create tests for data_model's EducationEntry class

rendercv/data_model.py

@@ -520,7 +520,7 @@ class Event(BaseModel):
                 end_date = Date.today()
             else:
                 end_date = model.end_date
-                
+
             if model.start_date > end_date:
                 raise ValueError(
                     '"start_date" is after "end_date". Please check the dates!'
@@ -537,17 +537,13 @@ class Event(BaseModel):
             date_and_location_strings.append(self.location)
 
         if self.date is not None:
-            # Then it means start_date and end_date are not provided.
-            try:
-                # If this runs, it means the date is an ISO format string, and it can be
-                # parsed
-                date = format_date(Date.fromisoformat(self.date))
-                date_and_location_strings.append(date)
-            except:
+            if isinstance(self.date, str):
                 date_and_location_strings.append(self.date)
-        else:
-            # Then it means start_date and end_date are provided.
-
+            elif isinstance(self.date, Date):
+                date_and_location_strings.append(format_date(self.date))
+            else:
+                raise RuntimeError("Date is neither a string nor a Date object!")
+        elif self.start_date is not None and self.end_date is not None:
             start_date = format_date(self.start_date)
 
             if self.end_date == "present":
@@ -694,7 +690,7 @@ class EducationEntry(Event):
         description="The type of the degree.",
         examples=["BS", "BA", "PhD", "MS"],
     )
-    gpa: Optional[str] = Field(
+    gpa: Optional[str | float] = Field(
         default=None,
         title="GPA",
         description="The GPA of the degree.",

tests/test_rendercv.py

@@ -87,6 +87,10 @@ class TestRendercv(unittest.TestCase):
             with self.subTest(msg="valid dates"):
                 data_model.Event(**input)
 
+        # Inputs without dates:
+        with self.subTest(msg="no dates"):
+            data_model.Event(**{})
+
         # Inputs with invalid dates:
         input = {
             "start_date": Date(year=2020, month=1, day=1),
@@ -162,7 +166,7 @@ class TestRendercv(unittest.TestCase):
         ]
         event = data_model.Event(**input)
         result = event.date_and_location_strings_with_timespan
-        with self.subTest(expected=expected):
+        with self.subTest(msg="start_date, end_date, and location are provided"):
             self.assertEqual(result, expected)
 
         input = {
@@ -175,7 +179,42 @@ class TestRendercv(unittest.TestCase):
         ]
         event = data_model.Event(**input)
         result = event.date_and_location_strings_with_timespan
-        with self.subTest(expected=expected):
+        with self.subTest(msg="date and location are provided"):
+            self.assertEqual(result, expected)
+
+        input = {
+            "date": Date(year=2020, month=1, day=1),
+        }
+        expected = [
+            "Jan. 2020",
+        ]
+        event = data_model.Event(**input)
+        result = event.date_and_location_strings_with_timespan
+        with self.subTest(msg="date is provided"):
+            self.assertEqual(result, expected)
+
+        input = {
+            "start_date": Date(year=2020, month=1, day=1),
+            "end_date": Date(year=2021, month=1, day=16),
+        }
+        expected = [
+            "Jan. 2020 to Jan. 2021",
+            "1 year 1 month",
+        ]
+        event = data_model.Event(**input)
+        result = event.date_and_location_strings_with_timespan
+        with self.subTest(msg="start_date and end_date are provided"):
+            self.assertEqual(result, expected)
+
+        input = {
+            "location": "My Location",
+        }
+        expected = [
+            "My Location",
+        ]
+        event = data_model.Event(**input)
+        result = event.date_and_location_strings_with_timespan
+        with self.subTest(msg="location is provided"):
             self.assertEqual(result, expected)
 
     def test_data_event_date_and_location_strings_without_timespan(self):
@@ -219,7 +258,7 @@ class TestRendercv(unittest.TestCase):
         ]
         event = data_model.Event(**input)
         result = event.highlight_strings
-        with self.subTest(expected=expected):
+        with self.subTest(msg="highlights are provided"):
             self.assertEqual(result, expected)
 
         input = {}
@@ -299,6 +338,107 @@ class TestRendercv(unittest.TestCase):
         with self.subTest(msg="date is provided"):
             self.assertEqual(result, expected)
 
+    def test_data_education_highlight_strings(self):
+        input = {
+            "institution": "My Institution",
+            "area": "My Area",
+            "gpa": 3.5,
+            "highlights": [
+                "My Highlight 1",
+                "My Highlight 2",
+            ],
+        }
+        expected = [
+            "GPA: 3.5",
+            "My Highlight 1",
+            "My Highlight 2",
+        ]
+        education = data_model.EducationEntry(**input)
+        result = education.highlight_strings
+        with self.subTest(msg="gpa and highlights are provided"):
+            self.assertEqual(result, expected)
+
+        input = {
+            "institution": "My Institution",
+            "area": "My Area",
+            "gpa": None,
+            "highlights": [
+                "My Highlight 1",
+                "My Highlight 2",
+            ],
+        }
+        expected = [
+            "My Highlight 1",
+            "My Highlight 2",
+        ]
+        education = data_model.EducationEntry(**input)
+        result = education.highlight_strings
+        with self.subTest(msg="gpa is not provided, but highlights are"):
+            self.assertEqual(result, expected)
+
+        input = {
+            "institution": "My Institution",
+            "area": "My Area",
+            "gpa": 3.5,
+            "highlights": [],
+        }
+        expected = [
+            "GPA: 3.5",
+        ]
+        education = data_model.EducationEntry(**input)
+        result = education.highlight_strings
+        with self.subTest(msg="gpa is provided, but highlights are not"):
+            self.assertEqual(result, expected)
+
+        input = {
+            "institution": "My Institution",
+            "area": "My Area",
+            "gpa": None,
+            "highlights": [],
+        }
+        expected = []
+        education = data_model.EducationEntry(**input)
+        result = education.highlight_strings
+        with self.subTest(msg="neither gpa nor highlights are provided"):
+            self.assertEqual(result, expected)
+
+        input = {
+            "institution": "My Institution",
+            "area": "My Area",
+            "gpa": 3.5,
+            "transcript_url": "https://www.example.com/",
+            "highlights": None,
+        }
+        expected = [
+            "GPA: 3.5 ([Transcript](https://www.example.com/))",
+        ]
+        education = data_model.EducationEntry(**input)
+        result = education.highlight_strings
+        with self.subTest(
+            msg="gpa and transcript_url are provided, but highlights are not"
+        ):
+            self.assertEqual(result, expected)
+
+        input = {
+            "institution": "My Institution",
+            "area": "My Area",
+            "gpa": "3.5",
+            "transcript_url": "https://www.example.com/",
+            "highlights": [
+                "My Highlight 1",
+                "My Highlight 2",
+            ],
+        }
+        expected = [
+            "GPA: 3.5 ([Transcript](https://www.example.com/))",
+            "My Highlight 1",
+            "My Highlight 2",
+        ]
+        education = data_model.EducationEntry(**input)
+        result = education.highlight_strings
+        with self.subTest(msg="gpa, transcript_url, and highlights are provided"):
+            self.assertEqual(result, expected)
+
 
 if __name__ == "__main__":
     unittest.main()