This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady
What I Built
A containerized, on-chain CLOB (Central Limit Order Book) trading bot pipeline deployed via GitHub and Railway. It automates repetitive dry-run tracking and order execution in the background, keeping hands off the keyboard so you don't have to manually babysit routine market loops.
Demo
https://dev.to/rcortez056/shipping-web3-automation-from-repository-fork-to-cloud-execution-2bc6
Code
rcortez056-spec
/
dreamdex-bot-kit-main
Build automated trading bots on DreamDEX (Somnia's on-chain CLOB)
dreamBot Kit
Build automated trading bots on DreamDEX — the on-chain central-limit order book (CLOB) on Somnia. This kit gives you a shared client library, five runnable strategies, operations docs for running a bot 24/7, and the sanitized source of the top bots from the first DreamDEX alpha trading competition.
For competent TS / Python devs, zero prior DreamDEX knowledge required. Everything on the DreamDEX protocol itself is documented at docs.dreamdex.io — this repo does not rewrite the docs, it links to them and shows you working code.
What's inside
| Path | What it is |
|---|---|
packages/core |
Shared client — auth, REST, WebSocket, order execution, gotcha guards, nonce manager. TypeScript and Python. Every strategy imports it. |
packages/backtest |
Bar-by-bar backtest engine (SimPool, fill model, metrics). Drive it with npm run backtest — see docs/backtesting.md. |
strategies/ |
Start with starter — the simplest bot, where you edit one decide() function. Then |
How I Built It
Leveraged open-source Python libraries, transparent repository forks, and a containerized cloud execution setup on Railway. Using environment variables for secure private key management, the pipeline runs continuous, autonomous background routines with zero local resource locks or manual intervention.
Why Does Open Innovation Matter?
Open infrastructure matters because it ensures total portability and zero vendor lock-in. Running on transparent Python frameworks and open-source foundations keeps sensitive key configurations completely under your direct control, avoiding closed APIs and rigid enterprise constraints.
My Agent Session
Automated dry-run loop and background execution pipeline running continuously via containerized cloud architecture.
The Lazy Payoff
By setting up the containerized pipeline once and letting it manage routine tracking autonomously, it eliminates the manual grind of babysitting terminal scripts—freeing up hours of time and keeping your focus locked entirely on high-level system architecture.
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