💡 Python Tips Part 1

A collection of essential Python tricks to make your code more efficient, readable, and "Pythonic." This part covers list comprehensions, f-strings, tuple unpacking, and using enumerate.

# Create a list of squares from 0 to 9
squares = [x**2 for x in range(10)]

print(squares)
# Output: [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

• List Comprehensions: A concise and often faster way to create lists. The syntax is [expression for item in iterable].

name = "Alex"
score = 95.5

# Using an f-string for easy formatting
message = f"Congratulations {name}, you scored {score:.1f}!"

print(message)
# Output: Congratulations Alex, you scored 95.5!

• F-Strings: The modern, readable way to format strings. Simply prefix the string with f and place variables or expressions directly inside curly braces {}.

numbers = (1, 2, 3, 4, 5)

# Unpack the first, last, and middle elements
first, *middle, last = numbers

print(f"First: {first}")   # 1
print(f"Middle: {middle}") # [2, 3, 4]
print(f"Last: {last}")     # 5

• Extended Unpacking: Use the asterisk * operator to capture multiple items from an iterable into a list during assignment. It's perfect for separating the "head" and "tail" from the rest.

items = ['keyboard', 'mouse', 'monitor']

for index, item in enumerate(items):
    print(f"Item #{index}: {item}")

# Output:
# Item #0: keyboard
# Item #1: mouse
# Item #2: monitor

• Using enumerate: The Pythonic way to get both the index and the value of an item when looping. It's much cleaner than using range(len(items)).

#Python #Programming #CodeTips #PythonTricks

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By: @DataScience4 ✨

💡 Python Tips Part 2

More essential Python tricks to improve your code. This part covers dictionary comprehensions, the zip function, ternary operators, and using underscores for unused variables.

# Create a dictionary of numbers and their squares
squared_dict = {x: x**2 for x in range(1, 6)}

print(squared_dict)
# Output: {1: 1, 2: 4, 3: 9, 4: 16, 5: 25}

• Dictionary Comprehensions: A concise way to create dictionaries, similar to list comprehensions. The syntax is {key_expr: value_expr for item in iterable}.

students = ["Alice", "Bob", "Charlie"]
scores = [88, 92, 79]

for student, score in zip(students, scores):
    print(f"{student}: {score}")

# Output:
# Alice: 88
# Bob: 92
# Charlie: 79

• Using zip: The zip function combines multiple iterables (like lists or tuples) into a single iterator of tuples. It's perfect for looping over related lists in parallel.

age = 20

# Assign a value based on a condition in one line
status = "Adult" if age >= 18 else "Minor"

print(status)
# Output: Adult

• Ternary Operator: A shorthand for a simple if-else statement, useful for conditional assignments. The syntax is value_if_true if condition else value_if_false.

# Looping 3 times without needing the loop variable
for _ in range(3):
    print("Hello, Python!")

# Unpacking, but only needing the last value
_, _, last_item = (10, 20, 30)
print(last_item) # 30

• Using Underscore _: By convention, the underscore _ is used as a variable name when you need a placeholder but don't intend to use its value. This signals to other developers that the variable is intentionally ignored.

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By: @DataScience4 ✨

💡 Python Tips Part 3

Advancing your Python skills with more powerful techniques. This part covers safe dictionary access with .get(), flexible function arguments with *args and **kwargs, and context managers using the with statement.

user_data = {"name": "Alice", "age": 30}

# Safely get a key that exists
name = user_data.get("name")

# Safely get a key that doesn't exist by providing a default
city = user_data.get("city", "Not Specified")

print(f"Name: {name}, City: {city}")
# Output: Name: Alice, City: Not Specified

• Dictionary .get() Method: Access dictionary keys safely. .get(key, default) returns the value for a key if it exists, otherwise it returns the default value (which is None if not specified) without raising a KeyError.

def dynamic_function(*args, **kwargs):
    print("Positional args (tuple):", args)
    print("Keyword args (dict):", kwargs)

dynamic_function(1, 'go', True, user="admin", status="active")
# Output:
# Positional args (tuple): (1, 'go', True)
# Keyword args (dict): {'user': 'admin', 'status': 'active'}

• *args and **kwargs: Use these in function definitions to accept a variable number of arguments. *args collects positional arguments into a tuple, and **kwargs collects keyword arguments into a dictionary.

# The 'with' statement ensures the file is closed automatically
try:
    with open("notes.txt", "w") as f:
        f.write("Context managers are great!")
    # No need to call f.close()
    print("File written and closed.")
except Exception as e:
    print(f"An error occurred: {e}")

• The with Statement: The with statement creates a context manager, which is the standard way to handle resources like files or network connections. It guarantees that cleanup code is executed, even if errors occur inside the block.

#Python #Programming #CodeTips #PythonTricks

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By: @DataScience4 ✨

Python tip:
Use f-strings for easy and readable string formatting.

name = "Alice"
age = 30
message = f"Hello, my name is {name} and I am {age} years old."
print(message)

Python tip:
Utilize list comprehensions for concise and efficient list creation.

numbers = [1, 2, 3, 4, 5]
squares = [x * x for x in numbers if x % 2 == 0]
print(squares)

Python tip:
Use enumerate() to iterate over a sequence while also getting the index of each item.

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

Python tip:
Use zip() to iterate over multiple iterables in parallel.

names = ["Alice", "Bob"]
ages = [25, 30]
for name, age in zip(names, ages):
    print(f"{name} is {age} years old.")

Python tip:
Always use the with statement when working with files to ensure they are properly closed, even if errors occur.

with open("example.txt", "w") as f:
    f.write("Hello, world!\n")
    f.write("This is a test.")
# File is automatically closed here

Python tip:
Use *args to allow a function to accept a variable number of positional arguments.

def sum_all(*args):
    total = 0
    for num in args:
        total += num
    return total

print(sum_all(1, 2, 3))
print(sum_all(10, 20, 30, 40))

Python tip:
Use **kwargs to allow a function to accept a variable number of keyword arguments (as a dictionary).

def display_info(**kwargs):
    for key, value in kwargs.items():
        print(f"{key}: {value}")

display_info(name="Bob", age=40, city="New York")

Python tip:
Employ defaultdict from the collections module to simplify handling missing keys in dictionaries by providing a default factory.

from collections import defaultdict

data = [("fruit", "apple"), ("vegetable", "carrot"), ("fruit", "banana")]
categorized = defaultdict(list)
for category, item in data:
    categorized[category].append(item)
print(categorized)

Python tip:
Use if __name__ == "__main__": to define code that only runs when the script is executed directly, not when imported as a module.

def greet(name):
    return f"Hello, {name}!"

if __name__ == "__main__":
    print("Running directly as a script.")
    print(greet("World"))
else:
    print("This module was imported.")

Python tip:
Apply type hints to your code for improved readability, maintainability, and to enable static analysis tools.

def add(a: int, b: int) -> int:
    return a + b

result: int = add(5, 3)
print(result)

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By: @DataScience4 ✨