Automated Daily Trading Analysis System

@diektech

Hi — Elias here from Miami. I see you're looking to automate TradingView alerts and store them in an SQLite database. This is a great way to streamline your trading analysis, but I understand that integrating multiple data sources can present some challenges. One common issue is ensuring that the alerts are received in real-time without delays. Another is managing the data effectively, especially when it comes to scaling your database as the number of alerts grows. My approach would be to set up a reliable system that consistently captures alerts and efficiently stores them in your database. I’d also implement some basic data validation to ensure you’re only working with accurate information. To get started, I’d like to know: what specific alerts are you looking to capture, and do you have any existing infrastructure that we need to integrate with? Looking forward to your thoughts.

@ZohaibRoy

⭐⭐⭐⭐⭐ Automate TradingView Alerts with Python and SQLite ❇️ Hi My Friend, I hope you're doing well. I reviewed your project needs and see you are looking for a system to automate TradingView alerts. You don't need to look further; Zohaib is here to help you! My team has successfully completed over 50 similar projects for trading automation. I will create a system to receive alerts, store them in SQLite, remove duplicates, analyze tickers using your ChatGPT model, rank them by trade probability, and generate a plain text daily report. ➡️ Why Me? I can easily build your TradingView alert automation system as I have 5 years of experience in Python, SQLite, and email integration. My expertise includes working with TradingView webhooks, data analysis, and AI-based models. I also have a strong grip on other relevant technologies, ensuring a smooth process for your project. ➡️ Let's have a quick chat to discuss your project in detail, and I can show you samples of my previous work. I look forward to talking with you! ➡️ Skills & Experience: ✅ Python Programming ✅ SQLite Database ✅ TradingView Webhooks ✅ Email Integration ✅ Data Analysis ✅ AI-Based Models ✅ Automation Solutions ✅ Report Generation ✅ Scripting ✅ Debugging ✅ API Integration ✅ Trading Strategies Waiting for your response! Best Regards, Zohaib

@Herculesz

Hi I have strong experience building Python automation systems with TradingView webhooks, Flask/FastAPI receivers, SQLite storage, duplicate filtering, scheduled jobs, OpenAI/ChatGPT API integration, ranking logic, and SMTP/email report delivery. The main technical challenge here is making the alert pipeline reliable from webhook receipt through deduplication, daily 22:00 GMT analysis, probability ranking, and plain-text report generation without missing or double-counting tickers. I can build a clean backend that stores every TradingView alert with timestamp, ticker, strategy data, raw payload, and processing status in SQLite. I can then connect your existing ChatGPT-based analysis model so all collected tickers are analyzed at the scheduled time and ranked by trade probability. The system can include duplicate rules, logging, error handling, retry-safe email delivery, and a clear daily report format that is easy to review. I will structure the code so webhook handling, database logic, analysis, ranking, and email sending are separated and easy to maintain. The final workflow will be simple to run, monitor, and adjust as your trading model evolves. Thanks, Hercules

@Guptapuru304

Hello, We've thoroughly reviewed your project details for the Automated Daily Trading Analysis System. It sounds like an exciting opportunity to integrate AI with automated trading analysis. We understand the requirements for handling TradingView alerts, data storage, analysis, and report generation, all timed perfectly at 22:00 GMT. In a previous project, we developed a similar system that automated trading alerts using AI analysis models, storing data efficiently, and delivering insightful reports. Our expertise in AI and LLMs fits perfectly with your need for ChatGPT-based analysis. With over 8 years of experience, we've honed our skills in Python, SQLite, and automation, ensuring robust and scalable solutions. Our proficiency with AI integrations, particularly with OpenAI and similar models, aligns seamlessly with your project needs. As a top 1% freelancer, we guarantee quality and reliability. Please message us with more details, and we'll provide a comprehensive proposal tailored to your project within 24 hours. Best regards, Puru Gupta Top 1% Freelancer on Freelancer.com

@CANWS

Hi, I can build an end-to-end automated pipeline that captures TradingView webhook alerts, stores them in SQLite, removes duplicates, runs your existing ChatGPT analysis model at 22:00 GMT, ranks all tickers by trade probability, generates a clean plain-text daily report, and emails it automatically. The solution will be reliable, modular, and easy to maintain, with scheduled execution, detailed logging, and clear documentation so you can update or extend it as your strategy evolves. A couple of questions: * How is your ChatGPT analysis model exposed (Python function, API, or script)? * Where will this run (VPS, local machine, or cloud server)? I can deliver a robust, fully automated workflow that requires minimal ongoing maintenance and is ready for daily use. Thanks

@skalogir

Hi, I understand you need a Python system that receives TradingView webhook alerts, stores them in SQLite, removes duplicate ticker signals, runs your existing analysis model daily at 22:00 GMT, ranks tickers by trade probability, and emails a plain-text report. I have experience building Python webhook services, TradingView alert receivers, SQLite schemas, scheduled jobs, duplicate filtering, email automation, API integrations, logging, and trading-data workflows with clean deployment documentation. I can implement a lightweight FastAPI/Flask listener, structured alert storage, deduplication rules, scheduled analysis execution, ranked report generation, and reliable email delivery using your current model. Q1: Where will this run: VPS, local machine, or cloud server? Q2: What fields are included in each TradingView alert payload? Q3: Should duplicate removal happen per day, per ticker, or by full alert content? Best regards, Stratos

@vladang

Your workflow is clear: TradingView is producing the signals, but the real value is making sure only clean, unique alerts reach your analysis model at the right time each day. I’d build this in Python with a small webhook endpoint to receive TradingView alerts, normalize the payload, and store each signal in SQLite with a uniqueness rule based on ticker, strategy, timestamp, and alert type so duplicates are rejected before analysis. At 22:00 GMT, a scheduled job would pull the day’s valid tickers, pass them through your existing ChatGPT-based model, capture scores/reasoning, then rank everything by trade probability. I’d also make the plain text report readable rather than just dumped data: ticker, score, key reason, and any skipped/error items. Email delivery would be handled with SMTP, with logging so failed sends or model errors don’t silently disappear. A small question: what exact TradingView alert payload format are you sending now? Ready to start.

@MSHOAIBK

Hello, I understand you need an automated system that receives TradingView alerts, stores and deduplicates them in SQLite, performs AI-based analysis using your existing ChatGPT model, ranks trade opportunities by probability, and generates a daily report delivered via email. I can build a reliable Python-based solution that handles TradingView webhooks, alert processing, duplicate detection, scheduled analysis at 22:00 GMT, ranking logic, report generation, and automated email delivery. The system will be designed to be modular, allowing your existing ChatGPT analysis model to be integrated as a prompt, API, or Python module. With experience in Python, SQL databases, APIs, workflow automation, reporting systems, and business process automation, I can deliver a maintainable solution with logging, error handling, scheduling, and clear documentation. I would be happy to review your existing ChatGPT analysis model and discuss the preferred deployment environment, data flow, and ranking methodology before finalizing the implementation plan. Regards, Muhammad Shoaib

@PINESCRIPTERR

Hi, I can build this as a small, reliable Python service around your existing ChatGPT-based analysis model. The flow would be simple: receive TradingView webhook alerts, validate and store them in SQLite, prevent duplicate ticker/signal entries, then run the daily analysis at 22:00 GMT and email you a plain-text ranked report. I’d structure it so each part is easy to maintain: webhook receiver, database layer, duplicate rules, scheduled analysis job, model call, ranking logic, and email sender. The SQLite database can keep raw alerts, processed tickers, timestamps, and report history so you can audit what was received and why something appeared in the final list. I’d also add logging and basic error handling, especially around webhook payloads, scheduler timing, model failures, and email delivery, so the workflow does not silently miss a day. Question 1: Will TradingView send alerts to a public server webhook, or do you want this running locally on your machine/VPS? Question 2: How should duplicates be defined: same ticker only, or same ticker plus alert type/timeframe/date? Regards, Houssame

@yuliussmayoru

Hello! The key here is making sure every TradingView alert is captured cleanly during the day, then turning that noisy alert stream into one useful ranked report at exactly 22:00 GMT. I can build this as a simple but reliable Python automation system that receives TradingView webhooks, validates the incoming payload, stores each alert in SQLite, and removes duplicates based on ticker, signal type, timestamp, or your preferred matching rule. I would set up a lightweight webhook endpoint with Flask or FastAPI, then create a scheduled daily job that pulls all unique tickers from the database at 22:00 GMT. From there, I will connect your existing ChatGPT based analysis model, run each ticker through it, capture the trade probability score, and rank the results from strongest to weakest. The final report will be generated in plain text, including ticker, signal details, probability, and any notes from your model. Then I will send it automatically by email using SMTP or your preferred mail service. I will also include clean setup instructions, database schema notes, environment variables, logging, and a simple way to test alerts before going live. This is a nice practical automation project, and I can make it stable enough to run quietly every day without babysitting. Warm regards, Yulius Mayoru

@OscarMozo

Hi, I can help you with this. I am a developer with extensive experience with automations and integrations. I've helped clients with similar projects. Let me know your interest, Sincerely, Nicolas

@mobasherreza10

As an experienced multi-disciplinary professional, my skills set me apart as a competent candidate for your Automated Daily Trading Analysis System. I have extensive knowledge in automation and data handling, which is crucial for this project's success. My proficiency with Python, SQLite, and MySQL aligns well with your database-centric needs. Also, I'm comfortable working with Automation tools including Zapier, Make, and N8n; this will undoubtedly simplify email integrations and enhance overall efficiency. Furthermore, my vast experience in software development and architecture will help me navigate the linking of your TradingView alerts to the SQLite database seamlessly.

@TechWagger2026

As an experienced web and mobile app developer, I bring a wide range of skills to your Trading Automation project. In particular, my expertise in automation, data management, and software architecture make me the perfect fit for this task. I’m skilled in Python and proficient with the use of SQLite, a key requirement for upkeeping your database. My significant experience with MySQL will be invaluable when it comes to efficiently analyzing and sorting your trading tickers' information. With over 416 successful projects completed in a career spanning 14 years, I understand "end-to-end solutions." I adopt an empathetic approach towards understanding clients' needs - both business-wise and technically - and create tailor-made products that add value to their operations. Your satisfaction is my top priority - let me use my Go-To-Market proficiency to bring faster results to your project! Let's leverage my experience to build an automated daily trading analysis system that streamlines your processes, amplifies productivity, and maximizes profits for you. I look forward to discussing this project in more detail with you soon!

@techmadigital

Hi, I’ve built multiple trading bots, TradingView webhook integrations, AI-powered trading systems, and automated market analysis platforms using Python. ✅ TradingView webhook receiver ✅ SQLite storage with duplicate detection ✅ ChatGPT-based ticker analysis integration ✅ Trade probability ranking & daily reports ✅ Automated email delivery ✅ Clean, modular, production-ready architecture Since you’ve already developed the ChatGPT analysis model, I can seamlessly integrate it into the workflow and automate the complete pipeline from TradingView alerts to ranked daily reports. I can start immediately. Thanks, Nikhil ✅ Preferred & Verified Freelancer | ⭐ 5 Star Rating | ✅ 100% Project Completion