Edited test error messages to include function calls and params. Edited docs for spelling and small grammar fixes. (#3528)

[no important files changed]

Author: BethanyG

concepts/lists/about.md

@@ -18,7 +18,7 @@ Accessing elements, checking for membership via `in`, or appending items to the
  For a similar data structure that supports memory efficient `appends`/`pops` from both sides, see [`collections.deque`][deque], which has approximately the same O(1) performance in either direction.
 
 
-Because lists are mutable and can contain references to arbitrary objects, they also take up more space in memory than a fixed-size [`array.array`][array.array] type of the same apparent length.
+Because lists are mutable and can contain references to arbitrary Python objects, they also take up more space in memory than an [`array.array`][array.array] or a [`tuple`][tuple] (_which is immutable_) of the same apparent length.
  Despite this, lists are an extremely flexible and useful data structure and many built-in methods and operations in Python produce lists as their output.
 
 
@@ -135,7 +135,8 @@ TypeError: 'int' object is not iterable
 
 ## Accessing elements
 
-Items inside lists (_as well as elements in other sequence types such as [`str`][string] & [`tuple`][tuple]_), can be accessed using  _bracket notation_. Indexes can be from **`left`** --> **`right`** (_starting at zero_) or **`right`** --> **`left`** (_starting at -1_).
+Items inside lists (_as well as elements in other sequence types such as [`str`][string] & [`tuple`][tuple]_), can be accessed using  _bracket notation_.
+Indexes can be from **`left`** --> **`right`** (_starting at zero_) or **`right`** --> **`left`** (_starting at -1_).
 
 
 <table>
@@ -173,9 +174,11 @@ Items inside lists (_as well as elements in other sequence types such as [`str`]
 'Toast'
 ```
 
-A section of 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_][slice notation] returns a copy of the "sliced" items and does not modify the original `list`.
+A section of 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_][slice notation] returns a copy of the "sliced" items and does not modify the original `list`.
 
-A `step` parameter can also be used in the slice (`[start:stop:step]`) to "skip over" or filter the returned elements (_for example, a `step` of 2 will select every other element in the section_):
+A `step` parameter can also be used in the slice (`<list>[<start>:<stop>:<step>]`) to "skip over" or filter the returned elements (_for example, a `step` of 2 will select every other element in the section_):
 
 ```python
 >>> colors = ["Red", "Purple", "Green", "Yellow", "Orange", "Pink", "Blue", "Grey"]
@@ -269,7 +272,7 @@ Lists can also be combined via various techniques:
 >>> first_one
 ['George', 5, 'cat', 'Tabby']
 
-# This loops through the first list and appends it's items to the end of the second list.
+# This loops through the first list and appends its items to the end of the second list.
 >>> first_one = ["cat", "Tabby"]
 >>> second_one = ["George", 5]
 
@@ -284,7 +287,7 @@ Lists can also be combined via various techniques:
 ## Some cautions
 
 Recall that variables in Python are _labels_ that point to _underlying objects_.
-`lists` add one more layer as  _container objects_ -- they hold object references for their collected items.
+`lists` add one more layer as  _container objects_ -- they hold object _references_ for their collected items.
 This can lead to multiple potential issues when working with lists, if not handled properly.
 
 
@@ -305,21 +308,22 @@ A `shallow_copy` will create a new `list` object, but **will not** create new ob
 
 #  Altering the list via the new name is the same as altering the list via the old name.
 >>> same_list.append("Clarke")
->>> same_list
 ["Tony", "Natasha", "Thor", "Bruce", "Clarke"]
+
 >>> actual_names
 ["Tony", "Natasha", "Thor", "Bruce", "Clarke"]
 
 #  Likewise, altering the data in the list via the original name will also alter the data under the new name.
 >>> actual_names[0] = "Wanda"
->>> same_list
 ['Wanda', 'Natasha', 'Thor', 'Bruce', 'Clarke']
 
 # If you copy the list, there will be two separate list objects which can be changed independently.
 >>> copied_list = actual_names.copy()
 >>> copied_list[0] = "Tony"
+
 >>> actual_names
 ['Wanda', 'Natasha', 'Thor', 'Bruce', 'Clarke']
+
 >>> copied_list
 ["Tony", "Natasha", "Thor", "Bruce", "Clarke"]
 ```
@@ -455,4 +459,4 @@ The collections module also provides a `UserList` type that can be customized to
 [set]: https://docs.python.org/3/library/stdtypes.html#set
 [slice notation]: https://docs.python.org/3/reference/expressions.html#slicings
 [string]: https://docs.python.org/3/library/stdtypes.html#text-sequence-type-str
-[tuple]: https://docs.python.org/3/library/stdtypes.html#tuple
+[tuple]: https://docs.python.org/3/library/stdtypes.html#tuple

exercises/concept/card-games/.docs/hints.md

@@ -4,45 +4,44 @@
 
 ## 1. Tracking Poker Rounds
 
-- Lists in Python may be [constructed][constructed] in several ways.
+- 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` already support [common operations][common sequence operations].
+- 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` already support a few [common operations][common sequence operations].
+- 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 sum/count.
+- 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` already 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.
-- In Python, negative indexing starts the count from the right-hand side. This mean that you can find the last element of a `list` at `index -1`.
+- 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.
+- 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.
+- 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
-[iterate over a list in python]: https://www.geeksforgeeks.org/iterate-over-a-list-in-python/
 [return]: https://www.w3schools.com/python/ref_keyword_return.asp
 [ways to modify `lists`]: https://realpython.com/python-lists-tuples/#lists-are-mutable

exercises/concept/card-games/.docs/introduction.md

@@ -2,7 +2,7 @@
 
 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-base index` from the right.
+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()`.

exercises/concept/card-games/lists_test.py

@@ -1,5 +1,6 @@
 import unittest
 import pytest
+
 from lists import (
     get_rounds,
     concatenate_rounds,
@@ -16,92 +17,121 @@ class CardGamesTest(unittest.TestCase):
     @pytest.mark.task(taskno=1)
     def test_get_rounds(self):
 
-        input_vars = [0, 1, 10, 27, 99, 666]
+        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]]
 
-        results = [[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}.')
 
-        for variant, (number, rounds) in enumerate(zip(input_vars, results), start=1):
-            error_message = f'Expected rounds {rounds} given the current round {number}.'
-            with self.subTest(f'variation #{variant}', input=number, output=rounds):
-                self.assertEqual(rounds, get_rounds(number), msg=error_message)
+                self.assertEqual(actual_result, expected, msg=error_message)
 
     @pytest.mark.task(taskno=2)
     def test_concatenate_rounds(self):
 
-        input_vars = [([], []), ([0, 1], []), ([], [1, 2]),
+        input_data = [([], []), ([0, 1], []), ([], [1, 2]),
                       ([1], [2]), ([27, 28, 29], [35, 36]),
                       ([1, 2, 3], [4, 5, 6])]
 
-        results = [[], [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}.')
 
-        for variant, ((rounds_1, rounds_2), rounds) in enumerate(zip(input_vars, results), start=1):
-            error_message = f'Expected {rounds} as the concatenation of {rounds_1} and {rounds_2}.'
-            with self.subTest(f'variation #{variant}', input=(rounds_1, rounds_2), output=rounds):
-                self.assertEqual(rounds, concatenate_rounds(rounds_1, rounds_2), msg=error_message)
+                self.assertEqual(actual_result, expected, msg=error_message)
 
     @pytest.mark.task(taskno=3)
     def test_list_contains_round(self):
 
-        input_vars = [([], 1), ([1, 2, 3], 0), ([27, 28, 29, 35, 36], 30),
-                      ([1], 1), ([1, 2, 3], 1), ([27, 28, 29, 35, 36], 29)]
+        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]
 
-        results = [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}.')
 
-        for variant, ((rounds, round_number), contains) in enumerate(zip(input_vars, results), start=1):
-            error_message = f'Round {round_number} {"is" if contains else "is not"} in {rounds}.'
-            with self.subTest(f'variation #{variant}', input=(rounds, round_number), output=contains):
-                self.assertEqual(contains, list_contains_round(rounds, round_number), msg=error_message)
+                self.assertEqual(actual_result, expected, msg=error_message)
 
     @pytest.mark.task(taskno=4)
     def test_card_average(self):
 
-        input_vars = [[1], [5, 6, 7], [1, 2, 3, 4], [1, 10, 100]]
+        input_data = [[1], [5, 6, 7], [1, 2, 3, 4], [1, 10, 100]]
+        result_data = [1.0, 6.0, 2.5, 37.0]
 
-        results = [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}.')
 
-        for variant, (hand, average) in enumerate(zip(input_vars, results), start=1):
-            error_message = f'Expected {average} as the average of {hand}.'
-            with self.subTest(f'variation #{variant}', input=hand, output=average):
-                self.assertEqual(average, card_average(hand), msg=error_message)
+                self.assertEqual(actual_result, expected, msg=error_message)
 
     @pytest.mark.task(taskno=5)
     def test_approx_average_is_average(self):
 
-        input_vars = [[0, 1, 5], [3, 6, 9, 12, 150], [1, 2, 3, 5, 9],
+        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]]
 
-        results = [False, False, False, False, True, True, True, True]
+        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.')
 
-        for variant, (hand, same) in enumerate(zip(input_vars, results), start=1):
-            error_message = f'Hand {hand} {"does" if same else "does not"} yield the same approximate average.'
-            with self.subTest(f'variation #{variant}', input=hand, output=same):
-                self.assertEqual(same, approx_average_is_average(hand), msg=error_message)
+                self.assertEqual(actual_result, expected, msg=error_message)
 
     @pytest.mark.task(taskno=6)
     def test_average_even_is_average_odd(self):
 
-        input_vars = [[5, 6, 8], [1, 2, 3, 4], [1, 2, 3], [5, 6, 7], [1, 3, 5, 7, 9]]
+        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]
 
-        results = [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.')
 
-        for variant, (hand, same) in enumerate(zip(input_vars, results), start=1):
-            error_message = f'Hand {hand} {"does" if same else "does not"} yield the same odd-even average.'
-            with self.subTest(f'variation #{variant}', input=hand, output=same):
-                self.assertEqual(same, average_even_is_average_odd(hand), msg=error_message)
+                self.assertEqual(actual_result, expected, msg=error_message)
 
     @pytest.mark.task(taskno=7)
     def test_maybe_double_last(self):
 
-        input_vars = [[1, 2, 11], [5, 9, 11], [5, 9, 10], [1, 2, 3]]
+        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]]
 
-        results = [[1, 2, 22], [5, 9, 22], [5, 9, 10], [1, 2, 3]]
+        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)}.')
 
-        for variant, (hand, doubled_hand) in enumerate(zip(input_vars, results), start=1):
-            error_message = f'Expected {doubled_hand} as the maybe-doubled version of {hand}.'
-            with self.subTest(f'variation #{variant}', input=hand, output=doubled_hand):
-                self.assertEqual(doubled_hand, maybe_double_last(hand), msg=error_message)
+                self.assertEqual(actual_result, expected, msg=error_message)