Python Developer for Real-Time Dashboard

@ZohaibRoy

⭐⭐⭐⭐⭐ Build a Real-Time Data Dashboard for NSE F&O Stocks with Python ❇️ Hi My Friend, I hope you are doing well. I've reviewed your project requirements and noticed you're looking for a Python developer to create a real-time web-based dashboard. Look no further; Zohaib is here to help you! My team has successfully completed 50+ similar projects for building efficient data processing systems. I will connect to the Angel One SmartAPI to stream live data, maintain a historical cache, and design a user-friendly dashboard to display the processed information. ➡️ Why Me? I can easily build your real-time dashboard as I have 5 years of experience in Python development, focusing on data processing, API integration, and UI design. My expertise includes working with databases like Redis and SQLite, ensuring a smooth data pipeline and effective performance. I also have a strong grip on frontend frameworks, enabling me to deliver a comprehensive solution. ➡️ Let's have a quick chat to discuss your project in detail. I can also share samples of my previous work. Looking forward to our conversation! ➡️ Skills & Experience: ✅ Python (Pandas, NumPy, Asyncio) ✅ WebSocket API Integration ✅ Data Pipeline Development ✅ Redis / SQLite Caching ✅ Frontend Development (Streamlit, Dash) ✅ Data Visualization ✅ Real-Time Data Processing ✅ Modular Code Design ✅ Database Management ✅ Performance Optimization ✅ Technical Documentation ✅ Problem Solving

@dvcontact

Hello Sir, How about I build a demo of the real-time dashboard solution before any commitment? With my expertise in Python and proven experience developing real-time data pipelines, I can create a robust system that streamlines the ingestion of live market data and processes it with custom indicators effectively. Let’s discuss how this innovative dashboard can empower your trading strategies, and I can provide you with a detailed plan and the demo at your earliest convenience. Regards, Smith

@denisSolution

Hi, I'm Denis, a full-stack developer experienced with real-time data pipelines and dashboards for financial systems. I've built live market data streams, WebSocket integrations, and modular calculation engines—exactly what you need. I understand your system must reliably ingest live NSE F&O data, maintain clean historical caches, and execute custom calculations independently. This separation lets you iterate on metrics without touching the pipeline or UI. My approach: Set up the Angel One WebSocket connection with robust error handling and reconnection logic. Build a local Redis or SQLite cache storing 1-minute and 5-minute candles efficiently. The calculation engine sits as an isolated module receiving dataframes and returning results—easy to modify formulas later. For the frontend, Streamlit is ideal for fast development and real-time updates. I'd structure it with summary cards, then an interactive table with live sorting, filtering, and search that refreshes as new candles close. Key consideration: data consistency during market hours. Aggregating 1-minute ticks into 5-minute candles while streaming requires synchronized caching and clean data rollover. I'll handle this with careful timestamp management and a clear rollover strategy. The timeline is tight but realistic with clear requirements. I'll need to confirm exact Angel One API behavior and test credentials. I'm ready to start immediately. Let's discuss the details. Thanks, Denis.

@koolvishruth

Hello Sir, I have build Trading dashboard also used DHAN API for it.I am software developer with 7 years of experience. Let’s connect

@Eliteinno

Hello, This is a well-defined Python data pipeline, but the real complexity is keeping WebSocket data, candle aggregation, historical seeding, rolling storage, and indicator execution synchronized across roughly 210 symbols. I’d structure the backend so ingestion, candle management, calculations, and dashboard delivery remain independent modules, with the indicator functions receiving clean Pandas dataframes exactly as specified. Redis or SQLite can handle the rolling cache depending on the required concurrency, while Streamlit can provide the interactive table without complicating the processing layer. I’d also account for reconnects, duplicate/missing ticks, market-session boundaries, API rate limits, and startup recovery so the dashboard does not silently produce incorrect metrics. Is the expected deployment a single machine, or will the processing and dashboard run separately? Have a nice day

@dataspro

Nice to meet you , It is a pleasure to communicate with you. My name is Anthony Muñoz, I am the lead engineer for DSPro IT agency and I would like to offer you my professional services. I have more than 10 years of working as a Backend and Software developer, I have successfully completed numerous jobs similar to yours therefore, and after carefully reading the requirements of your project, I consider this job to be suitable to my area of knowledge and skills. I would love to work together to make this project a reality. I greatly appreciate the time provided and I remain pending for any questions or comments. Feel free to contact me. Greetings

@arslanshahid386

Hi, I noticed you're looking to build a real-time web-based dashboard for ~210 NSE F&O stocks, utilizing the Angel One SmartAPI for live market data. I specialize in Python and JavaScript, which are ideal for creating efficient data processing pipelines and interactive web interfaces. With my expertise in these technologies, I can develop a modular calculation engine to execute your custom indicator logic seamlessly. This will ensure the dashboard is lightweight yet powerful, maintaining a 1-day rolling historical cache of intraday candles for accurate analysis. Could you provide more details on the specific custom indicators you envision for this dashboard?

@lazarr4

Hello, I can build a modular real-time dashboard using Python, Streamlit, and Angel One SmartAPI while keeping the calculation engine independent of the data pipeline. I’ve built a similar system for a stock tracking tool that used Redis for caching and modular indicator functions—it processed 150 NSE stocks in real-time with 200ms latency. I’d structure this with a WebSocket handler for live data, SQLite for 1-day history, and Streamlit for the dashboard—keeping the indicator calculations in a separate Python file to allow future formula changes without touching the pipeline. The biggest improvement will come from using Redis for real-time updates instead of polling, which will make the dashboard feel instant. Proper setup will let you monitor stocks with real-time metrics and filters without waiting for manual data refreshes. I’ll also include a clear documentation on how to update the indicator formulas later. Once the project is complete, I’ll walk through the setup and ensure the dashboard works smoothly before handing it over. If this approach fits your needs, I’d be happy to discuss the technical details further. Thanks, Lazar.

@codeandcommand

A real-time dashboard in Python usually lives or dies on the data pipeline, not the charts. I would use Streamlit for the front end with Pandas handling the processing, and structure it so refresh intervals do not choke on larger datasets. Can start today, working version by Friday. The budget and timeline here are starting points based on the post. Once we go over the actual data sources and refresh needs, I will firm both up. Want me to send a quick scope doc so we can get moving?

@SkillCrafts

I can efficiently build your real-time NSE F&O dashboard, leveraging Python's robust ecosystem to mirror the performance and low-latency requirements you've outlined. My experience with streaming data APIs and asynchronous processing is directly applicable to ingesting and handling live market data from Angel One SmartAPI. My technical approach will involve FastAPI for the backend framework, enabling high-performance API endpoints and WebSocket communication. I'll utilize `asyncio` and libraries like `websockets` or `aiohttp` for efficient real-time data ingestion and processing. Pandas will manage the 1-day rolling historical cache, and I'll design a modular Python class structure for the calculation engine to easily integrate and test custom indicator logic. The frontend will be built with a lightweight framework like Streamlit or Dash for interactive table rendering. To ensure alignment, could you elaborate on the expected update frequency for the real-time data, and are there any specific charting libraries you prefer for the interactive dashboard? I'm eager to discuss how my skills can bring this project to fruition.

@Abror86

Hi, Abror here, from Uzbekistan. "Real-Time Trading Dashboard System" - I can build your Python dashboard with live market data processing and modular indicators. I can develop the system using Python, Pandas, WebSockets, Redis/SQLite, and Streamlit to process real-time NSE stock data efficiently. I can integrate Angel One SmartAPI, create caching pipelines, modular calculation engines, interactive dashboards, and maintainable architecture for future formula changes. I will deliver tested source code, environment setup, documentation, backend scripts, and dashboard launch instructions within your expected development timeline. Can you provide Angel One SmartAPI access details and indicator formulas? Could you please clarify the following questions to help me better understand the project? : 1. Which indicators should be implemented initially? 2. Do you prefer Redis or SQLite for local data storage? 3. What deployment environment should support the dashboard? Looking forward toworking with you. thanks

@loxtic

Hi, how are you doing? I have considerable experience with Python, async data pipelines, and real-time dashboards, including working with market data streams and caching with Redis/SQLite. I’ve built modular calculation engines and lightweight frontends using Streamlit and Dash, plus integration with WebSocket feeds. I can deliver a clean codebase, clear docs, and a runnable environment in 3–5 days. Let me know further if interested.

@obademio1

Hello, With over 10 years of experience in Python and web development, I am confident in delivering a high-quality real-time dashboard and data processing pipeline for your project. I have thoroughly reviewed your requirements and understand the need for a lightweight system that efficiently processes live market data from NSE F&O stocks. I will ensure seamless data ingestion from Angel One SmartAPI, implement a robust caching mechanism using Redis or SQLite, and develop a modular calculation engine for custom indicators as per your specifications. The frontend dashboard will be interactive and user-friendly, providing real-time data visualization and filtering options. Let's discuss your project further in detail. Please feel free to start the chat so we can explore the project requirements and my approach to achieving your goals. Best regards, Olusoji

@ujjwalmahar01

I will start by implementing the Angel One WebSocket V2 handler to manage the stream for 210 symbols and setting up a Redis cache to handle the 1-day rolling window for intraday candles. I will structure the calculation engine as a decoupled module where you can update your mathematical formulas in the indicator file without touching the ingestion logic. A few questions to better understand the scope: Q1 - Are you currently using a specific Python library for the Angel One authentication and WebSocket connection? Q2 - Should the dashboard refresh rates be set to a fixed interval or triggered immediately upon candle close? Q3 - Do you have a preference between Streamlit for rapid deployment or a FastAPI backend with a custom HTML/JS frontend for the dashboard? I am ready to start on the repository setup and the data pipeline immediately.

@GenomyR

Good day, Regarding your project (Python Developer for Real-Time Dashboard): I can build and optimize the store with a streamlined checkout flow, mobile-responsive styling, and verified payment gateway configuration. My delivery approach: 1. Stage 1 (50% Milestone): Catalog setup, theme configuration in Python / Django / FastAPI and PostgreSQL / Supabase / Firebase, and staging review within 2-3 business days. 2. Stage 2 (50% Milestone): Payment gateway integration, mobile checkout QA, and live production launch. Which specific payment processors (Stripe/PayPal) and third-party apps do you need configured? Best regards, Tumisang

@Maanie786

Hello, I understand you need a Python developer to create a real-time dashboard for NSE F&O stocks, integrating live data from the Angel One SmartAPI. My expertise in Python, particularly with Pandas and WebSockets, aligns perfectly with your requirements. I can design a robust data pipeline that efficiently caches historical data and implements your custom calculation engine for Metrics A and B. Additionally, I have experience with frontend frameworks like Streamlit, which will ensure an interactive and user-friendly dashboard. Starting a conversation could provide you with valuable insights, even if we don't proceed. The worst that could happen is you get a free consultation from me about your project. Regards, Maanie

@bojans9

Hello, this is Bojan. Thank you for sharing your project. To be transparent: although I work in software development, backend systems, automation, and embedded engineering, I don’t take on real‑time trading dashboards or broker‑API market‑data systems, including SmartAPI WebSocket ingestion, intraday candle caching, modular indicator engines, or Streamlit/Dash‑based live dashboards. This scope requires a developer focused specifically on market‑data pipelines and trading‑tech architectures - outside my domain. Since you need live NSE F&O ingestion, rolling OHLC caching, modular metric functions, and a real‑time interactive dashboard, a specialist in trading‑data engineering will serve you much better. If you ever need technical workflow planning or automation strategy, I can help - but I’m not the right fit for this project.