Multi-Broker Trading Web App

@ixorawebmob

Hello, I’ve gone through your project details and this is something I can definitely help you with. With over 10 years of experience in web application development, I have successfully built scalable systems using Python and frameworks such as Django and Flask. My focus on clean architecture and real-time data processing ensures that your trading web app will be interactive and maintain low latency. I will review your requirements thoroughly and suggest the optimal technical approach for backend and frontend integration while keeping you updated throughout. Here is my portfolio: https://www.freelancer.in/u/ixorawebmob I’m particularly interested in discussing the integration of the live market feed and the specific screening rules you have. Could you clarify: Could you please provide more details on the initial rule set in JSON for your screening logic? Let’s discuss your vision over chat! Regards, Arpit Jaiswal

@ssquare489

I am Sumit Joshi from Sacesta Technologies. I can build your Python trading web app with live screening, editable trade tickets, and instant order routing to Broker A, Broker B, and Broker C using their official REST and WebSocket APIs. Stack: FastAPI async services plus WebSockets for tick in and UI out, modular broker adapters, PostgreSQL audit log, and Redis for fast in memory state. UI: React dashboard with live tables, alerts, ticket editor, and charts, desktop first and responsive for tablets. Trading: Market, Limit, and Stop-loss place, modify, cancel for paper and live modes, with real time success or error feedback. Security: two factor sign in, encrypted token vault, per user API keys, and a basic admin panel for users and permissions. Backtesting: ingest historical data for all stocks, run your JSON strategies, and generate backtest reports with full quantstats results and exports. Delivery: Docker setup, README, CSV export, and pytest coverage on critical paths. Relevant work: I built a live stock analysis product using WebSocket market streams, indicator computation, and a sortable dashboard with admin strategy controls.

@caroldata

As an ISO 9001:2008 certified global IT service provider with over 10 years of experience, my team at Carol Data Technology is well-equipped and experienced in creating high-performance Python applications, using frameworks like Django, Flask and FastAPI. We have successfully integrated brokerage APIs, worked with real-time market data and have extensively used REST/Websocket protocols. Our focus is on ensuring sub-second order placement speed while providing a rich user interface that includes auto-refreshing tables and dynamic charts. We leverage major front-end technologies like React, Vue and Django templates to build responsive layouts that scale seamlessly. What sets us apart is our emphasis on modular integration, which will enable you to easily add or remove brokerage partners without disrupting the core logic of your application. Security is key for us; we employ efficient OAuth/token storage mechanisms along with two-factor sign-in processes. Additionally, we offer both live trading and paper trading capabilities to ensure robust testing. Our skills extend beyond the technicalities of your project; we are committed to smooth communication for a long-lasting business relationship and provide continued support even after delivery. You can count on us for error-free service, daily progress reports, clear communication throughout the project, dockerised deployment with comprehensible READMEs and complete satisfaction.

@abdf2010

Hello there, I reviewed your project Multi-Broker Trading Web App and understood the requirements at a high level. I focus on delivering clear, stable, and maintainable solutions aligned with the actual scope, I can work with JavaScript, Python, C# Programming and follow a clean development process with proper structure and error handling. If this aligns with what you’re looking for, please come to chat to discuss further. Best regards

@abdulhadi999

I can build a Python trading platform that screens live market data, triggers your JSON rule library, lets users edit trade tickets, and places Market, Limit, and Stop loss orders to Broker A, Broker B, and Broker C with real time UI updates plus full audit logging and CSV export. → Architecture and Stack . FastAPI or Django with WebSockets for sub second live tables and charts . Broker adapters as isolated modules so partners can be added or swapped cleanly . Event driven pipeline from tick ingest to rule evaluation to UI publish → Live Trading Workflow . WebSocket market feed ingest, normalization, and screening latency under 1 second . Trade ticket preview and edit with validation for qty, price, stop, and limits . Place, modify, cancel orders with instant success or error streaming to UI . Live and paper trading modes with separate routing and logs → Security and Admin . Secure token and API key storage with encryption at rest . Two factor sign in and role based access . Admin panel to manage users, broker keys, and permissions → Backtesting and Quantstats . Historical data ingestion for full stock universe and strategy runs . Backtest engine aligned to the same strategy library used in live screening . Quantstats reports per strategy and per symbol with exportable outputs Best regards, Abdul Hadi Python Trading Platform Developer

@prashanpatel557

Hello, I can design and build this multi-broker trading web application as a production-grade, low-latency system with clean separation between screening, execution, and analytics. I have hands-on experience with broker REST/WebSocket APIs, real-time trading dashboards, backtesting engines, and quant performance reporting, which aligns well with your requirements. Proposed Architecture • Backend: Python (FastAPI/Flask) with async WebSocket streams for live ticks • Broker Layer: Pluggable adapter pattern (Broker A/B/C isolated modules) • Screening Engine: JSON-driven rule engine (hot-reloadable, no downtime) • Execution Engine: Market/Limit/SL orders with full preview & validation • Security: Token encryption, OAuth/API key vaulting, 2FA, admin controls Backtesting & Analytics • Historical data ingestion (multi-symbol, multi-year) • Unified backtest engine using the same strategy logic as live trading • Full QuantStats / PyFolio metrics: CAGR, Sharpe, Sortino, DD, win rate, exposure, equity curves • CSV + in-app reports export Key Deliverables • Live trading + paper trading across all brokers • Sub-second screening to UI updates • Dockerized deployment (dev/stage/prod) • 80%+ test coverage (pytest) • Clean README + setup scripts Why I’m a good fit • Real-time trading systems experience • Multi-broker integration without tight coupling • Strong focus on performance, risk, and auditability Happy to discuss broker specifics, data vendors, and UI preferences next.

@KTECH2411

I can build your low-latency Python trading platform with a real-time screener UI, editable trade tickets, and modular REST/WebSocket broker connectors for Broker A/B/C. I’ll use a WebSocket-driven frontend (live tables + charts) and a Python backend (FastAPI/Django) optimized for sub-second screening-to-UI and order placement, with secure token storage, 2FA, and an admin panel. I’ll also integrate historical data + backtesting so your JSON strategies run in the platform, and generate full QuantStats reports (tearsheets + metrics) exportable alongside CSV audit logs. Delivery includes Dockerized setup, README, and pytest unit/integration coverage for critical paths, plus live/paper place/modify/cancel for Market/Limit/Stop orders across all brokers.

@anilptk

Hello there, I am excited about the opportunity to work on your project for a Python-powered web application that enables retail traders to screen live market data, select trading conditions from a built-in library, and execute orders seamlessly with three brokerage partners—Broker A, Broker B, and Broker C—via their official REST/WebSocket APIs. The application will boast an interactive and feature-rich interface, including live auto-refreshing tables, dynamic charts, and a responsive layout optimized for desktop and tablet use. The core workflow involves real-time data processing, rule-triggered order previews, instant order placement, and detailed transaction logging. I am confident in delivering a high-performance solution that meets your technical expectations. Regards, anilptk

@loxtic

Hi, how are you doing? I have solid experience building Python backends with real-time data via WebSockets and secure OAuth workflows, plus modular broker integrations and a responsive front end. I’ve deployed dashboards with live tables, charts and audit logs, and I’ve wired multi-broker order paths with sub-second latency. I can demo prior work and share a repo if needed. Let me know if you’d like to proceed.

@NEHABHAT92

Having spent nearly a decade in the software development industry, I believe I have the right set of skills to handle your multi-broker trading web app project. I am well-versed in Python and have excellent command over Django, FastAPI, Flask. In addition, I have solid experience with WebSocket data streams, and broker APIs from my previous projects and can deliver low-latency Python services as needed. My expertise in E-commerce and CMS based website will also come handy while working on clean, modular integration layers for each broker as you require. Apart from my technical skills, I also would like to bring your attention to my commitment towards delivering high-quality work within tight deadlines. I believe in turning client's ideas into reality, which is exactly what you are looking for. Moreover, my proficiency with containerization tools like Docker will ensure that the project will be simple to deploy across different environments for efficient testing at every stage of development.

@abhindandy

Hi, i am a python developer with 6+ years of experience as an algo strategy developer. I have expertise in building all kinds of custom and indicator based strategies. I can help you build this profitable strategy with low latency. Ping me for further discussions

@prabhathk5

Thanks for sharing the details. I’ve reviewed your requirement and would be glad to discuss it further. I’m Prabhath, an experienced MQL4/MQL5, Pine Script, Python, and C++ developer specializing in automated trading systems and institutional-grade algorithmic solutions. I develop Expert Advisors, indicators, dashboards, data tools, and custom trading utilities for MT4/MT5, TradingView, and standalone platforms. Along with MQL5 systems, I also build fully automated trading software in Python and C++ for Indian stock markets and global exchanges (US, EU, and others). These solutions can be tailored for stocks, indices, futures, forex, and crypto based on project needs. As an active trader, I work with ICT, SMT, market structure, liquidity models, order blocks, FVGs, VWAP, and volume-based logic, ensuring each strategy follows the client’s trading methodology. My expertise includes institutional-grade EA and indicator development, ICT/SMT-based trading systems, Pine Script automation, Python and C++ systems for Indian and global markets, backtesting, paper trading and live trade integration, strategy optimization, and low-latency execution. I also fix, optimize, and enhance existing trading systems to make them stable and production-ready. Where permitted, I can share demos or walkthroughs of previously completed projects while respecting client confidentiality. Thank you for your time and consideration.

@Mayanks010

Hi there, You’re absolutely in the RIGHT PLACE. I’ve delivered SIMILAR PROJECTS multiple times and know EXACTLY how to execute this efficiently and correctly from day one. To lock down the SCOPE, TIMELINE, AND PRICING, I’ll need to ask you a few key questions. Unfortunately, Freelancer’s 1500 CHARACTER LIMIT doesn’t allow me to break everything down properly here. Let’s jump on CHAT so I can show you my PROVEN PAST WORK, walk you through the REAL RESULTS I’ve delivered, and outline a CLEAR ACTION PLAN for your project. You’ll immediately see why my approach is DIFFERENT and EFFECTIVE. If you’re serious about getting this done RIGHT, I’m ready to move forward. Looking forward to CONNECTING and WINNING TOGETHER. Cheers, Mayank Sahu

@rajmalviyamalviy

Hello, "I’ve done this before, I can do it for you—within your budget, on your timeline, and with zero hassle. Let’s get started today!" I can develop a scalable solution covering real-time screening, trade ticket preview/editing, order placement (Market, Limit, Stop-loss) across multiple brokers, and full transaction logging with CSV export. The architecture will use clean, modular broker adapters, secure OAuth/token handling, 2FA, and an admin panel for user and API key management. I also have experience integrating historical market data for strategy backtesting, with detailed performance analytics and full QuantStats reports (returns, drawdowns, Sharpe, CAGR, win rate, etc.) directly on the platform. I’m comfortable with FastAPI/Django, React-based dashboards, WebSockets, pytest coverage, and Dockerised deployments. I can share relevant demos or repositories showcasing similar systems. Looking forward to discussing this further. Best regards, Raj M

@mrkk4ever

Dear Client I saw your requirements regarding to develop a auto trading bot for multiple btoker at same time in stock market of India using python. I can develop this application ASAP based your requirements. I developed many applications is similar to your requirements. Such as indicators, analysis applications, auto trading bot for various exchanges. Let share further details. Thanks and Regards Kannadasan K

@eugenej9

Drawing on my vast experience as a project manager in the digital space, I am confident that I can deliver on your ambitious and complex Multi-Broker Trading Web App. My team is highly skilled in Python, especially in Django, Flask, or FastAPI, as well as React, Vue, and Django templates for the frontend. We have significant experience with broker APIs, WebSocket data streams, and similar low-latency Python services—all essential for your project's success. Moreover, our proficiency in screening real-time market data accurately and processing it through customized rules will ensure your trading condition library is comprehensive and reliable. The live-refreshing tables and dynamic charts you require will be meticulously incorporated into our design scheme for an interactive and resourceful user interface. Your need for clean integration layers and modular structures to accommodate future changes aligns perfectly with our scalable approach to projects. We deliver high-performance digital systems that meet targets with minimal refactoring in mind. Not only can we help you manage all three brokerage partners simultaneously without compromising core logic, but we can also implement the necessary security measures such as OAuth/token storage and two-factor sign-ins to protect user accounts and API keys.

@nadiad382

With my extensive experience in backend development using Python (including Django and Flask) and strong proficiency in frontend frameworks including React, I believe I am the ideal candidate to execute your vision for this multi-broker trading web app. Digging deep into broker APIs and working with WebSocket data streams has been my bread and butter, so you can rest assured that I'm well-versed with the technological demands identified in your project description. In addition to working with high-frequency trading data in my previous roles, I have a keen eye for delivering low latency services - ensuring real-time data streaming is as seamless as possible. My attention to details extends to ensuring unit and integration tests cover at least 80% of critical paths (pytest preferred), just as you've stipulated. Also, I'm quite comfortable working with Docker for easy deployment. Finally, given your need for scalability & expandability, I emphasize clean modular integration layers - allowing you to easily add or remove a brokerage partner without necessarily refactoring the core logic. In conclusion, collaborating with me means benefitting from clean code, SEO-ready optimization, clear communication, on-time delivery, and a custom solution tailored exactly to your requirements. Let's turn your idea into a robust web app that achieves exceptional results! Don't hesitate to reach out if you require more desde me

@technosagainfot3

Hello, I can build a high-performance Python trading platform that supports real-time screening, live/paper trading with multiple brokers, and full historical backtesting with QuantStats. I have experience with broker REST/WebSocket APIs, low-latency services, and real-time UIs. What I’ll deliver (brief): Python backend (FastAPI/Django) with sub-second screening and order execution Modular broker adapters for Broker A, B, C (easy to add/remove) WebSocket-driven UI (React/Vue/Django) with live tables & charts Order preview/edit + Market/Limit/SL place/modify/cancel Historical data backtesting with full QuantStats reports Secure auth (OAuth/2FA), admin panel, audit logs & CSV export 80%+ test coverage (pytest) and Dockerized deployment with README Happy to share relevant repos/demos and discuss broker specifics and latency targets. Ready to proceed.

@sathvikj5

Hello, I’d be glad to build your Python-based trading platform covering live screening, multi-broker order execution, and full strategy backtesting. I have solid experience with low-latency Python services, broker REST/WebSocket APIs, and real-time trading dashboards. Tech Stack Backend: FastAPI (async, sub-second order placement), PostgreSQL, Redis Frontend: React with WebSockets for live tables, charts, and trade tickets Architecture: Modular broker adapters (Broker A/B/C) for easy expansion Key Features Real-time market feed with JSON-based screening rules Editable trade ticket + Market, Limit, Stop-loss orders Live & paper trading, order modify/cancel Full audit logs with CSV export Backtesting & Analytics Historical data integration for all stocks Strategy reuse between live trading & backtests Complete QuantStats performance reports Security & Deployment OAuth, encrypted API keys, 2FA, admin panel Pytest coverage (80%+ critical paths) Fully Dockerized with clear README. Why Me Proven experience with broker APIs, WebSocket streams, and low-latency Python systems Clean, maintainable architecture focused on performance and extensibility Strong understanding of quant trading workflows, not just code Happy to share a live demo or GitHub repo showcasing similar systems