Budget: 10000 UAH Deadline: 2 days
Good day! I am ready to complete this project. Extensive experience in developing various applications.
Development of a spot arbitrage bot for cryptocurrencies (only monitoring, no auto-trading) is needed. The bot works with EXMO, WhiteBIT, and 10 top exchanges (Binance, Bybit, OKX, Gate.io, MEXC, Bitget, HTX, Kraken, Coinbase, LBank) and sends detailed messages to Telegram in a format similar to the attached screenshot.
Mandatory exchanges: EXMO, WhiteBIT + 10 popular (total 12).
Upon launch, the bot automatically pulls all available pairs to USDT from each exchange.
The list of pairs is periodically updated (so that new coins are automatically picked up).
Real-time price comparison across all USDT pairs between exchanges.
Calculation: spread in percentage, expected profit in USDT for a given volume, considering:
trading fees of each exchange;
fees for depositing/withdrawing coins between exchanges (hedging/withdrawal).
Filter by minimum spread/profit (for example, show only >0.5%).
The notification should look as similar as possible to the example in the screenshot and contain:
Pair name of exchanges and pair, for example: EXMO → WhiteBIT | MASK/USDT.
Buy block:
volume in USDT and in coin;
buy price range.
Sell block:
volume in coin and in USDT;
sell price range.
Profit in USDT and spread in %.
Hedging / Withdrawal block:
which exchanges can balance;
which network (ERC20, TRC20, etc.) and withdrawal fee.
Transaction time and, optionally, an attached file (table or screenshot).
Language: Python using ccxt or official exchange APIs.
Asynchronous data collection from all exchanges.
Flexible settings (spread threshold, base trade volume, scan frequency) via config file or variables in code.
Budget: 10000 UAH Deadline: 2 days
Good day! I am ready to complete this project. Extensive experience in developing various applications.
Budget: 8000 UAH Deadline: 3 days
Hello.
I will create a spot arbitrage bot for monitoring. Upon launch, the bot will automatically pull all available pairs to USDT from each exchange and will regularly update the list so that new listings are captured without manual editing. I have already done monitoring of quotes and Telegram notifications for crypto projects: asynchronous collection, normal request limits, protection against duplicates, stable operation 24/7. In the calculation, I will show the spread in percentage and the expected profit in USDT for the specified volume, taking into account trading fees, as well as withdrawal fees and networks. I will make the format of messages in Telegram as similar as possible to your example: exchange pair and pair, blocks "Buy/Sell," profit and spread, "Hedging/Withdrawal," time.
Budget: 11111 UAH Deadline: 9 days
I have done several similar ones, I will do it for you too, contact me, quickly, qualitatively, a lot of work done.
Budget: 5000 UAH Deadline: 3 days
Hello. There is a similar bot, but it is written in PHP. To avoid thinking that this is simple, you should know that most exchanges will require keys. Because information about networks, about fees when transferring coins is only available in private requests through API keys.
Budget: 10000 UAH Deadline: 7 days
Hello! I can implement this project using Zennoposter. If it's relevant - write to me, we will discuss.
Тут можно подключить сигналы к своему каналу Arbitrage VIP signal Bot. Как для проверки, сможете ли свой канал раскрутить,
Development of a Telegram Mini App (Bot + WebApp) for selling digital goods and in-game currencies (Python / aiogram) Project description: A Telegram bot with a full WebApp interface is required for the automated sale of digital goods (Telegram Stars, Telegram Premium, in-game currencies/donations for PUBG Mobile, Steam, etc.). The project is called Aspect App. The main focus is on speed, smooth UI/UX in a Web3/minimalist style, and complete automation of product delivery after payment. Technology stack: Backend: Python 3.10+, aiogram 3.x (FastAPI for Webhook/API is welcome). Database: PostgreSQL / Redis (for sessions and caching). Frontend (WebApp): React.js / Vue.js / Next.js (at the developer's discretion, speed and smoothness of animations are important). Integrations: Telegram WebApp API. Main functionality (MVP): 1. Client side (Telegram Mini App): Main screen: Product categories (Telegram Assets, In-game Donations). Banner grid for promotions. Product catalog: Product cards with volume selection (e.g., 50, 100, 500 Telegram Stars or UC). Fields for entering player data (Player ID for PUBG). Cart and Checkout: Quick purchase in 2 clicks. Payment module: Integration of payment methods (CryptoBot API / TON Connect / other fiat gateways by agreement). Personal account: Order history, status tracking, referral system (balance within the app). 2. Admin panel (built into WebApp or separate bot): Catalog management (adding/removing products, changing prices). Order monitoring and sales statistics. User database mailing system. 3. Automation logic (A plus): Readiness of the architecture for integration with supplier APIs (API for auto-purchasing Stars/UC). At the MVP stage, some products may be issued with codes from the database. What is required from the contractor: 1. Development of the database and backend architecture in Python. 2. Layout and integration of WebApp (design mockup to be discussed, clean Web3 style, Glassmorphism is important). 3. Setting up secure transactions and payment webhooks. 4. Deployment on the server (Docker, Ubuntu, SSL setup). Candidate requirements: Experience in commercial development of Telegram WebApps for at least 1 year. Portfolio with launched and working Mini Apps (please provide links in your response). Clean, documented code. Working conditions: Work only through the Secure Deal (Safe / Escrow) of the platform. Payment is staged (the project is divided into Sprint 1: Backend + DB, Sprint 2: Frontend WebApp, Sprint 3: Payment integration and testing). Budget: To be discussed with the successful candidate (please indicate your price range and timelines in your response)
Looking for a streamer, ideally with subscribers on Twitch; the more subscribers, the better. We need to promote the website so that as many people as possible learn about it.
We are looking for a specialist in Solana security programs to conduct an audit of the smart contract before deployment on the mainnet. Contract stack: Rust + Anchor framework SPL Token (transfer/storage of tokens in PDA) Mechanics: timing rounds, escrow of bets, resolver of final price, calculation and distribution of payouts, claim instructions, emergency pause + refund, fee configuration through admin authority Check for common vulnerabilities in Solana/Anchor: missing ownership/signer checks, account validation, integer overflow, PDA seeds collisions, reentrancy patterns, authority key privileges Analysis of payout distribution logic (rounding, edge cases with multiple participants) Verification of emergency mechanisms (pause, refund) — whether they can be bypassed or abused Report with classification of findings by criticality (Critical/High/Medium/Low) and recommendations Re-check after fixes (re-audit fixes) Requirements for the performer: Proven experience in auditing or developing Solana programs (Rust/Anchor) — please provide links to GitHub, previous audits, or examples of found vulnerabilities Understanding of SPL Token and PDA-escrow patterns Experience with static analysis tools (Soteria, Sec3, cargo-audit) will be a plus In your response, please indicate: Experience specifically with Solana (not EVM) — specific projects Estimated cost and timeline for a contract of this scope Report format (example, if available)
What we are calculating in the project: Realized PnL, ROI, and Win Rate for cryptocurrency wallets - how profitable the wallet traded a certain token over the selected period. Based on what data: the history of on-chain transactions of the wallet (swaps, token transfers) + the market price of the token at the time of each transaction. The main data source is Moralis: two calls during the initial loading of the wallet - native ETH transfers and all ERC-20 token transfers. What we are comparing with: Nansen.io - we take it as a benchmark, comparing our calculated metrics with what Nansen shows for the same wallets over the same period. Problem: our figures significantly differ from Nansen, and we do not fully understand the rules by which some actions of the wallet should be classified for PnL purposes. We need to fix the calculation of Realized PnL, ROI, and Win Rate to match Nansen. In your application, please write: - experience with similar tasks - experience with Nansen - experience with Moralis - experience with DeFiLlama - experience with articles on crypto transactions - approximate cost and timeline for the fix
It is important to start - TODAY I need a person who has experience in writing trading bots on DEXs (needed on the BSC network) with an understanding of transaction costs, gas, etc. I want to test several trading strategies on a real trading agent I need to quickly develop an autonomous trading agent that uses the Trust Wallet and CoinMarketCap APIs to execute trades on the BNB Chain (BSC) based on 3–5 embedded strategies. Technology stack (mandatory) - Trust Wallet Agent Kit (TWAK) — for self-custodial signing and executing transactions (https://portal.trustwallet.com) - CoinMarketCap AI Agent Hub — for obtaining market data and signals (https://coinmarketcap.com/api/agent) - BNB AI Agent SDK — for quick integration (https://github.com/bnb-chain/bnbagent-sdk) Functional requirements Data (CMC AI Agent Hub) - Data retrieval via MCP or x402 (https://coinmarketcap.com/api/agent) - Use of ready-made Skills for RSI, MACD, Fear & Greed, volumes Execution (Trust Wallet Agent Kit) - Local signing of transactions — keys remain with the user (https://portal.trustwallet.com) - Autonomous mode: the agent signs and sends trades by itself - Limitations: drawdown, daily limit, stop-loss, token whitelist - Use of x402 for payment of data/computations Strategies - Implement 3–5 described strategies with the ability to switch between them - Examples: combination of funding rates + Fear & Greed, DCA based on sentiments with filters Technical requirements - Language: Python (preferred) or TypeScript/JavaScript - Tools: TWAK CLI, CMC CLI, BNB AI Agent SDK Who can take this on?