Creating a Simple Login System with Conditions in Python

Claude Opus 4.7 just dropped and I have to say I am disappointed. Poor Behaviors from today: - Asking questions in plan mode then completely ignoring the answers when generating the code. "I'm sorry I was exercising an abundance of caution when ignoring your answer" (note I asked it not to build an image on every single code commit) - Creating wildly elaborate and hacky solutions to simple problems. claude wanted to insert a bash script into cicd to manually traverse a node repo and hack in version.ts files to fix an issue where a module depending on another that hadn't been built yet. "You are right. That is an overly complicated solution and not appropriate for production builds" - Choosing to write elaborate python scripts and asking permission to execute for very simple plugin tasks like doing a code diff from a pr. "You are right, I should just use the gh plugin"

🚀✨ 𝗗𝗮𝘆 𝟳 𝗼𝗳 𝗠𝘆 𝗣𝘆𝘁𝗵𝗼𝗻 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗝𝗼𝘂𝗿𝗻𝗲𝘆🐍💻 Today I explored File Handling in Python and understood how programs can actually store and manage data permanently💾🔥 🔹 📂 𝗪𝗵𝗮𝘁 𝗜 𝗟𝗲𝗮𝗿𝗻𝗲𝗱: 📁 Types of Files: ✔️ Text Files → (.txt, .csv, .log) ✔️ Binary Files → (.jpg, .png, .mp4, .pdf, .exe) 📖 File Handling Methods: 👉 open()→ to open files 👉 read(), readline(), readlines()→ to read data 👉 write()→ to store data 👉 "a" mode → to append data 🔐 Best Practice: ✔️ Used with open() for automatic file closing 🔧 File Management (New Learning): 👉 Copy files → shutil.copy() 👉 Rename files → os.rename() 👉 Delete files → os.remove() 🔹 ✨ 𝗞𝗲𝘆 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀: ✔️ File handling makes programs practical ✔️ Data can be stored and reused anytime ✔️ Learned how to manage files using Python 🔥 𝗗𝗮𝘆 𝟳 — 𝗙𝗿𝗼𝗺 𝗖𝗼𝗱𝗲 𝘁𝗼 𝗥𝗲𝗮𝗹-𝗪𝗼𝗿𝗹𝗱 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀! Thank you Saumya Singh for making learning so easy #Python #LearningJourney #Day7 #FileHandling #Coding #Programming #🚀

I’m excited to share a mini-automation project I recently completed: An Automated Certificate Generator. 🎓 Manually creating certificates for a large number of participants is tedious and prone to errors. To solve this, I built a Python script that handles the entire process efficiently. How it works: ✅ Data Driven: It reads participant details (Names & Departments) directly from a CSV file/Worksheet using Pandas. ✅ Dynamic Overlay: Uses the Pillow (PIL) library to precisely place text onto a high-quality certificate template. ✅ Bulk Processing: Can generate thousand of personalized certificates in a single run. Tech Stack: 🐍 Python | 🐼 Pandas | 🖼️ Pillow (PIL) Check out the code on GitHub: https://lnkd.in/dx__bkxy #Python #Automation #Programming #FullStackDeveloper #Efficiency #OpenSource #CertificateGenerator

Sharing my latest project : Automatic Certificate Automation System I developed a system that automates the entire certificate generation process — from data collection to PDF creation and email delivery. 🔹 Key Features: • Automated certificate generation (Completion & Experience) • Dynamic data processing from sheets • Email integration for instant delivery • Logging and status tracking system • User-friendly dashboard for management This project helped me strengthen my skills in Python, Flask, automation, and backend development. 🔗 GitHub: https://lnkd.in/ggW_mMxy #Python #Flask #Automation #Data Science#Project #BackendDevelopment #LearningJourney

Empty files waste storage. Cleaning them manually wastes time. I built a tool to solve that. ZeroByteCleaner — Automated File System Cleanup Tool A Python automation tool that runs in the background and keeps your directory clean — without any manual effort. How it works: → Point it to any folder → It recursively scans every file and subfolder → Detects all empty (0-byte) files → Deletes them automatically → Generates a timestamped log report → Repeats on schedule — every minute, hour, or day The real challenge was making it reliable: → What if the path doesn't exist? → What if it's a file, not a folder? → What if a file is locked by the system? Handling edge cases is what separates a working script from a production-ready tool. 🔧 Tech Used Language : Python 3.13 Libraries : os · sys · time · schedule Concepts : File Automation · Scheduling · Log Generation 📂 GitHub → https://lnkd.in/gK-rhJMw #Python #Automation #OpenSource #GitHub #ProblemSolving #PythonDeveloper #SoftwareDevelopment #PythonProjects

Bash(python3 /tmp/claude/summarize-session2.py 2>&1)   ⎿ Total: 0 human messages, 339 assistant messages Only assistant messages. The user messages might have a different format. Let me check the structure: [...] It’s “type”: “user” not “human”. 🤔 ...

Day 30 of #100DaysOfPython 𝐔𝐩𝐠𝐫𝐚𝐝𝐞𝐝 𝐭𝐡𝐞 𝐏𝐚𝐬𝐬𝐰𝐨𝐫𝐝 𝐌𝐚𝐧𝐚𝐠𝐞𝐫 𝐀𝐩𝐩 𝐭𝐨𝐝𝐚𝐲. I moved from saving data in a text file to using JSON, which makes the data more structured and easier to manage. I also added a search feature to retrieve saved credentials. 𝐖𝐡𝐚𝐭 𝐈 𝐢𝐦𝐩𝐫𝐨𝐯𝐞𝐝: 𝑺𝒘𝒊𝒕𝒄𝒉𝒆𝒅 𝒕𝒐 𝑱𝑺𝑶𝑵 𝒇𝒐𝒓 𝒔𝒕𝒓𝒖𝒄𝒕𝒖𝒓𝒆𝒅 𝒅𝒂𝒕𝒂 𝒔𝒕𝒐𝒓𝒂𝒈𝒆 𝑰𝒎𝒑𝒍𝒆𝒎𝒆𝒏𝒕𝒆𝒅 𝒔𝒆𝒂𝒓𝒄𝒉 𝒇𝒖𝒏𝒄𝒕𝒊𝒐𝒏𝒂𝒍𝒊𝒕𝒚 𝒇𝒐𝒓 𝒔𝒂𝒗𝒆𝒅 𝒑𝒂𝒔𝒔𝒘𝒐𝒓𝒅𝒔 𝑯𝒂𝒏𝒅𝒍𝒆𝒅 𝒆𝒓𝒓𝒐𝒓𝒔 𝒖𝒔𝒊𝒏𝒈 𝒕𝒓𝒚/𝒆𝒙𝒄𝒆𝒑𝒕 (𝒎𝒊𝒔𝒔𝒊𝒏𝒈 𝒇𝒊𝒍𝒆, 𝒎𝒊𝒔𝒔𝒊𝒏𝒈 𝒅𝒂𝒕𝒂, 𝒆𝒎𝒑𝒕𝒚 𝑱𝑺𝑶𝑵) 𝑰𝒎𝒑𝒓𝒐𝒗𝒆𝒅 𝒐𝒗𝒆𝒓𝒂𝒍𝒍 𝒖𝒔𝒆𝒓 𝒆𝒙𝒑𝒆𝒓𝒊𝒆𝒏𝒄𝒆 𝒊𝒏 𝒕𝒉𝒆 𝑮𝑼𝑰 This version feels much closer to a real application. Managing data properly and handling edge cases made a big difference. Also a good reminder that writing code is one thing, but making it robust and user-friendly is another level. #100DaysOfCode #100DaysOfPython #Python #Tkinter #PasswordManager #JSON #ErrorHandling #PythonProjects #LearningToCode #CodingJourney #BuildInPublic

OAuth, API keys, pagination — the real-world API skills nobody teaches in tutorials. This free notebook covers what matters: → Authentication types: API keys, Bearer tokens, OAuth 2.0 → Making authenticated requests with proper headers → Rate limiting — how to not get banned → Error handling — retries, backoff, status codes → Paginated endpoints — fetching ALL the data, not just page 1 → Loading API responses directly into Pandas DataFrames Most API tutorials stop at requests.get(url). Real APIs need auth, pagination, and error handling. This notebook teaches the other 80%. Free: https://lnkd.in/gHapNtJY Day 3/7. #Python #API #DataEngineering #OAuth #DataScience #REST #WebDevelopment #FreeResources

Day 15 – Unlocking Linked Lists 🔗 I’ve officially moved beyond static arrays and into the world of Linked Lists! Today’s challenge was all about dynamic memory allocation and pointer management. Unlike arrays, where data is stored in contiguous blocks, Linked Lists allow for flexible data growth by linking "Nodes" together across memory. What I implemented: Node Creation: Building a custom class to store both data and a reference to the next element. List Traversal: Writing logic to navigate through the "chain" from the head to the tail. Tail Insertion: Efficiently appending new data to the end of a dynamic structure. Understanding these fundamentals is key to grasping how more complex structures like Stacks, Queues, and Trees actually work under the hood. One step closer to the 4th star! ⭐⭐⭐+⭐ #DataStructures #Python #LinkedLists #CodingJourney #ComputerScience #SoftwareEngineering #DailyCoding

Built an anomaly detection engine, in Python. No Fail2Ban. No rate-limiting libraries. Everything custom: Sliding window deques tracking per-IP and global request rates over 60 seconds Rolling 30-minute baseline with per-hour slots that adapts to time-of-day traffic Z-score + multiplier detection, flags anomalies statistically, not with hardcoded limits Automatic iptables blocking with backoff unban schedule (10min → 30min → 2hr → permanent) Slack alerts for every ban, unban, and global spike Live metrics dashboard refreshing every 3 seconds Full write-up on how it works, sliding windows, z-scores, iptables : https://lnkd.in/eWeKbqWg GitHub: https://lnkd.in/eq8C9FBJ