Implement new Concept Exercise: dicts (new PR) (exercism#1936)

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exercises/concept/dicts/.docs/after.md

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+Python dictionaries are very powerful and you will be using them a lot if you're working with APIs and such. Dictionaries are essentially an array of _keys_ paired with _values_.
+
+## Dictionaries and lists
+
+Just like `lists`, dictionaries are ordered by insertion order, they are mutable (which means you can change their content without changing their identity). They can also (just like `lists`) be nested, which means that a dictionary can contain another dictionary. Dictionaries are generally used in databases for use cases where looking up things by _key_ are used over and over, although they are not generally used for use cases with demand for high-speed insertion. This [blog post][listsvdicts] by _Jessica Yung_ goes into what data type is preferred in what use cases, on a more _scientific_ level.
+
+## Dealing with dictionaries
+
+Dictionaries have different methods to change them, like getting a value from a specific key in the dictionary, setting a default value for a key and many more. Dictionaries are also iterable by their keys. For a full explanation of dictionaries in python refer to the [official documentation][docs] and on how to use them look at [W3-Schools.com'][how-to] tutorial.
+
+Now that you know the basics of _creation_, _membership_ and _retrieval_ here are some useful `dict` methods. You can get values from a dictionary by using the `.get(key, [default])`, which returns the value of the given key in the dictionary, if the key does not exist it returns the `default` value. Dictionaries also have the `.setdefault(key, [default])` method, which is almost the same as `.get()`, but it also places that key with the default value if it does not exist inside the dictionary.
+
+## The collections module
+
+The [`collections`][collections-docs] module adds more functionality to Python's standard collection-based datatypes (`dictionary`, `set`, `list`, `tuple`). A handy member of this module is the [`Counter`][counter-dicts] class, which can count items and return them in a dictionary form. There is also [`OrderedDict`][ordered-dicts-docs] which has methods specialized for re-arranging the order of a dictionary. Finally, there is `defaultdict`- a subclass of the built-in `dict` module that overrides one method and adds one new one. The `collections` module is a handy module to use if you need some _extra_ or extended functionality for your container-based datatypes.
+
+[listsvdicts]: https://www.jessicayung.com/python-lists-vs-dictionaries-the-space-time-tradeoff/
+[docs]: https://docs.python.org/3/tutorial/datastructures.html#dictionaries
+[how-to]: https://www.w3schools.com/python/python_dictionaries.asp
+[collections-docs]: https://docs.python.org/3/library/collections.html
+[counter-dicts]: https://docs.python.org/3/library/collections.html#collections.Counter
+[ordered-dicts-docs]: https://docs.python.org/3/library/collections.html#collections.OrderedDict

exercises/concept/dicts/.docs/hints.md

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+# TO DO

exercises/concept/dicts/.docs/instructions.md

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+In this exercise you'll be managing an inventory system.
+
+You will be given a list of items. Each time an item is in the given list, add `1` to the key in the _given_ inventory. Each item should be organized by their name and the amount of that item. You will also have to delete items from the inventory.
+
+You will also have to implement a function which returns a list of `tuples` of all the key-value pairs in the _given_ inventory.
+
+## 1. Create an inventory from a list
+
+Implement the `create_inventory()` function that creates an "inventory" from a list of items. It should return a `dictionary` representing the types and amounts of the items.
+
+```python
+>>> create_inventory(["coal", "wood", "wood", "diamond", "diamond", "diamond"])
+{"coal":1, "wood":2 "diamond":3}
+```
+
+## 2. Add items from a list to an existing dictionary
+
+Implement the `add_items()` function that adds a list of items to a passed in inventory dictionary:
+
+```python
+>>> add_items({"coal":1}, ["wood", "iron", "coal", "wood"])
+{"coal":2, "wood":2, "iron":1}
+```
+
+## 3. Remove items from the inventory
+
+Implement the `delete_items()` function that removes items in the passed-in list from the passed inventory dictionary:
+
+```python
+>>> delete_items({"coal":3, "diamond":1, "iron":5}, ["diamond", "coal", "iron", "iron"])
+{"coal":2, "diamond":0, "iron":3}
+```
+
+Item counts should not fall below `0`, if the amount of an item in the list exceeds the amount of items in the inventory, the value should stop at `0` and not go into negative numbers.
+
+```python
+>>> delete_items({"coal":2, "wood":1, "diamond":2}, ["coal", "coal", "wood", "wood", "diamond"])
+{"coal":0, "wood":0, "diamond":1}
+```
+
+## 4. Return the inventory content
+
+Implement the `list_inventory()` function that takes an inventory and returns a list of `(item, amount)` tuples. Only include items where the amount is greater than zero:
+
+```python
+>>> list_inventory({"coal":7, "wood":11, "diamond":2, "iron":7, "silver": 0})
+[('coal', 7), ('diamond', 2), ('iron', 7), ('wood', 11)]
+```

exercises/concept/dicts/.docs/introduction.md

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+A _dictionary_ is Python's primary mapping type that connects _hashable keys_ with values. The looking up of keys is more efficient than searching through an array, but does require more memory.
+
+## Dict construction
+
+Dictionaries can be created in various ways. You can either use the `dict()` class constructor or the literal declaration of a _dict_.
+
+### Use the `dict()` constructor
+
+```python
+>>> bear = dict(name="Black Bear", amount=5, land_animal=True)
+{'name': 'Panda', 'amount': 15, 'land_animal': True}
+```
+
+### Declare a _dict_ literal
+
+```python
+>>> whale = {"name":"Blue Whale", "amount":2, "land_animal":False}
+{'name': 'Dolphin', 'amount': 2, 'land_animal': False}
+```
+
+With literal declaration keep in mind that _keys_ are replaced with _data types_ and the `=` is replaced with a `:`.
+
+## Accessing values
+
+You can access items in a dictionary in two ways, using the _key_ of the value.
+
+### Using _square brackets_ after the dict object
+
+```python
+>>> request_brackets = bear["amount"]
+5
+```
+
+### Using `.get()`
+
+```python
+>>> request_get = whale.get("name")
+Blue Whale
+```
+
+## Changing values
+
+You can easily change a value of an item using it's _key_.
+
+```python
+>>> bear["name"] = "Grizzly Bear"
+{'name': 'Grizzly Bear', 'amount': 5, 'land_animal': True}
+
+>>> whale["amount"] = 7
+{'name': 'Blue Whale', 'amount': 7, 'land_animal': False}
+```
+
+## Looping through a dictionary
+
+Looping through a dictionary using a `for` loop only returns the _keys_ of the items.
+
+```python
+>>> for key in bear:
+>>>     print(key)
+name
+amount
+land_animal
+```
+
+But you can also make a `for` loop return the _values_ of a dictionary with a simple trick.
+
+```python
+>>> for key in whale:
+>>>    print(whale[key])
+Blue Whale
+7
+False
+```

exercises/concept/dicts/.meta/config.json

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+{
+  "authors": [
+    {
+      "github_username": "j08k",
+      "exercism_username": "j08k"
+    }
+  ]
+}

exercises/concept/dicts/.meta/design.md

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+# Design
+
+## Goal
+
+The goal of this exercise is to teach the basics of the `dict` (dictionary, mapping) data type in Python.
+
+## Things to teach
+
+- create a `dict` via constructor and literal.
+- access values in a `dict` via `keys`.
+- assign values in a `dict` via key reference.
+- check for membership of a key in a given dictionary.
+- add new `key`:`value` pairs to the `dict`.
+- remove `key`:`value` pairs from the `dict`.
+- iterate through a `dict` using `dict.keys()`, `dict.values()`, or `dict.items()`.
+- `dict` method `setdefault()`
+
+## Things not to teach
+
+- Dictionary comprehensions
+- `dict` methods such as `get()` or `clear()`.
+- Built-in functions as they relate to this data structure (_e.g._ `copy()`, `len()`, or `enumerate()`.
+- Sorting by `keys` or `values`.
+- Swapping `keys` for `values`.
+- Knowing that Dictionaries can be _nested_, _-- e.g._ ' a dictionary of dictionaries'.
+- Mutability
+- `copy()` vs `deepcopy()`
+- Related `collections` module with `Counter()` and `defaultdict()`
+- Memory and performance characteristics.
+
+## Concepts
+
+- `dicts`
+
+## Prerequisites
+
+- `booleans`
+- `for-loops`
+- `functions`
+- `if-keyword`
+- `in-keyword`
+- `integers`
+- `return-keyword`
+- `strings`
+- `tuples`
+- `lists`
+
+## Representer
+
+This exercise does not require any logic to be added to the [representer][representer]
+
+## Analyzer
+
+This exercise does not require any logic to be added to the [analyzer][analyzer].
+
+[builtin-types]: https://github.com/exercism/v3/tree/master/languages/python/reference/concepts/builtin_types
+[data-types]: https://github.com/exercism/v3/blob/master/languages/python/reference/concepts/data_structures.md
+[analyzer]: https://github.com/exercism/python-analyzer
+[representer]: https://github.com/exercism/python-representer

exercises/concept/dicts/.meta/example.py

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+def create_inventory(items):
+    inventory = dict()
+    add_items(inventory, items)
+    return inventory
+
+
+def add_items(inventory, items):
+    for item in items:
+        inventory.setdefault(item, 0)
+        inventory[item] += 1
+    return inventory
+
+
+def delete_items(inventory, items):
+    for item in items:
+        inventory.setdefault(item, 0)
+        inventory[item] = max(inventory[item] - 1, 0)
+    return inventory
+
+
+def list_inventory(inventory):
+    output = list()
+    for item in sorted(inventory.items()):
+        if item[1] > 0:
+            output.append(item)
+    return output

exercises/concept/dicts/dicts.py

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+def create_inventory(items):
+    pass
+
+def add_items(inventory, items):
+    pass
+
+def delete_items(inventory, items):
+    pass
+
+def list_inventory(inventory):
+    pass

exercises/concept/dicts/dicts_test.py

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+import unittest
+from dicts import *
+
+class test_inventory(unittest.TestCase):
+    def test_create_inventory(self):
+        self.assertEqual(create_inventory(["wood", "iron", "iron", "diamond", "diamond"]),
+                         {"wood":1, "iron":2, "diamond":2})
+
+    def test_add_one_item(self):
+        self.assertEqual(add_items({"wood":4, "iron":2}, ["iron", "iron"]),
+                         {"wood":4, "iron":4})
+
+    def test_add_multiple_items(self):
+        self.assertEqual(add_items({"wood":2, "gold":1, "diamond":3}, ["wood", "gold", "gold"]),
+                         {"wood":3, "gold":3, "diamond":3})
+
+    def test_add_new_item(self):
+        self.assertEqual(add_items({"iron":1, "diamond":2}, ["iron", "wood", "wood"]),
+                         {"iron":2, "diamond":2, "wood":2})
+
+    def test_add_from_empty_dict(self):
+        self.assertEqual(add_items({}, ["iron", "iron", "diamond"]),
+                         {"iron":2, "diamond":1})
+
+    def test_delete_items(self):
+        self.assertEqual(delete_items({"iron":3, "diamond":4, "gold":2},
+                                      ["iron", "iron", "diamond", "gold", "gold"]),
+                         {"iron":1, "diamond":3, "gold":0})
+
+    def test_not_below_zero(self):
+        self.assertEqual(delete_items({"wood":2, "iron":3, "diamond":1},
+                                      ["wood", "wood", "wood", "iron", "diamond", "diamond"]),
+                        {"wood":0, "iron":2, "diamond":0})
+
+    def test_list_inventory(self):
+        self.assertEqual(list_inventory({"coal":15, "diamond":3, "wood":67}),
+                         [("coal", 15), ("diamond", 3), ("wood", 67)])
+
+if __name__ == "__main__":
+    unittest.main()