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Collection of Utilities

Project description

wakatime

WorkToy v0.40.28

pip install worktoy

Table of Contents

  1. WorkToyClass
    1. maybe
    2. maybeType
    3. maybeTypes
    4. searchKey
    5. searchKeys
    6. maybeKey
    7. maybeKeys
  2. WorkToyClass.Guards
    1. noneGuard
    2. someGuard
    3. overRideGuard
    4. functionGuard
    5. intGuard
    6. strGuard
  3. Descriptors
    1. Attribute
  4. Metaclass
    1. type
    2. NameSpace
  5. Wait A Minute!
    1. MetaXcept
    2. MetaTypeSupportError
    3. FieldDecoderException
    4. FieldEncoderException
    5. MissingArgumentException
    6. RecursiveCreateGetError
    7. TypeSupportError
    8. UnavailableNameException
    9. UnexpectedEventException
    10. UnsupportedSubclassException
  6. Core

WorkToyClass

Parent class providing general utility functions on the class itself.

from worktoy.worktoyclass import WorkToyClass


class MyClass(WorkToyClass):
  """Example class"""

  def __init__(self, *args, **kwargs) -> None:
    WorkToyClass.__init__(self, *args, **kwargs)

By inheriting from the WorkToyClass, instances now have access to a collection of utility functions:

WorkToyClass.maybe

from typing import Any

from worktoy.worktoyclass import WorkToyClass


class MyClass(WorkToyClass):
  """Example class"""

  def instanceMethod(self, *args) -> Any:
    """Instance method using ``maybe`` use a default argument value."""
    return self.maybe(*args)


myInstance = MyClass()
myInstance.instanceMethod(None, [], )  # >>> []  

WorkToyClass.maybeType

from worktoy.worktoyclass import WorkToyClass


class MyClass(WorkToyClass):
  """Example class"""

  def instanceMethod(self, *args, **kwargs) -> int:
    """Instance method using ``maybeType`` to extract an integer from the 
    positional arguments. """
    return self.maybeType(int, *args)


myInstance = MyClass()
myInstance.instanceMethod('one', 2, '3', 4, 5)  # >>> 2  

WorkToyClass.maybeTypes

from worktoy.worktoyclass import WorkToyClass


class MyClass(WorkToyClass):
  """Example class"""

  def instanceMethod(self, *args, **kwargs) -> int:
    """Instance method using 'maybeTypes' to extract every integer from the 
    positional arguments."""
    out = self.maybeTypes(int, *args)
    if isinstance(out, int):
      return out


myInstance = MyClass()
myInstance.instanceMethod('one', 2, '3', 4, 5)  # >>> [2, 4, 5] 

WorkToyClass.searchKey

from worktoy.worktoyclass import WorkToyClass


class MyClass(WorkToyClass):
  """Example class"""

  def instanceMethod(self, *keys, **kwargs) -> int:
    """Instance method using ``searchKey`` to search for keyword argument 
    value."""
    return self.searchKey(*keys, **kwargs)


myInstance = MyClass()
myInstance.instanceMethod('count', 'Count', 'amount', count=7)  # >>> 7 

WorkToyClass.searchKeys

from worktoy.worktoyclass import WorkToyClass


class MyClass(WorkToyClass):
  """Example class"""

  def instanceMethod(self, *keys, **kwargs) -> int:
    """Instance method using ``searchKeys`` to search for every keyword 
    argument."""
    return self.searchKeys(*keys, **kwargs)


myInstance = MyClass()
myInstance.instanceMethod('a', 'd', 'e', a=1, b=2, c=3, d=4)  # >>> [1, 4] 

WorkToyClass.maybeKey

from worktoy.worktoyclass import WorkToyClass


class MyClass(WorkToyClass):
  """Example class"""

  def instanceMethod(self, *args, **kwargs) -> int:
    """Instance method using ``maybeKey`` to search for a keyword argument 
    value with a type restriction argument."""
    return self.maybeKey(*args, **kwargs)


myInstance = MyClass()
myInstance.instanceMethod('a', 'b', int, a='1', b=2, c=3, d=4)  # >>> 2 

WorkToyClass.maybeKeys

from worktoy.worktoyclass import WorkToyClass


class MyClass(WorkToyClass):
  """Example class"""

  def instanceMethod(self, *args, **kwargs) -> int:
    """Instance method using ``maybeKeys`` to search for every keyword 
    argument restricted to a certain type."""
    return self.maybeKeys(*args, **kwargs)


myInstance = MyClass()
myInstance.instanceMethod('a', 'b', int, a=1, b=2, c=3, d=4)  # >>> [1, 2] 

WorkToyClass - Guards

The following methods are various type guards.

WorkToyClass.noneGuard

Raises UnavailableNameException if the given object is not None.

WorkToyClass.someGuard

Raises MissingArgumentException if given object is None

WorkToyClass.overRideGuard

Raises UnavailableNameException if given object is not None

WorkToyClass.functionGuard

Raises TypeSupportError if given object is not a function

WorkToyClass.intGuard

Raises TypeSupportError if given object is None or not an integer

WorkToyClass.floatGuard

Raises TypeSupportError if given object is None or not a float

WorkToyClass.strGuard

Raises TypeSupportError if given object is None or not a string

Descriptors

The Attribute class implements flexible descriptors.

class Attribute(WorkToyClass):
  """WorkToy - Fields - Field
  Basic descriptor implementation."""

  def __init__(self, defVal: Any = None, *args, **kwargs) -> None:
    WorkToyClass.__init__(self, *args, **kwargs)
    self._defaultValue = None
    self._defaultType = None

case 1:

Receives a default value that is not a type

if defVal is not None and not isinstance(defVal, type):
  self._setDefaultValue(defVal)
  self._defaultType = type(self._defaultValue)

case 2:

Receives a default value that is a type. This is taken to mean that the attribute is to hold a value of that type. The type is then called without argument to attempt to create a default value.

if isinstance(defVal, type):
  self._setDefaultValue(defVal)
  self._defaultValue = defVal()

case 3

Receives no argument. In this case, the instance is responsible for providing a default value. For example in the instance __init__ method using the public setter. Please note, that fields must do one of the following:

  1. Provide a default value in the Field creation call (RECOMMENDED)
  2. Define a Field type in the creation call. (NOT RECOMMENDED)
  3. Have the owning class defer default instance creation to the first call to the getter-function. This advanced use case allows the owning class to control specifically when and how to create instances. This is supported and encouraged, for advanced owning classes. (ADVANCED USE CASE)
  4. Subclass attribute to the specific type. (ADVANCED USE CASE)

ATTENTION!

Doing none of the above leads to HIGHLY UNDEFINED BEHAVIOUR! The Attribute is intended to raise MissingArgumentException in such cases.

self._fieldName = None
self._fieldOwner = None
self._getterFunctionName = None
self._setterFunctionName = None
self._deleterFunctionName = None

MetaClass

Metaclasses are certainly the most powerful tool available in Python development. The WorkToy package provides a basic skeleton for implementing custom metaclasses in the form of AbstractMetaClass and AbstractNameSpace. Before explaining the merits of these, a examination of how metaclasses work seem appropriate.

Introduction to metaclasses

You are already familiar with the default baseclass: type. In a somewhat unfortunate choice of nomenclature, we face an ambiguity here: do we mean type as in: isinstance(int, type) or do we mean: type(int)? The first treats type as a type, but the second treats type as a function. To illustrate how unfortunate this nomenclature is, consider this expression:

type(type) is type or isinstance(type, type) >>> True

A metaclass is a custom type. Consider TestClass defined below:

from worktoy.worktoyclass import WorkToyClass


class TestClass(WorkToyClass):
  """Created with traditional class body."""

  def __init__(self, *args, **kwargs) -> None:
    WorkToyClass.__init__(self, *args, **kwargs)

  def instanceMethod(self, *args, **kwargs) -> int:
    """Instance method"""
    return self.maybeType(int, *args)

The above is entirely equivalent to:

from typing import Any

from worktoy.worktoyclass import WorkToyClass


def initFunc(instance: Any, *args, **kwargs) -> None:
  """Init function"""
  WorkToyClass.__init__(instance, *args, **kwargs)


def someFunc(self, *args, **kwargs) -> int:
  """Instance Method"""
  return self._maybeType(int, *args)


name = 'TestClass'
bases = (WorkToyClass,)
nameSpace = dict(__init__=initFunc, instanceMethod=someFunc)
TestClass = type(name, bases, nameSpace)

type

The type object used above specifies the creation of new classes. By creating a custom metaclass, we are able to define our own class creation. Below we define a metaclass that behaves entirely like type allowing us to recognize the class creation we are familiar with and see how we can change this behaviour.

(Please note, the naming convention: mcls: metaclass, cls: new class, self new instance).

from typing import Any


class BaseMeta(type):  # metaclasses inherit from type
  """Base metaclass behaving line ``type``"""

  @classmethod
  def __prepare__(mcls, name: str, bases: tuple[type], **kwargs) -> dict:
    """The prepare method creates the empty mapping object providing the 
    namespace for the newly created class. The base implementation 
    returns an empty instance of ``dict``."""
    return {}

  def __new__(mcls, name: str, bases: tuple[type], nameSpace: dict,
              **kwargs) -> type:
    """The ``__new__`` method createds the new class,"""
    cls = type.__new__(mcls, name, bases, nameSpace, **kwargs)
    return cls

  def __init__(cls, name: str, bases: tuple[type], nameSpace: dict,
               **kwargs) -> None:
    """Once the new class is created it is initialised by this method. """
    type.__init__(cls, name, bases, nameSpace, **kwargs)

  def __call__(cls: type, *args, **kwargs) -> Any:
    """This method specifies how the newly creatd class creates instances 
    of itself. The default behaviour is as shown below: The instance is 
    created with the __new__ method on the newly created class, and then 
    it is initialized with the __init__ on the newly created class."""
    self = cls.__new__(cls, )
    cls.__init__(self, *args, **kwargs)
    return self

By introducing custom metaclasses, we are free to customize the above steps to achieve any imaginable functionality. People say that Python does not support function overloading. What they mean is that function overloading in Python must be implemented at the metaclass level. (That is dumb, function overloading should not require custom metaclasses, but the point stands).

NameSpace

Customizing the __prepare__ method gives the greatest opportunity to customize the class creation. Let us examine the requirements for the namespace object returned by the __prepare__ method. When attempting to use a custom class for this purppose, one is likely to encounter errors like:

"""TypeError: type.__new__() argument 3 must be dict, not NameSpace"""
"""TypeError: META.__prepare__() must return a mapping, not NameSpace"""
"""TypeError: ``NameSpace`` object does not support item assignment"""

It is possible to create a custom class that does not trigger any such TypeError, which is able to create classes without any problem. Until one day, you introduce a staticmethod and then receive:

"""
    @staticmethod
     ^^^^^^^^^^^^
TypeError: ``NoneType`` object is not callable"""

What even is that error message? The above happens if the __getitem__ method on the namespace object does not raise a KeyError when receiving a missing key. The expected behaviour from the namespace object receiving a missing key is to raise a KeyError with the missing key as the message. For example:

from typing import Any


def __getitem__(self, key: str, ) -> Any:
  try:
    dict.__getitem__(self, key)
  except KeyError as e:
    print(key)
    raise e

By including the print statement, we can see that the problems occur where the class body has a valid expression without an equal sign. For example when decorating a function. Consider the following example:

from typing import Any, Callable


class NameSpace(dict, ):
  """NameSpace custom class"""

  def __getitem__(self, key: str, ) -> Any:
    """Prints missing keys that are encountered."""
    try:
      return dict.__getitem__(self, key)
    except KeyError as e:
      print(key)
      raise e


class META(type):
  """Metaclass implementing the __prepare__ method which returns an
  instance of the NameSpace class."""

  @classmethod
  def __prepare__(mcls, name, bases, **kwargs) -> Any:
    nameSpace = NameSpace()
    return nameSpace


def func(f: Callable) -> None:
  """Decorator"""
  return f


class TestClass(metaclass=META):
  """TestClass """

  @staticmethod
  @func
  def a(self) -> None:
    pass


if __name__ == '__main__':
  TestClass()

When running the above script, we see the following printed to the console:

'__name__'
'staticmethod'
'func'

Fortunately, WorkToy provides the AbstractNameSpace class which implements all required mapping functionality. Besides implementing dict methods, it logs every line in the class body.

Wait A Minute!

In this module, WorkToy provides the custom exceptions used throughout the entire package.

MetaXcept

Just like the SYM module, the custom exceptions implement a custom metaclass inheriting from AbstractMetaClass. This metaclass MetaXcept uses a custom namespace class inheriting from the AbstractNameSpace in its __prepare__ method.

Below is a reference list of the custom exceptions currently implemented:

MetaTypeSupportError

Description

Indicates that an instance is not a member of class derived from the correct metaclass.

Signature

from typing import Any

expMetaClass: type  # The expected metaclass
actualValue: Any  # The actual value received
argName: str  # Argument name

FieldDecoderException

Custom exception raised when an instance of DataField attempts to decode with default JSON decoder. The exception catches the JSONDecodeError and brings additional information.

FieldEncoderException

Custom exception raised when an instance of DataField attempts to serialize its value to JSON format, but where the value is not serializable.

MissingArgumentException

Description

Invoked when a function is called before it is ready.

Signature

from typing import Any

missingArgument: str  # Argument name

RecursiveCreateGetError

Description

Raised when a getter function calls a creator function a second time.

Signature

from worktoy.core import Function

from typing import Any

creator: Function  # The expected type
variableType: type  # The type of the variable
variableName: str  # Argument name

TypeSupportError

Description

This exception should be raised when the argument type is not supported.

Signature

from typing import Any

expectedType: type  # The expected type
actualValue: Any  # The actual value received
argName: str  # Argument name

UnavailableNameException

Description

Exception raised when a name is already occupied. Meaning that the named argument were expected to be None.

Signature

from typing import Any

argName: str  # The unavailable name
existingValue: Any  # The present value at the name
newValue: str  # The new value attempted to set

UnexpectedEventException

Description

Raised when receiving a QEvent of the wrong QEvent.Type. (Please note that this exception is intended for use with the companion WorkSide module.)

Signature

from typing import Any

expectedQEventType: str  # The expected QEvent.Type
actualEvent: Any  # The actual instance of QEvent received
argumentName: str  # The argument name

UnsupportedSubclassException

Description

This exception should be raised when encountering a variable of correct type, but of incorrect subclass.

Signature

from typing import Any

argumentName: str  # The argument name
expectedParent: type  # The actual instance of QEvent received
actualValue: str  # The actual value of the variable

Core

This module provides common types and constants.

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