Learn Python Coding
Lesson: Mastering Python Lists: Common Pitfalls and Best Practices ๐ 1. The Peril of Shallow Copies: Understanding References ๐ง Description: When you assign one list to another using =, you're not creating a new list; you're creating a new reference to theโฆ
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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๐ง Python Cheatsheet โ 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 ๐ฉโ๐ป
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 ๐ฉโ๐ป
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For example, a list supports indexing, is mutable, and stores duplicates, while a set stores only unique elements and has no order.
The picture shows a brief summary of the main data types and their properties: order, mutability, duplicates, and indexing.
Save it to remember!
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๐ ๐ฎ๐๐๐ฒ๐ฟ_๐ฃ๐๐๐ต๐ผ๐ป_๐๐ต๐ฒ_๐ฅ๐ถ๐ด๐ต๐_๐ช๐ฎ๐.pdf
6.6 MB
Master Python the Right Way โ Without Procrastination. ๐โจ
When I first started learning Python, I quickly realized:
You can't master a programming language just by reading syntax or watching tutorials. ๐๐ซ
Real growth happens when you practice, build, and solve problems on your own. ๐ ๐ป
That's exactly why I've compiled a collection of Python programs โ designed to take you from basics to advanced logic-building. ๐๐ง
What is this collection about? ๐ค
โ๏ธ Beginner to advanced programs with clear explanations
โ๏ธ Pattern-based exercises to strengthen core fundamentals
โ๏ธ Problem-solving programs that sharpen logical thinking
Why is this important? ๐
You don't just learn "how to code", you start learning "how to think like a programmer". ๐ง โก๏ธ
This is perfect for: ๐ฏ
โข Preparing for technical interviews ๐ค
โข Participating in coding challenges ๐
โข Building real-world Python projects ๐
https://t.me/pythonRe
When I first started learning Python, I quickly realized:
You can't master a programming language just by reading syntax or watching tutorials. ๐๐ซ
Real growth happens when you practice, build, and solve problems on your own. ๐ ๐ป
That's exactly why I've compiled a collection of Python programs โ designed to take you from basics to advanced logic-building. ๐๐ง
What is this collection about? ๐ค
โ๏ธ Beginner to advanced programs with clear explanations
โ๏ธ Pattern-based exercises to strengthen core fundamentals
โ๏ธ Problem-solving programs that sharpen logical thinking
Why is this important? ๐
You don't just learn "how to code", you start learning "how to think like a programmer". ๐ง โก๏ธ
This is perfect for: ๐ฏ
โข Preparing for technical interviews ๐ค
โข Participating in coding challenges ๐
โข Building real-world Python projects ๐
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
๐ @PythonRe
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%
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