Python + AI Script for Stock Summary

@programmingarena

Hello there, ✸✸✸Python Expert is Here✸✸✸ I’ve checked your project – “Python + AI Script for Stock Summary” And read the description carefully. As a professional Python Developer, I’m able to “build a clean script that can be executed at the end of the trading day” as you required. I’ve completed a lot of Python project based on ✔Django, ✔Pandas, ✔Flask, ✔FastAPI, ✔Jupyter Notebook, ✔Automation, ✔Selenium & etc. Libraries in various platform. Here are some of my recent completed Python Project: ✔️ https://www.freelancer.com/projects/api-developmet/Python-IBKR-Trading-Template/details ✔️ https://www.freelancer.com/projects/python/Python-Programmer-for-Mathematical/details ✔️ https://www.freelancer.com/projects/python/Looking-for-Python-expert-code/details ✔️ https://www.freelancer.com/projects/python/Python-Backgammon-Game-Debugging-37926848/details Also you can visit my profile and check all the Reviews of my previous all Python Project to get the idea about my knowledge and skills. I’m ready to be hired or ready to be awarded as I can start this task Right Now. So, come on chat box and let’s connect. Best Regards! Eng. Bablu Mondol

@ASSAMWEB

Greetings, I have reviewed your project description and recently worked on a similar project. I believe I can help you deliver this successfully. Let’s open a chat to discuss your requirements in detail and determine the best approach for your project. Regards,

@michaelbukachi

Hi, I am a senior Python developer with extensive experience building automated financial data scrapers and integrating LLM APIs for structured document intelligence. I can deliver a clean, turnkey daily announcement processing script tailored to your exact workflow. Implementation details: 1. Announcement Extraction: Resilient Python script to pull daily BSE/NSE corporate announcements directly from public exchange endpoints, handling pagination and rate limits cleanly. 2. LLM Analysis Engine: Structured API prompt (OpenAI or Claude) generating consistent, deterministic outputs: - Concise AI Summary (TL;DR) - Objective Impact Assessment (Positive, Neutral, Negative) - Action Required 3. Structured Excel/CSV Output: Automatic generation of your daily workbook matching the exact 8-column layout: Timestamp, Company Name, Ticker, Original Title, AI Summary, Impact Assessment, Action Required, URL Link. 4. Beginner-Friendly Handover: A clear, step-by-step markdown/PDF guide covering Python installation, entering your API key in a .env file, and running the tool with a single command. Would you prefer OpenAI (gpt-4o-mini for minimal cost) or Anthropic Claude for the summarization engine? Looking forward to hearing from you.

@DeyaaAhmed

Hi, I can build your automated Python script to scrape daily BSE/NSE corporate announcements and generate AI-powered summaries with impact assessments using OpenAI's API. I will ensure the output matches your exact Excel/CSV column structure including Timestamp, Company Name, Ticker, Original Title, AI Summary, Impact Assessment, Action Required, and URL Link, while implementing robust error handling for market data sources. The solution will be delivered as clean, executable code with comprehensive beginner-friendly documentation covering Python installation, library setup, API key configuration, and daily execution steps so you can run it independently without technical support. You will receive the complete script, sample output file, and handover guide ensuring seamless daily operation post-delivery. My extensive experience integrating LLM APIs with financial data pipelines guarantees accurate summarization logic and reliable automation tailored specifically to Indian stock market announcement formats. I also offer FREE post-delivery support to verify initial summary accuracy, troubleshoot any API rate limits or scraping changes, and assist with minor prompt adjustments during the first month. Let's discuss the project in more details.

@anandinfraveo

**Available now to build your BSE/NSE daily summary script** I will build you a one-time Python setup you can run yourself daily after market close 1. Python: clean script pulling daily BSE/NSE corporate announcements with ticker title timestamp and URL 2. AI: each announcement sent to OpenAI API to generate AI Summary TLDR plus Impact Assessment as Positive Neutral Negative plus Action Required in plain words 3. Excel/CSV: daily file with your exact columns Timestamp Company Name Ticker Original Title AI Summary Impact Assessment Action Required URL Link 4. Handover: beginner-friendly steps to install Python install libraries add your own API key and run daily plus testing with you I bring Strong Python scraping and financial data work plus Experience with OpenAI and Anthropic summarization and I am Able to write simple non-technical handover docs Recent work: NSE results tracker to Excel saving 10 hrs weekly; AI news summarizer with sentiment tags for a trader I can do this fixed-price for $149 in 3 days — can you share a sample Excel row so I match columns exactly

@vishal1145

Your script will fail if BSE/NSE rate-limits your scraper or if their HTML structure changes mid-run. Most developers hard-code selectors that break within weeks, leaving you with incomplete data and no way to debug it yourself. Quick questions - are you planning to scrape directly from BSE/NSE websites, or do you have API access? And what's your fallback if OpenAI hits token limits on days with 200+ announcements? Here's the architectural approach: - PYTHON + WEB SCRAPING: Build a resilient scraper with retry logic and fallback parsers that handle BSE/NSE structure changes without breaking your daily runs. - OPENAI INTEGRATION: Implement batch processing with token management so you don't hit rate limits, plus cost tracking so you know exactly what each daily run costs before scaling. - EXCEL OUTPUT: Generate structured CSV files with proper encoding for Indian company names and validation checks to catch missing data before you act on incomplete summaries. I've built similar financial data pipelines for 2 fintech clients that process 500+ daily filings without manual intervention. Let's schedule a quick call to walk through edge cases like market holidays and API failures before you commit to a build.

@muneeb6767

I can build a clean Python script to collect daily BSE/NSE corporate announcements, send the original text to OpenAI/Anthropic for TL;DR, impact assessment, and action-required analysis, then generate your exact Excel/CSV structure with timestamps and source links. I’ll also provide beginner-friendly setup instructions so you can run it daily with your own API key.

@prashanpatel557

Hello, I can build your one-time Python automation to collect daily BSE/NSE corporate announcements, process them through an AI API, and generate the required Excel/CSV report. I have experience with Python automation, financial data processing, web/API integrations, Pandas, Excel generation, and LLM API integration. I can implement: - Automated collection of daily BSE/NSE announcements - Company, ticker, timestamp, title and source URL extraction - OpenAI/LLM integration for concise summaries - Positive / Neutral / Negative impact assessment - Action Required classification - Exact Excel/CSV column structure you specified - Duplicate handling and basic error/retry logic - API-key configuration through a simple environment/config file - Clean, beginner-friendly setup and daily execution instructions - Complete source-code handover I will keep the script modular so announcement sources or the AI provider can be changed later if required. Price: ₹10,000 - 15000/- Estimated delivery: 3–5 days I can start by confirming the preferred BSE/NSE announcement sources and AI API. Regards, Prashant Patel

@zditanuel

Hi! Your BSE/NSE daily summary pipeline is exactly the kind of Python automation I build. I hold a 5.0 rating across 39 reviews working with Python, web scraping (Selenium, Scrapy, XPath) and API integrations. My plan for your one-time setup: 1. Scraper module for BSE + NSE daily corporate announcements, with retry and error handling so one bad response never breaks the run. 2. OpenAI API integration generating exactly your columns: TL;DR summary, Impact assessment (Positive / Neutral / Negative), and Action Required. 3. Excel export matching your template: Timestamp, Company Name, Ticker, Original Title, AI Summary, Impact Assessment, Action Required, URL Link. 4. Handover: clean commented code plus a beginner-friendly guide (installing Python, installing libraries, adding your API key, and the daily run, including optional Windows Task Scheduler automation). I will deliver the tested script plus docs in 3 days and do a live run with you on day one so you can operate it yourself with confidence. One question before I start: should the script rely only on official BSE/NSE endpoints, or is HTML scraping an acceptable fallback if an endpoint is unavailable? Thanks, I can start right away.

@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

@UzeeTech

Your BSE/NSE announcement summarizer needs dependable end-of-day collection, a stable schema, and transparent AI output—not a spreadsheet that silently misses items. I’ll keep impact as documented classification, not a trading signal. I’ll build configurable Python collection from approved URLs/API, with date filters, deduplication, retries, and logs. It will normalize text, preserve title/URL, send required content to the LLM, validate summary/impact/action, and write the supplied Excel/CSV columns. Secrets stay out of source, prompts are versioned, and failures are recorded for retry. I’ll add timezone-aware scheduling guidance, sample fixtures, output checks, and beginner-friendly setup for Python, libraries, credentials, and daily runs. My relevant real work includes Jyotish AI on Android/web and an AI website generation platform, backed by 9+ years; I won’t claim financial-data deployment. Which official BSE/NSE source or API should be used, and which LLM provider do you prefer? My ₹7,000 bid covers 5 days for the script, AI integration, Excel/CSV output, tests, documentation, and handover. I can begin with the source and column-schema review.

@NEHABHAT92

As an experienced developer with a strong background in Python, I am well-equipped to handle your project and deliver the stock market script you need. Over my 9+ years of experience, I have honed my skills in web scraping, financial APIs, and data manipulation with Python. Additionally, I have previous experience working with OpenAI and Anthropic APIs for text summarization - making me adept at leveraging AI technologies to meet your requirements. What sets me apart is my ability to write clear, beginner-friendly instructions. This means that after I've built and tested the script to your satisfaction, I'll provide you with comprehensive documentation that will walk you through every step of the process. In terms of pricing, I'm open to discussing this with you further. My aim is to provide effective cost of project along with efficient and quality service. Ultimately, selecting me for this project means you're choosing a highly skilled professional dedicated to turning your vision into reality while offering continued support and value in the long run.

@Tacticssoft

Hi, I’m an experienced Python and AI developer and can build a reliable end-of-day script that collects BSE/NSE corporate announcements and converts them into structured AI insights. I’ll implement the announcement collection layer with proper filtering, deduplication, timestamps, company/ticker mapping, URL capture, and error handling so the daily run produces consistent results. For AI processing, I can integrate OpenAI or another LLM API to generate the requested TL;DR, Positive/Neutral/Negative impact assessment, and Action Required in a controlled structured format. The output will follow your exact Excel/CSV columns: Timestamp, Company Name, Ticker, Original Title, AI Summary, Impact Assessment, Action Required, and URL Link. I’ll also handle API failures, missing announcement content, duplicate records, rate limits, and invalid responses so one problematic announcement does not stop the entire run. The final Python code will be clean, configurable, and easy to run manually or schedule at the end of each trading day. You’ll receive beginner-friendly documentation covering Python installation, dependencies, API-key configuration, script execution, troubleshooting, and daily usage. I’m available to start immediately and can deliver the complete script, testing, and handover documentation as a self-contained project.

@bojans9

Hello Hope you are doing well "Automated Stock Announcement Summarization" - I can build it using Python, OpenAI API, web scraping, and automated Excel generation. I can develop reliable BSE/NSE collection, AI summaries, impact classification, action recommendations, URL tracking, and exact Excel or CSV output formatting. I will provide clean Python code, API-key configuration, dependency setup, daily execution instructions, testing, validation, and complete beginner-friendly handover documentation. Would you prefer OpenAI API integration or support for multiple AI providers? Looking forward to working with you.

@mikes126

The key here is making the daily process reliable enough that you can run one Python command after market close and get a clean Excel/CSV report without manually cleaning announcements or AI output. I’d build the script as a simple pipeline: BSE/NSE announcements → extract/normalize data → AI analysis → structured Excel/CSV It would cover: Daily collection of corporate announcements from the required BSE/NSE sources Timestamp, company, ticker, title and original URL extraction Handling of announcement text/PDF content where required OpenAI/Anthropic API integration for: TL;DR summary Positive / Neutral / Negative impact Action Required Strict structured output matching your exact columns Error handling for missing/duplicate announcements and API failures API key stored separately rather than hard-coded CSV and Excel generation

@naeem1114

Hi, I see that handling large volumes of daily corporate announcements from the Indian stock market can be tricky, especially when it comes to summarizing them accurately using an AI API like OpenAI ChatGPT. I'd approach this by setting up a Python script that can efficiently scrape the announcements and then integrate it with the AI API for summarization. This way, the script can output a daily Excel/CSV file with the required information. In my experience, a common mistake is not accounting for variations in announcement formats, which can affect the AI's summarization accuracy. I'll set up the script to handle such variations and ensure the AI integration is robust. I'm ready to start immediately, and I'll make sure the handover documentation is clear and easy to follow, so you can run the script daily without any issues.

@adriank06

Hi, This is a project I can help with. I can build a Python script that collects corporate announcements, sends the relevant text to an AI model for summarization and impact analysis, and generates a clean Excel/CSV report with the fields you need. I’ll keep the script simple to run daily and include clear setup instructions so you can use it without needing a developer every time. The main thing I’d like to confirm is which announcement sources you prefer to use (official BSE/NSE feeds, websites, or another source). I can start right away. Thanks

@petropankovdev

Hi, this is a good fit for us: a daily Python script that pulls the BSE/NSE corporate announcements, sends each one to the LLM and writes the Excel/CSV in your exact 8 columns (Timestamp, Company Name, Ticker, Original Title, AI Summary, Impact Assessment, Action Required, URL Link). How I would build it: - Pull the day's announcements from the exchanges' public announcement feeds, not by clicking through pages, so it stays fast and stable. Many filings are PDF attachments, so the script extracts the PDF text before summarising, otherwise the AI only sees a one-line title. - One structured prompt per announcement returning TL;DR, Positive/Neutral/Negative and Action Required, so the columns never come back messy. Your own API key goes in a small config file. - Duplicates skipped if you run it twice, and a failed item is logged instead of stopping the whole run. Handover: the code plus a beginner guide (install Python, libraries, add your key, run it daily), written for someone who has never used a terminal. As a first step I can send you a sample file from one real trading day so you can check the summaries before we finish. Our account has two completed projects, both rated 5 out of 5, delivered on time and on budget. We have also built large scrapers that collect data from public sources into clean spreadsheets. Price 8000 INR, 4 days. Petro Pankov, BotCraft Group

@alfatrade2

BSE and NSE don't expose a public announcements API, so the pull step means scraping their corporate-announcements pages or using a paid feed like NSE's bulk data — which one are you expecting, since that changes the reliability of the daily run? I've built scrapers that sit behind anti-bot protection and feed structured data into downstream processing, so the crawl and Excel export side is straightforward. For the AI layer, do you want the impact assessment forced into just those three labels, or should the model explain its reasoning too?