Automated NSE & US Stock Screener

@vishal1145

Your biggest risk is API rate-limiting across four exchanges simultaneously. NSE and BSE have strict throttling rules, and if you poll too aggressively without a queue system, you'll hit 429 errors within minutes and lose real-time data flow. Quick questions - are you planning to use paid data feeds like Zerodha Kite or Alpha Vantage, or do you need me to architect a free-tier solution with smart caching? And what's your acceptable data latency - sub-second ticks or 5-minute delayed snapshots? Here's the architectural approach: - PYTHON + PYQT: Build a multi-threaded desktop app with async API calls to NSE, BSE, NYSE, and NASDAQ endpoints, using Redis for local caching to minimize redundant requests and stay under rate limits. - API INTEGRATION: Implement fallback logic across multiple data providers (Alpha Vantage, Yahoo Finance, NSE official API) so if one source throttles, the screener switches automatically without breaking your workflow. - DESKTOP APPLICATION: Package with PyInstaller for Windows, include SQLite for filter presets and CSV export, and embed a WebView component so clicking any row opens the live quote page without leaving the app. I've built three similar screeners for prop trading desks that process 10K+ symbols across multiple exchanges without API failures. Let's schedule a 20-minute technical call to lock down your data provider strategy before I start the build.

@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

@anandinfraveo

**Free to start today, I've built exactly this kind of screener before** Read through your spec and it's very doable. I'd go with Python and PyQt for the desktop shell since it packages into a clean Windows installer easily, and pull NSE/BSE via NSEpy or a paid data feed and NYSE/NASDAQ via a service like Polygon or IEX depending on your budget for API costs, happy to break down the cost tradeoffs once we talk. Local SQLite caching keeps you off rate limits between refreshes. Recent work: built a desktop portfolio tracker pulling live NSE/BSE quotes with custom alert rules, and an Electron app with a saved-filter panel and CSV export for a US equities research team. Want me to start with the filter panel and CSV export first so you can see it working end to end?

@jiyayadav

As an experienced developer with a broad skill set including C#, Java, PHP, and Python, I am confident that I can successfully deliver the automated NSE & US Stock Screener solution you're looking for. Efficient stock screening is a critical aspect of financial management, and my expertise in creating streamlined, responsive desktop interfaces aligns perfectly with your project needs. I have in-depth knowledge of frameworks like PyQt, Tkinter, and Electron which will aid in facilitating a cross-platform solution for you. Furthermore, my familiarity with commercial and open-source data APIs complements your Tech preferences for cost-effective solutions. At your disposal are trustworthy APIs to ensure accurate real-time data feed pulled from NSE, BSE, NYSE, and NASDAQ without any manual intervention. I prioritize user-friendliness in my projects, and will provide you with detailed setup instructions along with a concise yet comprehensive user guide to ensure smooth sailing. Additionally, reliable local caching implementation will eliminate unnecessary API calls ensuring efficient usage.

@KasjanovaEste

Hi, I looked at your requirements and the real priority is a dependable desktop screener that can handle the full NSE, BSE, NYSE and NASDAQ symbol universe while keeping filtering fast and API usage controlled. I’d build the Windows-first application in Python/PyQt with separate data, caching, filtering and UI layers. I’ll integrate suitable market-data APIs, document their limits and costs, and implement automatic symbol refresh, configurable filters, saved presets, sorting, search, quote links and exact CSV export. I’ll also package the application, test the four exchange workflows and provide the source, setup guide and walkthrough. Quick questions: Q1. Do you already have API subscriptions for the four exchanges, or should I evaluate suitable providers? Q2. Which specific financial fields should the initial filter panel support? These clarify the data-source constraints and the required screening model. I can keep the architecture flexible so additional exchanges or screening fields can be added later without restructuring the application. Fernando Garcia

@bojans9

I can build the Windows-first stock screener in Python with a clean desktop UI, background data fetching, local caching, configurable filters, presets, sorting, search and exact CSV export. I will separate the data-provider layer so NSE, BSE, NYSE and NASDAQ feeds can be changed without redesigning the application. For market data, I will first verify suitable licensed APIs for all four exchanges, including request limits and subscription costs, rather than relying on an unstable unofficial feed. The final deliverable will include the compiled application, commented source, setup/user documentation and a working demonstration. Bid: INR 12,500 fixed Timeline: 5-7 days

@larencea30

Hi, I can build this as a Windows-first desktop screener using Python, PySide6, SQLite, and a packaged installer. This stack provides a fast native table experience, background data processing, and straightforward distribution without requiring Python on each machine. For market data, I recommend licensed providers rather than fragile exchange scraping: • TrueData for authorized NSE/BSE real-time or delayed feeds • A US provider such as Massive/Polygon or Financial Modeling Prep for NYSE/NASDAQ • Provider accounts and subscriptions owned directly by you The application will include: • Automatic symbol-list refresh for all four exchanges • Configurable numeric/Boolean filters and saved presets • Instant local filtering, sorting, and search • CSV export matching the visible results • Quote-page links and configurable columns • SQLite caching, rate-limit handling, and refresh status • Secure API-key storage, logs, and failure recovery Estimated delivery: 6–8 days, including a provider-integration proof, interface milestone, installer, QA, source code, guide, and walkthrough. Before estimating the feed precisely, which filters and fundamentals are required, how fresh must prices be, and how many machines/users will run the application?

@apoorvar16

Hi, I can build this as a complete production-ready desktop stock screener covering NSE, BSE, NYSE and NASDAQ, with the focus on fast filtering and reliable data handling rather than just displaying market data. I have 3+ years of full-stack/software development experience and currently work as Co-founder of Zipply, building data-driven SaaS platforms, dashboards, APIs and automation systems. My implementation plan: • Windows-first desktop application using Python + PyQt or Electron, based on the best fit after finalizing the data provider • Automated symbol/data fetching for NSE, BSE, NYSE and NASDAQ • Live/near-real-time updates with intelligent local caching to minimize API usage and cost • Dynamic filter engine supporting multiple numeric and Boolean conditions simultaneously • Enable/disable filters and save reusable screening presets • Instant table updates, sorting and symbol/company search • Exact CSV export of filtered results • One-click opening of the selected stock’s full quote page • Proper handling of API limits, failed requests and stale data I’ll also help select the most cost-effective market-data API before development, clearly separating free/delayed data options from licensed real-time feeds so there are no unexpected recurring costs. You’ll receive the compiled installer, complete well-commented source code, setup/user documentation and a working demo across all four exchanges. Apoorva Co-founder, Zipply

@nakabirik

Hi, Muheebwa here, from the United Arab Emirates. Thank you very much for your chance. I have read your project description carefully. I'm a Web, AI & Android developer with over 8 years of experience working with Python, Desktop Application and API. I understand you need a Windows desktop screener that pulls NSE, BSE, NYSE and NASDAQ symbols and lets you filter, sort and export to CSV; what really matters is a data feed that does not break mid-session. The real challenge is the data source: NSE and BSE have no free official real-time API, and NYSE/NASDAQ free feeds run 15 minutes delayed. A common issue: scraping NSE gets you IP-blocked within hours, so the app needs a fallback. My approach: first, confirm one data provider for all four exchanges and check its cost. Then, build the PyQt app with cached symbol lists, filter panel and presets. Finally, test filters, CSV export and quote links, then package the installer. I've worked with Python and API on desktop tooling like this, so I watch for rate limits that only appear after a few hours of use. A few questions to better understand the scope: Q1 - Is 15-minute delayed US data acceptable, or do you need true real-time? That decides the provider and monthly cost. Q2 - Do you have a paid data subscription already? If yes, I build against it and skip scraping entirely. If this approach works for you, I’d be happy to proceed with the update. Best regards , Muheebwa

@ReonVR

I recently helped a business build a complete digital platform that improved their online operations, and if you’re not happy, you don’t have to pay. I can help you develop a reliable, scalable stock screener with a seamless experience from front end to back end. Your focus on a clean, responsive interface and efficient data handling aligns perfectly with my expertise. I can handle full stack development, ensuring a reliable data feed from NSE, BSE, NYSE, and NASDAQ, along with a flexible filter panel, local caching, and all required functionalities. I have experience with Python and can use suitable APIs to meet your needs while keeping costs in check. Even if you don’t end up working with me, you will get a free consultation, message me! Regards, ReonVR.

@muhammadaariyan

HI, a desktop application developer with 2 plus years in Python, C++, JavaScript, and API integration can build this screener with a responsive filtering workflow and reliable local data handling. Stale or inconsistent market data will make the screening results unreliable, so I would structure the app around a background data service with local caching and PyQt for the desktop interface. The cache reduces unnecessary API calls while keeping filter updates instant. The key trade off is choosing feeds that legally provide near real time data across all four exchanges, since exchange licensing can affect API cost and redistribution. Which data provider or API access do you already have, if any, and does it permit use across several installed machines? Happy to discuss details in chat. Regards, Muhammad Arriyan

@tome29

Hello, With a robust background in building APIs, the skills I bring to the table are primed for developing your automated stock screener. Your needs outline a clean, responsive desktop interface and reliable data feed - two primary elements that I specialize in. Throughout my extensive career, I have honed my command over the preferred technologies you listed (Python - PyQt/Tkinter, C#, or Java) and hold remarkable proficiency in organizing and storing vast amounts of data efficiently. Plus, as you mentioned, my exposure to a range of commercial and open-source data APIs will help in finding economical yet dependable solutions for your project. As an automation enthusiast, I commit to not only delivering a working product but also optimizing its performance consistently. I will use local caching techniques to minimize unnecessary API calls and ensure swift data processing. Further, given my well-versed understanding of backend implementation, authentication, security and deployment on major platforms like AWS, Azure or GCP among others, I will make the final installation process as smooth and simple for you as possible. I believe the most compelling reason to select me is my genuine passion for leveraging technology to amplify productivity and efficiency. Combining this with your project's comprehensive description lays the foundation for an unmatched collaboration. My previous experience developing similar tools and integrating e Thanks!

@mariamshaikh018

Hi, a desktop app that pulls live data from NSE, BSE, NYSE and NASDAQ and lets you filter, sort and export results on the fly. The fiddly part is juggling four feeds and caching them so you are not burning API calls all day. Any preferred data providers already, or should we pick ones? I've built market data dashboards with live feeds and local caching before. Regards, Mariam

@hooriyaamir

Hey, I have a few quick questions before we get started: • Do you already have a preferred data API? • How close to real-time should data be? • Will the app run on Windows only? Your project caught my attention because this is the kind of desktop tool where speed and a clean workflow really matter. I can build a stock screener that brings NSE, BSE, NYSE, and NASDAQ data into one simple interface, so you can quickly filter the companies you want without manually checking different sources. I can build the app with a flexible filter panel, numeric and Boolean filters, saved presets, quick search, column sorting, CSV export, company quote links, and local caching to reduce unnecessary API calls. I will also handle the background data updates so the symbol lists and market data stay fresh without manual work. For the first version, I would focus on Windows with Python and PyQt, unless another option makes more sense after checking the data APIs. I will clearly explain the API I use, its pricing, and any limits before development. You will receive the compiled desktop application, commented source code, setup instructions, user guide, and a demo showing the screener working across all four exchanges. I'd love to discuss the data sources and your filter requirements with you. Feel free to message me through Upwork, and we can go over the best approach and next steps. I'll be looking forward to hearing from you. Warm Regards, Hira

@zxngxtsu

Hello, I can build this stock screener as a clean desktop application with a fast, practical UI and reliable data handling. My suggested approach is Python + PyQt, because it allows quick delivery, a responsive interface, CSV export, local caching, and simple maintenance. The app can support symbol/data loading for NSE, BSE, NYSE, and NASDAQ, advanced filtering, sortable columns, quick search, saved presets, and one-click opening of company quote pages. I can structure it with: desktop UI for filtering and results background data fetching and caching CSV export matching on-screen data configurable filters and presets clean source code with setup guide short demo video after completion For market data, I can integrate suitable APIs depending on your budget and reliability requirements, and I can clearly explain the cost implications before development starts. Deliverables: Working desktop application Source code Setup instructions User guide Demo video Estimated timeline: 5–8 days depending on final API choice and feature depth. If you want, I can also help you define the best architecture first and start with an MVP version to deliver faster.

@jblignau42

The hard part here is not the screener, it is the data, and that is where these projects usually stall. NSE and BSE have no free official feed, and scraping them breaks the moment they change the site or rate limit you, which they do. So before I write a line of code I would settle which source you are using and what it costs, because a screener is only ever as good as the feed underneath it. US data is both easier and cheaper, so the two markets are not the same problem. Once that is settled the rest is ordinary work: Python with PyQt, a local SQLite cache so repeated filtering costs you nothing in API calls, saveable filter presets, CSV export, sortable columns, and one Windows installer you can copy across machines. Do you already pay for a data subscription, or is choosing one part of the job?

@morne01

?IF YOU'RE NOT HAPPY, YOU DON'T PAY.? Recently, I helped a client develop a stock analysis tool that streamlined their investment decisions. They were thrilled with the efficiency it brought to their process. I can help you create a desktop-based stock screener that pulls live data from NSE, BSE, NYSE, and NASDAQ. Your need for a clean, professional, user-friendly interface with reliable data feeds and flexible filters resonates with my experience. I have extensive experience outside of freelancer, but I am new to Freelancer. I specialize in building responsive applications using Python and C#, ensuring seamless integration and automated functionality. Regards, MORNE.

@MartinZz03

Hi, I'm a Python Algo Trading Bot Developer experienced in live market data systems. I reviewed your Trade-Ideas and StockRover images. I understand exactly what you need: a data-dense, responsive table UI with lightning-fast filtering and no chart clutter. My technical blueprint: 1. APIs: yfinance can handle US and Indian (via .NS/.BO) markets for free. For fundamental data (like your MarketSmith screenshot), I can integrate AlphaVantage or EODHD. 2. Engine: pandas will handle the heavy lifting, applying complex Boolean/Numeric filters across 10,000+ tickers instantly. 3. Caching: A local SQLite database will cache the daily universe to prevent API drain. The CSV export will mirror your filtered views exactly. 4. GUI & Deploy: I will use CustomTkinter for a clean, modern interface (far superior to standard Tkinter), packaged into a simple .exe Windows installer using PyInstaller. My technical writing focus guarantees you will receive crystal-clear, commented code and a concise User Guide. I can deliver the .exe, source code, and demo video in 7-10 days. Let's discuss your preferred API provider! Best, Martino

@LuanCoetzee42

⚡ MOST FREELANCERS WILL TELL YOU WHAT THEY CAN DO. I’LL SHOW YOU WHAT I’VE ALREADY DONE I recently completed a desktop stock screener for a financial analyst, which integrated live data from multiple exchanges, including efficient filtering and export features. The client reported a 30% increase in productivity due to the tool's responsiveness and ease of use. I have over five years of experience in developing desktop applications using Python and C#. My background includes working with various APIs to ensure reliable data fetching, specifically for financial applications, which directly aligns with your requirements. I understand that your goal is to create a powerful and flexible stock screener that updates in real-time. I would implement a robust data handling system with local caching to minimize API calls, ensuring smooth operation even under heavy usage. Effective communication and execution are my top priorities, ensuring we achieve long-term success together. I'm excited to bring your vision to life. The difference between an average result and an exceptional one is usually decided before the work even begins. Regards, luan