Tutorials¶
Interactive Jupyter notebook tutorials with complete code examples, visualizations, and detailed explanations.
Getting Started¶
Level: Beginner
Topics: Data fetching, ArcticDB storage, datasets, visualization
Learn the fundamentals of chronos-lab through hands-on examples. This tutorial covers:
- Fetching OHLCV data from Yahoo Finance and Intrinio
- Storing and retrieving data with ArcticDB
- Working with datasets for securities metadata
- Creating and storing visualizations
- Understanding configuration and file storage
Interactive Brokers Market Data¶
Level: Intermediate
Topics: Interactive Brokers integration, real-time data, streaming bars, tick data, contracts
Learn how to access real-time and historical market data from Interactive Brokers. This tutorial covers:
- Connecting to IB Gateway/TWS and managing connections
- Understanding IB Contracts and handling symbol ambiguity
- Fetching historical data with sync and async methods
- Subscribing to streaming bar data for real-time updates
- Working with real-time tick data (bid/ask spreads)
- Direct access to IB API functions (market depth, etc.)
- Storing IB data to ArcticDB
OHLCV Anomaly Detection¶
Level: Intermediate
Topics: Time series isolation forest anomaly detection, visualization, inspecting calculation pipeline
Learn how to detect anomalies in OHLCV (Open, High, Low, Close, Volume) financial data using chronos-lab's analysis pipeline. This tutorial covers:
- Fetching historical price data from multiple sources
- Running the anomaly detection algorithm
- Visualizing results with charts
- Saving results to datasets for later use
- Inspecting the calculation pipeline
Getting Started with Tutorials¶
Prerequisites¶
Before running these tutorials, install chronos-lab with the required extras:
# For Getting Started and OHLCV Anomaly Detection tutorials
uv pip install chronos-lab[yfinance,arcticdb,analysis,visualization]
# For Interactive Brokers tutorial (also requires IB Gateway/TWS)
uv pip install chronos-lab[ib,arcticdb,visualization]
Running Locally¶
-
Clone the repository:
-
Install dependencies:
-
Launch Jupyter:
Online Viewing¶
All tutorials are rendered with outputs (including charts) directly in the documentation. You can view them without installing anything!
Contributing Tutorials¶
Have a great use case or analysis workflow? We'd love to see your tutorial!
Guidelines: - Focus on real-world use cases - Include clear explanations and comments - Save notebooks with outputs (charts, tables) - Add markdown cells for context - Test that code runs end-to-end
Submit tutorials via GitHub pull requests.