Merge pull request #49 from christianhelle/resolve-sonarcloud-warnings

resolve sonarcloud warnings

.github/workflows/build-python-313-linux.yml

@@ -19,4 +19,4 @@ jobs:
     uses: ./.github/workflows/build.yml
     with:
       python_version: 3.13
-      os: ubuntu-latest3
+      os: ubuntu-latest

src/autofaker/generator.py

@@ -58,7 +58,7 @@ def _get_type_name(t) -> str:
             # because it will always be a string. This is because, annotations
             # transforms any type into a string object. Therefore, if the type
             # is a string, assess if it is the name of a known primitive type.
-            elif type(t) == str and t in PRIMITIVE_TYPES:
+            elif t.isinstance(str) and t in PRIMITIVE_TYPES:
                 return t
             return type(t).__name__
 

tests/test_create_anonymous_builtins.py

@@ -1,80 +1,80 @@
 import unittest
 from abc import abstractmethod
+from typing import Type
 
 from autofaker import Autodata
 
 
 class CreateTestCase(unittest.TestCase):
     @abstractmethod
-    def getType(self):
+    def getType(self) -> Type:
         pass
 
     def test_create_returns_not_none(self):
-        if self.getType() is None:
-            return
-        self.assertIsNotNone(Autodata.create(self.getType()))
+        if self.getType() is not None:
+            self.assertIsNotNone(Autodata.create(self.getType()))
 
     def test_create_returns_not_type(self):
-        if self.getType() is None:
-            return
-        self.assertNotIsInstance(Autodata.create(self.getType()), type)
+        if self.getType() is not None:
+            self.assertNotIsInstance(Autodata.create(self.getType()), type)
 
     def test_create_returns_not_default(self):
-        if self.getType() is None or self.getType() is bool or range:
-            return
-        self.assertNotEqual(Autodata.create(self.getType()), self.getType()())
+        if (self.getType() is not None
+            and not bool
+            and not range):
+            self.assertNotEqual(Autodata.create(self.getType()), self.getType()())
 
 
 class AnonymousIntegerTestCase(CreateTestCase):
-    def getType(self):
+    def getType(self) -> Type[int]:
         return int
 
 
 class AnonymousStringTestCase(CreateTestCase):
-    def getType(self):
+    def getType(self) -> Type[str]:
         return str
 
 
 class AnonymousFloatTestCase(CreateTestCase):
-    def getType(self):
+    def getType(self) -> Type[float]:
         return float
 
 
 class AnonymousBooleanTestCase(CreateTestCase):
-    def getType(self):
+    def getType(self) -> Type[bool]:
         return bool
 
 
 class AnonymousComplexTestCase(CreateTestCase):
-    def getType(self):
+    def getType(self) -> Type[complex]:
         return complex
 
 
 class AnonymousRangeTestCase(CreateTestCase):
-    def getType(self):
+    def getType(self) -> Type[range]:
         return range
 
 
 class AnonymousBytesTestCase(CreateTestCase):
-    def getType(self):
+    def getType(self) -> Type[bytes]:
         return bytes
 
 
 class AnonymousByteArrayTestCase(CreateTestCase):
-    def getType(self):
+    def getType(self) -> Type[bytearray]:
         return bytearray
 
 
 class AnonymousMemoryViewTestCase(CreateTestCase):
-    def getType(self):
+    def getType(self) -> Type[memoryview]:
         return memoryview
 
 
 class AnonymousSetTestCase(CreateTestCase):
-    def getType(self):
+    def getType(self) -> Type[set]:
         return set
 
 
 class AnonymousFrozensetTestCase(CreateTestCase):
-    def getType(self):
+    def getType(self) -> Type[frozenset]:
         return frozenset

tests/test_create_anonymous_dataframe_pandas.py

@@ -40,16 +40,16 @@ def test_can_create_anonymous_pandas_dataframes_from_class_with_constructor_argu
         self,
     ):
         df = Autodata.create_pandas_dataframe(SimpleClassB)
-        self.assertTrue("id" in df.columns)
-        self.assertTrue("name" in df.columns)
-        self.assertTrue("text" in df.columns)
+        self.assertIn("id", df.columns)
+        self.assertIn("name", df.columns)
+        self.assertIn("text", df.columns)
 
     def test_can_create_anonymous_pandas_dataframes_from_class_with_constructor_class_arguments(
         self,
     ):
         df = Autodata.create_pandas_dataframe(SimpleClassC)
-        self.assertTrue("a" in df.columns)
-        self.assertTrue("b" in df.columns)
+        self.assertIn("a", df.columns)
+        self.assertIn("b", df.columns)
 
 
 class CreateFakePandasDataFrameTests(unittest.TestCase):
@@ -69,16 +69,16 @@ def test_can_create_fake_pandas_dataframes_from_class_with_constructor_arguments
         self,
     ):
         df = Autodata.create_pandas_dataframe(SimpleClassB, use_fake_data=True)
-        self.assertTrue("id" in df.columns)
-        self.assertTrue("name" in df.columns)
-        self.assertTrue("text" in df.columns)
+        self.assertIn("id", df.columns)
+        self.assertIn("name", df.columns)
+        self.assertIn("text", df.columns)
 
     def test_can_create_fake_pandas_dataframes_from_class_with_constructor_class_arguments(
         self,
     ):
         df = Autodata.create_pandas_dataframe(SimpleClassC, use_fake_data=True)
-        self.assertTrue("a" in df.columns)
-        self.assertTrue("b" in df.columns)
+        self.assertIn("a", df.columns)
+        self.assertIn("b", df.columns)
 
 
 @dataclass
@@ -118,16 +118,16 @@ def test_can_create_anonymous_pandas_dataframes_from_class_with_constructor_clas
         self,
     ):
         df = Autodata.create_pandas_dataframe(HybridClassA)
-        self.assertTrue("b" in df.columns)
-        self.assertTrue("a" in df.columns)
+        self.assertIn("b", df.columns)
+        self.assertIn("a", df.columns)
 
     def test_can_create_anonymous_pandas_dataframes_from_class_with_constructor_hybrid_class_arguments(
         self,
     ):
         df = Autodata.create_pandas_dataframe(HybridClassB)
-        self.assertTrue("c" in df.columns)
-        self.assertTrue("b" in df.columns)
-        self.assertTrue("a" in df.columns)
+        self.assertIn("c", df.columns)
+        self.assertIn("b", df.columns)
+        self.assertIn("a", df.columns)
 
 
 class CreateFakePandasDataFrameFromDataClassTests(unittest.TestCase):
@@ -147,13 +147,13 @@ def test_can_create_fake_pandas_dataframes_from_class_with_constructor_class_arg
         self,
     ):
         df = Autodata.create_pandas_dataframe(HybridClassA, use_fake_data=True)
-        self.assertTrue("b" in df.columns)
-        self.assertTrue("a" in df.columns)
+        self.assertIn("b", df.columns)
+        self.assertIn("a", df.columns)
 
     def test_can_create_anonymous_pandas_dataframes_from_class_with_constructor_hybrid_class_arguments(
         self,
     ):
         df = Autodata.create_pandas_dataframe(HybridClassB, use_fake_data=True)
-        self.assertTrue("c" in df.columns)
-        self.assertTrue("b" in df.columns)
-        self.assertTrue("a" in df.columns)
+        self.assertIn("c", df.columns)
+        self.assertIn("b", df.columns)
+        self.assertIn("a", df.columns)