init()

s1_a4.py

@@ -5,6 +5,6 @@ if __name__ == "__main__":
     approximate_value = 0
     divider = 1
     while series_value != round(approximate_value, 6):
-        approximate_value += 1/divider**2
+        approximate_value = 1/divider**2
         divider += 1
     print("The sum equals", series_value, "after adding", divider-1, "reciprocal square numbers.")

s1_a51.py

@@ -3,10 +3,10 @@ class SparseMatrix:
         self.__matrix = dict()
 
     def save(self, matrix) -> None:
-        for row in range(len(matrix)):
+        for row, values in enumerate(matrix):
-            for col in range(len(matrix[row])):
+            for col, value in enumerate(values):
-                if matrix[row][col] != 0:
+                if value != 0:
-                    self.__matrix[(row, col)] = matrix[row][col]
+                    self.__matrix[(row, col)] = value
 
     def get(self, row, col) -> int or None:
         if self.__matrix[(row, col)]:

s1_a53_6.py

@@ -5,8 +5,7 @@ if __name__ == "__main__":
 
     # 5.4
     def remove_duplicates(word: str):
-        result = "".join(sorted(set(word), key=word.index))
+        return "".join(sorted(set(word), key=word.index))
-        print(word, len(word), "\n", result, len(result))
     remove_duplicates("Donaudampfschiffahrtsgesellschaftsstewardess")
 
     # 5.5
@@ -15,5 +14,4 @@ if __name__ == "__main__":
 
     # 5.6
     def get_animal_sound(animal: str) -> str:
-        animal_dictionary = {"Lion": "Growl", "Dog": "Bark", "Cat": "Meow"}
+        return {"Lion": "Growl", "Dog": "Bark", "Cat": "Meow"}.get(animal, "Not found.")
-        return animal_dictionary.get(animal, "Not found.")