ChartBook
A developer platform for data science teams.
Discover, document, and share data science work across your organization. ChartBook provides a centralized catalog for data pipelines, charts, and documentation—making it easy to find, understand, and reuse analytics work.
Terminology
ChartBook supports two project types:
- Pipeline — A single analytics pipeline with its own charts, dataframes, and documentation
- Catalog — A collection of multiple pipelines aggregated into a unified documentation site
See Documenting a Pipeline and Catalogs and Data Access for how the two fit together.
Features
- Pipeline Catalog — Organize and discover data pipelines across your team
- Documentation Generation — Build searchable documentation websites from your analytics work
- Data Governance — Track data sources, licenses, and access permissions
- Programmatic Data Access — Load pipeline outputs directly into pandas or polars
- Multi-Pipeline Catalogs — Aggregate multiple pipelines into a single documentation site
Installation
pip install chartbook
One install, everything included: data loading, plotting utilities, and the CLI for building documentation.
Development:
pip install -e ".[dev]"
Quick Start
Load data from a pipeline
from chartbook import data
df = data.load(pipeline="fred_charts", dataframe="interest_rates")
Build documentation
chartbook build
Browse your catalog
# List all pipelines, dataframes, and charts
chartbook ls
# List dataframes only
chartbook ls dataframes
# Get path to a dataframe's parquet file
chartbook data get-path --pipeline fred_charts --dataframe interest_rates
See the documentation for configuration options and detailed guides.
Documentation
Full documentation is available at backofficedev.github.io/chartbook.
Contributing
Contributions are welcome. See CONTRIBUTING for guidelines.
License
Modified BSD License
1 maintainer
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