orderflow_backtest/docs/modules/dependencies.md

External Dependencies

Overview

This document describes all external dependencies used in the orderflow backtest system, their purposes, versions, and justifications for inclusion.

Production Dependencies

Core Framework Dependencies

Dash (^2.18.2)

• Purpose: Web application framework for interactive visualizations
• Usage: Real-time chart rendering and user interface
• Justification: Mature Python-based framework with excellent Plotly integration
• Key Features: Reactive components, built-in server, callback system

Dash Bootstrap Components (^1.6.0)

• Purpose: Bootstrap CSS framework integration for Dash
• Usage: Responsive layout grid and modern UI styling
• Justification: Provides professional appearance with minimal custom CSS

Plotly (^5.24.1)

• Purpose: Interactive charting and visualization library
• Usage: OHLC candlesticks, volume bars, depth charts, OBI metrics
• Justification: Industry standard for financial data visualization
• Key Features: WebGL acceleration, zooming/panning, dark themes

Data Processing Dependencies

Pandas (^2.2.3)

• Purpose: Data manipulation and analysis library
• Usage: Minimal usage for data structure conversions in visualization
• Justification: Standard tool for financial data handling
• Note: Usage kept minimal to maintain performance

Typer (^0.13.1)

• Purpose: Modern CLI framework
• Usage: Command-line argument parsing and help generation
• Justification: Type-safe, auto-generated help, better UX than argparse
• Key Features: Type hints integration, automatic validation

Data Storage Dependencies

SQLite3 (Built-in)

• Purpose: Database connectivity for historical data
• Usage: Read-only access to orderbook and trade data
• Justification: Built into Python, no external dependencies, excellent performance
• Configuration: Optimized with immutable mode and mmap

Development and Testing Dependencies

Pytest (^8.3.4)

• Purpose: Testing framework
• Usage: Unit tests, integration tests, test discovery
• Justification: Standard Python testing tool with excellent plugin ecosystem

Coverage (^7.6.9)

• Purpose: Code coverage measurement
• Usage: Test coverage reporting and quality metrics
• Justification: Essential for maintaining code quality

Build and Package Management

UV (Package Manager)

• Purpose: Fast Python package manager and task runner
• Usage: Dependency management, virtual environments, script execution
• Justification: Significantly faster than pip/poetry, better lock file format
• Commands: uv sync, uv run, uv add

Python Standard Library Usage

Core Libraries

• sqlite3: Database connectivity
• json: JSON serialization for IPC
• pathlib: Modern file path handling
• subprocess: Process management for visualization
• logging: Structured logging throughout application
• datetime: Date/time parsing and manipulation
• dataclasses: Structured data types
• typing: Type annotations and hints
• tempfile: Atomic file operations
• ast: Safe evaluation of Python literals

Performance Libraries

• itertools: Efficient iteration patterns
• functools: Function decoration and caching
• collections: Specialized data structures

Dependency Justifications

Why Dash Over Alternatives?

• vs. Streamlit: Better real-time updates, more control over layout
• vs. Flask + Custom JS: Integrated Plotly support, faster development
• vs. Jupyter: Better for production deployment, process isolation

Why SQLite Over Alternatives?

• vs. PostgreSQL: No server setup required, excellent read performance
• vs. Parquet: Better for time-series queries, built-in indexing
• vs. CSV: Proper data types, much faster queries, atomic transactions

Why UV Over Poetry/Pip?

• vs. Poetry: Significantly faster dependency resolution and installation
• vs. Pip: Better dependency locking, integrated task runner
• vs. Pipenv: More active development, better performance

Version Pinning Strategy

Patch Version Pinning

• Core dependencies (Dash, Plotly) pinned to patch versions
• Prevents breaking changes while allowing security updates

Range Pinning

• Development tools use caret (^) ranges for flexibility
• Testing tools can update more freely

Lock File Management

• uv.lock ensures reproducible builds across environments
• Regular updates scheduled monthly for security patches

Security Considerations

Dependency Scanning

• Regular audit of dependencies for known vulnerabilities
• Automated updates for security patches
• Minimal dependency tree to reduce attack surface

Data Isolation

• Read-only database access prevents data modification
• No external network connections required for core functionality
• All file operations contained within project directory

Performance Impact

Bundle Size

• Core runtime: ~50MB with all dependencies
• Dash frontend: Additional ~10MB for JavaScript assets
• SQLite: Zero overhead (built-in)

Startup Time

• Cold start: ~2-3 seconds for full application
• UV virtual environment activation: ~100ms
• Database connection: ~50ms per file

Memory Usage

• Base application: ~100MB
• Per 1000 OHLC bars: ~5MB additional
• Plotly charts: ~20MB for complex visualizations

Maintenance Schedule

Monthly

• Security update review and application
• Dependency version bump evaluation

Quarterly

• Major version update consideration
• Performance impact assessment
• Alternative technology evaluation

Annually

• Complete dependency audit
• Technology stack review
• Migration planning for deprecated packages