busfare

challenges/week_1/checker.py

@@ -1,4 +1,4 @@
-import bus_fare_challenge
+import bus_fare_challenge as solution
 import datetime
 import unittest
 
@@ -12,7 +12,7 @@ def setUp(self) -> None:
             "Tue": 100,
             "Wed": 100,
             "Thu": 100,
-            "Thu": 100,
+            "Fri": 100,
             "Sat": 60,
             "Sun": 80,
         }
@@ -22,15 +22,15 @@ def test_date(self) -> None:
         Tests whether the date returned by the program is correct.
         """
         actual = self.date
-        given = bus_fare_challenge.date
+        given = solution.date
         self.assertEqual(actual, given, f"Today's date is Wrong by {given - actual}!")
 
     def test_day(self) -> None:
         """
         Tests whether the day returned by the program is correct.
         """
         actual = self.day
-        given = bus_fare_challenge.day
+        given = solution.day
         self.assertEqual(
             actual, given, f"Today is wrong, expexted {actual} but got {given}!"
         )
@@ -40,7 +40,7 @@ def test_fare(self) -> None:
         Tests whether the fare returned by the program is correct.
         """
         actual = self.charts[self.day]
-        given = bus_fare_challenge.fare
+        given = solution.fare
         self.assertEqual(
             actual, given, f"Fare is wrong, expected {actual} but got {given}!"
         )

challenges/week_5/checker.py

@@ -0,0 +1,62 @@
+import unittest
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+from sklearn.model_selection import train_test_split
+from sklearn.linear_model import LinearRegression
+from sklearn import metrics
+import linear_regression_solution as solution
+
+
+class TestLinearRegressionChallenge(unittest.TestCase):
+    def setUp(self) -> None:
+        self.df = pd.read_csv(
+            "/home/tim/Dev/DS/Learning/python-bootcamp/challenges/week_5/data.csv",
+            index_col=0,
+        )
+        self.X = np.array(self.df.dropna()["x"]).reshape(-1, 1)
+        self.y = np.array(self.df.dropna()["y"]).reshape(-1, 1)
+        self.performance = solution.performance
+
+    def test_prep_data(self) -> None:
+        actual = self.df.dropna().size
+        given = solution.clean_data.size
+        self.assertEqual(
+            actual,
+            given,
+            f"Expected {actual} but got {given}. Please clean your data off null values!",
+        )
+
+    def test_feature_shape(self) -> None:
+        actual = (970, 1)
+        given = solution.X.shape
+        self.assertEqual(
+            actual,
+            given,
+            f"Expected {actual} but got {given}. Please reshape your features!",
+        )
+        given = solution.y.shape
+        self.assertEqual(
+            actual,
+            given,
+            f"Expected {actual} but got {given}. Please reshape your features!",
+        )
+
+    def test_model_evaluation(self) -> None:
+        actual_type = tuple
+        given_type = type(solution.performance)
+        self.assertEqual(
+            actual_type,
+            given_type,
+            f"Expected {actual_type} but got {given_type}. Model evaluation fuction should return a tuple!",
+        )
+
+
+if __name__ == "__main__":
+
+    print("=========================================================================")
+    print("=========================================================================")
+    print("===== Start: Checking ********************************************* =====")
+    unittest.main(exit=False)
+    print("===== End: Checking ********************************************* =======")
+    print("=========================================================================")