Merge branch 'main' into release

.github/workflows/test.yml

@@ -31,16 +31,6 @@ jobs:
         with:
           python-version: ${{ matrix.python_version }}
 
-      - name: Sleep for 60 seconds (Bash)
-        if: ${{ inputs.os != 'windows-latest' }}
-        run: sleep 60s
-        shell: bash
-
-      - name: Sleep for 60 seconds (Powershell)
-        if: ${{ inputs.os == 'windows-latest' }}
-        run: Start-Sleep -s 60
-        shell: powershell
-
       - name: Install Requirements
         run: |
           pip install pytest

setup.py

@@ -1,21 +1,21 @@
 import setuptools
 
-with open('docs/pypi.md', 'r', encoding='utf-8') as fh:
+with open("docs/pypi.md", "r", encoding="utf-8") as fh:
     long_description = fh.read()
 
 setuptools.setup(
-    name='autofaker',
-    version='0.1.0',
-    url='https://github.com/christianhelle/autofaker',
-    license='MIT License',
+    name="autofaker",
+    version="0.1.0",
+    url="https://github.com/christianhelle/autofaker",
+    license="MIT License",
     license_files=["LICENSE"],
-    author='Christian Helle',
-    author_email='christian.helle@outlook.com',
-    description='Python library designed to minimize the setup/arrange phase of your unit tests',
+    author="Christian Helle",
+    author_email="christian.helle@outlook.com",
+    description="Python library designed to minimize the setup/arrange phase of your unit tests",
     long_description=long_description,
-    long_description_content_type='text/markdown',
-    package_dir={'': 'src'},
-    packages=setuptools.find_packages(where='src'),
-    python_requires='>=3.7',
-    install_requires=['pandas', 'faker', 'typing_inspect'],
+    long_description_content_type="text/markdown",
+    package_dir={"": "src"},
+    packages=setuptools.find_packages(where="src"),
+    python_requires=">=3.7",
+    install_requires=["pandas", "faker", "typing_inspect"],
 )

src/autofaker/attributes.py

@@ -4,7 +4,8 @@ def __init__(self, instance):
 
     def get_members(self):
         return [
-            attr for attr in dir(self.instance)
+            attr
+            for attr in dir(self.instance)
             if not callable(getattr(self.instance, attr)) and not attr.startswith("__")
         ]
 

src/autofaker/dataframe.py

@@ -15,8 +15,11 @@ def __init__(self, t, rows: int = 3, use_fake_data: bool = False):
 
     def generate(self):
         members = [
-            attr for attr in dir(self.data[0])
-            if dataclasses.is_dataclass(getattr(self.data[0], attr)) or not callable(getattr(self.data[0], attr)) and not attr.startswith("__")
+            attr
+            for attr in dir(self.data[0])
+            if dataclasses.is_dataclass(getattr(self.data[0], attr))
+            or not callable(getattr(self.data[0], attr))
+            and not attr.startswith("__")
         ]
         rows = []
         for d in self.data:

src/autofaker/dates.py

@@ -5,27 +5,28 @@
 
 
 def is_date_type(type_name) -> bool:
-    return type_name in [
-        'datetime',
-        'date'
-    ]
+    return type_name in ["datetime", "date"]
 
 
 class DatetimeGenerator(TypeDataGeneratorBase):
     def generate(self):
         year = datetime.date.today().year
-        return datetime.datetime(random.randint(year - 10, year + 10),
-                                 random.randint(1, 12),
-                                 random.randint(1, 28),
-                                 random.randint(0, 23),
-                                 random.randint(0, 59),
-                                 random.randint(0, 59),
-                                 random.randint(0, 999))
+        return datetime.datetime(
+            random.randint(year - 10, year + 10),
+            random.randint(1, 12),
+            random.randint(1, 28),
+            random.randint(0, 23),
+            random.randint(0, 59),
+            random.randint(0, 59),
+            random.randint(0, 999),
+        )
 
 
 class DateGenerator(TypeDataGeneratorBase):
     def generate(self):
         year = datetime.date.today().year
-        return datetime.datetime(random.randint(year - 10, year + 10),
-                                 random.randint(1, 12),
-                                 random.randint(1, 28))
+        return datetime.datetime(
+            random.randint(year - 10, year + 10),
+            random.randint(1, 12),
+            random.randint(1, 28),
+        )

src/autofaker/decorators.py

@@ -33,9 +33,21 @@ def test_create_str_argument_using_decorator(self, text, number, decimal, boolea
     def decorator(function):
         def wrapper(*args):
             if __get_class_that_defined_method(function) is None:
-                return function(*tuple(__create_function_args(function, *tuple(types), use_fake_data=use_fake_data)))
-            return function(__get_test_class(*args),
-                            *tuple(__create_function_args(function, *tuple(types), use_fake_data=use_fake_data)))
+                return function(
+                    *tuple(
+                        __create_function_args(
+                            function, *tuple(types), use_fake_data=use_fake_data
+                        )
+                    )
+                )
+            return function(
+                __get_test_class(*args),
+                *tuple(
+                    __create_function_args(
+                        function, *tuple(types), use_fake_data=use_fake_data
+                    )
+                )
+            )
 
         return wrapper
 
@@ -65,9 +77,19 @@ def test_create_fake_arguments(self, text: str, number: int, decimal: float, boo
     def decorator(function):
         def wrapper(*args):
             if __get_class_that_defined_method(function) is None:
-                return function(*tuple(__create_function_args(function, *tuple(types), use_fake_data=True)))
-            return function(__get_test_class(*args),
-                            *tuple(__create_function_args(function, *tuple(types), use_fake_data=True)))
+                return function(
+                    *tuple(
+                        __create_function_args(
+                            function, *tuple(types), use_fake_data=True
+                        )
+                    )
+                )
+            return function(
+                __get_test_class(*args),
+                *tuple(
+                    __create_function_args(function, *tuple(types), use_fake_data=True)
+                )
+            )
 
         return wrapper
 
@@ -85,7 +107,9 @@ def autopandas(t: object, rows: int = 3, use_fake_data: bool = False):
 
     def decorator(function):
         def wrapper(*args):
-            pdf = PandasDataFrameGenerator(t, rows, use_fake_data=use_fake_data).generate()
+            pdf = PandasDataFrameGenerator(
+                t, rows, use_fake_data=use_fake_data
+            ).generate()
             if __get_class_that_defined_method(function) is None:
                 return function(pdf)
             return function(__get_test_class(*args), pdf)
@@ -108,18 +132,22 @@ def fakepandas(t, rows: int = 3):
 def __get_test_class(*args):
     test_class = args[0]
     if issubclass(test_class.__class__, unittest.TestCase) is False:
-        raise NotImplementedError("This way of creating anonymous objects are only supported from unit tests")
+        raise NotImplementedError(
+            "This way of creating anonymous objects are only supported from unit tests"
+        )
     return test_class
 
 
 def __get_class_that_defined_method(meth):
     if inspect.isfunction(meth):
-        cls = getattr(inspect.getmodule(meth),
-                      meth.__qualname__.split('.<locals>', 1)[0].rsplit('.', 1)[0],
-                      None)
+        cls = getattr(
+            inspect.getmodule(meth),
+            meth.__qualname__.split(".<locals>", 1)[0].rsplit(".", 1)[0],
+            None,
+        )
         if isinstance(cls, type):
             return cls
-    return getattr(meth, '__objclass__', None)  # handle special descriptor objects
+    return getattr(meth, "__objclass__", None)  # handle special descriptor objects
 
 
 def __create_function_args(function, *types, use_fake_data: bool = False) -> List:
@@ -133,5 +161,7 @@ def __create_function_args(function, *types, use_fake_data: bool = False) -> Lis
     if __get_class_that_defined_method(function) is None:
         pos = 0
     if len(argtpes.args) - pos != len(values):
-        raise ValueError("Missing argument annotations. Please declare the type of every argument")
+        raise ValueError(
+            "Missing argument annotations. Please declare the type of every argument"
+        )
     return values

src/autofaker/enums.py

@@ -1,10 +1,11 @@
 import random
+from enum import Enum
 
 from autofaker.base import TypeDataGeneratorBase
 
 
 def is_enum(t) -> bool:
-    return t.__base__.__name__ == 'Enum'
+    return isinstance(t, Enum.__class__)
 
 
 class EnumGenerator(TypeDataGeneratorBase):

src/autofaker/factory.py

@@ -1,52 +1,56 @@
 from autofaker.builtins import (
-    IntegerGenerator,
-    FloatGenerator,
     BooleanGenerator,
+    ByteArrayGenerator,
+    BytesGenerator,
     ComplexGenerator,
+    FloatGenerator,
+    IntegerGenerator,
+    MemoryViewGenerator,
     RangeGenerator,
-    BytesGenerator,
-    ByteArrayGenerator,
-    MemoryViewGenerator
 )
-from autofaker.fakes import FakeStringGenerator, StringGenerator, FakeIntegerGenerator
+from autofaker.fakes import FakeIntegerGenerator, FakeStringGenerator, StringGenerator
 
 
 class BuiltinTypeDataGeneratorFactory:
     @staticmethod
     def is_supported(type_name) -> bool:
         return type_name in [
-            'int',
-            'str',
-            'float',
-            'complex',
-            'bool',
-            'range',
-            'bytes',
-            'bytearray',
-            'memoryview'
+            "int",
+            "str",
+            "float",
+            "complex",
+            "bool",
+            "range",
+            "bytes",
+            "bytearray",
+            "memoryview",
         ]
 
     @staticmethod
     def create(type_name, field_name: str = None, use_fake_data: bool = False):
-        if type_name == 'int':
-            return FakeIntegerGenerator() \
-                if field_name is not None and use_fake_data is True \
+        if type_name == "int":
+            return (
+                FakeIntegerGenerator()
+                if field_name is not None and use_fake_data is True
                 else IntegerGenerator()
-        if type_name == 'str':
-            return FakeStringGenerator(field_name) \
-                if field_name is not None and use_fake_data is True \
+            )
+        if type_name == "str":
+            return (
+                FakeStringGenerator(field_name)
+                if field_name is not None and use_fake_data is True
                 else StringGenerator()
-        if type_name == 'float':
+            )
+        if type_name == "float":
             return FloatGenerator()
-        if type_name == 'complex':
+        if type_name == "complex":
             return ComplexGenerator()
-        if type_name == 'bool':
+        if type_name == "bool":
             return BooleanGenerator()
-        if type_name == 'range':
+        if type_name == "range":
             return RangeGenerator()
-        if type_name == 'bytes':
+        if type_name == "bytes":
             return BytesGenerator()
-        if type_name == 'bytearray':
+        if type_name == "bytearray":
             return ByteArrayGenerator()
-        if type_name == 'memoryview':
+        if type_name == "memoryview":
             return MemoryViewGenerator()