amarket 0.1.0

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amarket

Abstract Market (or "Any Market", or just "A Market") is a high-level implementation of market entities like Orders, Positions, etc. (Abstract market functions/classes, that works on any market.)

This module use only standard Python library and contain no external dependencies from anywhere, except OHLC-related parts of it, that requires numpy and pandas (and also TA-Lib for calculating technical analysis features over OHLC data)

Overview

The amarket package provides a comprehensive framework for working with financial markets in a standardized way, abstracting away the specifics of different exchanges and trading platforms. It's designed to work with various market data sources while providing consistent interfaces for:

• Market representation (symbols, exchanges, timeframes)
• OHLC (Open-High-Low-Close) data handling
• Trading positions and orders
• Portfolio management and rebalancing
• Market data providers

Key Components

Core Interfaces

• IMarket: Abstract interface representing any trading market with specific symbol and timeframe
• IOhlc: Interface for OHLC data management
• ITradingAccount: Interface for trading account operations

Base Classes

• MarketBase: Base class for implementing specific market functionality
• Ohlc: Class for managing OHLC time-series data with support for current and closed candles
• Portfolio: Class for portfolio management, including rebalancing and value calculation

Modules

• base/: Core abstract classes and interfaces
• interfaces/: Abstract interfaces defining the contract for market components
• ohlc/: OHLC data handling and processing functionality
• portfolio/: Portfolio management capabilities
• types/: Type definitions used throughout the package

Features

1. Exchange Agnostic: Designed to work with any exchange or trading platform through abstraction
2. OHLC Data Management: Robust handling of time-series market data with configurable timeframes
3. Portfolio Management: Tools for portfolio construction, rebalancing, and value tracking
4. Singleton Pattern: Market instances are managed as singletons to ensure consistency
5. Thread Safety: Built-in locking mechanisms for concurrent access

Dependencies

The project requires standard Python libraries plus:

• numpy>=2.3.1 (for amarket.ohlc and amarket.portfolio packages)
• pandas>=2.3.0 (for amarket.ohlc)
• TA-Lib>=0.6.4 (for amarket.ohlc.Featurizer)

Usage

The package is designed to be extended by specific implementations for different exchanges or trading platforms, providing a consistent API while allowing for exchange-specific behavior.