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Ruff pandas vet (#10281)

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* 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>
This commit is contained in:
Christian Clauss 2023-10-11 20:30:02 +02:00 committed by GitHub
parent d5323dbaee
commit 3f094fe49d
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28 changed files with 260 additions and 241 deletions
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2
.pre-commit-config.yaml
View File

@ -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:

1
DIRECTORY.md
View File

@ -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)

6
blockchain/diophantine_equation.py
View File

@ -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)

18
ciphers/xor_cipher.py
View File

@ -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:

3
conversions/decimal_to_hexadecimal.py
View File

@ -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

28
data_structures/binary_tree/binary_search_tree_recursive.py
View File

@ -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:

4
data_structures/hashing/tests/test_hash_map.py
View File

@ -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)

6
data_structures/linked_list/circular_linked_list.py
View File

@ -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

3
digital_image_processing/test_digital_image_processing.py
View File

@ -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():

60
graphs/graph_adjacency_list.py
View File

@ -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]))
self.assertTrue(undirected_graph.contains_edge(edge[1], edge[0]))
self.assertTrue(directed_graph.contains_edge(edge[0], edge[1]))
assert undirected_graph.contains_edge(edge[0], edge[1])
assert undirected_graph.contains_edge(edge[1], edge[0])
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]))
self.assertFalse(undirected_graph.contains_edge(edge[1], edge[0]))
self.assertFalse(directed_graph.contains_edge(edge[0], edge[1]))
assert not undirected_graph.contains_edge(edge[0], edge[1])
assert not undirected_graph.contains_edge(edge[1], edge[0])
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))
self.assertTrue(directed_graph.contains_vertex(vertex))
assert undirected_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))
self.assertFalse(directed_graph.contains_vertex(vertex))
assert not undirected_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)
self.assertTrue(directed_graph.directed)
assert not undirected_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(
num in random_vertices, undirected_graph.contains_vertex(num)
)
self.assertEqual(
num in random_vertices, directed_graph.contains_vertex(num)
)
assert (num in random_vertices) == undirected_graph.contains_vertex(num)
assert (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)

60
graphs/graph_adjacency_matrix.py
View File

@ -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]))
self.assertTrue(undirected_graph.contains_edge(edge[1], edge[0]))
self.assertTrue(directed_graph.contains_edge(edge[0], edge[1]))
assert undirected_graph.contains_edge(edge[0], edge[1])
assert undirected_graph.contains_edge(edge[1], edge[0])
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]))
self.assertFalse(undirected_graph.contains_edge(edge[1], edge[0]))
self.assertFalse(directed_graph.contains_edge(edge[0], edge[1]))
assert not undirected_graph.contains_edge(edge[0], edge[1])
assert not undirected_graph.contains_edge(edge[1], edge[0])
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))
self.assertTrue(directed_graph.contains_vertex(vertex))
assert undirected_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))
self.assertFalse(directed_graph.contains_vertex(vertex))
assert not undirected_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)
self.assertTrue(directed_graph.directed)
assert not undirected_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(
num in random_vertices, undirected_graph.contains_vertex(num)
)
self.assertEqual(
num in random_vertices, directed_graph.contains_vertex(num)
)
assert (num in random_vertices) == undirected_graph.contains_vertex(num)
assert (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)

2
hashes/sha256.py
View File

@ -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:

16
knapsack/tests/test_greedy_knapsack.py
View File

@ -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(
IndexError, "The length of profit and weight must be same."
)
pytest.raises(IndexError, match="The length of profit and weight must be same.")
if __name__ == "__main__":

8
knapsack/tests/test_knapsack.py
View File

@ -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__":

11
linear_algebra/src/lib.py
View File

@ -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 (
isinstance(x, Vector)
and isinstance(y, Vector)
and (isinstance(scalar, (int, float)))
)
assert isinstance(x, Vector)
assert isinstance(y, Vector)
assert isinstance(scalar, (int, float))
return x * scalar + y

7
linear_algebra/src/schur_complement.py
View File

@ -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)

69
linear_algebra/src/test_linear_algebra.py
View File

@ -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)
self.assertEqual(x.component(2), 3)
assert x.component(0) == 1
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)
self.assertAlmostEqual(y.euclidean_length(), 7.416, 3)
self.assertEqual(z.euclidean_length(), 0)
self.assertAlmostEqual(w.euclidean_length(), 7.616, 3)
assert x.euclidean_length() == pytest.approx(2.236, abs=1e-3)
assert y.euclidean_length() == pytest.approx(7.416, abs=1e-3)
assert z.euclidean_length() == 0
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)
self.assertEqual((x + y).component(1), 3)
self.assertEqual((x + y).component(2), 4)
assert (x + y).component(0) == 2
assert (x + y).component(1) == 3
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)
self.assertEqual((x - y).component(1), 1)
self.assertEqual((x - y).component(2), 2)
assert (x - y).component(0) == 0
assert (x - y).component(1) == 1
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)")
self.assertEqual((a * b), 0)
assert str(x * 3.0) == "(3.0,6.0,9.0)"
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))
self.assertEqual("|2,4,6|\n|8,10,12|\n|14,16,18|\n", str(a * 2))
assert str(a * x) == "(14,32,50)"
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(
"|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)),
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"
)

4
machine_learning/dimensionality_reduction.py
View File

@ -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

69
machine_learning/k_means_clust.py
View File

@ -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:
df - dataframe with predicted cluster column
Generate a clustering report given these two arguments:
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()
>>> data['numbers'] = [1, 2, 3]
>>> data['col1'] = [0.5, 2.5, 4.5]
>>> data['col2'] = [100, 200, 300]
>>> data['col3'] = [10, 20, 30]
>>> data['Cluster'] = [1, 1, 2]
>>> report_generator(data, ['col1', 'col2'], 0)
>>> predicted = pd.DataFrame()
>>> predicted['numbers'] = [1, 2, 3]
>>> predicted['col1'] = [0.5, 2.5, 4.5]
>>> predicted['col2'] = [100, 200, 300]
>>> predicted['col3'] = [10, 20, 30]
>>> predicted['Cluster'] = [1, 1, 2]
>>> 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)
df["dummy"] = 1
numeric_cols = df.select_dtypes(np.number).columns
predicted = predicted.fillna(value=fill_missing_report)
predicted["dummy"] = 1
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
clustersize.Type = (
"ClusterSize" # rename created cluster df to match report column names
)
].copy()
# rename created predicted cluster 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:].values.sum() # calculating the proportion of cluster
clustersize.iloc[:, 2:].to_numpy() / clustersize.iloc[:, 2:].to_numpy().sum()
)
clusterproportion[
"Type"
] = "% of Customers" # rename created cluster df to match report column names
# rename created predicted cluster to match report column names
clusterproportion["Type"] = "% of Customers"
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
- clustersize.iloc[:, 2:].values
report[report["Type"] == "count"].iloc[:, 2:].to_numpy()
- clustersize.iloc[:, 2:].to_numpy()
)
) # generating df with count of nan values
)
a["Features"] = 0
a["Type"] = "# of nan"
a.Features = report[
report["Type"] == "count"
].Features.tolist() # filling values in order to match report
# filling values in order to match report
a.Features = report[report["Type"] == "count"].Features.tolist()
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(
report[report.Type == "count"].index
) # drop count values except for cluster size
report = pd.concat(
[report, a, clustersize, clusterproportion], axis=0
) # concat report with cluster size and nan values
# drop count values except for cluster size
report = report.drop(report[report.Type == "count"].index)
# concat report with cluster size and nan values
report = pd.concat([report, a, clustersize, clusterproportion], axis=0)
report["Mark"] = report["Features"].isin(clustering_variables)
cols = report.columns.tolist()
cols = cols[0:2] + cols[-1:] + cols[2:-1]

4
maths/least_common_multiple.py
View File

@ -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])
self.assertEqual(fast_result, self.expected_results[i])
assert slow_result == self.expected_results[i]
assert fast_result == self.expected_results[i]
if __name__ == "__main__":

10
maths/modular_division.py
View File

@ -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)

48
maths/prime_check.py
View File

@ -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))
self.assertTrue(is_prime(3))
self.assertTrue(is_prime(5))
self.assertTrue(is_prime(7))
self.assertTrue(is_prime(11))
self.assertTrue(is_prime(13))
self.assertTrue(is_prime(17))
self.assertTrue(is_prime(19))
self.assertTrue(is_prime(23))
self.assertTrue(is_prime(29))
assert is_prime(2)
assert is_prime(3)
assert is_prime(5)
assert is_prime(7)
assert is_prime(11)
assert is_prime(13)
assert is_prime(17)
assert is_prime(19)
assert is_prime(23)
assert is_prime(29)
def test_not_primes(self):
with self.assertRaises(AssertionError):
with pytest.raises(AssertionError):
is_prime(-19)
self.assertFalse(
is_prime(0),
"Zero doesn't have any positive factors, primes must have exactly two.",
)
self.assertFalse(
is_prime(1),
"One only has 1 positive factor, primes must have exactly two.",
)
self.assertFalse(is_prime(2 * 2))
self.assertFalse(is_prime(2 * 3))
self.assertFalse(is_prime(3 * 3))
self.assertFalse(is_prime(3 * 5))
self.assertFalse(is_prime(3 * 5 * 7))
assert not is_prime(
0
), "Zero doesn't have any positive factors, primes must have exactly two."
assert not is_prime(
1
), "One only has 1 positive factor, primes must have exactly two."
assert not is_prime(2 * 2)
assert not is_prime(2 * 3)
assert not is_prime(3 * 3)
assert not is_prime(3 * 5)
assert not is_prime(3 * 5 * 7)
if __name__ == "__main__":

6
matrix/sherman_morrison.py
View File

@ -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

28
matrix/tests/test_matrix_operation.py
View File

@ -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()

14
project_euler/problem_054/test_poker_hand.py
View File

@ -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

8
pyproject.toml
View File

@ -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?

3
strings/knuth_morris_pratt.py
View File

@ -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"

3
strings/rabin_karp.py
View File

@ -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"