Joe Wood Notes

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Conditional

def check_number(num: int) -> str:
    if num > 0:
        return "Positive"
    elif num < 0:
        return "Negative"
    else:
        return "Zero"

print(check_number(10))  # "Positive"
print(check_number(-5))  # "Negative"
print(check_number(0))   # "Zero"

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Ternary Operator

result = "Positive" if num > 0 else "Negative" if num < 0 else "Zero"

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Loop Over

Python supports multiple looping constructs.

Basic for loop (iterates over a range of numbers):

for i in range(5):
    print(i)

Loop over lists (for...in):

numbers = [1, 2, 3]
for num in numbers:
    print(num)

Loop over dictionary keys and values:

user = {"id": 1, "name": "Alice"}
for key, value in user.items():
    print(f"{key}: {value}")

Enumerate iteration (index + value):

fruits = ["apple", "banana", "cherry"]
for index, fruit in enumerate(fruits):
    print(index, fruit)

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Loop Conditional Exit

Python does not have a built-in do...while loop like some other programming languages. However, you can achieve similar functionality using a while loop with a condition that is checked after the first iteration.

Example: Using a while loop for conditional exit:

count = 0
while count < 5:
    print(count)
    count += 1

Emulating a do...while loop:

To emulate a do...while loop (where the condition is checked after the first iteration), you can use a while True loop with a break statement:

count = 0
while True:
    print(count)
    count += 1
    if count >= 5:
        break

for i in range(10):
    if i == 5:
        break
    print(i)
# Output: 0, 1, 2, 3, 4

for i in range(5):
    if i == 2:
        continue
    print(i)
# Output: 0, 1, 3, 4

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Coroutines and yield

Coroutines in Python are a special type of function that can pause and resume execution. They are often used for asynchronous programming and cooperative multitasking. The yield keyword is used to create generators, which are a type of coroutine.

Using yield to Create Generators: - The yield keyword allows a function to return a value and pause its execution, resuming from where it left off when called again.

def count_up_to(n):
    count = 0
    while count < n:
        yield count
        count += 1

# Using the generator
for num in count_up_to(5):
    print(num)
# Output: 0, 1, 2, 3, 4

Coroutines are functions that can consume values sent to them using the send() method. They are defined using the yield keyword.

def coroutine_example():
    print("Coroutine started")
    while True:
        value = yield
        print(f"Received: {value}")

# Using the coroutine
coro = coroutine_example()
next(coro)  # Start the coroutine
coro.send(10)  # Send a value to the coroutine
coro.send(20)  # Send another value

yield from for Delegating Generators. The yield from statement is used to delegate part of a generator's operations to another generator.

def sub_generator():
    yield 1
    yield 2
    yield 3

def main_generator():
    yield from sub_generator()
    yield 4

# Using the generator
for value in main_generator():
    print(value)
# Output: 1, 2, 3, 4

Asynchronous Coroutines with async def. In modern Python, coroutines are often used with async def and await for asynchronous programming.

import asyncio

async def async_example():
    print("Start")
    await asyncio.sleep(1)  # Simulate an asynchronous operation
    print("End")

# Running the coroutine
asyncio.run(async_example())

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Exception Handling

Python provides a robust mechanism for handling runtime errors using try, except, else, and finally blocks. This allows you to gracefully handle errors and ensure proper cleanup.

Basic Exception Handling: - the try block lets you test a block of code for errors, and the except block lets you handle the error.

try:
    result = 10 / 0
except ZeroDivisionError as e:
    print(f"Error: {e}")
# Output: Error: division by zero

Catching Multiple Exceptions. You can catch multiple exceptions by specifying them in a tuple.

try:
    num = int("abc")
    result = 10 / 0
except (ValueError, ZeroDivisionError) as e:
    print(f"Error: {e}")
# Output: Error: invalid literal for int() with base 10: 'abc'

Using else with try. The else block runs if no exceptions are raised in the try block.

try:
    result = 10 / 2
except ZeroDivisionError as e:
    print(f"Error: {e}")
else:
    print(f"Result: {result}")
# Output: Result: 5.0

Using finally for Cleanup. The finally block always executes, regardless of whether an exception was raised or not. It is typically used for cleanup operations.

try:
    file = open("example.txt", "r")
    content = file.read()
except FileNotFoundError as e:
    print(f"Error: {e}")
finally:
    print("Closing the file.")
    if 'file' in locals() and not file.closed:
        file.close()
# Output: Error: [Errno 2] No such file or directory: 'example.txt'
#         Closing the file.

Raising Exceptions: - You can raise exceptions explicitly using the raise keyword.

def check_positive(num):
    if num < 0:
        raise ValueError("Number must be positive")
    return num

try:
    check_positive(-5)
except ValueError as e:
    print(f"Error: {e}")
# Output: Error: Number must be positive

Custom Exceptions: - You can define your own exceptions by creating a custom class that inherits from the Exception class.

class CustomError(Exception):
    pass

try:
    raise CustomError("This is a custom error")
except CustomError as e:
    print(f"Error: {e}")
# Output: Error: This is a custom error