test: test case for pandas filter roews (tutorial for fixture)

src/tutorial/testing/practice/bmi.py

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+# Task: Schreibt für die folgende Aufgabe einige Unit-Test. Nutzt dazu für den Happy-Path einen parametrisierten Test für
+# einige valide Inputs und Outputs
+
+
+def calculate_bmi(weight_kg: float, height_m: float) -> float:
+    """
+    Berechnet den Body Mass Index (BMI).
+    BMI = Gewicht (kg) / Grösse (m)^2
+    """
+    if weight_kg <= 0 or height_m <= 0:
+        raise ValueError("Gewicht und Grösse müssen positiv sein.")
+    return weight_kg / (height_m**2)
+
+
+if __name__ == "__main__":
+    print(calculate_bmi(weight_kg=72, height_m=1.84))

src/tutorial/testing/practice/catching_exeptions.py

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+# TASK: Schreibe sinnvolle Tests für die folgende Funktion
+# Schreibe Tests für die korrekte Struktur des Outputs der Funktion
+# Teste, ob bei Übergabe von 'falschem' Parameter data eine Exception geworfen wird
+
+# https://docs.python.org/3/library/exceptions.html
+# Passing arguments of the wrong type (e.g. passing a list when an int is expected) should result in a TypeError,
+# but passing arguments with the wrong value (e.g. a number outside expected boundaries) should result in a ValueError.
+
+
+def double_integers(data: list[int]) -> list[int]:
+    """Doubles a list of given integers
+
+    :param data: list of integers
+    :return: list of doubled integers
+    """
+
+    if not isinstance(data, list):
+        raise TypeError("data must be a list")
+    if not all([isinstance(i, int) for i in data]):
+        raise TypeError("data may contain only integers")
+
+    return [i * 2 for i in data]
+
+
+if __name__ == "__main__":
+
+    data = [1, 2, 3]
+    result = double_integers(data)
+    print(result)

src/tutorial/testing/practice/kata_list_filtering.py

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+# https://www.codewars.com/kata/53dbd5315a3c69eed20002dd
+# level: 7 kyu
+
+# In this kata you will create a function that takes a list of non-negative integers and strings and returns a new
+# list with the strings filtered out.
+#
+# Example
+# filter_list([1,2,'a','b']) == [1,2]
+# filter_list([1,'a','b',0,15]) == [1,0,15]
+# filter_list([1,2,'aasf','1','123',123]) == [1,2,123]
+
+
+def filter_list(a_list):
+    return [i for i in a_list if isinstance(i, int)]

src/tutorial/testing/practice/pandas_filter_rows.py

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+# https://www.codewars.com/kata/5ea2baed9345eb001e8ce394
+# 7 kyu
+
+# Input parameters
+
+# dataframe: pandas.DataFrame object
+# col: target column
+# func: filter function
+
+# Task
+# Your function must return a new pandas.DataFrame object with the same columns as the original input. However,
+# include only the rows whose cell values in the designated column evaluate to False by func.
+#
+# Input DataFrame will never be empty. The target column will always be one of the dataframe columns. Filter function
+# will be a valid one. Index value must remain the same.
+
+# REMARK: leichte Modifikation -> es wird ausgegeben, was in der Funktion definiert wurde (True) und nicht umgekehrt.
+
+import pandas as pd
+
+
+def filter_dataframe(df, col, func):
+    if col not in df.columns:
+        raise ValueError(f"Column '{col}' is not present in the DataFrame.")
+    mask = df[col].apply(func)
+    return df[mask]
+
+
+if __name__ == "__main__":
+
+    df = pd.DataFrame(
+        {
+            "A": [1, 2, 3, 4, 5],
+        }
+    )
+
+    print(filter_dataframe(df, "A", lambda x: x >= 4))

src/tutorial/testing/practice/vowel_count.py

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+# https://www.codewars.com/kata/54ff3102c1bad923760001f3
+# level: 7 kyu
+
+# Return the number (count) of vowels in the given string.
+# We will consider a, e, i, o, u as vowels for this Kata (but not y).
+# The input string will only consist of lower case letters and/or spaces.
+
+
+def get_count(inputStr):
+    num_vowels = 0
+    for char in inputStr:
+        if char in "aeiouAEIOU":
+            num_vowels = num_vowels + 1
+    return num_vowels
+
+
+if __name__ == "__main__":
+    print(get_count("Hello World"))

tests/test_tutorial/test_catching_exeptions.py

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+from src.tutorial.testing.practice.catching_exeptions import double_integers
+import pytest
+
+
+@pytest.mark.parametrize(
+    ("input", "expected"),
+    [
+        ([1, 2, 3], [2, 4, 6]),
+        ([5], [10]),
+        ([100, 900, -2], [200, 1800, -4]),
+    ],
+)
+def test_double_integers(input, expected):
+    assert double_integers(input) == expected
+
+
+def test_argument_is_list():
+    with pytest.raises(TypeError, match="data must be a list"):
+        double_integers(4)
+
+
+def test_list_with_integers_only():
+    with pytest.raises(TypeError, match="data may contain only integers"):
+        double_integers([4, 3, 2, "str"])

tests/test_tutorial/test_kata_list_filtering.py

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+from src.tutorial.testing.practice.kata_list_filtering import filter_list
+import pytest
+
+
+@pytest.mark.parametrize(
+    ("input", "expected"),
+    [
+        ([3, 5, "m", "0", 7], [3, 5, 7]),
+        (["3", "5", "m", "0", "f"], []),
+        ([1, 2, 3], [1, 2, 3]),
+    ],
+)
+def test_filter_list(input, expected):
+    assert filter_list(input) == expected
+
+
+def test_parameter_is_list():
+    input = [7, 9, 0]
+    result = isinstance(input, list)
+    assert result
+
+    input = 9
+    result = isinstance(input, list)
+    assert not result

tests/test_tutorial/test_pandas_filter_rows.py

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+from src.tutorial.testing.practice.pandas_filter_rows import filter_dataframe
+import pytest
+import pandas as pd
+
+
+@pytest.fixture
+def standard_df():
+    df = pd.DataFrame(
+        {
+            "A": [1, 2, 3, 4, 5],
+            "B": [0, 2, 2, 4, 5],
+            "C": [1, 2, 3, 8, 5],
+        }
+    )
+    return df
+
+
+def test_col_not_in_dataframe(standard_df):
+    with pytest.raises(ValueError):
+        filter_dataframe(standard_df, "Z", lambda x: x >= 4)