Learn Python Coding

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Python: simple things that improve code If you write like this:

if type(x) == str:
    print("This is a string")

it might work, but it breaks on subclasses of str. It's better to use isinstance(). It takes into account inheritance and is more consistent with polymorphism.

if isinstance(x, str):
    print("This is a string")

This variant will work for str and its subclasses. Conclusion: type(x) == str is only suitable for simple cases, but it's fragile. isinstance(x, str) is a more stable and correct option almost always.

Python Basics Arrays & Loops 🐍 Essential you need to start strong 💪 https://t.me/pythonRe 🔗

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There's a floating-point number in Python and you need to output it as a percentage - use the % format in the f-string

x = .023
print(f'{x:.2%}')  # 2.30%

x = .02375
print(f'{x:.2%}')  # 2.38% -- rounded off!

x = 1.02375
print(f'{x:.2%}')  # 102.38%

👉 @PythonRe

🧐 Python Cheatsheet — a convenient cheat sheet for Python that really saves time at work! The repository contains a summary of key topics: from basic syntax and data structures to working with files, environments, and OOP with classes and magic methods. Everything is presented compactly, without unnecessary theory, with examples that can be immediately applied in code. Repo: https://github.com/onyxwizard/python-cheatsheet📱 https://t.me/pythonRe 👩‍💻

codes = ["A", "B", "C"]
found = False
for code in codes:
    if code == "B":
        found = True
        break
if found:
    print("Incorrect: Code B found (less efficient).")

Brief Explanation: The in operator is optimized for membership checks, offering better performance and cleaner code than manual loops, especially for larger lists. --- 5. Avoiding Unnecessary List Conversions Description: Many functions and methods return iterators or generator objects for efficiency. Converting these directly to a list without need can waste memory and computation if you only need to process elements one by one. Correct Usage: Process iterators directly when possible, convert to list only if multiple passes or random access is needed.

squares_gen = (x*x for x in range(5)) # Generator expression
for s in squares_gen: # Process elements one by one
    print(f"Correct: {s}", end=" ") # Output: 0 1 4 9 16
print()

# If you need the full list:
squares_list = list(x*x for x in range(5))
print(f"Correct (list conversion): {squares_list}") # Output: [0, 1, 4, 9, 16]

Incorrect Usage: Unnecessarily converting iterators to lists when single-pass processing suffices.

data_stream = map(str.upper, ['apple', 'banana', 'cherry'])
# If you only need to print them once:
full_list = list(data_stream) # Unnecessary list creation
for item in full_list:
    print(f"Incorrect: {item}", end=" ") # Output: APPLE BANANA CHERRY
print()

Brief Explanation: Iterators/generators are memory-efficient for single-pass operations. Convert to list() only when random access, repeated iteration, or a material collection is strictly required. https://t.me/pythonRe 🌟

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