Ruff pandas vet (#10281)

* Python linting: Add ruff rules for Pandas-vet and Pytest-style

* updating DIRECTORY.md

---------

Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>

.pre-commit-config.yaml

@@ -51,7 +51,7 @@ repos:
       - id: validate-pyproject
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.5.1
+    rev: v1.6.0
     hooks:
       - id: mypy
         args:

DIRECTORY.md

@@ -532,6 +532,7 @@
   * [Logistic Regression](machine_learning/logistic_regression.py)
   * Loss Functions
     * [Binary Cross Entropy](machine_learning/loss_functions/binary_cross_entropy.py)
+    * [Categorical Cross Entropy](machine_learning/loss_functions/categorical_cross_entropy.py)
     * [Huber Loss](machine_learning/loss_functions/huber_loss.py)
     * [Mean Squared Error](machine_learning/loss_functions/mean_squared_error.py)
   * [Mfcc](machine_learning/mfcc.py)

blockchain/diophantine_equation.py

@@ -83,7 +83,8 @@ def extended_gcd(a: int, b: int) -> tuple[int, int, int]:
     (1, -2, 3)
 
     """
-    assert a >= 0 and b >= 0
+    assert a >= 0
+    assert b >= 0
 
     if b == 0:
         d, x, y = a, 1, 0
@@ -92,7 +93,8 @@ def extended_gcd(a: int, b: int) -> tuple[int, int, int]:
         x = q
         y = p - q * (a // b)
 
-    assert a % d == 0 and b % d == 0
+    assert a % d == 0
+    assert b % d == 0
     assert d == a * x + b * y
 
     return (d, x, y)

ciphers/xor_cipher.py

@@ -38,7 +38,8 @@ class XORCipher:
         """
 
         # precondition
-        assert isinstance(key, int) and isinstance(content, str)
+        assert isinstance(key, int)
+        assert isinstance(content, str)
 
         key = key or self.__key or 1
 
@@ -56,7 +57,8 @@ class XORCipher:
         """
 
         # precondition
-        assert isinstance(key, int) and isinstance(content, list)
+        assert isinstance(key, int)
+        assert isinstance(content, list)
 
         key = key or self.__key or 1
 
@@ -74,7 +76,8 @@ class XORCipher:
         """
 
         # precondition
-        assert isinstance(key, int) and isinstance(content, str)
+        assert isinstance(key, int)
+        assert isinstance(content, str)
 
         key = key or self.__key or 1
 
@@ -99,7 +102,8 @@ class XORCipher:
         """
 
         # precondition
-        assert isinstance(key, int) and isinstance(content, str)
+        assert isinstance(key, int)
+        assert isinstance(content, str)
 
         key = key or self.__key or 1
 
@@ -125,7 +129,8 @@ class XORCipher:
         """
 
         # precondition
-        assert isinstance(file, str) and isinstance(key, int)
+        assert isinstance(file, str)
+        assert isinstance(key, int)
 
         try:
             with open(file) as fin, open("encrypt.out", "w+") as fout:
@@ -148,7 +153,8 @@ class XORCipher:
         """
 
         # precondition
-        assert isinstance(file, str) and isinstance(key, int)
+        assert isinstance(file, str)
+        assert isinstance(key, int)
 
         try:
             with open(file) as fin, open("decrypt.out", "w+") as fout:

conversions/decimal_to_hexadecimal.py

@@ -57,7 +57,8 @@ def decimal_to_hexadecimal(decimal: float) -> str:
     >>> decimal_to_hexadecimal(-256) == hex(-256)
     True
     """
-    assert type(decimal) in (int, float) and decimal == int(decimal)
+    assert isinstance(decimal, (int, float))
+    assert decimal == int(decimal)
     decimal = int(decimal)
     hexadecimal = ""
     negative = False

data_structures/binary_tree/binary_search_tree_recursive.py

@@ -12,6 +12,8 @@ from __future__ import annotations
 import unittest
 from collections.abc import Iterator
 
+import pytest
+
 
 class Node:
     def __init__(self, label: int, parent: Node | None) -> None:
@@ -78,7 +80,7 @@ class BinarySearchTree:
                 node.right = self._put(node.right, label, node)
             else:
                 msg = f"Node with label {label} already exists"
-                raise Exception(msg)
+                raise ValueError(msg)
 
         return node
 
@@ -95,14 +97,14 @@ class BinarySearchTree:
         >>> node = t.search(3)
         Traceback (most recent call last):
             ...
-        Exception: Node with label 3 does not exist
+        ValueError: Node with label 3 does not exist
         """
         return self._search(self.root, label)
 
     def _search(self, node: Node | None, label: int) -> Node:
         if node is None:
             msg = f"Node with label {label} does not exist"
-            raise Exception(msg)
+            raise ValueError(msg)
         else:
             if label < node.label:
                 node = self._search(node.left, label)
@@ -124,7 +126,7 @@ class BinarySearchTree:
         >>> t.remove(3)
         Traceback (most recent call last):
             ...
-        Exception: Node with label 3 does not exist
+        ValueError: Node with label 3 does not exist
         """
         node = self.search(label)
         if node.right and node.left:
@@ -179,7 +181,7 @@ class BinarySearchTree:
         try:
             self.search(label)
             return True
-        except Exception:
+        except ValueError:
             return False
 
     def get_max_label(self) -> int:
@@ -190,7 +192,7 @@ class BinarySearchTree:
         >>> t.get_max_label()
         Traceback (most recent call last):
             ...
-        Exception: Binary search tree is empty
+        ValueError: Binary search tree is empty
 
         >>> t.put(8)
         >>> t.put(10)
@@ -198,7 +200,7 @@ class BinarySearchTree:
         10
         """
         if self.root is None:
-            raise Exception("Binary search tree is empty")
+            raise ValueError("Binary search tree is empty")
 
         node = self.root
         while node.right is not None:
@@ -214,7 +216,7 @@ class BinarySearchTree:
         >>> t.get_min_label()
         Traceback (most recent call last):
             ...
-        Exception: Binary search tree is empty
+        ValueError: Binary search tree is empty
 
         >>> t.put(8)
         >>> t.put(10)
@@ -222,7 +224,7 @@ class BinarySearchTree:
         8
         """
         if self.root is None:
-            raise Exception("Binary search tree is empty")
+            raise ValueError("Binary search tree is empty")
 
         node = self.root
         while node.left is not None:
@@ -359,7 +361,7 @@ class BinarySearchTreeTest(unittest.TestCase):
         assert t.root.left.left.parent == t.root.left
         assert t.root.left.left.label == 1
 
-        with self.assertRaises(Exception):  # noqa: B017
+        with pytest.raises(ValueError):
             t.put(1)
 
     def test_search(self) -> None:
@@ -371,7 +373,7 @@ class BinarySearchTreeTest(unittest.TestCase):
         node = t.search(13)
         assert node.label == 13
 
-        with self.assertRaises(Exception):  # noqa: B017
+        with pytest.raises(ValueError):
             t.search(2)
 
     def test_remove(self) -> None:
@@ -517,7 +519,7 @@ class BinarySearchTreeTest(unittest.TestCase):
         assert t.get_max_label() == 14
 
         t.empty()
-        with self.assertRaises(Exception):  # noqa: B017
+        with pytest.raises(ValueError):
             t.get_max_label()
 
     def test_get_min_label(self) -> None:
@@ -526,7 +528,7 @@ class BinarySearchTreeTest(unittest.TestCase):
         assert t.get_min_label() == 1
 
         t.empty()
-        with self.assertRaises(Exception):  # noqa: B017
+        with pytest.raises(ValueError):
             t.get_min_label()
 
     def test_inorder_traversal(self) -> None:

data_structures/hashing/tests/test_hash_map.py

@@ -65,14 +65,14 @@ _add_with_resize_down = [
 
 @pytest.mark.parametrize(
     "operations",
-    (
+    [
         pytest.param(_add_items, id="add items"),
         pytest.param(_overwrite_items, id="overwrite items"),
         pytest.param(_delete_items, id="delete items"),
         pytest.param(_access_absent_items, id="access absent items"),
         pytest.param(_add_with_resize_up, id="add with resize up"),
         pytest.param(_add_with_resize_down, id="add with resize down"),
-    ),
+    ],
 )
 def test_hash_map_is_the_same_as_dict(operations):
     my = HashMap(initial_block_size=4)

data_structures/linked_list/circular_linked_list.py

@@ -124,7 +124,8 @@ class CircularLinkedList:
         if not 0 <= index < len(self):
             raise IndexError("list index out of range.")
 
-        assert self.head is not None and self.tail is not None
+        assert self.head is not None
+        assert self.tail is not None
         delete_node: Node = self.head
         if self.head == self.tail:  # Just one node
             self.head = self.tail = None
@@ -137,7 +138,8 @@ class CircularLinkedList:
             for _ in range(index - 1):
                 assert temp is not None
                 temp = temp.next
-            assert temp is not None and temp.next is not None
+            assert temp is not None
+            assert temp.next is not None
             delete_node = temp.next
             temp.next = temp.next.next
             if index == len(self) - 1:  # Delete at tail

digital_image_processing/test_digital_image_processing.py

@@ -73,7 +73,8 @@ def test_median_filter():
 
 def test_sobel_filter():
     grad, theta = sob.sobel_filter(gray)
-    assert grad.any() and theta.any()
+    assert grad.any()
+    assert theta.any()
 
 
 def test_sepia():

graphs/graph_adjacency_list.py

@@ -22,6 +22,8 @@ import unittest
 from pprint import pformat
 from typing import Generic, TypeVar
 
+import pytest
+
 T = TypeVar("T")
 
 
@@ -185,9 +187,9 @@ class TestGraphAdjacencyList(unittest.TestCase):
         directed_graph: GraphAdjacencyList,
         edge: list[int],
     ) -> None:
-        self.assertTrue(undirected_graph.contains_edge(edge[0], edge[1]))
+        assert undirected_graph.contains_edge(edge[0], edge[1])
-        self.assertTrue(undirected_graph.contains_edge(edge[1], edge[0]))
+        assert undirected_graph.contains_edge(edge[1], edge[0])
-        self.assertTrue(directed_graph.contains_edge(edge[0], edge[1]))
+        assert directed_graph.contains_edge(edge[0], edge[1])
 
     def __assert_graph_edge_does_not_exist_check(
         self,
@@ -195,9 +197,9 @@ class TestGraphAdjacencyList(unittest.TestCase):
         directed_graph: GraphAdjacencyList,
         edge: list[int],
     ) -> None:
-        self.assertFalse(undirected_graph.contains_edge(edge[0], edge[1]))
+        assert not undirected_graph.contains_edge(edge[0], edge[1])
-        self.assertFalse(undirected_graph.contains_edge(edge[1], edge[0]))
+        assert not undirected_graph.contains_edge(edge[1], edge[0])
-        self.assertFalse(directed_graph.contains_edge(edge[0], edge[1]))
+        assert not directed_graph.contains_edge(edge[0], edge[1])
 
     def __assert_graph_vertex_exists_check(
         self,
@@ -205,8 +207,8 @@ class TestGraphAdjacencyList(unittest.TestCase):
         directed_graph: GraphAdjacencyList,
         vertex: int,
     ) -> None:
-        self.assertTrue(undirected_graph.contains_vertex(vertex))
+        assert undirected_graph.contains_vertex(vertex)
-        self.assertTrue(directed_graph.contains_vertex(vertex))
+        assert directed_graph.contains_vertex(vertex)
 
     def __assert_graph_vertex_does_not_exist_check(
         self,
@@ -214,13 +216,13 @@ class TestGraphAdjacencyList(unittest.TestCase):
         directed_graph: GraphAdjacencyList,
         vertex: int,
     ) -> None:
-        self.assertFalse(undirected_graph.contains_vertex(vertex))
+        assert not undirected_graph.contains_vertex(vertex)
-        self.assertFalse(directed_graph.contains_vertex(vertex))
+        assert not directed_graph.contains_vertex(vertex)
 
     def __generate_random_edges(
         self, vertices: list[int], edge_pick_count: int
     ) -> list[list[int]]:
-        self.assertTrue(edge_pick_count <= len(vertices))
+        assert edge_pick_count <= len(vertices)
 
         random_source_vertices: list[int] = random.sample(
             vertices[0 : int(len(vertices) / 2)], edge_pick_count
@@ -281,8 +283,8 @@ class TestGraphAdjacencyList(unittest.TestCase):
             self.__assert_graph_edge_exists_check(
                 undirected_graph, directed_graph, edge
             )
-        self.assertFalse(undirected_graph.directed)
+        assert not undirected_graph.directed
-        self.assertTrue(directed_graph.directed)
+        assert directed_graph.directed
 
     def test_contains_vertex(self) -> None:
         random_vertices: list[int] = random.sample(range(101), 20)
@@ -297,12 +299,8 @@ class TestGraphAdjacencyList(unittest.TestCase):
 
         # Test contains_vertex
         for num in range(101):
-            self.assertEqual(
+            assert (num in random_vertices) == undirected_graph.contains_vertex(num)
-                num in random_vertices, undirected_graph.contains_vertex(num)
+            assert (num in random_vertices) == directed_graph.contains_vertex(num)
-            )
-            self.assertEqual(
-                num in random_vertices, directed_graph.contains_vertex(num)
-            )
 
     def test_add_vertices(self) -> None:
         random_vertices: list[int] = random.sample(range(101), 20)
@@ -507,9 +505,9 @@ class TestGraphAdjacencyList(unittest.TestCase):
         ) = self.__generate_graphs(20, 0, 100, 4)
 
         for vertex in random_vertices:
-            with self.assertRaises(ValueError):
+            with pytest.raises(ValueError):
                 undirected_graph.add_vertex(vertex)
-            with self.assertRaises(ValueError):
+            with pytest.raises(ValueError):
                 directed_graph.add_vertex(vertex)
 
     def test_remove_vertex_exception_check(self) -> None:
@@ -522,9 +520,9 @@ class TestGraphAdjacencyList(unittest.TestCase):
 
         for i in range(101):
             if i not in random_vertices:
-                with self.assertRaises(ValueError):
+                with pytest.raises(ValueError):
                     undirected_graph.remove_vertex(i)
-                with self.assertRaises(ValueError):
+                with pytest.raises(ValueError):
                     directed_graph.remove_vertex(i)
 
     def test_add_edge_exception_check(self) -> None:
@@ -536,9 +534,9 @@ class TestGraphAdjacencyList(unittest.TestCase):
         ) = self.__generate_graphs(20, 0, 100, 4)
 
         for edge in random_edges:
-            with self.assertRaises(ValueError):
+            with pytest.raises(ValueError):
                 undirected_graph.add_edge(edge[0], edge[1])
-            with self.assertRaises(ValueError):
+            with pytest.raises(ValueError):
                 directed_graph.add_edge(edge[0], edge[1])
 
     def test_remove_edge_exception_check(self) -> None:
@@ -560,9 +558,9 @@ class TestGraphAdjacencyList(unittest.TestCase):
                     more_random_edges.append(edge)
 
         for edge in more_random_edges:
-            with self.assertRaises(ValueError):
+            with pytest.raises(ValueError):
                 undirected_graph.remove_edge(edge[0], edge[1])
-            with self.assertRaises(ValueError):
+            with pytest.raises(ValueError):
                 directed_graph.remove_edge(edge[0], edge[1])
 
     def test_contains_edge_exception_check(self) -> None:
@@ -574,14 +572,14 @@ class TestGraphAdjacencyList(unittest.TestCase):
         ) = self.__generate_graphs(20, 0, 100, 4)
 
         for vertex in random_vertices:
-            with self.assertRaises(ValueError):
+            with pytest.raises(ValueError):
                 undirected_graph.contains_edge(vertex, 102)
-            with self.assertRaises(ValueError):
+            with pytest.raises(ValueError):
                 directed_graph.contains_edge(vertex, 102)
 
-        with self.assertRaises(ValueError):
+        with pytest.raises(ValueError):
             undirected_graph.contains_edge(103, 102)
-        with self.assertRaises(ValueError):
+        with pytest.raises(ValueError):
             directed_graph.contains_edge(103, 102)
 
 

graphs/graph_adjacency_matrix.py

@@ -22,6 +22,8 @@ import unittest
 from pprint import pformat
 from typing import Generic, TypeVar
 
+import pytest
+
 T = TypeVar("T")
 
 
@@ -203,9 +205,9 @@ class TestGraphMatrix(unittest.TestCase):
         directed_graph: GraphAdjacencyMatrix,
         edge: list[int],
     ) -> None:
-        self.assertTrue(undirected_graph.contains_edge(edge[0], edge[1]))
+        assert undirected_graph.contains_edge(edge[0], edge[1])
-        self.assertTrue(undirected_graph.contains_edge(edge[1], edge[0]))
+        assert undirected_graph.contains_edge(edge[1], edge[0])
-        self.assertTrue(directed_graph.contains_edge(edge[0], edge[1]))
+        assert directed_graph.contains_edge(edge[0], edge[1])
 
     def __assert_graph_edge_does_not_exist_check(
         self,
@@ -213,9 +215,9 @@ class TestGraphMatrix(unittest.TestCase):
         directed_graph: GraphAdjacencyMatrix,
         edge: list[int],
     ) -> None:
-        self.assertFalse(undirected_graph.contains_edge(edge[0], edge[1]))
+        assert not undirected_graph.contains_edge(edge[0], edge[1])
-        self.assertFalse(undirected_graph.contains_edge(edge[1], edge[0]))
+        assert not undirected_graph.contains_edge(edge[1], edge[0])
-        self.assertFalse(directed_graph.contains_edge(edge[0], edge[1]))
+        assert not directed_graph.contains_edge(edge[0], edge[1])
 
     def __assert_graph_vertex_exists_check(
         self,
@@ -223,8 +225,8 @@ class TestGraphMatrix(unittest.TestCase):
         directed_graph: GraphAdjacencyMatrix,
         vertex: int,
     ) -> None:
-        self.assertTrue(undirected_graph.contains_vertex(vertex))
+        assert undirected_graph.contains_vertex(vertex)
-        self.assertTrue(directed_graph.contains_vertex(vertex))
+        assert directed_graph.contains_vertex(vertex)
 
     def __assert_graph_vertex_does_not_exist_check(
         self,
@@ -232,13 +234,13 @@ class TestGraphMatrix(unittest.TestCase):
         directed_graph: GraphAdjacencyMatrix,
         vertex: int,
     ) -> None:
-        self.assertFalse(undirected_graph.contains_vertex(vertex))
+        assert not undirected_graph.contains_vertex(vertex)
-        self.assertFalse(directed_graph.contains_vertex(vertex))
+        assert not directed_graph.contains_vertex(vertex)
 
     def __generate_random_edges(
         self, vertices: list[int], edge_pick_count: int
     ) -> list[list[int]]:
-        self.assertTrue(edge_pick_count <= len(vertices))
+        assert edge_pick_count <= len(vertices)
 
         random_source_vertices: list[int] = random.sample(
             vertices[0 : int(len(vertices) / 2)], edge_pick_count
@@ -300,8 +302,8 @@ class TestGraphMatrix(unittest.TestCase):
                 undirected_graph, directed_graph, edge
             )
 
-        self.assertFalse(undirected_graph.directed)
+        assert not undirected_graph.directed
-        self.assertTrue(directed_graph.directed)
+        assert directed_graph.directed
 
     def test_contains_vertex(self) -> None:
         random_vertices: list[int] = random.sample(range(101), 20)
@@ -316,12 +318,8 @@ class TestGraphMatrix(unittest.TestCase):
 
         # Test contains_vertex
         for num in range(101):
-            self.assertEqual(
+            assert (num in random_vertices) == undirected_graph.contains_vertex(num)
-                num in random_vertices, undirected_graph.contains_vertex(num)
+            assert (num in random_vertices) == directed_graph.contains_vertex(num)
-            )
-            self.assertEqual(
-                num in random_vertices, directed_graph.contains_vertex(num)
-            )
 
     def test_add_vertices(self) -> None:
         random_vertices: list[int] = random.sample(range(101), 20)
@@ -526,9 +524,9 @@ class TestGraphMatrix(unittest.TestCase):
         ) = self.__generate_graphs(20, 0, 100, 4)
 
         for vertex in random_vertices:
-            with self.assertRaises(ValueError):
+            with pytest.raises(ValueError):
                 undirected_graph.add_vertex(vertex)
-            with self.assertRaises(ValueError):
+            with pytest.raises(ValueError):
                 directed_graph.add_vertex(vertex)
 
     def test_remove_vertex_exception_check(self) -> None:
@@ -541,9 +539,9 @@ class TestGraphMatrix(unittest.TestCase):
 
         for i in range(101):
             if i not in random_vertices:
-                with self.assertRaises(ValueError):
+                with pytest.raises(ValueError):
                     undirected_graph.remove_vertex(i)
-                with self.assertRaises(ValueError):
+                with pytest.raises(ValueError):
                     directed_graph.remove_vertex(i)
 
     def test_add_edge_exception_check(self) -> None:
@@ -555,9 +553,9 @@ class TestGraphMatrix(unittest.TestCase):
         ) = self.__generate_graphs(20, 0, 100, 4)
 
         for edge in random_edges:
-            with self.assertRaises(ValueError):
+            with pytest.raises(ValueError):
                 undirected_graph.add_edge(edge[0], edge[1])
-            with self.assertRaises(ValueError):
+            with pytest.raises(ValueError):
                 directed_graph.add_edge(edge[0], edge[1])
 
     def test_remove_edge_exception_check(self) -> None:
@@ -579,9 +577,9 @@ class TestGraphMatrix(unittest.TestCase):
                     more_random_edges.append(edge)
 
         for edge in more_random_edges:
-            with self.assertRaises(ValueError):
+            with pytest.raises(ValueError):
                 undirected_graph.remove_edge(edge[0], edge[1])
-            with self.assertRaises(ValueError):
+            with pytest.raises(ValueError):
                 directed_graph.remove_edge(edge[0], edge[1])
 
     def test_contains_edge_exception_check(self) -> None:
@@ -593,14 +591,14 @@ class TestGraphMatrix(unittest.TestCase):
         ) = self.__generate_graphs(20, 0, 100, 4)
 
         for vertex in random_vertices:
-            with self.assertRaises(ValueError):
+            with pytest.raises(ValueError):
                 undirected_graph.contains_edge(vertex, 102)
-            with self.assertRaises(ValueError):
+            with pytest.raises(ValueError):
                 directed_graph.contains_edge(vertex, 102)
 
-        with self.assertRaises(ValueError):
+        with pytest.raises(ValueError):
             undirected_graph.contains_edge(103, 102)
-        with self.assertRaises(ValueError):
+        with pytest.raises(ValueError):
             directed_graph.contains_edge(103, 102)
 
 

hashes/sha256.py

@@ -203,7 +203,7 @@ class SHA256HashTest(unittest.TestCase):
         import hashlib
 
         msg = bytes("Test String", "utf-8")
-        self.assertEqual(SHA256(msg).hash, hashlib.sha256(msg).hexdigest())
+        assert SHA256(msg).hash == hashlib.sha256(msg).hexdigest()
 
 
 def main() -> None:

knapsack/tests/test_greedy_knapsack.py

@@ -1,5 +1,7 @@
 import unittest
 
+import pytest
+
 from knapsack import greedy_knapsack as kp
 
 
@@ -16,7 +18,7 @@ class TestClass(unittest.TestCase):
         profit = [10, 20, 30, 40, 50, 60]
         weight = [2, 4, 6, 8, 10, 12]
         max_weight = 100
-        self.assertEqual(kp.calc_profit(profit, weight, max_weight), 210)
+        assert kp.calc_profit(profit, weight, max_weight) == 210
 
     def test_negative_max_weight(self):
         """
@@ -26,7 +28,7 @@ class TestClass(unittest.TestCase):
         # profit = [10, 20, 30, 40, 50, 60]
         # weight = [2, 4, 6, 8, 10, 12]
         # max_weight = -15
-        self.assertRaisesRegex(ValueError, "max_weight must greater than zero.")
+        pytest.raises(ValueError, match="max_weight must greater than zero.")
 
     def test_negative_profit_value(self):
         """
@@ -36,7 +38,7 @@ class TestClass(unittest.TestCase):
         # profit = [10, -20, 30, 40, 50, 60]
         # weight = [2, 4, 6, 8, 10, 12]
         # max_weight = 15
-        self.assertRaisesRegex(ValueError, "Weight can not be negative.")
+        pytest.raises(ValueError, match="Weight can not be negative.")
 
     def test_negative_weight_value(self):
         """
@@ -46,7 +48,7 @@ class TestClass(unittest.TestCase):
         # profit = [10, 20, 30, 40, 50, 60]
         # weight = [2, -4, 6, -8, 10, 12]
         # max_weight = 15
-        self.assertRaisesRegex(ValueError, "Profit can not be negative.")
+        pytest.raises(ValueError, match="Profit can not be negative.")
 
     def test_null_max_weight(self):
         """
@@ -56,7 +58,7 @@ class TestClass(unittest.TestCase):
         # profit = [10, 20, 30, 40, 50, 60]
         # weight = [2, 4, 6, 8, 10, 12]
         # max_weight = null
-        self.assertRaisesRegex(ValueError, "max_weight must greater than zero.")
+        pytest.raises(ValueError, match="max_weight must greater than zero.")
 
     def test_unequal_list_length(self):
         """
@@ -66,9 +68,7 @@ class TestClass(unittest.TestCase):
         # profit = [10, 20, 30, 40, 50]
         # weight = [2, 4, 6, 8, 10, 12]
         # max_weight = 100
-        self.assertRaisesRegex(
+        pytest.raises(IndexError, match="The length of profit and weight must be same.")
-            IndexError, "The length of profit and weight must be same."
-        )
 
 
 if __name__ == "__main__":

knapsack/tests/test_knapsack.py

@@ -20,12 +20,12 @@ class Test(unittest.TestCase):
         val = [0]
         w = [0]
         c = len(val)
-        self.assertEqual(k.knapsack(cap, w, val, c), 0)
+        assert k.knapsack(cap, w, val, c) == 0
 
         val = [60]
         w = [10]
         c = len(val)
-        self.assertEqual(k.knapsack(cap, w, val, c), 0)
+        assert k.knapsack(cap, w, val, c) == 0
 
     def test_easy_case(self):
         """
@@ -35,7 +35,7 @@ class Test(unittest.TestCase):
         val = [1, 2, 3]
         w = [3, 2, 1]
         c = len(val)
-        self.assertEqual(k.knapsack(cap, w, val, c), 5)
+        assert k.knapsack(cap, w, val, c) == 5
 
     def test_knapsack(self):
         """
@@ -45,7 +45,7 @@ class Test(unittest.TestCase):
         val = [60, 100, 120]
         w = [10, 20, 30]
         c = len(val)
-        self.assertEqual(k.knapsack(cap, w, val, c), 220)
+        assert k.knapsack(cap, w, val, c) == 220
 
 
 if __name__ == "__main__":

linear_algebra/src/lib.py

@@ -200,7 +200,8 @@ def unit_basis_vector(dimension: int, pos: int) -> Vector:
     at index 'pos' (indexing at 0)
     """
     # precondition
-    assert isinstance(dimension, int) and (isinstance(pos, int))
+    assert isinstance(dimension, int)
+    assert isinstance(pos, int)
     ans = [0] * dimension
     ans[pos] = 1
     return Vector(ans)
@@ -213,11 +214,9 @@ def axpy(scalar: float, x: Vector, y: Vector) -> Vector:
     computes the axpy operation
     """
     # precondition
-    assert (
+    assert isinstance(x, Vector)
-        isinstance(x, Vector)
+    assert isinstance(y, Vector)
-        and isinstance(y, Vector)
+    assert isinstance(scalar, (int, float))
-        and (isinstance(scalar, (int, float)))
-    )
     return x * scalar + y
 
 

linear_algebra/src/schur_complement.py

@@ -1,6 +1,7 @@
 import unittest
 
 import numpy as np
+import pytest
 
 
 def schur_complement(
@@ -70,14 +71,14 @@ class TestSchurComplement(unittest.TestCase):
         det_a = np.linalg.det(a)
         det_s = np.linalg.det(s)
 
-        self.assertAlmostEqual(det_x, det_a * det_s)
+        assert np.is_close(det_x, det_a * det_s)
 
     def test_improper_a_b_dimensions(self) -> None:
         a = np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]])
         b = np.array([[0, 3], [3, 0], [2, 3]])
         c = np.array([[2, 1], [6, 3]])
 
-        with self.assertRaises(ValueError):
+        with pytest.raises(ValueError):
             schur_complement(a, b, c)
 
     def test_improper_b_c_dimensions(self) -> None:
@@ -85,7 +86,7 @@ class TestSchurComplement(unittest.TestCase):
         b = np.array([[0, 3], [3, 0], [2, 3]])
         c = np.array([[2, 1, 3], [6, 3, 5]])
 
-        with self.assertRaises(ValueError):
+        with pytest.raises(ValueError):
             schur_complement(a, b, c)
 
 

linear_algebra/src/test_linear_algebra.py

@@ -8,6 +8,8 @@ This file contains the test-suite for the linear algebra library.
 """
 import unittest
 
+import pytest
+
 from .lib import (
     Matrix,
     Vector,
@@ -24,8 +26,8 @@ class Test(unittest.TestCase):
         test for method component()
         """
         x = Vector([1, 2, 3])
-        self.assertEqual(x.component(0), 1)
+        assert x.component(0) == 1
-        self.assertEqual(x.component(2), 3)
+        assert x.component(2) == 3
         _ = Vector()
 
     def test_str(self) -> None:
@@ -33,14 +35,14 @@ class Test(unittest.TestCase):
         test for method toString()
         """
         x = Vector([0, 0, 0, 0, 0, 1])
-        self.assertEqual(str(x), "(0,0,0,0,0,1)")
+        assert str(x) == "(0,0,0,0,0,1)"
 
     def test_size(self) -> None:
         """
         test for method size()
         """
         x = Vector([1, 2, 3, 4])
-        self.assertEqual(len(x), 4)
+        assert len(x) == 4
 
     def test_euclidean_length(self) -> None:
         """
@@ -50,10 +52,10 @@ class Test(unittest.TestCase):
         y = Vector([1, 2, 3, 4, 5])
         z = Vector([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
         w = Vector([1, -1, 1, -1, 2, -3, 4, -5])
-        self.assertAlmostEqual(x.euclidean_length(), 2.236, 3)
+        assert x.euclidean_length() == pytest.approx(2.236, abs=1e-3)
-        self.assertAlmostEqual(y.euclidean_length(), 7.416, 3)
+        assert y.euclidean_length() == pytest.approx(7.416, abs=1e-3)
-        self.assertEqual(z.euclidean_length(), 0)
+        assert z.euclidean_length() == 0
-        self.assertAlmostEqual(w.euclidean_length(), 7.616, 3)
+        assert w.euclidean_length() == pytest.approx(7.616, abs=1e-3)
 
     def test_add(self) -> None:
         """
@@ -61,9 +63,9 @@ class Test(unittest.TestCase):
         """
         x = Vector([1, 2, 3])
         y = Vector([1, 1, 1])
-        self.assertEqual((x + y).component(0), 2)
+        assert (x + y).component(0) == 2
-        self.assertEqual((x + y).component(1), 3)
+        assert (x + y).component(1) == 3
-        self.assertEqual((x + y).component(2), 4)
+        assert (x + y).component(2) == 4
 
     def test_sub(self) -> None:
         """
@@ -71,9 +73,9 @@ class Test(unittest.TestCase):
         """
         x = Vector([1, 2, 3])
         y = Vector([1, 1, 1])
-        self.assertEqual((x - y).component(0), 0)
+        assert (x - y).component(0) == 0
-        self.assertEqual((x - y).component(1), 1)
+        assert (x - y).component(1) == 1
-        self.assertEqual((x - y).component(2), 2)
+        assert (x - y).component(2) == 2
 
     def test_mul(self) -> None:
         """
@@ -82,20 +84,20 @@ class Test(unittest.TestCase):
         x = Vector([1, 2, 3])
         a = Vector([2, -1, 4])  # for test of dot product
         b = Vector([1, -2, -1])
-        self.assertEqual(str(x * 3.0), "(3.0,6.0,9.0)")
+        assert str(x * 3.0) == "(3.0,6.0,9.0)"
-        self.assertEqual((a * b), 0)
+        assert a * b == 0
 
     def test_zero_vector(self) -> None:
         """
         test for global function zero_vector()
         """
-        self.assertEqual(str(zero_vector(10)).count("0"), 10)
+        assert str(zero_vector(10)).count("0") == 10
 
     def test_unit_basis_vector(self) -> None:
         """
         test for global function unit_basis_vector()
         """
-        self.assertEqual(str(unit_basis_vector(3, 1)), "(0,1,0)")
+        assert str(unit_basis_vector(3, 1)) == "(0,1,0)"
 
     def test_axpy(self) -> None:
         """
@@ -103,7 +105,7 @@ class Test(unittest.TestCase):
         """
         x = Vector([1, 2, 3])
         y = Vector([1, 0, 1])
-        self.assertEqual(str(axpy(2, x, y)), "(3,4,7)")
+        assert str(axpy(2, x, y)) == "(3,4,7)"
 
     def test_copy(self) -> None:
         """
@@ -111,7 +113,7 @@ class Test(unittest.TestCase):
         """
         x = Vector([1, 0, 0, 0, 0, 0])
         y = x.copy()
-        self.assertEqual(str(x), str(y))
+        assert str(x) == str(y)
 
     def test_change_component(self) -> None:
         """
@@ -120,14 +122,14 @@ class Test(unittest.TestCase):
         x = Vector([1, 0, 0])
         x.change_component(0, 0)
         x.change_component(1, 1)
-        self.assertEqual(str(x), "(0,1,0)")
+        assert str(x) == "(0,1,0)"
 
     def test_str_matrix(self) -> None:
         """
         test for Matrix method str()
         """
         a = Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]], 3, 3)
-        self.assertEqual("|1,2,3|\n|2,4,5|\n|6,7,8|\n", str(a))
+        assert str(a) == "|1,2,3|\n|2,4,5|\n|6,7,8|\n"
 
     def test_minor(self) -> None:
         """
@@ -137,7 +139,7 @@ class Test(unittest.TestCase):
         minors = [[-3, -14, -10], [-5, -10, -5], [-2, -1, 0]]
         for x in range(a.height()):
             for y in range(a.width()):
-                self.assertEqual(minors[x][y], a.minor(x, y))
+                assert minors[x][y] == a.minor(x, y)
 
     def test_cofactor(self) -> None:
         """
@@ -147,14 +149,14 @@ class Test(unittest.TestCase):
         cofactors = [[-3, 14, -10], [5, -10, 5], [-2, 1, 0]]
         for x in range(a.height()):
             for y in range(a.width()):
-                self.assertEqual(cofactors[x][y], a.cofactor(x, y))
+                assert cofactors[x][y] == a.cofactor(x, y)
 
     def test_determinant(self) -> None:
         """
         test for Matrix method determinant()
         """
         a = Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]], 3, 3)
-        self.assertEqual(-5, a.determinant())
+        assert a.determinant() == -5
 
     def test__mul__matrix(self) -> None:
         """
@@ -162,8 +164,8 @@ class Test(unittest.TestCase):
         """
         a = Matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]], 3, 3)
         x = Vector([1, 2, 3])
-        self.assertEqual("(14,32,50)", str(a * x))
+        assert str(a * x) == "(14,32,50)"
-        self.assertEqual("|2,4,6|\n|8,10,12|\n|14,16,18|\n", str(a * 2))
+        assert str(a * 2) == "|2,4,6|\n|8,10,12|\n|14,16,18|\n"
 
     def test_change_component_matrix(self) -> None:
         """
@@ -171,14 +173,14 @@ class Test(unittest.TestCase):
         """
         a = Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]], 3, 3)
         a.change_component(0, 2, 5)
-        self.assertEqual("|1,2,5|\n|2,4,5|\n|6,7,8|\n", str(a))
+        assert str(a) == "|1,2,5|\n|2,4,5|\n|6,7,8|\n"
 
     def test_component_matrix(self) -> None:
         """
         test for Matrix method component()
         """
         a = Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]], 3, 3)
-        self.assertEqual(7, a.component(2, 1), 0.01)
+        assert a.component(2, 1) == 7, 0.01
 
     def test__add__matrix(self) -> None:
         """
@@ -186,7 +188,7 @@ class Test(unittest.TestCase):
         """
         a = Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]], 3, 3)
         b = Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 10]], 3, 3)
-        self.assertEqual("|2,4,10|\n|4,8,10|\n|12,14,18|\n", str(a + b))
+        assert str(a + b) == "|2,4,10|\n|4,8,10|\n|12,14,18|\n"
 
     def test__sub__matrix(self) -> None:
         """
@@ -194,15 +196,14 @@ class Test(unittest.TestCase):
         """
         a = Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]], 3, 3)
         b = Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 10]], 3, 3)
-        self.assertEqual("|0,0,-4|\n|0,0,0|\n|0,0,-2|\n", str(a - b))
+        assert str(a - b) == "|0,0,-4|\n|0,0,0|\n|0,0,-2|\n"
 
     def test_square_zero_matrix(self) -> None:
         """
         test for global function square_zero_matrix()
         """
-        self.assertEqual(
+        assert str(square_zero_matrix(5)) == (
-            "|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n",
+            "|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n"
-            str(square_zero_matrix(5)),
         )
 
 

machine_learning/dimensionality_reduction.py

@@ -169,7 +169,7 @@ def test_linear_discriminant_analysis() -> None:
     dimensions = 2
 
     # Assert that the function raises an AssertionError if dimensions > classes
-    with pytest.raises(AssertionError) as error_info:
+    with pytest.raises(AssertionError) as error_info:  # noqa: PT012
         projected_data = linear_discriminant_analysis(
             features, labels, classes, dimensions
         )
@@ -185,7 +185,7 @@ def test_principal_component_analysis() -> None:
     dimensions = 2
     expected_output = np.array([[6.92820323, 8.66025404, 10.39230485], [3.0, 3.0, 3.0]])
 
-    with pytest.raises(AssertionError) as error_info:
+    with pytest.raises(AssertionError) as error_info:  # noqa: PT012
         output = principal_component_analysis(features, dimensions)
         if not np.allclose(expected_output, output):
             raise AssertionError

machine_learning/k_means_clust.py

@@ -128,7 +128,7 @@ def plot_heterogeneity(heterogeneity, k):
 def kmeans(
     data, k, initial_centroids, maxiter=500, record_heterogeneity=None, verbose=False
 ):
-    """This function runs k-means on given data and initial set of centroids.
+    """Runs k-means on given data and initial set of centroids.
     maxiter: maximum number of iterations to run.(default=500)
     record_heterogeneity: (optional) a list, to store the history of heterogeneity
                           as function of iterations
@@ -195,20 +195,20 @@ if False:  # change to true to run this test case.
 
 
 def report_generator(
-    df: pd.DataFrame, clustering_variables: np.ndarray, fill_missing_report=None
+    predicted: pd.DataFrame, clustering_variables: np.ndarray, fill_missing_report=None
 ) -> pd.DataFrame:
     """
-    Generates a clustering report. This function takes 2 arguments as input:
+    Generate a clustering report given these two arguments:
-        df - dataframe with predicted cluster column
+        predicted - dataframe with predicted cluster column
         fill_missing_report - dictionary of rules on how we are going to fill in missing
         values for final generated report (not included in modelling);
-    >>> data = pd.DataFrame()
+    >>> predicted = pd.DataFrame()
-    >>> data['numbers'] = [1, 2, 3]
+    >>> predicted['numbers'] = [1, 2, 3]
-    >>> data['col1'] = [0.5, 2.5, 4.5]
+    >>> predicted['col1'] = [0.5, 2.5, 4.5]
-    >>> data['col2'] = [100, 200, 300]
+    >>> predicted['col2'] = [100, 200, 300]
-    >>> data['col3'] = [10, 20, 30]
+    >>> predicted['col3'] = [10, 20, 30]
-    >>> data['Cluster'] = [1, 1, 2]
+    >>> predicted['Cluster'] = [1, 1, 2]
-    >>> report_generator(data, ['col1', 'col2'], 0)
+    >>> report_generator(predicted, ['col1', 'col2'], 0)
                Features               Type   Mark           1           2
     0    # of Customers        ClusterSize  False    2.000000    1.000000
     1    % of Customers  ClusterProportion  False    0.666667    0.333333
@@ -226,11 +226,11 @@ def report_generator(
     """
     # Fill missing values with given rules
     if fill_missing_report:
-        df = df.fillna(value=fill_missing_report)
+        predicted = predicted.fillna(value=fill_missing_report)
-    df["dummy"] = 1
+    predicted["dummy"] = 1
-    numeric_cols = df.select_dtypes(np.number).columns
+    numeric_cols = predicted.select_dtypes(np.number).columns
     report = (
-        df.groupby(["Cluster"])[  # construct report dataframe
+        predicted.groupby(["Cluster"])[  # construct report dataframe
             numeric_cols
         ]  # group by cluster number
         .agg(
@@ -267,46 +267,43 @@ def report_generator(
         .rename(index=str, columns={"level_0": "Features", "level_1": "Type"})
     )  # rename columns
     # calculate the size of cluster(count of clientID's)
+    # avoid SettingWithCopyWarning
     clustersize = report[
         (report["Features"] == "dummy") & (report["Type"] == "count")
-    ].copy()  # avoid SettingWithCopyWarning
+    ].copy()
-    clustersize.Type = (
+    # rename created predicted cluster to match report column names
-        "ClusterSize"  # rename created cluster df to match report column names
+    clustersize.Type = "ClusterSize"
-    )
     clustersize.Features = "# of Customers"
+    # calculating the proportion of cluster
     clusterproportion = pd.DataFrame(
-        clustersize.iloc[:, 2:].values
+        clustersize.iloc[:, 2:].to_numpy() / clustersize.iloc[:, 2:].to_numpy().sum()
-        / clustersize.iloc[:, 2:].values.sum()  # calculating the proportion of cluster
     )
-    clusterproportion[
+    # rename created predicted cluster to match report column names
-        "Type"
+    clusterproportion["Type"] = "% of Customers"
-    ] = "% of Customers"  # rename created cluster df to match report column names
     clusterproportion["Features"] = "ClusterProportion"
     cols = clusterproportion.columns.tolist()
     cols = cols[-2:] + cols[:-2]
     clusterproportion = clusterproportion[cols]  # rearrange columns to match report
     clusterproportion.columns = report.columns
+    # generating dataframe with count of nan values
     a = pd.DataFrame(
         abs(
-            report[report["Type"] == "count"].iloc[:, 2:].values
+            report[report["Type"] == "count"].iloc[:, 2:].to_numpy()
-            - clustersize.iloc[:, 2:].values
+            - clustersize.iloc[:, 2:].to_numpy()
         )
-    )  # generating df with count of nan values
+    )
     a["Features"] = 0
     a["Type"] = "# of nan"
-    a.Features = report[
+    # filling values in order to match report
-        report["Type"] == "count"
+    a.Features = report[report["Type"] == "count"].Features.tolist()
-    ].Features.tolist()  # filling values in order to match report
     cols = a.columns.tolist()
     cols = cols[-2:] + cols[:-2]
     a = a[cols]  # rearrange columns to match report
     a.columns = report.columns  # rename columns to match report
-    report = report.drop(
+    # drop count values except for cluster size
-        report[report.Type == "count"].index
+    report = report.drop(report[report.Type == "count"].index)
-    )  # drop count values except for cluster size
+    # concat report with cluster size and nan values
-    report = pd.concat(
+    report = pd.concat([report, a, clustersize, clusterproportion], axis=0)
-        [report, a, clustersize, clusterproportion], axis=0
-    )  # concat report with cluster size and nan values
     report["Mark"] = report["Features"].isin(clustering_variables)
     cols = report.columns.tolist()
     cols = cols[0:2] + cols[-1:] + cols[2:-1]

maths/least_common_multiple.py

@@ -67,8 +67,8 @@ class TestLeastCommonMultiple(unittest.TestCase):
             slow_result = least_common_multiple_slow(first_num, second_num)
             fast_result = least_common_multiple_fast(first_num, second_num)
             with self.subTest(i=i):
-                self.assertEqual(slow_result, self.expected_results[i])
+                assert slow_result == self.expected_results[i]
-                self.assertEqual(fast_result, self.expected_results[i])
+                assert fast_result == self.expected_results[i]
 
 
 if __name__ == "__main__":

maths/modular_division.py

@@ -28,7 +28,9 @@ def modular_division(a: int, b: int, n: int) -> int:
     4
 
     """
-    assert n > 1 and a > 0 and greatest_common_divisor(a, n) == 1
+    assert n > 1
+    assert a > 0
+    assert greatest_common_divisor(a, n) == 1
     (d, t, s) = extended_gcd(n, a)  # Implemented below
     x = (b * s) % n
     return x
@@ -86,7 +88,8 @@ def extended_gcd(a: int, b: int) -> tuple[int, int, int]:
     ** extended_gcd function is used when d = gcd(a,b) is required in output
 
     """
-    assert a >= 0 and b >= 0
+    assert a >= 0
+    assert b >= 0
 
     if b == 0:
         d, x, y = a, 1, 0
@@ -95,7 +98,8 @@ def extended_gcd(a: int, b: int) -> tuple[int, int, int]:
         x = q
         y = p - q * (a // b)
 
-    assert a % d == 0 and b % d == 0
+    assert a % d == 0
+    assert b % d == 0
     assert d == a * x + b * y
 
     return (d, x, y)

maths/prime_check.py

@@ -3,6 +3,8 @@
 import math
 import unittest
 
+import pytest
+
 
 def is_prime(number: int) -> bool:
     """Checks to see if a number is a prime in O(sqrt(n)).
@@ -50,33 +52,31 @@ def is_prime(number: int) -> bool:
 
 class Test(unittest.TestCase):
     def test_primes(self):
-        self.assertTrue(is_prime(2))
+        assert is_prime(2)
-        self.assertTrue(is_prime(3))
+        assert is_prime(3)
-        self.assertTrue(is_prime(5))
+        assert is_prime(5)
-        self.assertTrue(is_prime(7))
+        assert is_prime(7)
-        self.assertTrue(is_prime(11))
+        assert is_prime(11)
-        self.assertTrue(is_prime(13))
+        assert is_prime(13)
-        self.assertTrue(is_prime(17))
+        assert is_prime(17)
-        self.assertTrue(is_prime(19))
+        assert is_prime(19)
-        self.assertTrue(is_prime(23))
+        assert is_prime(23)
-        self.assertTrue(is_prime(29))
+        assert is_prime(29)
 
     def test_not_primes(self):
-        with self.assertRaises(AssertionError):
+        with pytest.raises(AssertionError):
             is_prime(-19)
-        self.assertFalse(
+        assert not is_prime(
-            is_prime(0),
+            0
-            "Zero doesn't have any positive factors, primes must have exactly two.",
+        ), "Zero doesn't have any positive factors, primes must have exactly two."
-        )
+        assert not is_prime(
-        self.assertFalse(
+            1
-            is_prime(1),
+        ), "One only has 1 positive factor, primes must have exactly two."
-            "One only has 1 positive factor, primes must have exactly two.",
+        assert not is_prime(2 * 2)
-        )
+        assert not is_prime(2 * 3)
-        self.assertFalse(is_prime(2 * 2))
+        assert not is_prime(3 * 3)
-        self.assertFalse(is_prime(2 * 3))
+        assert not is_prime(3 * 5)
-        self.assertFalse(is_prime(3 * 3))
+        assert not is_prime(3 * 5 * 7)
-        self.assertFalse(is_prime(3 * 5))
-        self.assertFalse(is_prime(3 * 5 * 7))
 
 
 if __name__ == "__main__":

matrix/sherman_morrison.py

@@ -114,7 +114,8 @@ class Matrix:
 
         # Validation
         assert isinstance(another, Matrix)
-        assert self.row == another.row and self.column == another.column
+        assert self.row == another.row
+        assert self.column == another.column
 
         # Add
         result = Matrix(self.row, self.column)
@@ -225,7 +226,8 @@ class Matrix:
         """
 
         # Size validation
-        assert isinstance(u, Matrix) and isinstance(v, Matrix)
+        assert isinstance(u, Matrix)
+        assert isinstance(v, Matrix)
         assert self.row == self.column == u.row == v.row  # u, v should be column vector
         assert u.column == v.column == 1  # u, v should be column vector
 

matrix/tests/test_matrix_operation.py

@@ -31,14 +31,14 @@ stream_handler = logging.StreamHandler(sys.stdout)
 logger.addHandler(stream_handler)
 
 
-@pytest.mark.mat_ops
+@pytest.mark.mat_ops()
 @pytest.mark.parametrize(
     ("mat1", "mat2"), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]
 )
 def test_addition(mat1, mat2):
     if (np.array(mat1)).shape < (2, 2) or (np.array(mat2)).shape < (2, 2):
+        logger.info(f"\n\t{test_addition.__name__} returned integer")
         with pytest.raises(TypeError):
-            logger.info(f"\n\t{test_addition.__name__} returned integer")
             matop.add(mat1, mat2)
     elif (np.array(mat1)).shape == (np.array(mat2)).shape:
         logger.info(f"\n\t{test_addition.__name__} with same matrix dims")
@@ -46,19 +46,19 @@ def test_addition(mat1, mat2):
         theo = matop.add(mat1, mat2)
         assert theo == act
     else:
+        logger.info(f"\n\t{test_addition.__name__} with different matrix dims")
         with pytest.raises(ValueError):
-            logger.info(f"\n\t{test_addition.__name__} with different matrix dims")
             matop.add(mat1, mat2)
 
 
-@pytest.mark.mat_ops
+@pytest.mark.mat_ops()
 @pytest.mark.parametrize(
     ("mat1", "mat2"), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]
 )
 def test_subtraction(mat1, mat2):
     if (np.array(mat1)).shape < (2, 2) or (np.array(mat2)).shape < (2, 2):
+        logger.info(f"\n\t{test_subtraction.__name__} returned integer")
         with pytest.raises(TypeError):
-            logger.info(f"\n\t{test_subtraction.__name__} returned integer")
             matop.subtract(mat1, mat2)
     elif (np.array(mat1)).shape == (np.array(mat2)).shape:
         logger.info(f"\n\t{test_subtraction.__name__} with same matrix dims")
@@ -66,12 +66,12 @@ def test_subtraction(mat1, mat2):
         theo = matop.subtract(mat1, mat2)
         assert theo == act
     else:
+        logger.info(f"\n\t{test_subtraction.__name__} with different matrix dims")
         with pytest.raises(ValueError):
-            logger.info(f"\n\t{test_subtraction.__name__} with different matrix dims")
             assert matop.subtract(mat1, mat2)
 
 
-@pytest.mark.mat_ops
+@pytest.mark.mat_ops()
 @pytest.mark.parametrize(
     ("mat1", "mat2"), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]
 )
@@ -86,33 +86,33 @@ def test_multiplication(mat1, mat2):
         theo = matop.multiply(mat1, mat2)
         assert theo == act
     else:
+        logger.info(
+            f"\n\t{test_multiplication.__name__} does not meet dim requirements"
+        )
         with pytest.raises(ValueError):
-            logger.info(
-                f"\n\t{test_multiplication.__name__} does not meet dim requirements"
-            )
             assert matop.subtract(mat1, mat2)
 
 
-@pytest.mark.mat_ops
+@pytest.mark.mat_ops()
 def test_scalar_multiply():
     act = (3.5 * np.array(mat_a)).tolist()
     theo = matop.scalar_multiply(mat_a, 3.5)
     assert theo == act
 
 
-@pytest.mark.mat_ops
+@pytest.mark.mat_ops()
 def test_identity():
     act = (np.identity(5)).tolist()
     theo = matop.identity(5)
     assert theo == act
 
 
-@pytest.mark.mat_ops
+@pytest.mark.mat_ops()
 @pytest.mark.parametrize("mat", [mat_a, mat_b, mat_c, mat_d, mat_e, mat_f])
 def test_transpose(mat):
     if (np.array(mat)).shape < (2, 2):
+        logger.info(f"\n\t{test_transpose.__name__} returned integer")
         with pytest.raises(TypeError):
-            logger.info(f"\n\t{test_transpose.__name__} returned integer")
             matop.transpose(mat)
     else:
         act = (np.transpose(mat)).tolist()

project_euler/problem_054/test_poker_hand.py

@@ -147,39 +147,39 @@ def generate_random_hands(number_of_hands: int = 100):
     return (generate_random_hand() for _ in range(number_of_hands))
 
 
-@pytest.mark.parametrize("hand, expected", TEST_FLUSH)
+@pytest.mark.parametrize(("hand", "expected"), TEST_FLUSH)
 def test_hand_is_flush(hand, expected):
     assert PokerHand(hand)._is_flush() == expected
 
 
-@pytest.mark.parametrize("hand, expected", TEST_STRAIGHT)
+@pytest.mark.parametrize(("hand", "expected"), TEST_STRAIGHT)
 def test_hand_is_straight(hand, expected):
     assert PokerHand(hand)._is_straight() == expected
 
 
-@pytest.mark.parametrize("hand, expected, card_values", TEST_FIVE_HIGH_STRAIGHT)
+@pytest.mark.parametrize(("hand", "expected", "card_values"), TEST_FIVE_HIGH_STRAIGHT)
 def test_hand_is_five_high_straight(hand, expected, card_values):
     player = PokerHand(hand)
     assert player._is_five_high_straight() == expected
     assert player._card_values == card_values
 
 
-@pytest.mark.parametrize("hand, expected", TEST_KIND)
+@pytest.mark.parametrize(("hand", "expected"), TEST_KIND)
 def test_hand_is_same_kind(hand, expected):
     assert PokerHand(hand)._is_same_kind() == expected
 
 
-@pytest.mark.parametrize("hand, expected", TEST_TYPES)
+@pytest.mark.parametrize(("hand", "expected"), TEST_TYPES)
 def test_hand_values(hand, expected):
     assert PokerHand(hand)._hand_type == expected
 
 
-@pytest.mark.parametrize("hand, other, expected", TEST_COMPARE)
+@pytest.mark.parametrize(("hand", "other", "expected"), TEST_COMPARE)
 def test_compare_simple(hand, other, expected):
     assert PokerHand(hand).compare_with(PokerHand(other)) == expected
 
 
-@pytest.mark.parametrize("hand, other, expected", generate_random_hands())
+@pytest.mark.parametrize(("hand", "other", "expected"), generate_random_hands())
 def test_compare_random(hand, other, expected):
     assert PokerHand(hand).compare_with(PokerHand(other)) == expected
 

pyproject.toml

@@ -19,6 +19,8 @@ ignore = [    # `ruff rule S101` for a description of that rule
   "PLW0120",  # `else` clause on loop without a `break` statement -- FIX ME
   "PLW060",   # Using global for `{name}` but no assignment is done -- DO NOT FIX
   "PLW2901",  # PLW2901: Redefined loop variable -- FIX ME
+  "PT011",    # `pytest.raises(Exception)` is too broad, set the `match` parameter or use a more specific exception
+  "PT018",    # Assertion should be broken down into multiple parts
   "RUF00",    # Ambiguous unicode character and other rules
   "RUF100",   # Unused `noqa` directive -- FIX ME
   "S101",     # Use of `assert` detected -- DO NOT FIX
@@ -37,6 +39,7 @@ select = [  # https://beta.ruff.rs/docs/rules
   "BLE",    # flake8-blind-except
   "C4",     # flake8-comprehensions
   "C90",    # McCabe cyclomatic complexity
+  "DJ",     # flake8-django
   "DTZ",    # flake8-datetimez
   "E",      # pycodestyle
   "EM",     # flake8-errmsg
@@ -52,9 +55,11 @@ select = [  # https://beta.ruff.rs/docs/rules
   "ISC",  # flake8-implicit-str-concat
   "N",      # pep8-naming
   "NPY",    # NumPy-specific rules
+  "PD",   # pandas-vet
   "PGH",    # pygrep-hooks
   "PIE",    # flake8-pie
   "PL",     # Pylint
+  "PT",   # flake8-pytest-style
   "PYI",    # flake8-pyi
   "RSE",    # flake8-raise
   "RUF",    # Ruff-specific rules
@@ -70,11 +75,8 @@ select = [  # https://beta.ruff.rs/docs/rules
   # "ANN",  # flake8-annotations  # FIX ME?
   # "COM",  # flake8-commas
   # "D",    # pydocstyle -- FIX ME?
-  # "DJ",   # flake8-django
   # "ERA",  # eradicate -- DO NOT FIX
   # "FBT",  # flake8-boolean-trap  # FIX ME
-  # "PD",   # pandas-vet
-  # "PT",   # flake8-pytest-style
   # "PTH",  # flake8-use-pathlib  # FIX ME
   # "Q",    # flake8-quotes
   # "RET",  # flake8-return  # FIX ME?

strings/knuth_morris_pratt.py

@@ -71,7 +71,8 @@ if __name__ == "__main__":
     pattern = "abc1abc12"
     text1 = "alskfjaldsabc1abc1abc12k23adsfabcabc"
     text2 = "alskfjaldsk23adsfabcabc"
-    assert knuth_morris_pratt(text1, pattern) and knuth_morris_pratt(text2, pattern)
+    assert knuth_morris_pratt(text1, pattern)
+    assert knuth_morris_pratt(text2, pattern)
 
     # Test 2)
     pattern = "ABABX"

strings/rabin_karp.py

@@ -60,7 +60,8 @@ def test_rabin_karp() -> None:
     pattern = "abc1abc12"
     text1 = "alskfjaldsabc1abc1abc12k23adsfabcabc"
     text2 = "alskfjaldsk23adsfabcabc"
-    assert rabin_karp(pattern, text1) and not rabin_karp(pattern, text2)
+    assert rabin_karp(pattern, text1)
+    assert not rabin_karp(pattern, text2)
 
     # Test 2)
     pattern = "ABABX"