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🐍📰 In this tutorial, you'll learn how and when to use the len() Python function. You'll also learn how to customize your class definitions so that objects of a user-defined class can be used as arguments in len() #python

🐍📰 Working With Files in Python In this tutorial, you'll learn how you can work with files by using built-in modules to perform practical tasks that involve groups of files, like renaming them, moving them, getting their metadata,and more. #python

🐍📰 How to Use the Python or Operator In this tutorial, you'll learn about how the Python or operator works and how to use it. You'll get to know its special features and see what kind of programming problems you can solve by using or in Python #python

🐍📰 Why Are Membership Tests So Fast for range() in Python? In Python, range() is commonly used in for loops. However, ranges have some other use cases too. In this tutorial, you'll explore why performing a membership test on a range is so fast. #python

🐍📰 In this step-by-step tutorial, you'll learn about Python's deque and how to use it to perform efficient pop and append operations on both ends of your sequences. Deques are commonly used to build queues and stacks #python

In case you are looking for something interesting to read about Python, here's a stack overflow answer on why Tuples are more efficient than Lists: #python https://lnkd.in/ddzr-GuP

🐍📰 How to Do a Binary Search in Python In this step-by-step tutorial, you'll learn how to implement this algorithm in Python. You'll learn how to leverage existing libraries as well as craft your own binary search Python implementation. #python

Easily the best feature in the upcoming version of Python: lazy imports. It's also designed to be forwards-compatible (so existing code can be reworked to start using it when run on the right version of the interpreter). https://lnkd.in/eUF3tZJ9

== vs is in Python — and why tuples sometimes fool you Everyone knows about == and is in Python. But can you predict this one? Quick recap: ✅ == checks if two objects have equal values ✅ is checks if they're the same object in memory That's why two lists with the same values are "equal" but not the same object in memory. With tuples, things get interesting. When you write two literal tuples like (1, 2, 3) on the same line, Python may reuse the same object — because tuples are immutable, it's safe to do so. Which is why: 👉 (1, 2, 3) is (1, 2, 3) → True (sometimes) 👉 Assign them separately, and it's False Even simple operators like is can reveal a lot about how Python works under the hood.

Three mistakes break binary search implementations in Python. Running it on unsorted data. The algorithm compares your target to the middle value to decide which half to search. On unsorted data, that decision is wrong from the start. Not handling duplicates. A standard binary search stops at the first match it finds. If the same value appears multiple times, you have no guarantee which index comes back. Off-by-one errors and infinite loops. Updating boundaries with mid instead of mid + 1 or mid - 1 means the middle element never gets excluded, which leads to skipped elements or an infinite loop. The guide by roadmap.sh covers all three with code examples showing the buggy version, the fix, and when Python's bisect module handles it for you.