Market Arbitrage Python Script

@techplusintl

Hi there, ★★★ Python Expert ★★★ 4+ Years of Experience ★★★ I understand you're looking for a Python script to identify arbitrage opportunities between Polymarket and Kalshi. To tackle the matching logic, I will implement tokenization and Jaccard similarity to ensure accurate pairing of bets, even with different wording. The script will poll the APIs every 30-60 seconds, extract the necessary data, and compile it into a JSON payload for your existing API. I'll ensure the code is clean and well-commented, and I'll handle rate limits gracefully by implementing retries and backoff strategies. Deliverables will include: 1. A Python 3 script with clear documentation. 2. A configuration section for API keys and polling intervals. 3. Sample output files for verification. 4. A README for setup and error handling. Ready to get started!

@ZohaibRoy

⭐⭐⭐⭐⭐ Create a Python Script for Cross-Platform Arbitrage Opportunities ❇️ Hi My Friend, I hope you're doing well. I just checked all of your project requirements and I can see you are looking for a Python script to identify arbitrage opportunities between Polymarket and Kalshi. You have no need to look any further as Zohaib is here to help you! My team has successfully completed over 50 similar projects focused on Python automation. I will build a solution that polls both platforms, identifies matching bets using advanced techniques, and compiles the necessary data into a JSON payload for your API. ➡️ Why Me? I can easily create your Python script to identify arbitrage opportunities as I have 5 years of experience in Python development, specializing in API integration, data analysis, and automation. Additionally, I have a strong grip on handling rate limits and ensuring clean, well-commented code. ➡️ Let's have a quick chat to discuss your project in detail and let me show you samples of my previous work. Looking forward to discussing this with you in chat. ➡️ Skills & Experience: ✅ Python Development ✅ API Integration ✅ Data Analysis ✅ JSON Handling ✅ Automation Scripting ✅ Error Handling ✅ Rate Limiting Strategies ✅ Logging Solutions ✅ CSV/JSON Backup ✅ Code Optimization ✅ Clean Code Practices ✅ Market Analysis Waiting for your response! Best Regards, Zohaib

@nikhilgarg96

Hello Greetings, After reviewing your project description, I feel confident and excited to work on this project for you. But I have some crucial things and queries to clear out. Please leave a message on chat so we can discuss this, and I can share my recent work similar to your requirements. Thanks for your time! I look forward to hearing from you soon. Best Regards.

@rizwange4

Hi There I just read your project details regarding the Project: Market Arbitrage Python Script Can we do a quick chat right now so that we can discuss the project briefly? I have 10 years of experience in PHP, WordPress, Woocommerce, Cake Php, Codeigniter, Magento, Shopify, Laravel, Adobe Photoshop, Adobe Illustrator, CorelDRAW, Bootstrap, HTML, CSS, Angular, Javascript, jQuery, and My SQL. I appreciate Muhammad Rizwan Atif

@DeveloperStation

Hi, We’ve built similar Python scripts that monitor multiple sources for arbitrage opportunities, including a product that checks Amazon and eBay prices to find profitable reselling options. We used advanced techniques like web scraping, browser automation, and API integrations to ensure reliable data collection. For your project, we can implement a robust matching algorithm that uses NLP techniques to identify similar events, even if the wording differs. We can also add features like email alerts for new opportunities and a web dashboard to manage and review signals. Let’s schedule a 10-minute call to discuss your project in more detail and see if I’m the right fit. I usually respond within 10 minutes. Best regards, Adil

@C0RETECHIES

Hi there, I see you're building an arbitrage detection script. The workflow is clear: poll Polymarket and Kalshi, perform a semantic match on the markets to find identical events despite wording differences, calculate the margin, and then push a structured JSON payload to your API endpoint, with a local backup for redundancy. To tackle the matching logic, I'd go beyond Jaccard similarity and use a sentence-transformer model. This converts market descriptions into dense vector embeddings. By calculating the cosine similarity between these vectors, we can find true semantic matches with high accuracy (e.g., >0.98 similarity). This is robust against rephrasing. For rate-limiting, the script will use httpx for efficient, asynchronous requests and implement an exponential backoff strategy with jitter when a 429 status is received. I'll also add a simple request governor to ensure we don't exceed a safe number of calls per minute, which we can tune. All configurations (API keys, endpoints, polling interval) will be managed via a standard .env file. Questions: 1. Do markets share common identifiers (e.g., category slugs) that can be used for a fast initial filtering pass before applying the NLP model? 2. Are you aware of any undocumented API rate limits, or should the script be built to discover and adapt to them cautiously? 3. Does your target API for receiving the JSON payload require any specific authentication headers, like a Bearer token?

@onkarkulkarni8

Hello, I can help with your "Market Arbitrage Python Script" project. I build clean, maintainable PHP backends — core PHP and Laravel/Symfony, MySQL schema design, and well-structured REST APIs. For work involving php, javascript, python, data processing, software architecture, json, api, data analysis, I pay close attention to validation, security, and readable code, delivering in small, testable milestones. I provide clean commits and clear documentation. Can we discuss the specifics before I firm up the timeline? ⭐ 5.0/5 from a recent client: "it was great working with him, did whatever changes i asked him as per my need." Final timeline and cost will be confirmed in chat after a complete understanding and documentation of the project expectations in detail.

@Tanmoy236

Hi There! I specialize in Python automation and API integrations with 9+ years of experience, building reliable data-processing tools that are accurate, maintainable, and production-ready. Here’s how I can help: 1. Build a Python script to poll Polymarket and Kalshi with smart event matching using tokenization and Jaccard similarity. 2. Handle rate limits, logging, JSON/CSV backups, and API payload delivery reliably. 3. Deliver clean, documented code with .env configuration, sample outputs, and a concise README. Do Polymarket and Kalshi already provide the API endpoints you want to use, or should I integrate their public APIs directly?

@usmanbashir12100

Hi I can build a reliable Python service that continuously polls Polymarket and Kalshi identifies true cross-platform arbitrage opportunities and pushes structured JSON payloads to your API. For matching I'd use a combination of text normalization tokenization Jaccard similarity and metadata such as market category and close date to ensure only equivalent events are paired. The script will include configurable polling intervals graceful rate limit handling with retries and backoff local CSV or JSON backups detailed logging and clean well documented code that is easy to maintain and extend. I'd be happy to discuss the API details and get started. Best Muhammad Usman

@XanvraTECH

Hello, I am interested in developing the Python script for the Market Arbitrage project. I understand the requirements of polling Polymarket and Kalshi for open markets, identifying arbitrage opportunities, and pushing JSON payloads to the API with relevant data. With expertise in Python, API integration, and data processing, I plan to use tokenization and Jaccard similarity for accurate market matching. - MY WORK STATS: ✨ https://www.freelancer.com/u/XanvraTECH I suggest a follow-up discussion to further delve into the matching logic and rate-limit strategies. Looking forward to working on this project. Best regards, Warda Haider

@ShaikhAneesa

Hi there, I have carefully analyzed the requirements for the Market Arbitrage Python Script project. I understand that you need a Python script to identify arbitrage opportunities between Polymarket and Kalshi by comparing open markets and pushing relevant data to your API. To handle your project, I will start with developing a Python script that utilizes tokenization and Jaccard similarity to accurately match bets across platforms. I will use the requests library for API interactions, implement robust error handling for rate limits, and ensure clean, well-commented code for easy maintenance. The deliverables for this project will include a Python 3 script with detailed docstrings, a configuration section for API keys and endpoints, sample output files, and a comprehensive README file. Before signing-off my bid, I would like to ask a question, i.e., how frequently do you anticipate encountering rate limits on the APIs? Warm Regards, Aneesa.

@durgesh8527

With over a decade of experience in the software development realm, my full-stack expertise includes Python, Django, and various technologies that make your arbitrage solution a reality. My strengths lie in creating scalable and efficient solutions, which fits perfectly into the requirements of your project. Handling rate limits gracefully is something I've done seamlessly and I accomplish this by understanding the constraints of your API and building the necessary precautions into my code. The matching logic and overcoming different wording poses a unique challenge, but it's one that I am well-prepared for. I intend to use a combination of tokenization and Jaccard similarity techniques to spot the precise bets across platforms - ensuring 100% match despite linguistic variations. By leveraging my extensive knowledge in handling various APIs (REST & GraphQL) I can confidently navigate any quirks and limitations; putting measures in place to guarantee nothing breaks in your production. In terms of deliverables, you can trust me to provide an organized single-file Python 3 script with clear docstrings and inline comments as well as a config section/.env example for easy manageability. Moreover, I will furnish you with sample output files including a JSON signal that's pushed out and local backups – using this backup you can always regenerate the NHX or CSV file on-demand if needed

@devendrathakur12

Hello, The interesting part is not fetching markets, but proving two differently written questions represent the same event. I would combine text normalization, token matching, similarity scoring, and event metadata like category and close date to reduce false matches. One question: should the script ignore partial matches completely, or return them with a confidence score for review? I would also build rate-limit handling with retries, caching, and structured logs so polling stays reliable. If the APIs nap for a minute, the script won't panic—it will patiently keep hunting for profit. Best regards, Dev S.

@mubeenm5026

As an accomplished software development company, Web Crest offers precisely the skill sets you're looking for. My team's proficiency in Python, PHP, and Software Architecture aligns perfectly with your requirements for a robust and data-driven market arbitrage script. Drawing on our vast experience in creating APIs and automated applications, we are well-equipped to build a solution that mirrors betting opportunities between Polymarket and Kalshi with high accuracy—a task that demands a meticulous matching logic execution. Notably, your project demands handling rate limits and other API intricacies gracefully, which is one of our core strengths. We've developed strategies centered around error tolerance while maintaining an optimal scraping rate using tools like requests or httpx. This includes thorough testing to ensure the code runs without breaking in production. Moreover, our dedication to transparency and excellent documentation is sure to meet your expectations for detailed output files. We're committed to delivering a clean, well-commented Python 3 script(s) integrated with any necessary config sections/.env files along with appropriate documentation outlining setup, matching logic approach, error rate-handling strategies, and more! Let's collaborate on this project to create an efficient and future-proof solution for your market arbitrage needs.

@tilalHusain

Hey there, Polling both Polymarket and Kalshi every 30 to 60 seconds only works if the matching layer is accurate enough to avoid false arbitrage signals. I would build that first. My approach is to normalize market titles, remove filler words, tokenize the text, then combine Jaccard similarity with fuzzy matching and event level checks like category, expiry date, outcome structure, and key entities. That produces reliable one to one market matches even when both platforms phrase the same event differently. Once confirmed I will calculate the arbitrage margin, collect prices, liquidity, volume, metadata, and push a structured JSON payload to your API while saving every signal locally as CSV or JSON with lightweight logging. The script will be built in clean Python using httpx with retry logic, exponential backoff, request throttling, connection pooling, timeout handling, and graceful recovery from rate limits or temporary API failures. Configuration will be handled through a simple .env file and the project will include sample payloads and a concise README for deployment. Let's discuss the details and get this running. Best Regards, Tilal

@rbtech1984

Hi There!!! ★★★★ (Develop a reliable Python arbitrage monitor that accurately matches markets across Polymarket and Kalshi in real time.) ★★★★ I’ve carefully reviewed your project and understand you need a Python script that polls Polymarket and Kalshi every 30–60 seconds, intelligently matches equivalent markets, calculates true arbitrage opportunities, pushes JSON signals to your API, and stores local backups with robust logging. ⚜ Real-time market polling ⚜ Intelligent market matching logic ⚜ Arbitrage detection & calculations ⚜ JSON API integration ⚜ CSV/JSON signal backups ⚜ Rate-limit & error handling ⚜ Clean, documented Python code I have experience developing API-driven Python automation and data processing solutions with clean, maintainable architecture. I'd approach the matching using tokenization, text normalization, Jaccard similarity, and metadata validation such as category and close date to improve accuracy. The script will use httpx with retry logic, exponential backoff, and graceful rate-limit handling to keep it stable in production. I'd be glad to discuss the APIs and start building a reliable MVP soon. Warm Regards, Farhin B.

@ayazakhtar75

Hello Client, This is definitely possible. I can see you need a Python script that polls Polymarket and Kalshi, matches identical bets across platforms — using smarter logic than simple string comparison — and flags genuine arbitrage opportunities with clean data pushed to your API. I'm confident I can build a reliable script with tokenisation or Jaccard similarity for matching, graceful rate-limit handling, and clear logging and backup files. Thank you, Ayaz Akhtar

@Cumuc

## Arbitrage Scanner Expert ## Hello, I’m very interested in your project, as it closely aligns with my skills and experience. After reviewing your requirements, I’m confident I can deliver a high-quality solution that meets your expectations. It seems you’re looking for a developer who can build a Python service that continuously polls Polymarket and Kalshi, intelligently matches equivalent markets, detects genuine arbitrage opportunities, and delivers structured JSON signals with reliable logging and backups. To handle rate limits, I'd implement configurable polling intervals, request throttling, exponential backoff with retries, HTTP connection pooling, and response caching where appropriate. The script would log API failures without interrupting processing and resume automatically after temporary rate-limit responses. I look forward to hearing from you and hopefully working together. Kind regards, Cuzmuc

@toriquldev123

Hello Dear! I’m Md Toriqul Islam, and I’m excited to partner with you. I can dive into your project immediately. I have 10+ years of experience in Python development, API integrations, data processing, automation, and financial data monitoring systems. I understand you need a Python script to poll Polymarket and Kalshi, intelligently match equivalent markets using semantic similarity, detect arbitrage opportunities, and push structured JSON data to your API. I’ve built similar API-driven automation and data aggregation solutions with robust error handling. I have rich experience in Python, APIs, automation, and data analysis. I am skilled in Python, httpx, REST APIs, JSON, CSV, and similarity algorithms. For matching, I’d combine token normalization, Jaccard similarity, and keyword weighting with date/category validation. For rate limits, I’d use retries, exponential backoff, request throttling, and efficient polling intervals. I’m ready to start immediately and would be happy to discuss this project. Looking forward to hearing from you. Best regards, Md Toriqul Islam