Pablo Bartolome Molina’s Post

Just started your Python journey? These 6 beginner mistakes could save you hours of debugging frustration! Here's what every beginner needs to know: 👩🏻💻👨🏻💻 1. Case Sensitivity Matters - Functions like if, else, return, import must be lowercase. Python won't recognize IF or Return. 2. File Location Logic - Keep input files in your project folder OR specify the complete file path. Missing files = instant errors. 3. CSV Data Conversion - All CSV data imports as strings by default. Use float() or int() to convert numerical fields before calculations. 4. Column Name Precision - Match your variable names exactly to your input file columns. One typo = broken code. 5. IDE Assistance (But Stay Alert!) - Tools like PyCharm suggest next steps, but watch your bracket placement: {}, [], () matter enormously. 6. Indentation = Everything - Python uses indentation to determine code structure. Wrong spacing = wrong results. The beauty of Python lies in its logical flow, but these fundamentals determine whether you're building solutions or debugging disasters. What's the most frustrating Python beginner mistake you've encountered? #PythonProgramming #CodingTips #MediaPilot

A New Era for Multithreading in Python For years, Python developers hit a hard limit: the Global Interpreter Lock (GIL) prevented true multithreading for CPU-bound tasks. Meanwhile, Go’s goroutines and scheduler delivered effortless concurrency and parallelism — one of the reasons Go became a favorite for high-performance systems. But that gap is starting to close. With Python 3.14, the long-awaited free-threaded (no-GIL) build is officially supported. Here’s what changes: 🔹 True parallelism in threads No-GIL means multiple Python threads can now execute bytecode simultaneously on multiple cores — something previously only Go could do efficiently. 🔹 New concurrency primitives Python adds concurrent.interpreters, enabling multiple isolated interpreters inside one process (similar to goroutines’ lightweight nature, though not as granular). 🔹 Improved thread safety & adaptive optimizations The standard library has been hardened for thread safety, and the adaptive interpreter keeps single-thread performance close to pre-3.14 levels. Takeaway: Python 3.14 doesn’t replace Go for concurrent systems yet — but it finally gives Python developers a native path to real multithreading without multiprocessing hacks. The GIL era is ending.🚀 #Python #GoLang #Concurrency #Multithreading #NoGIL #Python314 #Programming

Today, for our Dev-Talk Tuesday we are going to go over some features within Python! Yesterday we talked a little bit about what we knew about Python, today, we are going to dive into a little of what makes Python. 1. Simple and Readable Syntax ▪️ Python's syntax is not natural language, but it is very close, which makes it easy to read and write. Example: # Example: Readable syntax user_age = 25 if user_age >= 18:   print("You are an adult.") 2. Extensive Standard Library ▪️ Python comes with a deep set of built-in modules for tasks like file handling, math, networking and much more. Example: import math # Using the math module print(math.sqrt(16)) # Output: 4.0 3. Cross-Platform and Portable ▪️ Python code runs on Windows, macOS, Linux, and more without modification. Example: import os file_path = os.path.join("folder", "file.txt") print(file_path) # Works on all OS 4. Vast Ecosystem of Libraries ▪️ Python has powerful libraries for data science, web development, AI/ML, and more. Example: # Example: Using the requests library import requests response = requests.get("https://api.github.com") print(response.status_code) # Example output: 200 These are just a few examples to show of Python's versatility and why it's a choice amongst developers. What is your favorite Python feature or library? Let us know in the comments! #StructDevelopment #SoftwareDevelopment #Python #DevTools #Coding #Tech

🚀 Python 3.14 is coming — and it’s not just another update! 🐍 Python continues to evolve, and version 3.14 brings improvements that make it faster, safer, and even more developer-friendly. Among the most exciting highlights: ⚡️ Performance upgrades — noticeable speed boost across the interpreter. 🧠 Better error messages — even clearer diagnostics for complex tracebacks. 🔒 Security enhancements — new runtime protections and stricter package validation. 🧩 Improved typing system — cleaner generics and more consistent type hints. As someone who works daily with Python and Django, I’m genuinely excited to see how these refinements will impact real-world projects — from backend APIs to data workflows. What new feature are you most looking forward to in Python 3.14? 👇 #Python #Programming #Developers #TechNews

🚀 Python 3.14 is here — and it’s packed with great upgrades! Released in November 2025, this version brings some of the most exciting improvements 👇 • 🧠 Deferred annotations by default – no more from __future__ imports for type hints. • 🧩 t-strings (t"") – a new kind of string literal for safer and more flexible templating. • 🖥️ Modern REPL – now with syntax highlighting, smarter autocomplete, and clearer error messages. • 🧵 Multiple interpreters – via the new concurrent.interpreters module for true process isolation. • ⚙️ Optional “no-GIL” build – experimental version that removes the Global Interpreter Lock for real multi-core parallelism. • 🗜️ Zstandard compression, UUID v6–8, optional brackets in except, built-in HMAC via HACL*, colored module output, and an experimental JIT compiler for performance gains. This release shows how far Python has come — from typing improvements to real concurrency and even JIT compilation. Exciting times ahead for developers and teams building modern apps in Python! 🐍✨ #Python #Python314 #Programming #SoftwareEngineering #Developers #DevOps #OpenSource #Microservices #TechUpdate

🚀 Python 3.14 Just Broke Its Biggest Limitation! For 30+ years, Python had a secret bottleneck — the GIL (Global Interpreter Lock) — the reason why your “multi-threaded” Python code still ran on just one CPU core 😅 That changes today with Python 3.14 💥 Python now has a free-threaded build (aka no-GIL Python) — meaning: ✅ True parallel execution across multiple cores ✅ Massive performance boost for CPU-heavy workloads ✅ Same Python you love — just faster Here’s the crazy part 👇 ```python import threading def work():     x = 0     for _ in range(10_000_000):         x += 1 threads = [threading.Thread(target=work) for _ in range(4)] for t in threads: t.start() for t in threads: t.join() ``` 🐍 Old Python: all threads fight for the GIL → 1 core used ⚡ Python 3.14 (no-GIL): all 4 cores blaze in parallel! This is the biggest performance leap since Python 3 itself — and it might finally silence the “Python is slow” crowd 😎 Would you switch to the no-GIL build or wait until libraries (NumPy, Pandas, etc.) catch up? #Python #Python314 #NoGIL #Performance #Developers #Programming #OpenSource #TechNews

Why Python 3.14 is a Game-Changer for Developers If you’ve ever felt frustrated by Python’s concurrency limits, there’s great news for you. Python 3.14 introduces free-threaded builds (no more global interpreter lock = GIL) and support for parallel sub-interpreters. These changes open the door to true multicore performance for CPU-intensive Python workloads. ✅ What this means: 1. Threads can run Python byte-code truly in parallel when built with GIL disabled, unlocking major gains especially in CPU-bound scenarios.  2. Sub-interpreters: You can isolate workstreams in the same process with less overhead than full processes. 3. Everyday developer quality-of-life upgrades: Better error messages, improved REPL, deferred type annotations, and syntax enhancements. ⚠️ Limitations & things to watch: 1. The GIL is still enabled by default. You’ll need to build or use a “free-threaded” interpreter variant to reap full parallel benefits. 2. Some third-party C-extensions and libraries may not yet be compatible with GIL-free builds, which could slow adoption in production.  3. Single-threaded code might see little or no benefit — or even a small performance dip in some cases. Whether you’re working on backend services, data-processing pipelines, or computational workflows — Python 3.14 is worth keeping an eye on and planning for. As always, test carefully before upgrading mission-critical systems. #python #programming #developers #multithreading #performance #softwareengineering

Python basics - Day 14 Day 14 – Exception Handling \(try / except\) Project: Build a “Safe Calculator” that handles user input errors gracefully. 01. Learning Goal By the end of this lesson, you will be able to: Understand what exceptions \(errors\) are in Python Handle errors using try and except blocks Use else and finally for structured control flow Prevent your program from crashing unexpectedly 02. Problem Scenario When users input wrong data or when files are missing, your program crashes. Your goal today is to handle exceptions safely and ensure the app continues running smoothly. 03. Step 1 – What is an Exception? An exception occurs when something goes wrong during execution. If not handled, it will stop the program. print\(10 / 0\) # ZeroDivisionError numbers = \[1, 2, 3\] print\(numbers\[5\]\) # IndexError Examples of common errors: Division by zero Accessing an invalid index File not found 04. Step 2 – Basic try / except Structure try: # Code that may cause an error except: # Code t https://lnkd.in/gKJNQxnj

Continuing my Python practice, I created a command line Expense Tracker — a simple program that helps record and manage daily spending using only Python. This program lets users: 1. Add new expenses by entering the date, category, and amount. 2. View all expenses in a clean, readable format directly in the terminal. 3. Generate a spending summary that shows total expenses and a category wise breakdown. 4. Save all data in “Expenses.csv” for future reference. The program runs in a loop with a user friendly menu, allowing continuous entry, viewing, and reporting without restarting. This project helped me understand how Python can handle file operations, loops, and user input together to create simple, real world applications that make daily tasks easier. 👉 Check out my GitHub Project: https://lnkd.in/eiRhmdbA #Python #Learning #Programming #GitHub #Projects #FileHandling #Coding #Automation #ExpenseTracker