New built-in type coming to Python: frozendict, an immutable dictionary This change is coming in Python 3.15, scheduled to be released in October of 2026. Say you have a `frozendict` instance. Trying to modify an existing key/value pair or adding a new key raises a `TypeError`: ```pycon >>> fd = frozendict({"one": 2}) >>> fd["one"] = 1 TypeError >>> fd["two"] = 2 TypeError ``` It's also worth noting that the immutability of a frozen dictionary is shallow. You can still mutate the underlying values: ```pycon >>> fd = frozendict({"list": []}) >>> fd frozendict({'list': []}) >>> fd["list"].append(73) >>> fd frozendict({'list': [73]}) ``` Remember that this behaviour matches the behaviour of a tuple! What will you use this for?

Create another palindrome use is_palindrome() method in python but use swap index of each char to reverse all index from backword. Notice if the length of the word or number not the same is false. py check_palindrome.py Enter a word or numbers: madam True Enter a word or numbers: python False Enter a word or numbers: 101 True

How Python Decides What Runs Next? Python follows a control flow to decide what runs next — by default it executes statements sequentially from top to bottom, but conditional statements (if/elif/else) and loops (for, while) change that flow based on decisions and repetition. Understanding this lets you predict exactly how and in what order your Python code runs. Learn from this video : https://lnkd.in/dmRxXPVF

Something interesting happens when you check membership in a Python dictionary. Whereas checking for membership using the keys of a dictionary runs in O(1) average time, the same runs in O(n) time if you use the values of the same dictionary. Here is why: Dictionary keys are stored in a hash table. Python hashes the key and uses that hash to locate the correct bucket in constant time. For values, Python has to draw lightweight view object and then traverse it till it finds the value. Checking values in a loop over a big dictionary can quietly become a performance bottleneck. I have attached code to illustrate this.

I’ve wanted to write something in Rust for a while, and recently got a bit excited about the idea of a Python library in Rust. So I open-sourced fast-ordset - an ordered set for Python implemented in Rust (PyO3 + indexmap). In benchmarks it’s about 2–10× faster than the pure-Python ordered-set on various operations. The extension is thread-safe and doesn’t hold the GIL, so it works with free-threaded Python. One downside: iteration is noticeably slower - each element crosses the Rust→Python boundary (serialization/copying), so for x in s and list(s) are slower than the Python implementation. For indexing s[i] and bulk operations it’s fine. Install: uv sync --all-extras and uv run maturin develop --release. MIT license. Repo: https://lnkd.in/dXRXdWqY #Python #Rust #OpenSource

Python 🐍: pip: HowTos: Get Package Versions Available and Installed Version Here’s a quick way to get all versions available of a particular package as well as, the latest and installed versions. pip index versions package-name #python #pip #pythonhowtos #pipindex

How Python Decides What Runs Next? Python follows a control flow to decide what runs next — by default it executes statements sequentially from top to bottom, but conditional statements (if/elif/else) and loops (for, while) change that flow based on decisions and repetition. Understanding this lets you predict exactly how and in what order your Python code runs. Learn from this video : https://lnkd.in/dWtrff9E

Solved problem 347 in Leetcode! Solution Python: class Solution: def topKFrequent(self, nums: List[int], k: int) -> List[int]: count_nums = {} for num in nums: count_nums[num] = count_nums.get(num, 0) + 1 array_nums = [[] for i in range(len(nums) + 1)] for num, count in count_nums.items(): array_nums[count].append(num) result = [] for i in range(len(nums), 0, -1): for num in array_nums[i]: result.append(num) if len(result) == k: return result

This one idea flips it: build fast, ship public. I wrote: “The OpenClaw Lesson: Build Fast, Ship Public — 12 Python Projects You Can Copy Today” ✅ 12 weekend-friendly Python projects ✅ why they get users ✅ how to ship them publicly 📖 Read it for free here: https://lnkd.in/dMMZZsFp #Python #OpenSource #SideProjects #BuildInPublic #SoftwareDevelopment #Automation #DeveloperTools #Productivity #Programming

Python Starters Day 19 Foundation Nugget For continuity, use While Loops While loops repeat until something changes. count = 0 while count < 5:   print(count)   count += 1 Be careful with the condition, because if the condition does not change, then the loop will never stop. This teaches responsibility, as automation without control can cause chaos. Loops must have an exit. Follow the Python 🐍 Starters Hub: WhatsApp: https://lnkd.in/dbjAFv52 LinkedIn: https://lnkd.in/dkJE3tZq Website: https://lnkd.in/eBHB2MqY