    if efficiency >= 60:
+        return "orange"
+    if efficiency >= 30:
+        return "red"
+
+    return "black"
+
+
+def fail_safe(temperature, neutrons_produced_per_second, threshold):
+    """Assess and return status code for the reactor.
+
+    :param temperature: int or float - value of the temperature in kelvin.
+    :param neutrons_produced_per_second: int or float - neutron flux.
+    :param threshold: int or float - threshold for category.
+    :return: str - one of ('LOW', 'NORMAL', 'DANGER').
+
+    1. 'LOW' -> `temperature * neutrons per second` < 90% of `threshold`
+    2. 'NORMAL' -> `temperature * neutrons per second` +/- 10% of `threshold`
+    3. 'DANGER' -> `temperature * neutrons per second` is not in the above-stated ranges
+    """
+
+    if temperature * neutrons_produced_per_second < threshold * 0.9:
+        return "LOW"
+
+    if temperature * neutrons_produced_per_second <= threshold * 1.1:
+        return "NORMAL"
+
+    if temperature * neutrons_produced_per_second > threshold * 1.1:
+        return "DANGER"

python/meltdown-mitigation/conditionals_test.py

@@ -0,0 +1,82 @@
+import unittest
+import pytest
+from conditionals import (is_criticality_balanced,
+                          reactor_efficiency,
+                          fail_safe)
+
+
+class MeltdownMitigationTest(unittest.TestCase):
+    """Test cases for Meltdown mitigation exercise.
+    """
+
+    @pytest.mark.task(taskno=1)
+    def test_is_criticality_balanced(self):
+        """Testing border cases around typical points.
+
+        T, n == (800, 500), (625, 800), (500, 1000), etc.
+
+        """
+
+        test_data = ((750, 650, True), (799, 501, True), (500, 600, True),
+                     (1000, 800, False), (800, 500, False), (800, 500.01, False),
+                     (799.99, 500, False), (500.01, 999.99, False), (625, 800, False),
+                     (625.99, 800, False), (625.01, 799.99, False), (799.99, 500.01, True),
+                     (624.99, 799.99, True), (500, 1000, False), (500.01, 1000, False),
+                     (499.99, 1000, True))
+
+        for variant, data in enumerate(test_data, start=1):
+            temp, neutrons_emitted, expected = data
+            with self.subTest(f'variation #{variant}', temp=temp, neutrons_emitted=neutrons_emitted, expected=expected):
+
+                # pylint: disable=assignment-from-no-return
+                actual_result = is_criticality_balanced(temp, neutrons_emitted)
+                failure_message = (f'Called is_criticality_balanced({temp}, {neutrons_emitted}). '
+                                   f' The function returned {actual_result}, '
+                                   f'but the test expected {expected} as the return value.')
+
+                self.assertEqual(actual_result, expected, failure_message)
+
+    @pytest.mark.task(taskno=2)
+    def test_reactor_efficiency(self):
+        voltage = 10
+        theoretical_max_power = 10000
+
+        # The numbers are chosen so that current == 10 x percentage
+        test_data = ((1000, 'green'), (999, 'green'), (800, 'green'),
+                     (799, 'orange'), (700, 'orange'), (600, 'orange'),
+                     (599, 'red'), (560, 'red'), (400, 'red'), (300, 'red'),
+                     (299, 'black'), (200, 'black'), (0, 'black'))
+
+        for variant, data in enumerate(test_data, start=1):
+            current, expected = data
+            with self.subTest(f'variation #{variant}', voltage=voltage, current=current,
+                              theoretical_max_power=theoretical_max_power, expected=expected):
+
+                # pylint: disable=assignment-from-no-return
+                actual_result = reactor_efficiency(voltage, current, theoretical_max_power)
+                failure_message =(f'Called reactor_efficiency({voltage}, {current}, {theoretical_max_power}). '
+                                  f'The function returned {actual_result}, '
+                                  f'but the test expected {expected} as the return value.')
+
+                self.assertEqual(actual_result, expected, failure_message)
+
+    @pytest.mark.task(taskno=3)
+    def test_fail_safe(self):
+        temp = 10
+        threshold = 10000
+        test_data = ((399, 'LOW'), (300, 'LOW'), (1, 'LOW'),
+                     (0, 'LOW'), (901, 'NORMAL'), (1000, 'NORMAL'),
+                     (1099, 'NORMAL'), (899, 'LOW'), (700, 'LOW'),
+                     (400, 'LOW'), (1101, 'DANGER'), (1200, 'DANGER'))
+
+        for variant, (neutrons_per_second, expected) in enumerate(test_data, start=1):
+            with self.subTest(f'variation #{variant}', temp=temp, neutrons_per_second=neutrons_per_second,
+                              threshold=threshold, expected=expected):
+
+                # pylint: disable=assignment-from-no-return
+                actual_result = fail_safe(temp, neutrons_per_second, threshold)
+                failure_message = (f'Called fail_safe({temp}, {neutrons_per_second}, {threshold}). '
+                                   f'The function returned {actual_result}, '
+                                   f'but the test expected {expected} as the return value.')
+
+                self.assertEqual(actual_result, expected, failure_message)