Gem-Terminal: Exchange Management and Execution Console

This CLI tool provides a unified interface for the Gemini exchange. It manages account state and executes trade logic across multiple asset classes for trading operations and execution engineering.

Functionality

The software performs the following operations:

• Weighted Indexing: The script allocates USD across a predefined list of assets. It distinguishes between yield-bearing symbols and standard symbols by applying a user-defined weight multiplier.
• Geometric Order Distribution: The execution engine uses numpy.geomspace to calculate price levels for limit orders. This ensures density near current market rates while maintaining coverage across a wide price range.
• Pre-Trade Validation: The system compares all orders against a local cache of exchange constraints. It validates tick sizes and minimum order increments before transmission to ensure fintech compliance.
• Portfolio Liquidation: The console includes a bulk sell routine. It references a configuration file to protect specific assets from automated liquidation during portfolio rebalancing.
• Account Monitoring: A dedicated thread tracks specific currency balances. It triggers system-level auditory alerts when a balance crosses a specified threshold.
• Metadata Persistence: The script fetches and stores exchange requirements in a local JSON file. This reduces API latency and prevents rate-limit violations during routine operations.

Architecture

The system utilizes a synchronous execution model to ensure state consistency. This approach requires each order to be confirmed by the exchange before the next instruction is sent. Auditory feedback provides real-time status updates for trading support and real-time monitoring.

System Capabilities

The tool targets specific functions in execution and quantitative support:

• Trading Operations: Automates routine account management and bulk order entry.
• Execution Engineering: Implements algorithmic scaling and liquidity-aware order placement.
• Fintech Automation: Integrates API-level constraints into a local execution workflow.
• Algorithmic Support: Provides a testing ground for geometric entry strategies and portfolio weighting.

Requirements

The implementation requires the following components:

• gemini-python
• numpy
• beepy
• tqdm
• python-dotenv

Configuration

The config.json file contains the logic for asset categorization. Users define the earnable_symbols list and the excluded_from_all_sell list within this file. The .env file stores the API credentials.