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Changelog

All notable changes to chronos-lab will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

Unreleased

0.2.1 - 2026-02-11

Added

  • Interactive Brokers Integration: Complete market data support with IBMarketData API for real-time ticks and historical bars, plus high-level ohlcv_from_ib and ohlcv_from_ib_async functions for seamless OHLCV data retrieval
  • TimeSeriesCollection class for multi-symbol data orchestration (experimental, undocumented, subject to change)

Documentation

  • New Interactive Brokers market data tutorial and API reference

0.2.0 – 2026-02-02

Added

  • Configurable OHLCV data sources in DAGs:
    Analysis calculations can now pull data directly from multiple sources (yfinance, intrinio, or arcticdb) using a unified configuration interface, making it easy to switch between a variable input and external providers.
  • Source-aware anomaly detection:
    AnalysisDriver.detect_anomalies now supports both preloaded OHLCV DataFrames and automatic retrieval from configured data sources.
  • Dynamic dataset and ArcticDB outputs:
    Analysis results can be flexibly routed to different datasets/backends, enabling easier experimentation and storage control.

Changed

  • AnalysisDriver improvements:
    Streamlined configuration, clearer parameters, and a more modular design for building composable analysis workflows.
  • OHLCV standardization:
    standardize_ohlcv updated to work consistently across dynamically selected data sources.
  • Validation and robustness:
    Added parameter validation and safer defaults for more predictable behavior.
  • Documentation refresh:
    Expanded guides and examples reflecting the new source configuration and AnalysisDriver-based workflows.

Removed

  • Legacy MCP dependencies and related modules.
  • The deprecated analysis.calculation module and outdated APIs.
  • Plot module is no longer a part of the official documented API.

Deprecated

  • Remaining legacy anomaly detection functions and parameters. Use AnalysisDriver going forward.

0.1.8 – 2026-01-29

Added

  • Configurable ArcticDB backends:
    ohlcv_from_arcticdb() and ohlcv_to_arcticdb() now support explicit selection of the ArcticDB backend (LMDB, S3, or MEM), allowing the same code to run against local, in-memory, or cloud-backed stores.
  • AnalysisDriver API:
    A new interface intended to serve as the foundation for multiple analysis calculations, with caching and Hamilton-based DAG execution.
  • Updated documentation and examples covering backend configuration and AnalysisDriver API.

Changed

  • Anomaly detection interface:
    detect_ohlcv_anomalies is deprecated in favor of AnalysisDriver-based analysis, aligning anomaly detection with the new unified analysis API.
  • Plot rendering behavior:
    Plotting logic was refined to ensure figures render correctly in notebooks and scripts without accumulating open figures.
  • Logging defaults:
    The global log level now defaults to WARNING for a quieter out-of-the-box experience.

Deprecated

  • The analysis.calculation module and related anomaly detection helpers. Migration guidance is available in the documentation.

0.1.7 - 2026-01-27

Added

  • New Tutorial: Getting Started with Chronos Lab
  • Anomaly executor configuration

Changed

  • Dependency updates
  • Documentation

0.1.6 - 2026-01-26

Changed

  • Documentation cleanup and enhancements

0.1.5 - 2026-01-25

Added

  • Anomaly Detection System: Complete ML-powered pipeline for detecting anomalies in OHLCV data using Isolation Forest, with Hamilton DAG-based architecture for scalable symbol-level processing
  • Visualization: Anomaly plots with mplfinance integration, featuring customizable styling, human-readable axis formatting (1K, 1M, 1B), and flexible date range filtering
  • Dataset Export: Export anomaly results to DynamoDB or local storage with configurable TTL support
  • File Storage: Save plots and data locally or to S3 with the new to_store utility
  • Interactive Documentation: Jupyter notebook support in documentation via mkdocs-jupyter, with comprehensive tutorials and API reference sections

Changed

  • Enhanced plotting with modular plot_ohlcv_anomalies function for reusability
  • Improved error handling for edge cases in anomaly collection

Dependencies

  • Added scikit-learn and sf-hamilton[visualization] for ML and DAG execution
  • Added mplfinance, matplotlib, and visualization support packages
  • Added mkdocs-jupyter for interactive documentation

0.1.4 - 2026-01-18

Added

  • AWS Integration: Comprehensive utilities for SSM parameters, Secrets Manager, S3, and DynamoDB operations
  • Dataset Management: Store and retrieve structured datasets locally or in DynamoDB with flexible mapping and serialization
  • Enhanced ArcticDB setup with shared AWS session for S3 backend

Documentation

  • New documentation modules: aws.md for AWS utilities and dataset.md for dataset handling
  • Expanded sources.md and storage.md with dataset examples

0.1.3 - 2026-01-18

Added

  • to_dataset function for saving structured datasets with DynamoDB or local storage support

0.1.2 - 2026-01-17

Added

  • Automated Documentation: GitHub Actions workflow for deploying documentation on version tags
  • MkDocs site with Material theme
  • Comprehensive docstrings and usage examples for core modules

0.1.1 - 2026-01-17

Changed

  • Updated Python requirement to >= 3.12 with improved cross-platform support

0.1.0 - 2026-01-17

Added

  • Core Data Access: Functions for reading and writing OHLCV data to ArcticDB (ohlcv_from_arcticdb, ohlcv_to_arcticdb)
  • Multi-Source Support: Fetch data from Intrinio (ohlcv_from_intrinio) and Yahoo Finance (ohlcv_from_yfinance)
  • Securities Discovery: Retrieve securities lists from Intrinio via securities_from_intrinio
  • Flexible Storage: Support for local and S3-backed ArcticDB instances
  • Auto-Configuration: Automatic .env file generation on first import
  • GitHub Actions workflow for PyPI publishing

Documentation

  • Complete README with installation, configuration, and usage examples

0.0.1 - 2026-01-14

Added

  • Initial project structure with Intrinio SDK integration
  • ArcticDB for time-series data storage
  • MCP server implementation
  • Docker support and environment configuration