Anuj Saini’s Post

I see a lot of tutorials teaching how to perform a background task, but they rarely mention what happens when the network blips or the database rolls back. Having learned these lessons the hard way over the years, I’ve mapped out the 6 stages of evolution for Celery/RabbitMQ setups: - Best Effort (Fire and forget) - Transactional Boundary (Atomic saves) - Publishing on Commit (delay_on_commit) - Publisher Confirms (Handling broker drops) - The Outbox Pattern (Persisting intent) - Clusters & Quorum Queues (High availability) I deep-dive into the "how" behind each of these in my latest article. #SystemDesign #SoftwareArchitecture #Django #BackendDevelopment #Python

Built a Python-based Directory Sync Tool to compare and synchronize files between two directories with reliability and control. Instead of relying only on file names or timestamps, the tool uses a combination of metadata and SHA-256 hashing to accurately detect new, modified, and missing files. Key highlights: • Recursive directory scanning with structured metadata (name, extensions, size, hash) • Efficient change detection using size-first filtering followed by hash comparison • Memory-efficient hashing using chunk-based file reading (handles large files) • Synchronization support with metadata preservation using shutil.copy2 • Safe cleanup by optionally removing extra files from the destination While building this, I focused on moving beyond a basic script and treating it like a real tool, structuring the code into clear components, improving output readability, and adding validation and error handling to make it more reliable in real use. GitHub:https://lnkd.in/gt-Ec3rF #Python #CLI #GitHubProjects #SoftwareDevelopment #LearningByBuilding #SystemsThinking

Starting my next course at SANS: SEC573: AI-Powered Security Automation - Building Tools with Python, LLMs, and MCP. This one has me excited! Python has always been foundational in security, but this course pushes it further by combining Python fundamentals with modern AI agent integration. AI and Python go hand in hand and having the ability to build your own tools, rather than relying on off-the-shelf solutions, is what separates good security practitioners from great ones. If anyone has already taken the course and can offer some study advice, note taking advice, or indexing advice I’d really appreciate it!

I just wrapped up a Student Result Management System built with Python, and I’m excited about the progress. What started as a simple logic exercise quickly turned into a functional tool. Key features I implemented: Data Structures: Used Dictionaries to efficiently map student names to their scores and grades. Control Flow: Applied loops and conditionals to automate grading and result processing. File Handling (The big win!): Integrated .txt file operations so that student data is saved and retrieved even after the program closes. Moving from volatile memory to File Handling felt like a major milestone—it’s the difference between a temporary script and a persistent application. 📂 I’m currently focusing on strengthening my backend fundamentals and building projects that solve small, real-world problems. Next up: Exploring how to structure this more efficiently using Functions or maybe even a CSV format for better data portability! Any tips from the dev community on optimizing file storage in Python? Let me know below! 👇 #Python #CodingJourney #BackendDevelopment #Programming #StudentProject #LearningToCode

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

A 40ms API became a 4ms API. Here's the only thing that changed. We were making 3 separate DB queries to assemble a response. Each was fast in isolation. Together, they were sequential — each waited for the previous. The fix: run them concurrently. In Python (asyncio), this went from: result_a = await get_a() result_b = await get_b() result_c = await get_c() To: result_a, result_b, result_c = await asyncio.gather(get_a(), get_b(), get_c()) That's it. No caching, no infra change, no complex refactor. The mental model that helps: always ask "are these operations actually dependent on each other?" before assuming they need to run in sequence. Most API latency problems aren't hard — they're just unexamined. #BackendDevelopment #PythonAsyncio #APIOptimization #SoftwareEngineering

Background jobs look simple until you're actually running them in production. I recently wired up Python + Celery + Redis for a project. The core setup was pretty quick and easy and is well documented. The harder decisions are about task design and finding the right granularity so tasks are meaningful without becoming a bottleneck or a maintenance headache. Some of the questions that cropped up: - What actually happens when a task fails and nobody notices? - How do I know what's queued vs running vs stuck? - At what point does adding retry logic just paper over a worse problem? Still working through some of it. Anyone who's dealt with Celery at scale, I'm curious how you handled task monitoring specifically.

pyload, Insufficient Session Expiration, CVE-2023-0227 (Medium) Technical Analysis: How CVE-2023-0227 Works CVE-2023-0227 is an Insufficient Session Expiration vulnerability affecting pyload, an open-source download manager written in Python. The root cause is the application's failure to properly invalidate user sessions when permissions are changed or a user logs out. The Flaw in Session Management 1. Session Persistence After Logout: When a user logs out, their session token remains valid in the backend session store (e.g., filesystem cache)....

pyload, Insufficient Session Expiration, CVE-2023-0227 (Medium) Technical Analysis: How CVE-2023-0227 Works CVE-2023-0227 is an Insufficient Session Expiration vulnerability affecting pyload, an open-source download manager written in Python. The root cause is the application's failure to properly invalidate user sessions when permissions are changed or a user logs out. The Flaw in Session Management 1. Session Persistence After Logout: When a user logs out, their session token remains valid in the backend session store (e.g., filesystem cache)....