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API Reference

High-Level APIs

These are the primary interfaces you'll use for most tasks:

  • Sources - Fetch data from Yahoo Finance, Intrinio, Interactive Brokers, ArcticDB, and Datasets
  • Storage - Persist data to ArcticDB, Datasets, and file Store
  • Analysis Drivers - Analysis calculations with Hamilton DAGs
  • Settings - Configuration management

Low-Level APIs

For advanced use cases requiring fine-grained control:

Module Overview

chronos_lab.analysis.driver

High-level driver for composable time series analysis:

  • AnalysisDriver - Hamilton Driver wrapper for analysis calculations
  • detect_anomalies() - Anomaly detection with Isolation Forest

View detailed documentation →

chronos_lab.arcdb

Low-level ArcticDB wrapper (advanced use):

  • ArcDB - Class for direct ArcticDB operations
  • batch_store() - Store multiple symbols
  • batch_read() - Read multiple symbols
  • batch_update() - Update existing symbols

View detailed documentation →

chronos_lab.aws

Low-level AWS integration utilities (advanced use):

  • aws_get_parameters_by_path() - Fetch SSM parameters by path
  • aws_get_parameters() - Fetch specific SSM parameters
  • aws_get_secret() - Retrieve Secrets Manager secret
  • parse_arn() - Parse AWS ARN into components
  • aws_get_resources() - Query resources by tags
  • aws_s3_list_objects() - List S3 bucket objects
  • DynamoDBDatabase - Class for DynamoDB operations

View detailed documentation →

chronos_lab.dataset

Low-level dataset management (advanced use):

  • Dataset - Class for direct dataset operations
  • get_dataset() - Retrieve dataset as dictionary
  • get_datasetDF() - Retrieve dataset as DataFrame
  • save_dataset() - Save dataset to local or DynamoDB
  • delete_dataset_items() - Remove items from dataset

View detailed documentation →

chronos_lab.ib

Low-level Interactive Brokers wrapper (advanced use):

  • get_ib() - Get IBMarketData singleton instance
  • IBMarketData - Singleton class for IB TWS/Gateway operations
  • connect() / disconnect() - Connection management
  • subscribe_bars() / subscribe_bars_async() - Subscribe to streaming bars
  • get_bars() - Retrieve subscribed bar data
  • sub_ticks() / unsub_ticks() - Manage tick subscriptions
  • get_ticks() - Retrieve tick data
  • get_hist_data() / get_hist_data_async() - Historical data retrieval
  • symbols_to_contracts() / symbols_to_contracts_async() - Contract qualification
  • lookup_cds() / lookup_cds_async() - Contract details lookup
  • map_interval_to_barsize() - Convert interval to IB bar size
  • calculate_ib_params() - Calculate IB API parameters
  • hist_to_ohlcv() - Convert historical data to OHLCV format

View detailed documentation →

chronos_lab.intrinio

Low-level Intrinio SDK wrapper (advanced use):

  • Intrinio - Class for direct Intrinio SDK access
  • get_all_securities() - Fetch securities lists
  • get_security_stock_prices() - Fetch price data

View detailed documentation →

chronos_lab.settings

Configuration management:

  • Settings - Pydantic model for application configuration
  • get_settings() - Get cached settings instance

View detailed documentation →

chronos_lab.sources

High-level functions for fetching OHLCV time series data:

  • ohlcv_from_yfinance() - Fetch data from Yahoo Finance
  • ohlcv_from_intrinio() - Fetch data from Intrinio API
  • ohlcv_from_ib() - Fetch historical data from Interactive Brokers
  • ohlcv_from_ib_async() - Fetch historical data from IB asynchronously
  • ohlcv_from_arcticdb() - Retrieve stored data from ArcticDB
  • securities_from_intrinio() - Fetch securities lists from Intrinio

View detailed documentation →

chronos_lab.storage

High-level functions for persisting data:

  • ohlcv_to_arcticdb() - Store OHLCV data in ArcticDB
  • to_dataset() - Save datasets to local JSON or DynamoDB
  • to_store() - Store files to local filesystem and/or S3

View detailed documentation →

Data Format Conventions

All OHLCV data in chronos-lab follows these conventions:

Column Names

  • date: UTC timezone-aware datetime
  • symbol: Ticker symbol
  • open: Opening price
  • high: High price
  • low: Low price
  • close: Closing price
  • volume: Trading volume

Index Structure

MultiIndex DataFrame (default): 

# (date, symbol) MultiIndex
                              open   high    low   close    volume
date                symbol
2024-01-17 05:00:00+00:00 AAPL   182.16  183.09  180.89  182.68  52242800
                          MSFT   388.39  397.11  385.17  396.95  34049200

Dictionary Format (when output_dict=True): 

{
    'AAPL': DataFrame with DatetimeIndex,
    'MSFT': DataFrame with DatetimeIndex,
    ...
}

Wide/Pivoted Format (when pivot=True): 

# DatetimeIndex with MultiIndex columns
date                      close_AAPL  close_MSFT  close_GOOGL
2024-01-17 05:00:00+00:00     182.68      396.95       141.82
2024-01-18 05:00:00+00:00     185.56      402.56       143.47