Tariq Muhammad
Python Dev building custom automation & Telegram bots
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đ Just deployed: The Archival Data Observatory v2.0 đȘ
I took a flat, complex historical text document full of geographical measurements, cosmological distances, and physics claimsâand digitized the entire thing into an interactive web app.
No static slide decks here. I built a live, standalone frontend utility that handles data analytics, real-time math, and visual simulations simultaneously.
Here is whatâs under the hood:
 The Heliospheric Engine: A canvas-driven 2D solar system model built on historical orbital paths. Click any planet, and it opens a dynamic data modal calculating localized light-speed and speed-of-thought travel delays.
 The Logic Chamber: A real-time mathematical sandbox with custom range sliders. It actively re-calculates complex kinematic word problems on the fly as you shift timelines.
 Terrestrial Insights: A 2D hydrological profile visualizer comparing historical text data right against modern deep-water sonar readings.
 UI/UX: A responsive, framework-free single-file architecture built using vanilla JavaScript, Chart.js, and Tailwind CSS, all wrapped in a high-fidelity "space glass" dark mode theme with an active background starfield particle engine running at 60 FPS.
It was an awesome challenge taking historical documentation and rendering it through the lens of modern empirical science and frontend engineering.
Check out the dashboard below and see how the math stacks up! đ
#WebDevelopment #JavaScript #DataVisualization #HTML5Canvas #Coding #TailwindCSS
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I engineered and deployed a 24/7 automated signaling system that streams real-time market insights for global oil benchmarks (WTI and Brent Crude) directly to a Telegram channel. The application integrates financial data feeds and parses incoming metrics through a custom analysis engine to identify market shifts.
To ensure maximum availability, I wrapped the automation logic inside a lightweight Flask backend web app and wired it to an external cron service. This infrastructure successfully bypasses standard server sleep cycles, keeping the bot actively listening and processing data around the clock. The entire pipeline is built defensively with error-handling loops to catch connection timeouts or malformed API data, isolating faults in the console shell without causing a system crash.
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I engineered backend scripts focused on data retrieval from financial market APIs to track live asset analytics and metrics. Using specific financial libraries, the core engine pulled, sorted, and calculated historical data trends and real-time shifts. To ensure the application survived volatile market hours when data traffic spikes, I implemented thorough error-handling loops that isolated connection timeouts. This architecture maintained clean data flow without dropping connections or interrupting background tasks.
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Web Automation & Scraping Developer
I designed and deployed custom web scraping scripts in Python to extract unstructured data from dynamic web pages and clean it for business use. The pipelines utilized defensive programming to handle common scraping hurdles, such as unexpected structural changes in target HTML or missing data keys. By incorporating advanced data-parsing logic, the system cleanly structured raw text and tables into reliable JSON and CSV outputs. I managed all script configurations, environment variables, and console debugging to ensure smooth execution.
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I engineered using replit and AI-Integration a custom, 24/7 background automation bot in Python to track global oil benchmarks (WTI/Brent Crude) and stream real-time market signals directly to Telegram. To prevent server dormancy issues common with free-tier hosting, I wrapped the script in a lightweight Flask web backend and linked it to an external cron service to maintain permanent uptime. The system uses strict fault-tolerant error blocks and defensive parsing loops, ensuring that corrupted third-party data feeds are safely isolated in the system console rather than causing a fatal application crash.
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