Maciej Gajewski’s Post

Just shipped a little Python tool to tame my Obsidian vault chaos! Like many of you, my Obsidian vault started as one big flat folder, notes (.md) and images (.png/.jpg/etc.) all mixed together. Obsidian's internal links made it work beautifully… until I wanted to compile related notes + visuals into clean folders for portfolio articles and blog posts. The headache: - Manually hunting down referenced images was time consuming So I built a quick MVP script that: 1. Takes a single note as input 2. Scans your entire vault to find all image references across every .md file 3. Identifies images referenced only in your chosen note (safe to move) 4. Creates a new folder (you name it or it defaults to the note's title) 5. Moves the note + its unique images into that folder — shared images stay untouched It's not pretty yet (procedural style, console output, no GUI), but it works reliably on my thousands-of-files vault. Next steps: refactor to classes, add CLI args / config file, maybe a simple Tkinter / Typer GUI, and support for other embeds (PDFs, etc.). Check out the commit where the MVP came together: https://lnkd.in/eX5e5A9p #Python #Obsidian #Automation #Scripting

【🐍-Python-Update】‐058‐【Render】Process-Specific Script Collection for Recording - Export - Output to Folders with Named Media https://lnkd.in/gptM7ARu Following up from last time, here's the Python version of the script that exports recorded takes into files named according to your naming rules🌟 It automatically excludes NG takes set previously, assigns numbers, and outputs files into separate folders per track. This lets you set filenames in seconds without errors📝 ◆Required Plans ・RIGDOCKS -BRONZE- ・RIGDOCKS -SILVER- ・RIGDOCKS -GOLD-

🚀 Day 45 of #100DaysOfCode ✅ Solved: Binary Gap (LeetCode 868) Today’s problem was about finding the longest distance between two consecutive 1s in the binary representation of a number. 🔎 Problem Insight: Given a positive integer n, convert it into binary and calculate the maximum distance between adjacent 1s. 💡 Key Idea: Instead of converting the number into a string, we can directly use bit manipulation: Traverse each bit using n & 1 Track the position of the previous 1 Update the maximum distance whenever a new 1 is found ⚡ Optimized Python Solution (O(log n) time | O(1) space) Python Copy code class Solution: def binaryGap(self, n: int) -> int: last = -1 max_dist = 0 position = 0 while n > 0: if n & 1: if last != -1: max_dist = max(max_dist, position - last) last = position n >>= 1 position += 1 return max_dist 🧠 What I Learned: Bitwise operations can make solutions more efficient Always think beyond string conversion for binary problems Tracking positions smartly reduces extra space usage Consistency > Motivation 🔥 One problem at a time towards mastering Data Structures & Algorithms. #LeetCode #ProblemSolving #Python #BitManipulation #DSA

# 𝑫𝒂𝒚 - 5 𝑷𝒚𝒕𝒉𝒐𝒏 𝑲𝒂 𝑫𝒂𝒊𝒍𝒚 𝑫𝒐𝒔𝒆 👇 𝐒𝐭𝐨𝐩 𝐮𝐬𝐢𝐧𝐠 𝐚𝐬𝐲𝐧𝐜𝐢𝐨.𝐠𝐚𝐭𝐡𝐞𝐫() 𝐟𝐨𝐫 𝐜𝐨𝐦𝐩𝐥𝐞𝐱 𝐭𝐚𝐬𝐤𝐬. If you are still managing multiple concurrent tasks in Python using old patterns, you might be leaving your applications vulnerable to "zombie tasks" and silent failures. 𝐄𝐧𝐭𝐞𝐫 𝐒𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐝 𝐂𝐨𝐧𝐜𝐮𝐫𝐫𝐞𝐧𝐜𝐲 𝐰𝐢𝐭𝐡 𝐚𝐬𝐲𝐧𝐜𝐢𝐨.𝐓𝐚𝐬𝐤𝐆𝐫𝐨𝐮𝐩. Introduced in Python 3.11, TaskGroup is the modern way to manage groups of tasks. Unlike asyncio.gather(), if one task in a group fails, TaskGroup ensures all other tasks in that group are cancelled automatically. 𝐖𝐡𝐲 𝐢𝐬 𝐭𝐡𝐢𝐬 𝐚 𝐠𝐚𝐦𝐞-𝐜𝐡𝐚𝐧𝐠𝐞𝐫? ✅ 𝐒𝐚𝐟𝐞𝐭𝐲: No more "leaked" tasks running in the background after an error. ✅ 𝐂𝐥𝐞𝐚𝐧 𝐄𝐱𝐜𝐞𝐩𝐭𝐢𝐨𝐧 𝐇𝐚𝐧𝐝𝐥𝐢𝐧𝐠: Uses ExceptionGroup to catch multiple errors at once. ✅ 𝐁𝐞𝐭𝐭𝐞𝐫 𝐅𝐥𝐨𝐰: The async with syntax makes it clear exactly where a group of tasks starts and ends. As we move through 2026, writing "Pythonic" code means writing robust code. Structured concurrency is no longer optional for senior devs—it's the standard. #Python #SoftwareEngineering #BackendDevelopment #AsyncIO #CleanCode #Python311 #ProgrammingTips #WebDev

🤖 Developed a Basic Rule-Based Chatbot using Python I built a simple chatbot that responds to predefined user inputs like: ✔ "Hello" ✔ "How are you?" ✔ "Bye" The chatbot provides instant automated replies using conditional logic. 🛠 Concepts Used: if-elif statements, functions, loops, input/output This project strengthened my understanding of logical thinking and user interaction in software applications. #pytgon #codealpha #chatbot #usernteraction CodeAlpha GitHub:https://lnkd.in/g4bt8gN6

🧠 Python Feature That Makes Multiple Dicts Feel Like One: collections.ChainMap 💻 No merging. 💻 No copying. Just smart lookup 👌 ❌ Common Way config = {} config.update(defaults) config.update(env) config.update(user) Messy and order-dependent 😬 ✅ Pythonic Way from collections import ChainMap config = ChainMap(user, env, defaults) Python searches left to right automatically ✨ 🧒 Simple Explanation Imagine checking for a toy 🧸 1️⃣ Check your bag 2️⃣ Check your cupboard 3️⃣ Check the store 💫 Stop as soon as you find it. 💫 That’s ChainMap. 💡 Why This Is Powerful ✔ No data copying ✔ Clean configuration handling ✔ Used in settings & overrides ✔ Interview-friendly concept ⚡ Real Use Case value = config["timeout"] # user → env → defaults 💻 Python doesn’t force you to merge data. 💻 It lets you layer it intelligently 💻 ChainMap is one of those tools you appreciate later. #Python #PythonTips #PythonTricks #AdvancedPython #CleanCode #LearnPython #Programming #DeveloperLife #DailyCoding #100DaysOfCode

Exploring Desktop Automation using PyAutoGUI in Python I recently built a simple automation script using pyautogui that simulates real keyboard typing on my system. The program waits for a few seconds so I can switch to Notepad, and then it automatically types my introduction and presses Enter — just like a human would. It’s a small script, but it clearly shows how powerful automation can be. Instead of manually typing repetitive text, Python can handle it in seconds. Through this hands-on experiment, I learned: • How pyautogui controls keyboard actions • How execution delays help manage task timing • How automation scripts mimic real user behavior • The foundation behind bots and GUI testing tools This concept can be extended to automate form filling, repetitive data entry, testing applications, and other productivity tasks. Sometimes the simplest projects teach the most practical lessons. Excited to keep exploring automation and real-world scripting with Python #Python #PyAutoGUI #Automation #LearningByDoing

Struggling with data failures in your Python scripts? 🐍💨 Real-world data is messy, and debugging can feel like finding a needle in a haystack. But don't panic! Mastering these 7 Python debugging tips will transform your workflow and help you conquer those stubborn data issues. 💪 Here's how to level up your debugging game: • Strategic Print Statements: Quick variable inspection. • Master the Debugger PDB, VS Code: Step-through code, examine states. • Robust Logging for Traceability: Capture events and variable values. • Pre-validate Data Inputs: Check schemas, types, and constraints. • Isolate & Reproduce Errors: Pinpoint exact failure points. • Implement Unit & Integration Tests: Proactive bug detection. • Utilize Version Control Git: Track changes, simplify rollbacks. Which tip saves you the most often? Share your insights below! 👇 #Python #Debugging #DataEngineering #DataScience #PythonTips #SoftwareDevelopment

Another subtle Python quirk that silently breaks production… The logs showed empty lists where data should be. No errors. No crashes. Just… silence from a core function. After tracing through permissions, database calls, and network timeouts, I found this: (See screenshot for code snippet) The villain? Iterator exhaustion. zip returns an iterator. The first list comprehension consumed it entirely. The second got nothing. This pattern is everywhere: map, filter, csv.reader, generator expressions — they’re all one-time use. Key Insight for System Design: Treat iterators as streams, not containers. A stream flows once. If you need a container, materialize it: data = list(iterator) It’s a simple rule that prevents insidious bugs. What looks like harmless variable reuse can become a source of Heisenbugs — bugs that vanish when you add debug prints (which also consume the iterator!). Python backend issues that don’t throw errors, but break systems quietly. What’s your most memorable “silent failure” bug? #python #debugging #bestpractices #backend #engineering

🚀 Python Journey — Day 7 | Number & String Logic Today I focused on solving problems involving numbers and strings using loops and conditions. Problems I solved independently: • Reverse a number • Palindrome number check • Count vowels in a string • Count consonants in a string • Count vowels and consonants • Perfect number check • Neon number check • Strong number check • Harshad number check • Fibonacci series I implemented most problems using loops and practiced handling both numbers and strings effectively Today's learnings: ✅ Working with digits using % and // ✅ Understanding number-based logic (perfect, neon, harshad) ✅ String analysis using loops ✅ Building sequences like Fibonacci ✅ Improving logical thinking and accuracy Today felt like a solid step in understanding deeper logic in programming Thanks to Rudra Sravan kumar sir for the guidance and continuous support.. Learning daily and getting more confident. 📌 Consistency > Motivation On to Day 8 💻 #PythonJourney #Day7 #PythonFullStack #10kcoders #LearningInPublic #Loops #ProblemSolving #CodeEveryDay #FutureDeveloper #KeepLearning #PythonDeveloper