Finalize & Expand Options Scanner

@Microlent

Hello, I understand your need to finalize and expand your Python-based options scanner efficiently. With over 5 years of experience in Python development and expertise in working with DigitalOcean, Alpaca, and options strategy modeling, I am confident in delivering the solutions you require. Based on your project requirements, I will ensure the successful integration of the last mile of code through thorough end-to-end testing. Additionally, I will expand the scanner to cover 500 optionable U.S. equities, implement live stock and options chains retrieval from Alpaca, and set up email alerts for the strongest defined-risk candidates within the specified price range. I will maintain the read-only nature of the trading functions to align with your manual entry process at IBKR. By leveraging Docker and the DigitalOcean API for provisioning, I will guarantee a seamless deployment process and provide comprehensive documentation for future reference. To kickstart our collaboration, I invite you to open a chat so we can discuss the technical approach in more detail and address any initial questions you may have. Looking forward to the opportunity to work together. Sincerely, Rajesh

@a4logic

Hello, I'm Yasir Shah, and I invite you to leverage my invaluable Python expertise to finalize and expand your options scanner. With 15+ years of experience, I have spearheaded numerous web, AI, automation, and cloud deployment projects for startups, agencies, and businesses. Your task aligns perfectly with my core competence in not just Python but also Linux and share market-oriented APIs like Alpaca. The fact that your system has already passed a significant number of unit and integration tests is remarkable, indicating a strong groundwork. And that's why you need someone like me to successfully complete it by conducting fresh end-to-end tests. Be it the code integration verification or expanding the system to scan 500 symbols four times daily or pulling live stock and options chains from Alpaca - I assure you quality deliverables aligned with your expectations. Another advantage of working with me is my penchant for clean, reproducible code - essential for a system like yours. I value clear communication and client satisfaction above all else. So if chosen for this project, you can expect nothing short of prompt responses, top-notch service, adherence to deadlines, thorough documentation updates as well as a comprehensive hand-off walkthough at project completion. Let's collaborate to take your options scanner to newer heights! Thanks!

@mak94pk

I see you need the last mile of code integration verified with fresh end‑to‑end tests and expansion to 500 equities scanned four times daily. First, I will run the current test suite in a fresh Docker container on DigitalOcean and add integration tests for the new scan logic. I will then implement the 500‑symbol schedule, integrate Alpaca market data, and build the email alert module with entry, max loss, profit, breakeven, and exit details. All code will be clean, commented, and fully reproducible. Delivery in 3 days. Do you have a preferred email service or SMTP credentials for the alerts?

@sabaehsan

Greetings, It looks like you need help finalizing and expanding your Python-based options scanner. Your project involves verifying the integration with end-to-end tests and then enhancing the system to scan 500 U.S. equities multiple times a day while pulling data from Alpaca. I can definitely assist with that. My approach would begin with ensuring that your existing tests are solid and that the integration is seamless. Once that's confirmed, I will implement the new scanning logic and set up the email notifications with all the necessary details for your defined-risk candidates. I’m well-versed in Python, Docker, and working with APIs like Alpaca, which will help ensure everything is efficient and organized. I’m excited to collaborate and make your options scanner even more powerful. Best regards, Saba Ehsan

@corpmember29

Hello, Finalize & Expand Options Scanner {{{ I HAVE CREATED SIMILAR BEFORE AND I CAN SHOW YOU }}} I have carefully reviewed your Options Scanner requirements and understand that the main goal is to verify the existing Python system, complete the deployment, and expand the scanner to approximately 500 liquid optionable US securities while keeping the entire system strictly read-only. I have 11+ years of software and automation development experience and have worked with Python, Linux, APIs, Docker, cloud deployments, market-data integrations, and automation systems. I can show you relevant previous work so you can see my experience with similar projects. I can first reproduce the existing 355-test suite on Ubuntu and verify the current deployment before making changes. I’ll identify any actual installer or runtime issues without weakening or removing existing tests, then implement the required fixes and provide a reproducible deployment and rollback process. For the scanner expansion, I’ll use a staged funnel rather than pulling complete option chains for all 500 symbols. The underlying data will be screened and ranked first, approximately 25-30 finalists will be selected, and only those symbols will go through complete option-chain processing. I can implement the four configurable market-session scans, calendar awareness, caching, provider rate limits, candidate ranking, defined-risk vertical spread construction, deduplication, and NO TRADE handling. Thanks, Christina

@denisSolution

Hi, I'm Denis, a full-stack developer who’s worked on similar Python-based scanning and alerting systems. Your options scanner is already well-tested and running, so the focus here is on stabilizing the last mile with fresh end-to-end tests and expanding the coverage to 500 symbols while keeping the Alpaca data feeds reliable. The key will be ensuring the Docker-based deployment on DigitalOcean remains reproducible and that the new scan logic stays efficient without overloading the API limits. The email module will need clear formatting for manual entry, with all critical numbers visible at a glance. I’ve handled similar Python systems that pull live market data, process scans in batches, and generate alerts with consistent output formats. The deployment and scheduling can be handled through DigitalOcean’s API and cron within the container, keeping everything self-contained. I can start working right away. Let's connect and discuss the details. Thanks, Denis.

@sdqtrades

As a seasoned IT professional with a focus on everything AI and Automation, I'm confident that my extensive skillset makes me the ideal fit for your options scanner project. Firstly, your request for AI-assisted coding aligns perfectly with my expertise, enabling me to add an extra layer of efficiency and intelligence to your system without compromising its clean and reproducible nature. Although automatic execution will be disabled as per your request, I'm well-versed in only developing read-only trading functions. This unique blend of capabilities paired with my commitment to punctuality, confidentiality, comprehensive documentation, and effective communication should set your mind at ease when entrusting this project to me. Let's get started today; I'm eagerly awaiting SSH access.

@Azursol

Hello, Your project to finalize and expand the options scanner aligns perfectly with my expertise in Python, Linux, Docker, and API integration, with a proven track record of delivering similar projects. I have successfully completed projects involving AI development and software architecture, ensuring clean, commented, and reproducible code. I propose a step-by-step approach to first verify the deployment and integration with fresh end-to-end tests, followed by expanding the scanner to cover 500 symbols and integrating live stock and options chains from Alpaca. I will focus on enhancing the email module to provide detailed information on defined-risk candidates within the specified price range. With a quick turnaround of 1–3 days, I am ready to provide fast and reliable delivery. Let's discuss how we can efficiently finalize and expand your options scanner. Looking forward to further discussing the project with you. Best regards,

@jayantkumar314

Hi,I can take the existing scanner through the final integration/E2E verification and expand it without introducing unnecessary changes to a codebase that already has strong test coverage.I would start by running the existing 355-test suite and reviewing the current deployment/integration points, then verify the complete workflow with fresh end-to-end tests before extending the scanner.

@shayankhan333

Read-only is the right call while the alert path is still being proven, so I'll gate every Alpaca and IBKR-adjacent call behind a hard switch in config before touching the scan expansion. I'll verify the end-to-end suite on the droplet, add the 4x-daily scheduler across 500 symbols with Alpaca chains, and ship the email module with entry, max loss/profit, breakeven and exit, plus Docker and handoff docs. Alpaca's options endpoints throttle hard on bulk chain pulls, so batching and caching per run matters. Python automation and API work here: https://www.freelancer.com/u/shayankhan333 1) Is the current scheduler cron, APScheduler, or something else? 2) Which defined-risk structures, verticals, iron condors, or both? Thanks Shayan

@arslanshahid386

Hi, I can help you with this project. I have relevant experience with PHP, Python, Software Architecture and can handle the work from development to testing and delivery. I've reviewed your requirements and can provide a clean, reliable, and responsive solution. Let's discuss the details and get started. Best, Arslan Shahid

@Tacticssoft

Hello, I’m an experienced Python developer specializing in API integrations, automation, Docker, and Linux deployments. I can thoroughly review your existing scanner and verify the remaining integration points with fresh end-to-end tests. I’ll extend the system to scan ~500 U.S. optionable equities four times per trading day. I’ll integrate Alpaca stock and options-chain data with all trading functionality remaining strictly read-only. The scanner will identify defined-risk candidates within your $200–$600 spread-price range. Email alerts will clearly include entry price, max loss/profit, breakeven, and exit plan. I’ll preserve your existing architecture and 355 passing tests while adding targeted coverage for new functionality. Docker, DigitalOcean deployment, scheduling, logging, error handling, and configuration will be fully documented. I can complete the work within your 1–3 day target for a fixed $140. I’m ready to begin immediately after receiving SSH/repository access and the required API/email configuration.

@AndrewJSMAN

I've built and deployed Python-based market data pipelines with Alpaca and DigitalOcean before—so this is right in my wheelhouse. I'll verify the existing test suite, add a scheduler for the 500 symbols with four daily runs, integrate Alpaca's REST API for live chains, and implement an email module that outputs entry price, max loss/profit, breakeven, and exit plan. The Dockerfile and DigitalOcean provisioning will be updated for reproducibility, with end-to-end validation before deployment. SSH access is all I need to move fast. Thanks, Andrii

@longngoc2307

==== Hi - Truong here ==== "OPTIONS SCANNER EXPANSION" — you need the final integration checked and reliable alerts running. I will first verify the existing Docker deployment and end-to-end flow, then add the 500-symbol scan schedule, Alpaca data handling, and read-only alert generation without touching execution logic. The important part is keeping your current passing tests intact while expanding features. I will keep the repo clean, reproducible, and update the docs so the system can be handed over easily. Can you confirm the current test command and whether Alpaca API credentials are already connected in the deployed environment? Looking forward to work with you

@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

@jonasdedzo

Hi there, I can finalize your Python options scanner quickly without disturbing the existing 355 passing tests or introducing any automatic trading. I’ll first verify the current deployment with fresh end-to-end tests, then complete the integration and expand the scanner to ~500 U.S. optionable symbols, running four times per trading day with Alpaca market/options data. I’ll keep execution strictly read-only for manual IBKR trading. I’ll implement defined-risk spread filtering in the $200–$600 range, with clear entry, max loss/profit, breakeven and exit-plan details in the email alerts. I’ll also handle scheduling, Docker, DigitalOcean deployment, logging, documentation and reproducible handover. I can work within your 1–3 day target and start as soon as SSH access is available. Looking forward to work with you. Thanks

@abdulhamidh2

Hello I just read about your Python options scanner on DigitalOcean, and the fact that you already have 355 passing tests tells me you're close to done—that's exactly the kind of project I enjoy jumping into. The last-mile integration work plus the expansion to 500 symbols with four daily scans is very doable in your 1–3 day window. Here's how I'd handle it. I'll start by running your existing test suite to verify the current state, then build the new scan logic as a separate module so we don't break what's already working. I've worked extensively with Alpaca's API for options chains and live pricing, and I've built similar defined-risk spread screeners before—so filtering for candidates in that $200–$600 range with clear max loss, profit, breakeven, and exit levels is something I can implement cleanly. I'll keep everything read-only, schedule the scans with cron inside Docker, and write the email module to lay out each candidate in plain, actionable language. I've also deployed several projects on DigitalOcean using their API for provisioning, so the infrastructure side won't slow us down. I can have SSH access set up and start verifying your deployment within hours of agreement. Do you have a preferred format for the email alerts, or should I match whatever your current test suite already expects? Cheers, AbdulHamid

@pasion0128

★•══•★ Hi client ★•══•★ I see the issue—your current setup is slow and eats up too much manual work. That’s exactly what I’d fix first. My approach is simple: find the bottleneck, solve it cleanly, and test everything before handing it back. No guesswork, no endless back-and-forth. I’ve done similar fixes before, so you’re not getting a rookie experimenting on your project. Shall we get started? Best regards, Rico

@demivision

Hi there, Thank you for sharing such a detailed project brief—I appreciate the clarity around your requirements and current stack. I’m confident I can help you finalize and expand your options scanner to robustly cover 500 US equities, integrate new scan logic, and deliver actionable email alerts while maintaining strict read-only safeguards. I have extensive experience working with Python-based trading and analytics systems on Linux, with multiple deployments on DigitalOcean using Docker for containerized, reproducible environments. My background includes integrating with APIs like Alpaca and IBKR, and architecting options strategy screeners that focus on defined-risk plays. I’m comfortable handling high-volume data pulls, optimizing scan performance, and ensuring reliability through comprehensive testing. For your project, I would begin by reviewing your existing unit and integration tests, then design and execute end-to-end test cases to validate full workflow integrity. Once stability is confirmed, I’ll expand the scan logic to efficiently handle 500+ symbols on schedule, ensuring data integrity and resource efficiency. I’ll build a robust email module to distill each candidate’s entry price, risk/reward, breakeven, and exit plan in an actionable format. Updated documentation, a clean Dockerfile, and a detailed hand-off walkthrough will be provided for seamless future maintenance. If you’d like to see relevant examples of my work with Python, DigitalOcean, and market data APIs, I’m happy to share links and code snippets. I’m ready to start as soon as access is provided and look forward to collaborating closely to meet your goals. Best regards, DemiVision, LLC