Python dev: NSE volume scanner, BUY CE/PE alerts, paper trading

@Jennycreation

Hello Sir, I have already worked on similar types of website and software development projects and I am confident that I can successfully handle your project. I am a full-time freelancer with **17+ years of experience** in web development, software development, automation, and API integrations. My expertise includes: * ASP.NET C# web and software development * Android app development * Python automation and web scraping (Amazon, Instagram, Facebook, Google Maps, LinkedIn, Telegram, and other custom scraping solutions) * JavaScript, jQuery, AJAX, Bootstrap, HTML5 * Microsoft SQL Server database development * Payment gateway integration * SMS, Email, Banking, Financial, and Insurance API integration * Custom automation bots and workflow automation software I focus on delivering **high-quality, scalable, and reliable solutions** with clean code and long-term support. Please contact me in private chat so we can discuss your requirements in detail. I can also show you a **demo of similar projects** I have completed. Looking forward to working with you. Thanks & Regards

@huzaifa306

I have extensive experience with Python automation, APIs, WebSocket data, and real time data processing, with three plus years of hands on experience. I can upgrade your NSE scanner with continuous scanning, configurable alerts, paper trading, Telegram notifications, and performance tracking. I can also handle the AWS deployment and provide a simple runbook. I am available to start immediately.

@techmadigital

Hi, Your NSE scanner needs a continuous engine, not a spreadsheet. I build real-time scanners with Dhan WebSocket data, one-minute refresh cycles, buy and sell volume classification, and configurable BUY CE and BUY PE alert rules. I have delivered MT5 and Python market research platforms with SQLite candle and signal storage, multi-timeframe indicators, risk filters, paper trading with stop-loss, target and charges, plus Streamlit dashboards, Telegram alerts and daily reports. I would run this on a small Mumbai EC2 with a clear runbook. I can show similar scanner and dashboard work on chat. Thanks, Nikhil

@mobasherreza10

Hi there, I’m Mobasher from Aesthetic Logic, where we pride ourselves on being a full-service software development and digital transformation agency. In our 55 successful projects, we’ve honed our skills in Python, JavaScript, API development and data analysis, all skills that are exactly what your NSE volume scanner project demands. We possess strong experience working with financial data and APIs and have previously built streaming applications, making us equipped to handle real-time refreshes with reliable precision. Furthermore, with my background in AI and machine learning, I can design intelligent rules to accurately classify BUY CE/PE alerts. Combined with our proficiency in algorithmic trading, options trading and paper trading simulations, I assure you that our version of the scanner will be capable of identifying opportunities for profit potential while keeping risk management intact. Best regards, Mobasher Reza

@Algokage

You can check my profile to see that I've just completed jobs on Python development. I am a skilled Python developer with experience in building trading tools and indicators. I have successfully delivered projects that involve real-time data processing, alert systems, and paper trading simulations. My expertise lies in creating efficient and reliable solutions for financial markets. I will upgrade your existing prototype into a comprehensive NSE volume scanner, providing real-time data, buy/sell volume classification, and alerts for Nifty 50, NIFTY, BANKNIFTY, and SENSEX stocks. The system will include a paper trading mode, Telegram alerts, and a user-friendly dashboard. I will ensure the code is clean, well-documented, and ready for deployment on a small AWS EC2 server in Mumbai. Thanks, Adegoke M.

@loxtic

Hi, how are you doing? I have considerable experience building Python tools for market data, including live feeds and paper trading flows, and I’ve worked on projects with NSE, option alerts, and dashboards. I’ve deployed apps on AWS EC2 and set up lightweight runbooks for cost-friendly setups. I can upgrade your RVOL scanner to a minute-refresh loop with WebSocket data, add buy/sell logic for CE/PE, include Nifty/NIFTY50, BANKNIFTY, and SENSEX coverage, and implement configurable rules plus a paper-trading engine with risk controls and P&L reporting. Telegram alerts, daily summaries, and a simple auto-refreshing dashboard can be included, with deployment notes for Mumbai. Let me know further if interested.

@bizvivo

Hello, I can upgrade your existing Python prototype into a robust, continuous NSE volume scanner with configurable option alerts and paper trading. Approach: Live feed: Integrate Dhan WebSocket for 1‑minute refreshes (09:15–15:30 IST). Volume classification: Implement tick rule + bid‑ask rule for buy/sell side detection. Coverage: Nifty 50 equities plus NIFTY, BANKNIFTY, and SENSEX indices. Option alerts: Configurable BUY CE / BUY PE signals with suggested contracts, delivered via Telegram. Paper trading: Simulated trades with stop‑loss, targets, brokerage charges, and P&L reporting—no real orders placed. Dashboard: Lightweight auto‑refreshing web UI showing live rankings, alerts, and daily summaries. Deployment: Containerised setup on a cost‑efficient AWS EC2 Mumbai instance, with runbook for maintenance. Deliverables: Production‑ready Python code, config files for rules, Telegram integration, dashboard, and deployment guide. Timeline: 4–6 weeks (scanner → alerts → paper trading → dashboard → deployment). Experience: Built trading automation tools with broker APIs, WebSocket feeds, and paper/live trading modes. Best regards, Suyash – Python Trading Automation Developer

@Abror86

Hi, Abror here, from Uzbekistan. I'm a full stack developer with 8+ years of experience working with Python, APIs, data analysis, and real-time application development. You need to turn the existing Dhan-based RVOL prototype into a continuous NSE scanner with 1-minute refreshes, volume classification, configurable CE/PE alerts, paper trading, Telegram notifications, dashboard, and low-cost AWS deployment. The main challenge is maintaining reliable real-time data flow and state while correctly separating volume signals, alert logic, simulated positions, P&L, and market-session timing. 1. Review the existing prototype and define the WebSocket data pipeline, RVOL calculations, classification rules, and configurable alert engine. 2. Implement Nifty 50/index coverage, CE/PE contract selection, paper trades with SL/target/charges, Telegram alerts, summaries, and dashboard updates. My Python and full-stack background fits the API integration, real-time processing, data analysis, dashboard, and deployment requirements here. A few questions to better understand the scope: Q1 - How does the prototype currently calculate RVOL? This helps preserve existing logic during the upgrade. Q2 - Should alert rules live in a config file? I recommend this for tuning without changing core code. Happy to go over the details here in chat and suggest the best approach. Looking forward to hearing from you.

@marvind18

Hi I can upgrade your existing Python prototype into a continuous NSE scanner with live volume processing, configurable CE/PE alerts, paper trading, Telegram notifications, and an auto refreshing dashboard. My recent work at Marin Software involved Python, AWS and real time data pipelines, including processing live data and building event driven workflows. I’m comfortable working with WebSocket feeds, API integrations, background workers, data analysis, and AWS deployment. I’d first review the existing RVOL logic and Dhan integration, then build the 1 minute scanning loop, buy/sell volume classification, option contract selection, and configurable alert rules. The paper trading layer can track entries, SL, targets, charges and P&L without placing real orders. I’ll also provide the EC2 setup and runbook.

@adriank06

Hi, I build Python trading tools with broker API integrations. Your existing RVOL prototype is a solid foundation — I'll upgrade it to a continuous WebSocket scanner with buy/sell volume classification, configurable alert rules, paper trading simulation, and a lightweight auto-refreshing dashboard. Approach: Dhan WebSocket feed → 1-min refresh, 09:15-15:30 IST, Nifty 50 + indices Tick rule + bid-ask volume classification → BUY CE/PE alerts with suggested contract Paper trading mode: SL/target/charges simulation, daily P&L report Telegram alerts + daily summary + dashboard AWS EC2 Mumbai deployment with runbook Timeline: 12-15 days. My quote: ₹10,000 Happy to sign NDA and review the existing code. Can you share the alert rule structure at a high level so I can confirm the logic is straightforward?

@ZohaibSathio

Hi, a continuous RVOL scanner on the Dhan socket that fires BUY CE and PE alerts and paper trades them. A dropped socket mid session is what kills these. How I would build it: one process holds the WebSocket, ticks classified buy or sell on arrival, a one minute rollup ranks RVOL and checks your rules, then alerts and simulated fills go to SQLite so the daily P and L just reads the table. Nifty 50 only for v1? I have kept pipelines like this alive on one small EC2 box for months. Regards, Zohaib

@MrDeaDpool707

hey i've worked on NSE stocks ( nifty , banknifty , sensex ) using api to fetch all tables i can build you a scanner that runs every minute in the market hours a demo trading ui , telkegram alets and hosting

@manishcomp123

Based on your existing Python prototype, I can upgrade it into a continuous scanner that meets your requirements. I will refresh the scanner every 1 minute from 09:15 to 15:30 IST, using Dhan's live WebSocket feed, and implement buy-side and sell-side volume classification using tick rules and bid-ask rules. I will also cover the Nifty 50 stocks, NIFTY, BANKNIFTY, and SENSEX. Additionally, I will configure BUY CE / BUY PE alerts with suggested option contract rules, which you will share after an NDA. I will also implement a paper trading mode that simulates trades on those alerts, with stop-loss, target, and charges, and reports pro. I have experience with JavaScript, Python, API, Data Visualization, Data Analysis, and Trading. I am confident that I can deliver this project to your satisfaction.

@Abxnfotech

Drawing on our extensive experience in Python development, particularly in working with financial data, we are uniquely equipped to enhance your NSE stock scanner as per your vision. Our familiarity with the Dhan API, its live WebSocket feed, and other requisite aspects of the project ensures that you’re engaging a team that is attuned to your needs. At Abxn Infotech Pvt Ltd, we’re tech enthusiasts who love finding innovative solutions to complex problems. Our expertise in JavaScript and Python aligns seamlessly with the languages required for your project. We're confident we can create a scanner that not only ranks stocks but also intelligently classifies buy-side and sell-side volumes, provides alerts based on your configurable rules for BUY CE/PE options, and simulates trades through paper trading mode. We understand the importance of not only being accurate but also timely and cost-effective which is why we propose deploying the system on a cost-efficient AWS EC2 server in Mumbai- a testament to our commitment towards elegant solutions. Lastly, we don't just consider our work done after the final delivery; at Abxn Infotech Pvt Ltd, the beginning of a relationship with our clients signifies the start of a long-term collaboration. You can expect from us not just exceptional technical skills, but also reliability, creativity and forthrightness i.e.,total dedication to making sure our work enables you to extract maximum value from your data.

@tranquilai

Hello, The main challenge is turning the existing RVOL prototype into a reliable 1-minute live engine without losing consistency with its current calculations. Our team can build on the supplied Python code, use Dhan WebSocket ticks to construct minute bars, handle reconnects and REST backfill, and keep the dashboard continuously updated during market hours. The ₹10,000 scope can cover Priority A: live 1-minute RVOL, tick-rule buy/sell classification, futures-based NIFTY/BANKNIFTY/SENSEX, configurable CE/PE alerts with Telegram, paper trading with P&L/charges, and low-cost AWS deployment. Priority B items such as bid-ask classification, rolling 5-minute RVOL, rollover history and trailing stops can be quoted separately if they do not fit without compromising the core system. The implementation will keep signal generation separate from paper execution and ensure no real order endpoint is called. Bid: ₹10,000 | Timeline: 4 days | Start: Immediate Milestone Breakdown Live Scanner & Dashboard: ₹2,500, 1 day Dhan WebSocket, 1-minute bars, RVOL and auto-refresh dashboard. Signals & Telegram: ₹2,500, 1 day Buy/sell classification, CE/PE logic, contract selection and alerts. Paper Trading: ₹2,500, 1 day Virtual entries/exits, charges, P&L, trade logs and summaries. AWS & Stabilization: ₹2,500, 1 day EC2 deployment, systemd, runbook, testing and fixes.

@patodeh

You need a continuously running Python scanner that pulls live NSE volume data every minute during market hours, classifies buy‑side and sell‑side volume, generates configurable CE/PE alerts, simulates paper trades with P&L reporting, and pushes notifications to Telegram plus a simple dashboard, all deployed on a low‑cost AWS EC2 instance with a runbook. I will build a robust WebSocket client for Dhan’s feed, implement tick‑rule and bid‑ask classification, extend coverage to Nifty 50, NIFTY, BANKNIFTY and SENSEX, create a modular alert engine with configurable option‑selection logic, develop a paper‑trading engine that applies stop‑loss, target and charges, generate real‑time Telegram alerts and daily summary reports, and set up an auto‑refreshing front‑end dashboard using lightweight JavaScript. I will containerize the whole stack with Docker, configure Nginx as a reverse proxy, automate deployment on the Mumbai EC2, and deliver detailed documentation and a runbook. Is there a preferred format for the dashboard UI or any specific charting library you want to use? Let’s chat, lock in the exact scope, and get started.

@Nayeem1217

I’m a Full Stack Developer with 10+ years of experience in **JavaScript, Python, WebSockets, AWS, and real-time data systems**. I can turn your prototype into a reliable **NSE volume scanner** using Dhan’s live WebSocket feed, with tick and bid-ask volume rules for BUY CE/PE alerts. I’ll also build **paper trading, stop-loss/target tracking, P&L reporting, Telegram alerts, daily summaries, and a real-time dashboard**—with no real orders executed. I can deploy it on a **cost-efficient AWS EC2 server in Mumbai** and provide post-launch support and improvements as needed.

@kuzshagra

Hi, I’m a Python/backend developer experienced with REST APIs, WebSockets, real-time systems, AWS, and automation. I can upgrade your existing Dhan prototype into the 1-minute NSE RVOL scanner. I can deliver the core scope within ₹10,000: • Dhan WebSocket with 1-minute bar aggregation, reconnects and REST backfill • 10-session same-time cumulative RVOL • Nifty 50 + NIFTY/BANKNIFTY/SENSEX using futures volume • Tick-rule buy/sell volume classification • Configurable BUY CE / BUY PE alerts with option selection • Telegram alerts + SQLite logging • Paper trading with bid/ask fills, slippage, charges, SL/target/time exits and P&L • Auto-refresh dashboard • AWS EC2 deployment, systemd, secure token handling and runbook • 5-day live test and fixes For WebSocket disconnects, I’ll detect missing minutes and backfill them through REST rather than silently dropping data. For indices, I’ll calculate RVOL from the appropriate futures contract. Priority B features such as bid-ask classification, 5-minute RVOL, rollover history, signal outcome tracking and trailing stops can be included where feasible or quoted separately. I’ll keep AWS costs low using one Mumbai EC2 + SQLite, with no RDS/NAT/load balancer. No real order endpoint will be implemented or called. I can start immediately after NDA and prototype access. Regards, Kush

@shoaibkhan754400

Hello Sir, I have solved this problem previously, and your problem looks similar to it. I have worked on Python based market scanners and trading automation where live market data, rule based signal generation, paper trading, and Telegram alerts all need to run as one reliable system. I understand that you already have a working RVOL prototype using the Dhan API. I would build on that instead of rewriting the project from scratch. For the upgraded version, I would use Dhan's WebSocket feed for live data and keep the scanner running from 09:15 to 15:30 IST. The volume logic can be kept separate from the signal logic, so your BUY CE and BUY PE rules can be changed later without changing the market data layer. I would also keep paper trading separate from real execution. Each alert can create a simulated trade with the defined entry, SL, target and charges, while tracking open trades, exits and daily P&L. The Telegram alerts and dashboard can read from the same stored state, so the scanner, paper trades and reports stay in sync. I would also keep the AWS setup light so it can run on a small EC2 instance without adding unnecessary infrastructure.