Python Developer for Algo Trading System

@OutsourceMan

Hi, CnEL India can develop your Python-based algo trading system with a controlled, test-first approach. Our methodology: * Set up the Python environment and validate Dhan API authentication/endpoints. * Implement real-time market data through WebSockets with reconnect/error handling. * Build modular strategy, screening, signal and order-execution components. * Add position sizing, stop-loss, trailing SL, targets and automated exit rules. * Build a backtesting framework using the provided historical data with performance reports. * Add logging, trade-state tracking, validation and duplicate-order protection. * Keep API credentials and sensitive configuration secure. * Test strategies using historical data and paper/controlled execution before live deployment. * Validate equities, futures and options workflows separately. * Provide setup documentation, operating guides and knowledge-transfer sessions. * Support troubleshooting and future strategy modifications. **Milestones:** API + market-data POC → strategy/backtesting → risk & execution engine → paper testing → controlled live deployment. We can first review the Dhan API documentation and strategy requirements, then confirm the implementation plan and timeline.

@ambientinfotech

Hi there, Writing working Python code is easy; building a fast, scalable, and memory-efficient system that doesn't break under load is where most implementations fail. As a Senior Python Engineer, I engineer robust backend architectures, automation pipelines, and custom API systems built for long-term production use: • Modern Backend APIs: High-performance, asynchronous REST & GraphQL services using FastAPI, Django, or Flask. • Intelligent Automation & Scraping: Headless browser automation (Playwright/Selenium), robust data scrapers with rotating proxy/anti-bot bypass, and custom Celery/Redis worker queues. • AI & LLM Integrations: Seamless integration with OpenAI, LangChain, vector databases (Pinecone/Chroma), and automated data pipelines. • Database & Query Optimization: PostgreSQL, MongoDB, Redis caching, and Dockerized deployments designed for high throughput and zero bottlenecks. I write clean, PEP-8 compliant, fully documented code that your team can easily maintain and scale. Do you have a technical spec, repo, or API documentation ready? Drop me a message in chat, and let’s discuss the fastest way to execute this. Best regards, Deva | Senior Python & Backend Engineer

@vishal1145

Your backtesting framework will fail if you don't account for slippage and liquidity constraints during high-volatility periods. Most algo systems look profitable in backtests but break live because they assume instant fills at mid-price. Quick questions - what's your expected order frequency during market open (are we talking 10 trades/day or 500)? And do you need multi-strategy portfolio management or single-strategy execution? Here's the architectural approach: - DHAN API + WEBSOCKETS: Build event-driven architecture with message queues to handle tick data bursts without dropping packets during NSE peak hours. - RISK MANAGEMENT: Implement pre-trade validation layer that blocks orders violating position limits, checks margin requirements, and enforces circuit breakers before hitting exchange. - BACKTESTING ENGINE: Design vectorized backtesting using pandas/numpy for 10-year datasets with realistic transaction costs, bid-ask spreads, and order rejection simulation. I've built 4 live algo systems for Indian markets (Zerodha, Upstox, IIFL APIs) processing 200+ trades daily with 99.7% uptime. Let's schedule a 20-minute call to walk through your strategy logic before we architect the execution engine.

@jayantkumar314

As a seasoned Python developer, I have vast experience in creating comprehensive applications from scratch, just like your Algo Trading System project. My in-depth knowledge and skillset include not only Python but also Dhan API - a platform that I have worked and integrated with before. This familiarity is crucial as it shortcuts the learning curve, allowing me to efficiently configure real-time market data using WebSockets for you. In the context of trading, my proficiency doesn't stop in API integration, I have hands-on experience building successful automated trading systems replete with bots for equities, futures, and options. My strategy-based trade screening will align perfectly with your requirements as it emphasizes on signal generation, order execution, position sizing, stop losses, trailing stop losses - all of which will be consolidated within a robust risk management system. Lastly, I align perfectly to your post-delivery support terms as that is the essence of long-term relationships and commitment to clients; after all - "There's extraordinary chemistry in long term relationships." I plan to be there at every stage - assisting with installation/on-boarding, troubleshooting inevitable errors/issues, and supporting future enhancements and strategy modifications. In conclusion, consider choosing me for this project would be both practical and beneficial.

@ssquare489

For this Dhan API trading system, I’d separate market-data ingestion, strategy logic, risk controls, execution, and backtesting into independent Python modules from day one. That is especially important when the same engine must handle equities, futures, and options without strategy code directly controlling broker orders. My two priorities would be integrations and maintainability. I’d use Dhan’s APIs with WebSocket market feeds, an event-driven strategy layer, and a centralized risk/execution engine covering position sizing, SL/TSL, targets, automated exits, order-state reconciliation, and reconnect/error handling. Backtesting would use the same strategy rules where practical, with performance reports covering P&L, drawdown, win rate, and trade history. I can handle setup, development, deployment documentation, knowledge transfer, and post-delivery troubleshooting. A relevant project is a live stock-market analysis platform I built using the GDFL WebSocket API for real-time market data and trading-oriented dashboards. I’d estimate 6-8 weeks for a production-ready first version, with cost finalized after the strategy count and execution rules are defined. Post-delivery support can include an initial bug-fix/onboarding period followed by ongoing enhancement support.

@prashanpatel557

Hello, I can build your Python-based Dhan API algo-trading system with real-time WebSocket data, automated execution, risk management, and backtesting. I have experience with Indian broker APIs, Python trading systems, options/futures automation, WebSockets, strategy engines, and paper/live execution. I can implement: - Dhan API setup, authentication and WebSocket market data - Equity, futures and options trading modules - Strategy screening, signal generation and automated execution - Position sizing, SL, trailing SL, targets and automated exits - Order/position monitoring with error handling and reconnection - Modular backtesting framework with performance reports - Historical-data integration for the available data period - Detailed logging and trade records - Setup/deployment documentation and knowledge-transfer session - Post-delivery troubleshooting and future strategy enhancements I’ll build the system modularly so additional strategies can be added without changing the core execution engine. Estimated timeline: 10–15 days Budget: ₹25,000–₹35,000 depending on strategy and backtesting scope. Support: 14 days post-delivery for bug fixes/setup assistance. Regards, Prashant Patel

@NEHABHAT92

As a seasoned Python developer, I am confident in my ability to deliver an automated trading system that will meet and exceed your expectations. Equipped with over 9+ years of hands-on experience and a robust understanding of both web and mobile app development, I bring versatile IT skills to the table. This includes a deep expertise in Python as well as proficiencies in Dhan API, WebSockets, Algorithmic Trading, backtesting systems, and risk management—the precise qualifications you seek. Throughout my career, I've consistently built structures that transcend ideation into practicality and have successfully transformed complex concepts into user-friendly solutions. Drawing on that same extensive repertoire, I will effectively set up your preferred trading system while ensuring real-time market data configuration, strategy-based trade screening, signal generation, order execution, and bulletproof risk management comprising all the essentials such as position sizing, stop-losses, trailing losses. Additionally, I will provide you with a comprehensive backtesting framework utilizing up to 10 years of historical data with thorough performance reporting. Moreover,next-gen perks like ongoing support post-delivery till you are comfortable operaing independently as well as scalable enhancements & modifications for future strategies aren't alien territory .Ethically priced and time-efficient work has always been my priority ;I'm more than positive t

@UzeeTech

A Dhan-powered algo desk — live WebSocket data, strategy-driven signals, risk management, and a backtesting framework over a decade of history — is exactly what I build. I'd build it in Python on the Dhan API: WebSocket streaming for quotes, a strategy engine for signals across equities, futures, and options, and execution with position sizing, stop losses, trailing stops, targets, and automated exits — plus a backtesting module replaying up to 10 years of data with full performance reporting. You'd get clean code, setup guides, knowledge transfer, and support until you run the system independently — including future strategy tweaks. With 7+ years building Python systems and trading automation, I know where live bots succeed or fail: WebSocket handling, faithful backtests, and risk controls that can't be bypassed. Two questions: is your Dhan API access active, and which strategies should I prioritise first? Happy to jump on a quick call to map the strategy list and timeline for the first version.

@TechWagger2026

With an outstanding proficiency in Python and a solid experience in building algorithmic trading systems, I am highly confident that TechWagger is the right fit for your project. We understand that this automated trading system requires not only advanced coding skills but also an in-depth knowledge of Dhan API, WebSockets and risk management. That's why our firm stands out - we have excelled in all those areas. At TechWagger, we have successfully created numerous automated systems using different APIs including Indian broker APIs over the years. Our team, led by me Arun, has developed a thorough understanding of market data manipulation using WebSocket and building real-time trading bots. Not-to-mention, our specialisation in risk management will ensure comprehensive implementation of position sizing, stop losses, trailing stop losses, targets, and automated exits as per your need. More than just delivering project milestones on time and within budget, we firmly believe in supporting clients till they are comfortable operating the system independently. Our ongoing support model will ensure that any error/issue arising later will be dealt swiftly and effectively thus making us the perfect choice for this complex project of yours. Trust TechWagger with your technological needs for the finest quality!

@FreeLancers360

Hi there, The moment I read "Python Developer for Algo Trading System", I knew it was a strong match for exactly what we do best. My goal isn’t simply to finish the task, but to give you real, lasting value for every bit you invest in it. From your brief I can see this involves php — all areas we handle in-house. We specialise in PHP, JavaScript, Python, Troubleshooting, which lines up directly with what you need. How we'd approach it: - Map out the scope, pages and data models up front - Build the frontend and backend with clean, scalable code - Test across devices and browsers, then deploy - Hand over with documentation and post-launch support Delivering at the scale of 10 years is no problem for us — we're set up for volume without dropping quality. I’ll fold in your feedback fast and keep refining until the result feels exactly right to you. Send over any references you have and I’ll come back with a clear plan and milestones. Best regards, FreeLancers360 Let’s connect in chat and get started — message me anytime and I’ll reply right away!

@Mayanks010

Hi, Thanks for sharing your project. It aligns well with work I’ve successfully completed for other clients, and I’m confident I can deliver a high-quality solution tailored to your requirements. Before providing an accurate timeline, scope, and budget, I’d like to clarify a few key details to ensure we're aligned from the start. Freelancer’s proposal character limit makes it difficult to cover everything thoroughly here. If you're available, let's connect via chat. I can walk you through similar projects I've completed, discuss the best approach for your specific requirements, and answer any questions you may have. Once I understand your expectations, I'll provide a clear execution plan with realistic timelines and pricing. I’m ready to get started as soon as we finalize the details and look forward to working with you. Best regards, Mayank Sahu

@aakaashberi

An algo system is only as safe as its risk layer. Stop losses, trailing stops, position sizing and a kill switch should sit between every signal and the Dhan order API, so no strategy can place an unchecked order. Approach: Python with the dhanhq SDK, a WebSocket feed handler, a pluggable strategy module (screen, signal, order), a separate risk manager and order executor with full logging, a paper-trading mode first, and a backtester on historical candles that reports win rate, drawdown and P&L using the same strategy code. Phase one: Dhan API + WebSocket setup, one strategy end-to-end in paper mode with stop loss/target/trailing exits, and the backtest report. First working version in 3 days. This builds and tests your strategy; no system can guarantee profits. Price: ₹7,500 for phase one; F&O bots and more strategies are quoted next. My past client work is under NDA, but you will see the paper-trading logs working on live market data before going real. Questions: which strategy should be built first (indicator rules or price action)? And will it run on your PC or a cloud server during market hours? Aakaash

@luckysadiwal7

I’ve gone through the requirement carefully, and the important part here is building a reliable trading pipeline around Dhan’s API—not just connecting an API and placing orders. The system needs clean separation between market-data handling, strategy signals, execution, risk controls, and historical testing. I can build the Python architecture around WebSocket market data, strategy-based screening/signals, order execution, position sizing, SL/target/trailing exits, and a backtesting layer using the available historical data. I’d also keep logging and error handling in place so live execution issues can be diagnosed without making the system difficult to maintain. The handover would include setup documentation, configuration guidance, troubleshooting support, and knowledge transfer so you can operate and modify the system yourself. I don’t have a verified Dhan-specific algo-trading project in the supplied portfolio, so I won’t claim one. If you share the exact strategies and Dhan account/API requirements, I can scope the modules, timeline, and implementation milestones accurately.

@Digitalizers010

Hi, a Python bot that reads the Dhan feed, fires orders on your rules and exits on its own when a trade turns. Reconnects are what break these. How we would build it: the Dhan WebSocket into a tick store, a strategy layer that emits signals kept apart from an execution layer that places them, sizing with stops and trailing stops in state that survives a restart, then that same strategy code replayed over 10 years of candles for the backtest. Equities or options live first? We've built broker API automation with reconnect and order reconciliation, the parts that fail in production. Happy to take the feed as milestone one so you see ticks before strategy work. Regards, Digitalizers

@shahnaitik

Hello there, I came across your Stock Trading App requirement and it strongly aligns with my experience in building secure, high-performance fintech platforms. with 10+ years of extensive experience in the Stock broking and Trading Industry, I have already built trading technology such as Strike for Jainam, so I understand the practical challenges involved in market-data handling, trading workflows, order execution, and real-time system performance. Your requirement for a complete Python + Dhan API algo-trading system is closely aligned with my experience, and I can build it with a scalable architecture from the beginning. My relevant work: Strike – Jainam Trading Platform: https://strike.jainam.in. I would love to show you a quick demo or walk you through similar work I have done. I am confident that it is the right fit for your work. Let’s discuss this over a call, and I can contribute to the success of your projects. Regards, Naitik S.

@indreshpnk

Hello, I understand you need a Python-based automated trading system integrated with Dhan API, including real-time WebSocket data, strategy-based signals, order execution, risk management, and historical backtesting. The goal is to build a reliable, well-documented system that can be tested and operated confidently. Here’s what I can provide: • Python + Dhan API integration with WebSocket market-data handling • Strategy engine with screening, signals, order execution, position sizing, SL/target/trailing exits • Backtesting framework, performance reports, logging, documentation, and deployment support I bring over 4+ years of experience in Python, backend development, APIs, automation, databases, and software architecture, with a focus on reliable and maintainable systems. I can structure the system modularly so strategies and risk parameters can be updated easily. Just to clarify a few things: • Which Dhan account/API environment and trading segments should be supported first? • Do you already have the trading strategies and entry/exit rules defined? Please come to the chat box to discuss more about your project. Best regards Indresh Kushwaha

@Ashoksahu001

Drawing from 12+ years of experience, I would be a formidable asset for your algo-trading project. My proficiency in Python, complemented by my extensive understanding of Algorithmic Trading and Risk Management poises me to not only build a robust automated trading system for you, but also provide steadfast support even after the project's conclusion. Having successfully designed numerous backtesting systems in the past, I am confident in my ability to leverage historical data spanning up to ten years while providing insightful performance reports. Additionally, my skills with WebSockets and Dhan API align perfectly with your requirements. Before working on live automated trading systems using Indian broker APIs became commonplace, I was among the few developers pioneering this frontier. As such, I possess comprehensive knowledge of Dhan API that transcends mere competency. For examples of my work and case studies illustrating successful project executions using similar technologies, I encourage you to take a look at my carefully curated GitHub/portfolio links. One thing I value above all else is building long-term partnerships based on trust and success. That's why every task assigned to me receives 100% on-time delivery and meticulous attention to detail within the agreed budget. So if you're looking for a skilled Python developer who can expertly navigate through complex projects like these while keeping your long-term goals in mind,

@rajeshrolen

Hi, At first glance, this looks straightforward but there’s usually one part that causes issues later. Happy to share a quick plan if you're open to it. Regards, Rajesh

@alfatrade2

Ten years of historical backtesting plus live WebSocket feeds plus trailing stop automation is easily a multi-week build, not a $130 job — which piece matters most for the first pass: signal execution or the backtest engine? I've built FastAPI services with data validation pipelines and structured record management, which covers the screening-and-order-logic layer here. Do you already have Dhan API credentials and sandbox access ready?