Python Supertrend Algo Deployment

@consultantcae

Hi, I am Sourabh Jain. I have built a generic fully automated option trading tool.I can provide option selling tool with your customized requirements for Rs 2000 per month as subscription fee. If you are interested, please let me know. Regards Sourabh

@mahads31

As a software development studio that thrives on solving real-world problems with reliable solutions, my team at Solves Inn fully understand and appreciate the importance of streamlining your option-selling strategy. I am confident that our deep expertise in API utilization, automation,and Python could be instrumental in not only coding your Supertrend-based process but also assisting you with its deployment and execution on your server. Over the years, we have successfully integrated numerous APIs into various platforms making us comfortable with navigating and communicating through REST or WebSocket protocols. Our proficiency in Python will enable us to accurately code the Supertrend concept, effectively turning it into market orders specific to Dhan's environment. Moreover, our passion for creating scalable solutions is well aligned with your needs, as seen by our experience in not only constructing clean code but also documenting it thoroughly. An important part of our delivery is enabling clients to maintain and customize their solutions independently even after project completion through comprehensive README files.

@muneeb6767

I’ve built Python-based trading automations with broker APIs and can implement your Supertrend option-selling strategy with clean architecture, risk management, paper-trading, and a production-ready Dhan integration including deployment support and documentation.

@meeranas

Hi, I can automate your **Supertrend-based option-selling strategy** using **Python** and the **Dhan API**. The bot will fetch live data, calculate Supertrend signals, place market/limit/stop orders, manage position sizing and stop-loss, support paper trading/backtesting, and include robust logging and error handling. I'll also help deploy it on your server, configure automatic startup, and provide well-documented source code with all settings in a single configuration file. Which timeframe and Supertrend parameters are you currently using?

@Algokage

Hello, I can efficiently deliver your Python Supertrend algo deployment by translating your strategy into clean, production-ready code and guiding you through local server setup. I’ll ensure the script connects to Dhan’s API, calculates Supertrend accurately, and places orders with position sizing, stop-loss, and exit logic. A back-test mode and well-commented code with a README for easy reconfiguration will be included. With 5+ years of experience in similar projects, I’ll meet your acceptance criteria seamlessly. Send a message to discuss further or see samples of my work. Thanks, Adegoke. M

@prabhathk5

Thanks for sharing the details. I’ve reviewed your requirement and would like to discuss it further. I’m Prabhath — an MQL4/MQL5, Pine Script, Python, and C++ developer with strong experience in building trading systems, advanced studies, and institutional-grade algorithmic solutions. I develop Expert Advisors, indicators, dashboards, data tools, and custom trading utilities for MT4/MT5 and TradingView. As an active trader, I work with concepts like ICT, SMT, market structure, liquidity models, order blocks, FVGs, VWAP, and volume-based logic. I build EAs and indicators that follow precise rules and match the user’s trading methodology perfectly. My expertise includes: Institutional-grade EA and indicator development ICT/SMT-based trading systems Pine Script indicators and automated strategies Python tools for data analysis, signals, and external integrations C++ modules for high-performance components Backtesting, forward testing, and full strategy optimization Strategy development, refinement, and consulting Once we discuss your project and you select me as the developer, I prefer a short call to confirm all details before starting. This ensures perfect clarity and avoids misunderstandings. I fix and optimize existing trading code by removing errors, correcting logic issues, and making your EA/indicator/bot stable and production-ready. Thank you.

@alluankit01

Hi, I can automate your Supertrend-based option-selling strategy in Python and deploy it locally with Dhan REST/WebSocket API integration, paper testing, live order execution, and configurable risk settings. The best solution is to first review your exact Supertrend rules, option selection logic, entry/exit conditions, stop-loss, position sizing, timeframe, and Dhan account/API setup. Then I’ll code the Supertrend calculation, connect live market data, generate signals, place market/limit/stop orders, and test the full workflow in paper mode before live execution. I’m comfortable with Python, Dhan API integration, WebSocket live data, REST order placement, Supertrend logic, option-selling workflows, backtesting/paper trading, JSON/YAML configuration, error handling, logging, cron/service deployment, and server setup. Deliverables will include: * Python Supertrend algo script * Dhan REST/WebSocket integration * Live data fetching * Signal-to-order execution * Position sizing and stop-loss logic * Exit management * Paper-trade/backtest mode * JSON/YAML/.env configuration * Auto-start service/cron setup * Well-commented source code * README and deployment guide I’ll focus on building a stable, configurable, and easy-to-run trading script that can be tested safely before going live and monitored without manual clicks. Best regards Ankit

@richard031596

You need your Supertrend option-selling logic off spreadsheets and into a Python bot that connects to Dhan's API, manages positions autonomously, and survives a reboot without manual intervention. I trade futures myself using ATR-based indicators and intraday signals, so I'm not just translating your rules into code blind — I understand why the Supertrend flips and what that means for an options seller's position management. I'll implement the calculation cleanly, wire it to Dhan's REST and WebSocket feeds, add a paper-trade mode with logged signal output so you can verify the logic firing before any real orders go through, and package all configurable inputs — symbol, timeframe, ATR period, multiplier, lot size, stop-loss — into a single .env file. Deployment includes a systemd service so the bot restarts automatically on reboot. One question: are you selling options on index expiries (Nifty/BankNifty weeklies) or stock options — and do you want the bot to auto-select strikes based on delta/premium, or will you specify the strike manually?

@loxtic

Hi,i have considerable experience with algo trading bots, using multiple broker apis, including dhan. have worked in stocks, FnO, commodity trading bots as well, across indian as well as american exchanges. Can demo previous bots if needed. Let me know further if interested

@Vsion2

Welcome to professional Python development services! Hi there, I'm Alema, a Python expert programmer who strives for clear code in atmospheric, numerical weather prediction, physics, and all other seminal fields. I'm ready to provide you with high-quality services. I have completed 350+ projects with a 100% Positive Rating. If you are looking for Quality work, look no further. Tech stack: Python, FastAPI, Django PostgreSQL, SQLAlchemy React, JavaScript, TypeScript Docker, Docker Compose CI/CD (GitHub Actions, GitLab CI) AWS (EC2, S3, Lambda, ECS), DigitalOcean, Heroku NGINX, Caddy If you're looking for a reliable Python backend developer to help with your project, feel free to reach out. Your faithfully. Eng. Alema Akter

@kshubham102

Hi, I've built automated options trading bots before, including Supertrend-based strategies on Indian broker APIs (Zerodha Kite, Dhan) with live order execution via REST/WebSocket. Happy to share code samples/demo on request. Approach: Python script with modular design — Supertrend calc (pandas/numpy or ta-lib), Dhan API wrapper for auth, live data feed, and order placement (market/limit/SL). Config-driven (YAML/.env) for symbol, timeframe, indicator params, lot size, SL%, and target%. Paper-trade mode toggles order execution off while logging signals for validation before going live. Includes: reconnect/retry logic for API drops, exception handling with logging, systemd service (or cron fallback) for auto-restart on reboot, and a README covering setup, config, and troubleshooting. We'll screen-share once paper-trade mode confirms signal accuracy, then place a live test order together. Can start this week with your Dhan API credentials (sandbox/test first). Let's connect to align on strategy specifics. Shubham Sharma

@ammarahmed20

Hello, I can help you transform your Supertrend based option selling strategy into a reliable, production ready Python trading bot integrated with the Dhan REST and WebSocket APIs. I will implement the complete trading logic including Supertrend signal generation, position sizing, stop loss, target and exit management, along with paper trading or backtesting support so the strategy can be validated before going live. The code will be clean, well documented, and fully configurable through a single JSON, YAML or .env file, and I will personally guide you through local deployment, dependency setup, automatic startup after reboot, and live testing over screen share to ensure the bot fetches market data, calculates signals correctly, and successfully places test or live orders while remaining stable for long running execution. I have experience building automated trading systems and API based Python applications and can deliver a maintainable solution tailored to your strategy. Kind regards Ammar Ahmed Malik

@shoaibkhan754400

Hello Sir I can build this for you. I have developed many Python-based trading systems for Indian brokers, including API integrations, automated option strategies, backtesting modules, and VPS deployments. I'll convert your Supertrend option-selling strategy into a clean Python application that connects directly to the Dhan API. The script will support live trading, paper trading, configurable risk management, stop-loss, exits, logging, and automatic startup after a system reboot. I have a few questions before we begin: Will the strategy trade a single underlying (such as NIFTY or BANKNIFTY), or should it support multiple symbols? How do you select the option contract—ATM, a fixed strike offset, or based on premium? Should I also include a trading session and news filter to prevent new entries during high-volatility periods? The source code will be clean, easy to understand, and include helpful comments throughout. We can also schedule a screen-sharing session to verify the Dhan connection, validate the Supertrend signals, and place a live or paper trade together before the project is completed

@JoseRCarvas

Hi — I read that you want your Supertrend option-selling strategy moved from spreadsheets/manual clicks into a production-ready Python script wired to your Dhan account, with hands-on help on the strategy implementation itself and local deployment on your own server. Approach: translate your single-indicator Supertrend rules into clean, testable Python (entry/exit exactly to your spec — no guessing your logic), integrate the Dhan API for live data + order placement, and — important for anything touching real orders — build in a dry-run/paper mode and safety checks (position limits, error handling, logging) so we validate behaviour before it trades live. Then guide you through deployment on your server with clear run/monitor instructions. To be clear: I build and hand you YOUR strategy as YOU define it — I don't advise on the trading logic itself. Rating 5.0 stars. Can you share your exact Supertrend rules (period/multiplier, entry/exit)? — Ricardo

@iterativeTech

With my experiences in designing and deploying intelligent models, building and optimizing scalable pipelines, and implementing analytics systems, I firmly believe I am the AI and Cloud Data Engineering Specialist you need to transform your option-selling strategy from spreadsheets to a fully automated Python script. I am well-versed in Python programming and proficient in the skills needed for the job including automation and software architecture. Additionally, my past projects have been aligned with your current needs. I have successfully calibrated numerous algorithms similar to Supertrend - incorporating market signals with stop-loss mechanisms while also ensuring unbroken performance. I have hands-on experience with API's like Dhan’s API and full-stack architecture including python on cloud platforms and can effectively guide you through server setup, dependency installation, and deployment process. My work is guided by a business-first mindset and technical expertise that ensures every solution delivers tangible ROI without which no project is complete. I understand none of what I promise is new to you hence, I will focus on delivering measurable outcomes like operational efficiency, cost reduction, and smarter decision-making by building scalable production ready system alligned with your business objectives. Let's get your strategy automated together!

@MKCHAND

Hi, I am the master of trading bots automation. See my portfolio of trading bots. I can easily create your desired trading system with in 2 days. See my work first then award your valuable project to me. Let’s discuss further on chat for detailed information.

@neerajkanti2703

hey sir , i have read your requirements , i am previously made many algo bot using python for dhan and kite api , strategies realted to price action , volumn analysis, gann levels , supertrends , atr and lot more ,, also i run algo strategies in my personal account which also i can show you the complete process. Looking forward to work with you . Regards Neeraj Kanti

@fizaa170

This is a good fit for a production-focused automation project because the requirements go beyond simply coding the Supertrend indicator. The key is building a stable trading bot with proper error handling, reconnection logic, configurable risk management, and a deployment setup that can run reliably for long sessions. I've worked on trading automation where the biggest challenge isn't the strategy itself, but making sure the execution layer remains dependable when dealing with live market data and broker APIs. I'd structure this by separating the strategy engine, Dhan API integration, order manager, and configuration so changing the symbol, timeframe, or Supertrend settings won't require modifying the core code. We'll also include a paper-trading mode, logging, automatic recovery, and a straightforward deployment on your local server with a single configuration file. During the screen-sharing session, we'll verify the API connection, validate the Supertrend signals against live data, and place a test order before moving to production mode. One question before we begin: is your current Supertrend strategy based on TradingView's default Supertrend (ATR Period and Multiplier), or does it include any custom entry, re-entry, or option strike selection rules?

@mussaibb7

I'd love to help you deploy a robust Python Supertrend Algo that streamlines your option-selling strategy. Based on my expertise in Python, software architecture, and API integration, I'm confident I can build a scalable and maintainable backend flow that handles real API, deployment, and error-handling conditions. The real work here is building a backend flow that stays clean under real API, deployment, and error-handling conditions. I've successfully delivered similar work through my multi-client ML inference API, which I believe maps well to the delivery risk in this job. For instance, I've deployed multi-client ML inference APIs with sub-200ms latency and production-grade cloud delivery. My execution plan involves working closely with you to clarify deployment targets, API boundaries, and whether this is a greenfield or existing service. I'll deliver clean backend code, environment setup instructions, and a well-documented README to ensure seamless integration. Before we begin, I'd like to clarify: Is the main pain point implementation, deployment, or stabilizing an existing backend flow?