DEAPack

DEAPack is an open-source Python framework for data envelopment analysis (DEA), efficiency measurement, productivity analysis, and environmental performance.

It is designed for researchers, students, and analysts who want broad method coverage without writing a separate optimization program for every analysis. A consistent data, model, and result interface connects classical DEA with economic, environmental, network, dynamic, and productivity methods.

Why DEAPack?

• Prepare validated data once and use a consistent estimator workflow.
• Inspect named score, target, slack, peer, component, diagnostic, and status tables.
• Move between closely related analysis families without changing packages.
• Create plots, reports, and reproducibility bundles from fitted results.
• Start with documented presets and teaching datasets while keeping model assumptions visible.

Installation

DEAPack 2.0.1 supports Python 3.10 through 3.13.

python -m pip install "DEAPack==2.0.1"

NumPy, pandas, and SciPy are the required runtime dependencies. Install DEAPack[viz] for optional Matplotlib result views.

Quick start

from deapack import BCCInput, DEAData, load_dataset

frame = load_dataset("frontier_1x1")
data = DEAData.from_frame(
    frame,
    dmu="dmu",
    inputs="input",
    outputs="output",
)

result = BCCInput().fit(data)
print(result.summary())
print(result.peers("E"))

This estimates an input-oriented variable-returns-to-scale frontier. The same result object provides targets, slacks, peer intensities, diagnostics, reporting, and visualization when those outputs are available for the chosen method.

Coverage

DEAPack includes:

• classical radial and non-radial DEA;
• productivity indexes and scale analysis;
• cost, revenue, profit, and allocative-efficiency analysis;
• undesirable-output and environmental technologies;
• network, dynamic, dynamic-network, panel, and metafrontier models; and
• super-efficiency, cross-efficiency, diagnostics, reporting, and visualization.

The installed method catalog is the authoritative inventory of executable methods. Planned or source-incomplete methods are not exposed as provisional estimators.

Documentation

• Package Documentation
• Installation guide
• Quick start
• Method catalog
• API reference
• Migration from 0.1.x

DEAPack 2.x is not a drop-in replacement for historical import DEAPack or ProdPack scripts; use the migration guide when updating an older project.

Citation and licensing

Use the repository's CITATION.cff and record the exact version used. Research using a particular DEA method should also cite its defining literature, linked from the corresponding Documentation page.

The software is licensed under GPL-3.0-only. Documentation and bundled data have their own recorded terms, and third-party data retain their upstream licenses. See the repository's component-license map and dataset-license map for precise boundaries.