Python Integer Cache: Optimized Engine Explained

Waited 16 seconds for a Python loop to finish? I did. Then I added one decorator and it dropped to 0.18 seconds. That is a 128x speedup, and the only change was this: @njit In my latest post, I break down exactly why Python loops are slow at the bytecode level, how Numba bypasses the interpreter entirely, and where Numba actually makes things worse (hint: strings). Covered in the post: - How the Python interpreter processes opcodes on every loop iteration - Why @njit works so well for NumPy workloads - Why @njit(parallel=True) crashes on string operations - Benchmark results on Apple M4 Pro with 20 million element arrays If you work with numerical data in Python, this one is worth 5 minutes. https://lnkd.in/gV3W_YCg #Python #Numba #NumPy #Performance #MachineLearning

One concept that often confuses developers (including me at first) is reference behavior in Python. In Python, variables don’t actually store values. They store references to objects in memory. a = [1, 2] b = a Here, a and b are not two separate lists. They both point to the same list in memory. So when you do b[0] = 3 you are modifying the same objects. That means print(a) => [3,2] print(b) => [3,2] 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: Understanding references helps avoid unexpected bugs, especially when working with:  • Lists  • Dictionaries  • Objects  • Nested data structures 𝗖𝗼𝗺𝗺𝗼𝗻 𝗠𝗶𝘀𝘁𝗮𝗸𝗲: a = [[0, 0, 0]] * 2 This doesn't create two separate list but creates two references to the same list. so when you do a[0][0] = 3 you may expect the output be a = [[3,0,0],[0,0,0]] But the actual output will be [[3,0,0],[3,0,0]] #Python #ProgrammingConcepts #SoftwareEngineering #CodingTips #LearnPython #DeveloperJourney #TechLearning

Stop using + to join strings in Python! 🐍 When you are first learning Python, it is tempting to use the + operator to build strings. It looks like this: name = "Gemini" status = "coding" print("Hello, " + name + " is currently " + status + ".") The Problem? In Python, strings are immutable. Every time you use +, Python has to create a brand-new string in memory. If you are doing this inside a big loop, your code will slow down significantly. The Pro Way: f-strings (Fast & Clean) Since Python 3.6, f-strings are the gold standard. They are faster, more readable, and handle data types automatically. The 'Pro' way: print(f"Hello, {name} is currently {status}.") Why use f-strings? Speed: They are evaluated at runtime rather than constant concatenation. Readability: No more messy quotes and plus signs. Power: You can even run simple math or functions inside the curly braces: print(f"Next year is {2026 + 1}") Small changes in your syntax lead to big gains in performance. Are you still using + or have you made the switch to f-strings? Let’s talk Python tips in the comments! 👇 #Python #CodingTips #DataEngineering #SoftwareDevelopment #CleanCode #PythonProgramming

Python : 03 🎯String operation: formatting string Here we'll be introduced how we can combine strings from the variable using formatting string. Let's take a look- variable1 = a variable2 = b lets call a variable called 'combined string' combined_string = f"{a} {b}" [💡# Here "f" stands for 'formatting'] print(combined_string) Result: a b [ 💡 Note: In Python (and most programming languages), quotes are the "boundary" that tells the computer: "Do not process this; just treat it as plain text. "When you omit the quotes, Python looks for a variable with that name. It goes to the memory location where combined_string is stored and grabs the value.] So, that is called a formatted string! ✅ This is the modern and most efficient way to format strings in Python. It evaluates the expressions inside the curly braces and converts them to text. Make sure you follow this account for more! #python #CodingCommunity #PythonDeveloper #coding #TechCommunity #Developers #pythonprogramming

I think dictionaries might be the first Python topic that actually feels like organizing real life. 🐍 Day 08 of my #30DaysOfPython journey was all about dictionaries, and this one felt especially useful because it is basically how Python stores meaningful information. A dictionary is an unordered, mutable key-value data type. You use a key to reach a value — simple, but powerful. Today I explored: 1. Creating dictionaries with dict() built-in function and {} 2. Storing different kinds of values like strings, numbers, lists, tuples, sets, and even another dictionary 3. Checking length with len() 4. Accessing values using key name in [] or get() method 5. Adding and modifying key-value pairs 6. Checking whether a key exists using in operator 7. Removing items with pop(key), popitem() (removes the last item), and del 8. Converting dictionary items with items() which returns a dict_item object that contains key-value pairs as tuples 9. Clearing a dictionary with clear() 10. Copying with copy() and avoids mutation 11. Getting all keys with keys() and values with values(). These will return views - dict_keys() and dict_values() What stood out to me today was how dictionaries make data feel searchable instead of just stored. That key-value structure makes them one of the most practical tools in Python when working with real information. One more day, one more topic, one more step toward thinking in Python instead of just reading Python. When did dictionaries finally stop feeling confusing for you — or are they still one of those topics that need a second look? Github Link - https://lnkd.in/ewzDyNyw #Python #LearnPython #CodingJourney #30DaysOfPython #Programming #DeveloperJourney

🚀 Python Pro-Tip: Stop using + to join strings. 🛑 If you’re building long strings or SQL queries with +, you’re hurting performance and readability. 📉 The Shortcut: f-Strings (Interpolation) ⚡ It’s faster, cleaner, and allows you to run code right inside the string. ❌ The Messy Way: url = "https://" + domain + "/" + path + "?id=" + str(user_id) ✅ The Clean Way: url = f"https://{domain}/{path}?id={user_id}" Why?? * Readability: It looks like the final result. * Performance: Python optimizes f-strings at runtime better than concatenation. * Power: You can even do math: f"Total: {price * 1.15:.2f}" Are you still using .format() or are you 100% on the f-string train? 👇 #Python #CleanCode #ProgrammingTips #SoftwareEngineering #BackendDev

Python: sort() vs sorted() Have you ever had to pause for a second and think: “Do I need sort() or sorted() here?” 😅 This is the common Python confusions. Let’s clear it up. 🔹 list.sort() ◾ A method (belongs to list objects) ◾ Works only on lists ◾ Sorts the list in-place ◾ Changes the original list ◾ Returns None Example: numbers = [3, 1, 4, 2] numbers.sort() print(numbers) # [1, 2, 3, 4] 🔹 sorted() ◾ A function (built-in Python function) ◾ Returns a new sorted list ◾ Does NOT change the original ◾ Works on any iterable Example: numbers = [3, 1, 4, 2] new_numbers = sorted(numbers) print(new_numbers) # [1, 2, 3, 4] print(numbers) # [3, 1, 4, 2] The key difference: sort() → changes your original data sorted() → keeps your original data safe 💡 Quick way to remember: 👉 If you want to keep the original, use sorted() 👉 If you want to modify the list directly, use sort() #Python #Programming #LearnPython #DataScience #LearningJourney #WomenInTech

🧠 Python Concept: zip() — Iterate Multiple Lists Together Stop using messy index loops 😵💫 ❌ Traditional Way names = ["Alice", "Bob", "Charlie"] scores = [85, 90, 95] for i in range(len(names)): print(names[i], scores[i]) ✅ Pythonic Way names = ["Alice", "Bob", "Charlie"] scores = [85, 90, 95] for name, score in zip(names, scores): print(name, score) 🧒 Simple Explanation Think of zip() like a zipper 🤐 ➡️ It joins multiple lists together ➡️ Pairs items one by one Example: ("Alice", 85), ("Bob", 90), ("Charlie", 95) 💡 Why This Matters ✔ Cleaner and readable code ✔ No index errors ✔ Works with multiple lists ✔ Very common in real-world data handling ⚡ Bonus Tip Unzip values: pairs = [("Alice", 85), ("Bob", 90)] names, scores = zip(*pairs) print(names) print(scores) 🐍 Python makes parallel iteration simple 🐍 Use zip() to write smarter loops #Python #PythonTips #CleanCode #LearnPython #Programming #DeveloperLife #100DaysOfCode

🔒 Name Mangling in Python — Why Private Attributes Aren't Really "Private"! Just uncovered an interesting Python quirk—how "private" attributes can still be accessed (if you know the trick)! 🤔 🔍 What's Actually Happening? ✅ "Name Mangling" – Python renames '__balance' to '_BankAccount__balance' internally. ✅ "Private" is a convention—not true security, just a warning. ✅ "The Trap"—'b1.__balance = 9999999' creates a "new" public attribute. ✅ "Real "Balance"—Still protected inside '_BankAccount__balance' 💡 Key Insight: | "What You Wrote" | "What Python Stores" | |--------------------|------------------------| | 'self.__balance' | '_BankAccount__balance' | | 'b1.__balance' | Creates NEW attribute '__balance' | 📌 How to Actually Access Private Attribute (If You Must): ***python*** # Not recommended, but possible! print(b1._BankAccount__balance) # Output: 12000 💡 Best Practices: ✅ Use "single underscore" ('_balance') for "protected" (convention). ✅ Use "double underscore" ('__balance') for name mangling (prevents accidental access). ✅ "Respect privacy"—don't access mangled attributes directly. ✅ Use "getter/setter methods" for controlled access 📌 Real-World Lesson: Python trusts developers to be responsible. Private attributes are a "convention," not a security feature. The language says, "Here's how to protect it, but if you really want to break it, you can!" #Python #OOP #Encapsulation #NameMangling #Coding #Programming #LearnPython #Developer #Tech #PrivateAttributes #PythonTips #CodingLife #SoftwareDevelopment #PythonInternals #Day57

🧠 Python Concept: f-strings (Formatted Strings) Stop using messy string formatting 😵💫 ❌ Traditional Way name = "Alice" age = 25 print("My name is " + name + " and I am " + str(age) + " years old") ❌ Old Formatting Way print("My name is {} and I am {} years old".format(name, age)) ✅ Pythonic Way (f-string) name = "Alice" age = 25 print(f"My name is {name} and I am {age} years old") 🧒 Simple Explanation Think of f-strings like a template 🧾 ➡️ Write normal text ➡️ Insert variables directly {} ➡️ Python fills it automatically 💡 Why This Matters ✔ Super readable ✔ Cleaner than + and .format() ✔ Faster performance ✔ Widely used in real-world apps ⚡ Bonus Example price = 99.456 print(f"Price: {price:.2f}") 👉 Output: Price: 99.46 🐍 Write strings like a pro 🐍 Keep your code clean & readable #Python #PythonTips #CleanCode #LearnPython #Programming #DeveloperLife #100DaysOfCode