fluent python chapter 1: python data model

python_sandbox/python_sandbox/fluent_python/README.md

@@ -0,0 +1,38 @@
+# How to run tests?
+python -m pytest
+
+# Python Data Model
+
+The first thing to know about special methods (__len__ etc) is that they are meant
+to be called the python interpreter, and not by you. You don't write `obj.__len__()`.
+You write `len(obj)`.
+
+More often than not, the special method call is implicit. For example, the statement
+`for i in x:` actually causes the invocation of `iter(x)`, which in turn may call
+`x.__iter__()` if that's available, or use `x.__getitem__()` as a fallback.
+
+You should be implementing them more often than invoking them explicitly.
+
+## __repr__ vs __str__
+https://stackoverflow.com/questions/1436703/what-is-the-difference-between-str-and-repr
+
+* The default implementation is useless (it’s hard to think of one which wouldn’t be, but yeah)
+* __repr__ goal is to be unambiguous
+* __str__ goal is to be readable
+
+## Collections API
+
+The "Collection" ABC (abstract base class) has 3 parents:
+* Iterable (`__iter__`): to support the `for` construct
+* Sized (`__len__`): to support the `len` function
+* Container (`__contains__`): to support the `in` operator
+
+The "Collection" ABC (abstract base class) has 3 children:
+* Sequence (__getitem__, __iter__, etc)
+* Mapping (__getitem__, __contains__, etc)
+* Set
+
+There's also a `Reversible` ABC and `Sequence` is a child of it.
+
+Note that python doesn't require concrete classes to actually inherit from any of
+these ABCs. Any class that implements `__len__` satisfies the `Sized` interface.

python_sandbox/python_sandbox/fluent_python/python_data_model/cards.py

@@ -0,0 +1,25 @@
+import collections
+
+Card = collections.namedtuple("Card", ["rank", "suit"])
+
+
+class FrenchDeck:
+    ranks = [str(n) for n in range(2, 11)] + list("JQKA")
+    suits = "spades diamonds clubs hearts".split()
+
+    def __init__(self):
+        self._cards = [Card(rank, suit) for suit in self.suits for rank in self.ranks]
+
+    def __len__(self):
+        return len(self._cards)
+
+    def __getitem__(self, position):
+        return self._cards[position]
+
+
+suit_values = dict(spades=3, hearts=2, diamonds=1, clubs=0)
+
+
+def spades_high(card):
+    rank_value = FrenchDeck.ranks.index(card.rank)
+    return rank_value * len(suit_values) + suit_values[card.suit]

python_sandbox/python_sandbox/fluent_python/python_data_model/tests/test_cards.py

@@ -0,0 +1,45 @@
+from python_data_model.cards import Card, FrenchDeck, spades_high
+from random import choice
+import sys
+
+
+def test_cards():
+    print(f"sys.path: {sys.path}")
+    beer_card = Card("7", "diamonds")
+    assert beer_card.rank == "7"
+    assert beer_card.suit == "diamonds"
+
+
+def test_deck():
+    deck = FrenchDeck()
+    assert len(deck) == 52
+    assert deck[0] == Card("2", "spades")
+    assert deck[-1] == Card("A", "hearts")
+    # choice works with a sequence and FrenchDeck is a sequence because it implements
+    # both __len__ and __getitem__
+    print(f"Pick a random card: {choice(deck)}")
+    print(f"Pick a random card: {choice(deck)}")
+
+    # slicing works
+    assert deck[:3] == [Card("2", "spades"), Card("3", "spades"), Card("4", "spades")]
+    assert deck[-3:] == [Card("Q", "hearts"), Card("K", "hearts"), Card("A", "hearts")]
+
+    # iteration works too because of __getitem__
+    print("iterating cards")
+    for card in deck:
+        print(card)
+
+    # in works too
+    # If a collection has no __contains__ method, the "in" operator does a sequential scan
+    assert Card("Q", "hearts") in deck
+    assert Card("7", "beasts") not in deck
+
+    # sort cards
+    print("sorted cards")
+    for card in sorted(deck, key=spades_high):
+        print(card)
+
+    # you can iterate the cards in reverse order
+    print("reversed cards")
+    for card in reversed(deck):
+        print(card)

python_sandbox/python_sandbox/fluent_python/python_data_model/tests/test_vectors.py

@@ -0,0 +1,13 @@
+from python_data_model.vectors import Vector
+
+
+def test_vectors():
+    v1 = Vector(2, 4)
+    v2 = Vector(2, 1)
+    assert v1 + v2 == Vector(4, 5)
+
+    v = Vector(3, 4)
+    assert abs(v) == 5.0
+
+    print("v * 3:", v * 3)
+    assert v * 3 == Vector(9, 12)

python_sandbox/python_sandbox/fluent_python/chapter1/vectors.py → python_sandbox/python_sandbox/fluent_python/python_data_model/vectors.py

@@ -7,7 +7,7 @@ def __init__(self, x=0, y=0):
         self.y = y
 
     def __repr__(self):
-        return 'Vector(%r, %r)' % (self.x, self.y)
+        return "Vector(%r, %r)" % (self.x, self.y)
 
     def __abs__(self):
         return hypot(self.x, self.y)
@@ -26,17 +26,5 @@ def __add__(self, other):
     def __mul__(self, scalar):
         return Vector(self.x * scalar, self.y * scalar)
 
-
-def main():
-    v1 = Vector(2, 4)
-    v2 = Vector(2, 1)
-    print('v1 + v2:', v1 + v2)
-
-    v = Vector(3, 4)
-    print('abs(v):', abs(v))
-
-    print('v * 3:', v * 3)
-
-
-if __name__ == '__main__':
-    main()
+    def __eq__(self, other):
+        return self.x == other.x and self.y == other.y

python_sandbox/requirements.txt

@@ -1,2 +1,3 @@
 hydra-core==0.11.3
 pyyaml==5.3.1
+pytest==7.1.3