### Facade Pattern Implementation in Python

Source: https://context7.com/faif/python-patterns/llms.txt

Simplify a complex subsystem with a single entry point. This example provides a 'start' method to boot a simulated computer.

```python
class CPU:
    def freeze(self) -> None:
        print("Freezing processor.")
    def jump(self, position: str) -> None:
        print(f"Jumping to: {position}")
    def execute(self) -> None:
        print("Executing.")

class Memory:
    def load(self, position: str, data: str) -> None:
        print(f"Loading from {position} data: '{data}'.")

class SolidStateDrive:
    def read(self, lba: str, size: str) -> str:
        return f"Some data from sector {lba} with size {size}"

class ComputerFacade:
    """Simplified interface for computer boot"""
    def __init__(self):
        self.cpu = CPU()
        self.memory = Memory()
        self.ssd = SolidStateDrive()

    def start(self):
        self.cpu.freeze()
        self.memory.load("0x00", self.ssd.read("100", "1024"))
        self.cpu.jump("0x00")
        self.cpu.execute()

# Usage - simple one-call interface
computer = ComputerFacade()
computer.start()
# Output:
# Freezing processor.
# Loading from 0x00 data: 'Some data from sector 100 with size 1024'.
# Jumping to: 0x00
# Executing.
```

--------------------------------

### Proxy Pattern Implementation in Python

Source: https://context7.com/faif/python-patterns/llms.txt

Control access to an object by providing a surrogate. This example implements a proxy that logs access and restricts functionality to 'admin' users.

```python
class Subject:
    def do_the_job(self, user: str) -> None:
        raise NotImplementedError()

class RealSubject(Subject):
    """The actual job performer"""
    def do_the_job(self, user: str) -> None:
        print(f"I am doing the job for {user}")

class Proxy(Subject):
    """Controls access to RealSubject with logging"""
    def __init__(self) -> None:
        self._real_subject = RealSubject()

    def do_the_job(self, user: str) -> None:
        print(f"[log] Doing the job for {user} is requested.")
        if user == "admin":
            self._real_subject.do_the_job(user)
        else:
            print("[log] I can do the job just for `admins`.")

# Usage
proxy = Proxy()

proxy.do_the_job('admin')
# Output:
# [log] Doing the job for admin is requested.
# I am doing the job for admin

proxy.do_the_job('anonymous')
# Output:
# [log] Doing the job for anonymous is requested.
# [log] I can do the job just for `admins`.
```

--------------------------------

### Implement Strategy Pattern in Python

Source: https://context7.com/faif/python-patterns/llms.txt

The Strategy pattern allows algorithms to be selected at runtime. This example defines an `Order` class that can apply different discount strategies, such as a fixed percentage or a sale discount with an additional fixed amount. The discount logic is encapsulated in separate functions.

```python
from __future__ import annotations
from typing import Callable

class Order:
    def __init__(self, price: float, discount_strategy: Callable = None) -> None:
        self.price = price
        self._discount_strategy = discount_strategy

    def apply_discount(self) -> float:
        if self._discount_strategy:
            discount = self._discount_strategy(self)
        else:
            discount = 0
        return self.price - discount

    def __repr__(self) -> str:
        name = getattr(self._discount_strategy, "__name__", None)
        return f"<Order price: {self.price} strategy: {name}>"

def ten_percent_discount(order: Order) -> float:
    return order.price * 0.10

def on_sale_discount(order: Order) -> float:
    return order.price * 0.25 + 20
```

--------------------------------

### Adapter Pattern Implementation in Python

Source: https://context7.com/faif/python-patterns/llms.txt

Use the Adapter pattern to make incompatible interfaces work together. This example unifies different animal sounds and human speech under a common 'make_noise' method.

```python
from typing import Callable, Any

class Dog:
    def __init__(self) -> None:
        self.name = "Dog"
    def bark(self) -> str:
        return "woof!"

class Cat:
    def __init__(self) -> None:
        self.name = "Cat"
    def meow(self) -> str:
        return "meow!"

class Human:
    def __init__(self) -> None:
        self.name = "Human"
    def speak(self) -> str:
        return "'hello'"

class Adapter:
    """Adapts an object by replacing methods."""
    def __init__(self, obj, **adapted_methods: Callable[..., Any]) -> None:
        self.obj = obj
        self.__dict__.update(adapted_methods)

    def __getattr__(self, attr: str) -> Any:
        return getattr(self.obj, attr)

# Usage - unify different interfaces
objects = []
dog = Dog()
objects.append(Adapter(dog, make_noise=dog.bark))

cat = Cat()
objects.append(Adapter(cat, make_noise=cat.meow))

human = Human()
objects.append(Adapter(human, make_noise=human.speak))

for obj in objects:
    print(f"A {obj.name} goes {obj.make_noise()}")
# Output:
# A Dog goes woof!
# A Cat goes meow!
# A Human goes 'hello'
```

--------------------------------

### Decorator Pattern Implementation in Python

Source: https://context7.com/faif/python-patterns/llms.txt

Dynamically add functionality to objects without altering their class. This example stacks bold and italic wrappers around text.

```python
class TextTag:
    """Base text tag"""
    def __init__(self, text: str) -> None:
        self._text = text

    def render(self) -> str:
        return self._text

class BoldWrapper(TextTag):
    """Wraps a tag in <b>"""
    def __init__(self, wrapped: TextTag) -> None:
        self._wrapped = wrapped

    def render(self) -> str:
        return f"<b>{self._wrapped.render()}</b>"

class ItalicWrapper(TextTag):
    """Wraps a tag in <i>"""
    def __init__(self, wrapped: TextTag) -> None:
        self._wrapped = wrapped

    def render(self) -> str:
        return f"<i>{self._wrapped.render()}</i>"

# Usage - decorators can be stacked
simple_hello = TextTag("hello, world!")
print(f"before: {simple_hello.render()}")
# Output: before: hello, world!

special_hello = ItalicWrapper(BoldWrapper(simple_hello))
print(f"after: {special_hello.render()}")
# Output: after: <i><b>hello, world!</b></i>
```

--------------------------------

### Implement Flyweight Pattern in Python

Source: https://context7.com/faif/python-patterns/llms.txt

The Flyweight pattern conserves memory by sharing common data between similar objects. This example uses `weakref.WeakValueDictionary` to pool card instances, ensuring that identical cards are represented by the same object in memory.

```python
import weakref

class Card:
    """Flyweight card - shared instances"""
    _pool: weakref.WeakValueDictionary = weakref.WeakValueDictionary()

    def __new__(cls, value: str, suit: str):
        obj = cls._pool.get(value + suit)
        if obj is None:
            obj = object.__new__(Card)
            cls._pool[value + suit] = obj
            obj.value, obj.suit = value, suit
        return obj

    def __repr__(self) -> str:
        return f"<Card: {self.value}{self.suit}>"

# Usage - same cards share instances
c1 = Card('9', 'h')
c2 = Card('9', 'h')

print(c1, c2)  # Output: <Card: 9h> <Card: 9h>
print(c1 == c2)  # Output: True
print(c1 is c2)  # Output: True (same object)

c3 = Card('A', 's')
print(c1 is c3)  # Output: False (different card)
```

--------------------------------

### Implement Observer Pattern in Python

Source: https://context7.com/faif/python-patterns/llms.txt

The Observer pattern facilitates loose coupling by allowing objects (observers) to subscribe to state changes in another object (subject). When the subject's state changes, all its observers are automatically notified. This example demonstrates a `Data` subject notifying `DecimalViewer` and `HexViewer` observers.

```python
from __future__ import annotations
from typing import List

class Observer:
    def update(self, subject: Subject) -> None:
        pass

class Subject:
    def __init__(self) -> None:
        self._observers: List[Observer] = []

    def attach(self, observer: Observer) -> None:
        if observer not in self._observers:
            self._observers.append(observer)

    def detach(self, observer: Observer) -> None:
        self._observers.remove(observer)

    def notify(self) -> None:
        for observer in self._observers:
            observer.update(self)

class Data(Subject):
    def __init__(self, name: str = "") -> None:
        super().__init__()
        self.name = name
        self._data = 0

    @property
    def data(self) -> int:
        return self._data

    @data.setter
    def data(self, value: int) -> None:
        self._data = value
        self.notify()

class HexViewer:
    def update(self, subject: Data) -> None:
        print(f"HexViewer: Subject {subject.name} has data 0x{subject.data:x}")

class DecimalViewer:
    def update(self, subject: Data) -> None:
        print(f"DecimalViewer: Subject {subject.name} has data {subject.data}")

# Usage
data = Data('Data 1')
view1 = DecimalViewer()
view2 = HexViewer()

data.attach(view1)
data.attach(view2)

data.data = 10

data.detach(view2)
data.data = 20
```

--------------------------------

### Swap Discount Strategies at Runtime

Source: https://context7.com/faif/python-patterns/llms.txt

Demonstrates how to dynamically change the discount strategy applied to an order object.

```python
order = Order(100, discount_strategy=ten_percent_discount)
print(order)  # Output: <Order price: 100 strategy: ten_percent_discount>
print(order.apply_discount())  # Output: 90.0

order = Order(100, discount_strategy=on_sale_discount)
print(order.apply_discount())  # Output: 55.0

order = Order(100)  # No discount
print(order.apply_discount())  # Output: 100
```

--------------------------------

### Dependency Injection Patterns in Python

Source: https://context7.com/faif/python-patterns/llms.txt

Demonstrates Constructor, Parameter, and Setter Injection for decoupling objects. Useful for enhancing testability and flexibility by passing dependencies to clients.

```python
import datetime
from typing import Callable

class ConstructorInjection:
    def __init__(self, time_provider: Callable) -> None:
        self.time_provider = time_provider

    def get_current_time_as_html_fragment(self) -> str:
        current_time = self.time_provider()
        return f'<span class="tinyBoldText">{current_time}</span>'

class ParameterInjection:
    def get_current_time_as_html_fragment(self, time_provider: Callable) -> str:
        current_time = time_provider()
        return f'<span class="tinyBoldText">{current_time}</span>'

class SetterInjection:
    def set_time_provider(self, time_provider: Callable):
        self.time_provider = time_provider

    def get_current_time_as_html_fragment(self):
        current_time = self.time_provider()
        return f'<span class="tinyBoldText">{current_time}</span>'

# Stub for testing
def midnight_time_provider() -> str:
    return "24:01"

# Production provider
def production_time_provider() -> str:
    now = datetime.datetime.now()
    return f"{now.hour}:{now.minute}"

# Usage - Constructor Injection
time_display = ConstructorInjection(midnight_time_provider)
print(time_display.get_current_time_as_html_fragment())
# Output: <span class="tinyBoldText">24:01</span>

# Usage - Parameter Injection
pi = ParameterInjection()
print(pi.get_current_time_as_html_fragment(midnight_time_provider))
# Output: <span class="tinyBoldText">24:01</span>

# Usage - Setter Injection
si = SetterInjection()
si.set_time_provider(midnight_time_provider)
print(si.get_current_time_as_html_fragment())
# Output: <span class="tinyBoldText">24:01</span>
```

--------------------------------

### State Pattern for Radio Tuning

Source: https://context7.com/faif/python-patterns/llms.txt

Demonstrates the State pattern by allowing a Radio object to change its behavior (AM/FM tuning) based on its internal state.

```python
from __future__ import annotations

class State:
    def scan(self) -> None:
        self.pos += 1
        if self.pos == len(self.stations):
            self.pos = 0
        print(f"Scanning... Station is {self.stations[self.pos]} {self.name}")

class AmState(State):
    def __init__(self, radio: Radio) -> None:
        self.radio = radio
        self.stations = ["1250", "1380", "1510"]
        self.pos = 0
        self.name = "AM"

    def toggle_amfm(self) -> None:
        print("Switching to FM")
        self.radio.state = self.radio.fmstate

class FmState(State):
    def __init__(self, radio: Radio) -> None:
        self.radio = radio
        self.stations = ["81.3", "89.1", "103.9"]
        self.pos = 0
        self.name = "FM"

    def toggle_amfm(self) -> None:
        print("Switching to AM")
        self.radio.state = self.radio.amstate

class Radio:
    def __init__(self) -> None:
        self.amstate = AmState(self)
        self.fmstate = FmState(self)
        self.state = self.amstate

    def toggle_amfm(self) -> None:
        self.state.toggle_amfm()

    def scan(self) -> None:
        self.state.scan()

# Usage
radio = Radio()
radio.scan()  # Output: Scanning... Station is 1380 AM
radio.scan()  # Output: Scanning... Station is 1510 AM
radio.toggle_amfm()  # Output: Switching to FM
radio.scan()  # Output: Scanning... Station is 89.1 FM
```

--------------------------------

### Factory Method Pattern in Python

Source: https://context7.com/faif/python-patterns/llms.txt

Demonstrates the Factory Method pattern using a factory function to create localizer objects based on language. This allows for flexible object creation.

```python
from typing import Dict, Protocol, Type

class Localizer(Protocol):
    def localize(self, msg: str) -> str: ...

class GreekLocalizer:
    def __init__(self) -> None:
        self.translations = {"dog": "σκύλος", "cat": "γάτα"}

    def localize(self, msg: str) -> str:
        return self.translations.get(msg, msg)

class EnglishLocalizer:
    def localize(self, msg: str) -> str:
        return msg

def get_localizer(language: str = "English") -> Localizer:
    """Factory function that creates appropriate localizer"""
    localizers: Dict[str, Type[Localizer]] = {
        "English": EnglishLocalizer,
        "Greek": GreekLocalizer,
    }
    return localizers.get(language, EnglishLocalizer)()

# Usage
e = get_localizer(language="English")
g = get_localizer(language="Greek")

for msg in "dog parrot cat bear".split():
    print(e.localize(msg), g.localize(msg))
# Output:
# dog σκύλος
# parrot parrot
# cat γάτα
# bear bear
```

--------------------------------

### Builder Pattern in Python

Source: https://context7.com/faif/python-patterns/llms.txt

Illustrates the Builder pattern by separating the construction of complex objects from their representation. This allows for different representations using the same construction process.

```python
class Building:
    def __init__(self) -> None:
        self.build_floor()
        self.build_size()

    def build_floor(self):
        raise NotImplementedError

    def build_size(self):
        raise NotImplementedError

    def __repr__(self) -> str:
        return f"Floor: {self.floor} | Size: {self.size}"

class House(Building):
    def build_floor(self) -> None:
        self.floor = "One"

    def build_size(self) -> None:
        self.size = "Big"

class Flat(Building):
    def build_floor(self) -> None:
        self.floor = "More than One"

    def build_size(self) -> None:
        self.size = "Small"

# Alternative: External builder function
class ComplexBuilding:
    def __repr__(self) -> str:
        return f"Floor: {self.floor} | Size: {self.size}"

class ComplexHouse(ComplexBuilding):
    def build_floor(self) -> None:
        self.floor = "One"
    def build_size(self) -> None:
        self.size = "Big and fancy"

def construct_building(cls) -> ComplexBuilding:
    building = cls()
    building.build_floor()
    building.build_size()
    return building

# Usage
house = House()
print(house)  # Output: Floor: One | Size: Big

flat = Flat()
print(flat)  # Output: Floor: More than One | Size: Small

complex_house = construct_building(ComplexHouse)
print(complex_house)  # Output: Floor: One | Size: Big and fancy
```

--------------------------------

### Prototype Pattern Implementation

Source: https://context7.com/faif/python-patterns/llms.txt

Creates new objects by cloning existing instances. Useful when object creation is expensive. The `PrototypeDispatcher` manages and registers prototypes.

```python
from __future__ import annotations
from typing import Any

class Prototype:
    def __init__(self, value: str = "default", **attrs: Any) -> None:
        self.value = value
        self.__dict__.update(attrs)

    def clone(self, **attrs: Any) -> Prototype:
        """Clone prototype and update attributes"""
        obj = self.__class__(**self.__dict__)
        obj.__dict__.update(attrs)
        return obj

class PrototypeDispatcher:
    def __init__(self):
        self._objects = {}

    def get_objects(self) -> dict[str, Prototype]:
        return self._objects

    def register_object(self, name: str, obj: Prototype) -> None:
        self._objects[name] = obj

    def unregister_object(self, name: str) -> None:
        del self._objects[name]

# Usage
dispatcher = PrototypeDispatcher()
prototype = Prototype()

d = prototype.clone()
a = prototype.clone(value='a-value', category='a')
b = a.clone(value='b-value', is_checked=True)

dispatcher.register_object('objecta', a)
dispatcher.register_object('objectb', b)
dispatcher.register_object('default', d)

print([{n: p.value} for n, p in dispatcher.get_objects().items()])
# Output: [{'objecta': 'a-value'}, {'objectb': 'b-value'}, {'default': 'default'}]

print(b.category, b.is_checked)
# Output: a True
```

--------------------------------

### Command Pattern for File Operations

Source: https://context7.com/faif/python-patterns/llms.txt

Implements the Command pattern to encapsulate file hiding and deletion operations, allowing for undo functionality.

```python
from typing import List, Union

class HideFileCommand:
    def __init__(self) -> None:
        self._hidden_files: List[str] = []

    def execute(self, filename: str) -> None:
        print(f"hiding {filename}")
        self._hidden_files.append(filename)

    def undo(self) -> None:
        filename = self._hidden_files.pop()
        print(f"un-hiding {filename}")

class DeleteFileCommand:
    def __init__(self) -> None:
        self._deleted_files: List[str] = []

    def execute(self, filename: str) -> None:
        print(f"deleting {filename}")
        self._deleted_files.append(filename)

    def undo(self) -> None:
        filename = self._deleted_files.pop()
        print(f"restoring {filename}")

class MenuItem:
    """The invoker - executes commands"""
    def __init__(self, command: Union[HideFileCommand, DeleteFileCommand]) -> None:
        self._command = command

    def on_do_press(self, filename: str) -> None:
        self._command.execute(filename)

    def on_undo_press(self) -> None:
        self._command.undo()

# Usage
delete_item = MenuItem(DeleteFileCommand())
hide_item = MenuItem(HideFileCommand())

delete_item.on_do_press('document.txt')
# Output: deleting document.txt

delete_item.on_undo_press()
# Output: restoring document.txt

hide_item.on_do_press('secret.txt')
# Output: hiding secret.txt

hide_item.on_undo_press()
# Output: un-hiding secret.txt
```

--------------------------------

### Publish-Subscribe Pattern in Python

Source: https://context7.com/faif/python-patterns/llms.txt

Implements the Publish-Subscribe pattern for loose coupling between publishers and subscribers via a message center. Publishers notify the message center, which then distributes messages to subscribed listeners.

```python
from __future__ import annotations

class Provider:
    def __init__(self) -> None:
        self.msg_queue = []
        self.subscribers = {}

    def notify(self, msg: str) -> None:
        self.msg_queue.append(msg)

    def subscribe(self, msg: str, subscriber: Subscriber) -> None:
        self.subscribers.setdefault(msg, []).append(subscriber)

    def unsubscribe(self, msg: str, subscriber: Subscriber) -> None:
        self.subscribers[msg].remove(subscriber)

    def update(self) -> None:
        for msg in self.msg_queue:
            for sub in self.subscribers.get(msg, []):
                sub.run(msg)
        self.msg_queue = []

class Publisher:
    def __init__(self, msg_center: Provider) -> None:
        self.provider = msg_center

    def publish(self, msg: str) -> None:
        self.provider.notify(msg)

class Subscriber:
    def __init__(self, name: str, msg_center: Provider) -> None:
        self.name = name
        self.provider = msg_center

    def subscribe(self, msg: str) -> None:
        self.provider.subscribe(msg, self)

    def run(self, msg: str) -> None:
        print(f"{self.name} got {msg}")

# Usage
message_center = Provider()
fftv = Publisher(message_center)

jim = Subscriber("jim", message_center)
jim.subscribe("cartoon")

jack = Subscriber("jack", message_center)
jack.subscribe("music")

fftv.publish("cartoon")
fftv.publish("music")
fftv.publish("cartoon")

message_center.update()
```

--------------------------------

### Borg (Monostate) Pattern Implementation

Source: https://context7.com/faif/python-patterns/llms.txt

The Borg pattern shares state across all instances. Changes to attributes are reflected across all objects. Use when singleton-like behavior is desired but distinct instances are acceptable.

```python
from typing import Dict

class Borg:
    _shared_state: Dict[str, str] = {}

    def __init__(self) -> None:
        self.__dict__ = self._shared_state

class YourBorg(Borg):
    def __init__(self, state: str = None) -> None:
        super().__init__()
        if state:
            self.state = state
        elif not hasattr(self, "state"):
            self.state = "Init"

    def __str__(self) -> str:
        return self.state

# Usage - all instances share state
rm1 = YourBorg()
rm2 = YourBorg()

rm1.state = 'Idle'
rm2.state = 'Running'

print(f'rm1: {rm1}')  # Output: rm1: Running
print(f'rm2: {rm2}')  # Output: rm2: Running

# Instances are different objects but share state
print(rm1 is rm2)  # Output: False

rm3 = YourBorg('Zombie')
print(f'rm1: {rm1}')  # Output: rm1: Zombie
print(f'rm3: {rm3}')  # Output: rm3: Zombie
```

--------------------------------

### Object Pool Pattern Implementation

Source: https://context7.com/faif/python-patterns/llms.txt

Manages a pool of reusable objects to reduce creation/destruction overhead. Uses a queue to store and retrieve objects. The context manager ensures objects are returned to the pool.

```python
from queue import Queue
from types import TracebackType
from typing import Union

class ObjectPool:
    def __init__(self, queue: Queue, auto_get: bool = False) -> None:
        self._queue = queue
        self.item = self._queue.get() if auto_get else None

    def __enter__(self) -> str:
        if self.item is None:
            self.item = self._queue.get()
        return self.item

    def __exit__(
        self,
        Type: Union[type[BaseException], None],
        value: Union[BaseException, None],
        traceback: Union[TracebackType, None],
    ) -> None:
        if self.item is not None:
            self._queue.put(self.item)
            self.item = None

# Usage
import queue

sample_queue = queue.Queue()
sample_queue.put('connection_1')
sample_queue.put('connection_2')

# Use with context manager - automatically returns to pool
with ObjectPool(sample_queue) as conn:
    print(f'Using: {conn}')
# Output: Using: connection_1

# Object is returned to pool and can be reused
with ObjectPool(sample_queue) as conn:
    print(f'Reusing: {conn}')
# Output: Reusing: connection_1
```

--------------------------------

### Abstract Factory Pattern in Python

Source: https://context7.com/faif/python-patterns/llms.txt

Implements the Abstract Factory pattern using Python classes as factories. Useful for creating families of related objects without specifying concrete classes.

```python
from typing import Type

class Pet:
    def __init__(self, name: str) -> None:
        self.name = name
    def speak(self) -> None:
        raise NotImplementedError

class Dog(Pet):
    def speak(self) -> None:
        print("woof")
    def __str__(self) -> str:
        return f"Dog<{self.name}>"

class Cat(Pet):
    def speak(self) -> None:
        print("meow")
    def __str__(self) -> str:
        return f"Cat<{self.name}>"

class PetShop:
    def __init__(self, animal_factory: Type[Pet]) -> None:
        self.pet_factory = animal_factory

    def buy_pet(self, name: str) -> Pet:
        pet = self.pet_factory(name)
        print(f"Here is your lovely {pet}")
        return pet

# Usage
cat_shop = PetShop(Cat)
pet = cat_shop.buy_pet("Lucy")
# Output: Here is your lovely Cat<Lucy>
pet.speak()
# Output: meow

dog_shop = PetShop(Dog)
pet = dog_shop.buy_pet("Max")
# Output: Here is your lovely Dog<Max>
pet.speak()
# Output: woof
```

--------------------------------

### Delegation Pattern in Python

Source: https://context7.com/faif/python-patterns/llms.txt

Implements the Delegation pattern using Python's dynamic features to achieve code reuse similar to inheritance. It forwards method calls to a delegate object.

```python
from __future__ import annotations
from typing import Any, Callable

class Delegator:
    def __init__(self, delegate: Delegate) -> None:
        self.delegate = delegate

    def __getattr__(self, name: str) -> Any | Callable:
        attr = getattr(self.delegate, name)

        if not callable(attr):
            return attr

        def wrapper(*args, **kwargs):
            return attr(*args, **kwargs)

        return wrapper

class Delegate:
    def __init__(self) -> None:
        self.p1 = 123

    def do_something(self, something: str, kw=None) -> str:
        return f"Doing {something}{kw or ''}"

# Usage
delegator = Delegator(Delegate())

print(delegator.p1)  # Output: 123

print(delegator.do_something("nothing"))
# Output: Doing nothing

print(delegator.do_something("something", kw=", today!"))
# Output: Doing something, today!
```

--------------------------------

### Iterator Pattern with Generators in Python

Source: https://context7.com/faif/python-patterns/llms.txt

Demonstrates the Iterator pattern using Python generators to traverse elements of a container without exposing its underlying representation. The `count_to` function yields elements one by one.

```python
def count_to(count: int):
    """Counts by word numbers using a generator"""
    numbers = ["one", "two", "three", "four", "five"]
    yield from numbers[:count]

# Usage
print("Counting to two:")
for number in count_to(2):
    print(number)

print("\nCounting to five:")
for number in count_to(5):
    print(number)
```

--------------------------------

### Implement Composite Pattern in Python

Source: https://context7.com/faif/python-patterns/llms.txt

Use the Composite pattern to represent part-whole hierarchies. It allows clients to treat individual objects and compositions of objects uniformly. Requires defining a common interface for both individual objects and composite objects.

```python
from abc import ABC, abstractmethod
from typing import List

class Graphic(ABC):
    @abstractmethod
    def render(self) -> None:
        raise NotImplementedError()

class CompositeGraphic(Graphic):
    def __init__(self) -> None:
        self.graphics: List[Graphic] = []

    def render(self) -> None:
        for graphic in self.graphics:
            graphic.render()

    def add(self, graphic: Graphic) -> None:
        self.graphics.append(graphic)

    def remove(self, graphic: Graphic) -> None:
        self.graphics.remove(graphic)

class Ellipse(Graphic):
    def __init__(self, name: str) -> None:
        self.name = name

    def render(self) -> None:
        print(f"Ellipse: {self.name}")

# Usage - build tree structure
ellipse1, ellipse2, ellipse3, ellipse4 = Ellipse("1"), Ellipse("2"), Ellipse("3"), Ellipse("4")

graphic1 = CompositeGraphic()
graphic1.add(ellipse1)
graphic1.add(ellipse2)
graphic1.add(ellipse3)

graphic2 = CompositeGraphic()
graphic2.add(ellipse4)

graphic = CompositeGraphic()
graphic.add(graphic1)
graphic.add(graphic2)

graphic.render()
```

--------------------------------

### Memento Pattern for State Management in Python

Source: https://context7.com/faif/python-patterns/llms.txt

Implements the Memento pattern to capture and restore an object's internal state. Useful for implementing undo functionality. The `Transaction` class provides a context manager for commit and rollback operations.

```python
from copy import copy, deepcopy
from typing import Any, Callable, List

def memento(obj: Any, deep: bool = False) -> Callable:
    state = deepcopy(obj.__dict__) if deep else copy(obj.__dict__)

    def restore() -> None:
        obj.__dict__.clear()
        obj.__dict__.update(state)

    return restore

class Transaction:
    """Transaction guard with commit/rollback"""
    def __init__(self, deep: bool, *targets: Any) -> None:
        self.deep = deep
        self.targets = targets
        self.commit()

    def commit(self) -> None:
        self.states = [memento(target, self.deep) for target in self.targets]

    def rollback(self) -> None:
        for a_state in self.states:
            a_state()

class NumObj:
    def __init__(self, value: int) -> None:
        self.value = value

    def __repr__(self) -> str:
        return f"<NumObj: {self.value!r}>"

    def increment(self) -> None:
        self.value += 1

# Usage
num_obj = NumObj(-1)
transaction = Transaction(True, num_obj)

try:
    for i in range(3):
        num_obj.increment()
        print(num_obj)
    transaction.commit()
    print('-- committed')

    for i in range(3):
        num_obj.increment()
        print(num_obj)
    num_obj.value += 'x'  # This will fail
except Exception:
    transaction.rollback()
    print('-- rolled back')

print(num_obj)
```

--------------------------------

### Chain of Responsibility for Request Handling

Source: https://context7.com/faif/python-patterns/llms.txt

Implements the Chain of Responsibility pattern to process requests through a series of handlers until one handles it.

```python
from abc import ABC, abstractmethod
from typing import Optional

class Handler(ABC):
    def __init__(self, successor: Optional["Handler"] = None):
        self.successor = successor

    def handle(self, request: int) -> None:
        res = self.check_range(request)
        if not res and self.successor:
            self.successor.handle(request)

    @abstractmethod
    def check_range(self, request: int) -> Optional[bool]:
        pass

class ConcreteHandler0(Handler):
    @staticmethod
    def check_range(request: int) -> Optional[bool]:
        if 0 <= request < 10:
            print(f"request {request} handled in handler 0")
            return True
        return None

class ConcreteHandler1(Handler):
    start, end = 10, 20

    def check_range(self, request: int) -> Optional[bool]:
        if self.start <= request < self.end:
            print(f"request {request} handled in handler 1")
            return True
        return None

class FallbackHandler(Handler):
    @staticmethod
    def check_range(request: int) -> Optional[bool]:
        print(f"end of chain, no handler for {request}")
        return False
```

--------------------------------

### Chain of Responsibility Pattern in Python

Source: https://context7.com/faif/python-patterns/llms.txt

Implements the Chain of Responsibility pattern to process requests through a series of handlers. Each handler decides whether to process the request or pass it to its successor.

```python
h0 = ConcreteHandler0()
h1 = ConcreteHandler1()
h2 = FallbackHandler()
h0.successor = h1
h1.successor = h2

for request in [2, 14, 22, 35]:
    h0.handle(request)
```

--------------------------------

### Lazy Evaluation Pattern Implementation

Source: https://context7.com/faif/python-patterns/llms.txt

Delays expensive computations until needed and caches the result. The `lazy_property` decorator handles this for class attributes.

```python
import functools
from typing import Callable, Type

class lazy_property:
    def __init__(self, function: Callable) -> None:
        self.function = function
        functools.update_wrapper(self, function)

    def __get__(self, obj, type_: Type) -> str:
        if obj is None:
            return self
        val = self.function(obj)
        obj.__dict__[self.function.__name__] = val
        return val

class Person:
    def __init__(self, name: str, occupation: str) -> None:
        self.name = name
        self.occupation = occupation

    @lazy_property
    def relatives(self) -> str:
        # Expensive computation - only runs once
        print("Computing relatives...")
        return "Many relatives."

# Usage
john = Person('John', 'Coder')

print(john.name)  # Output: John
print('relatives' in john.__dict__)  # Output: False

# First access triggers computation
print(john.relatives)
# Output: Computing relatives...
# Output: Many relatives.
```

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