powerlaw

library2.0.0pypypi✓ verified 86d ago

A toolbox for testing if a probability distribution fits a power law, including fitting power laws, comparing to other distributions via likelihood ratio tests, and plotting. Current version is 2.0.0 (released 2023-12-31), with major refactor from v1.x. Release cadence is irregular.

data ai-ml

pip install powerlaw

package ↗

INSTALL

IMPORT

SIG · POWERLAW

powerlaw

datapythonv2.0.0

Install

12.0s avg

Import

3686ms

Disk

329MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v2.0.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 3.758s · 325.9MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 12.0s · import 3.614s · 313MB

329MB installed

● package 329MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

powerlaw

✓ import powerlaw

✗ from powerlaw import powerlaw

Library is imported directly as 'powerlaw' module; no submodule

Fit a power law to data and compare to alternative distributions.

import powerlaw import numpy as np # Generate sample data x = np.random.pareto(2.5, 1000) # Fit power law fit = powerlaw.Fit(x) # Print alpha and xmin print(fit.alpha, fit.xmin) # Compare to exponential R, p = fit.distribution_compare('power_law', 'exponential')

Debug

Known issues

breakingVersion 2.0.0 is a major refactor with API changes. The previous API (e.g., `powerlaw.Fit` returning a `Result` object with `.power_law.alpha`) has been simplified. Ensure you update code and refer to new documentation.

fix

Review the new API: `Fit` now directly returns the fitted parameters (alpha, xmin) as attributes. Use `fit.distribution_compare(...)` for comparisons.

affects: >=2.0.0

deprecatedOld plotting functions from v1.x (e.g., `fit.plot_pdf()`) may be removed. Use `fit.plot_ccdf()` or `fit.plot_pdf()` as per new API.

fix

See the documentation for new plotting methods; they have similar names but may have different signatures.

affects: >=2.0.0

gotchaData with values <= 0 will cause errors. Power law distributions are defined for positive values only.

fix

Ensure your data is strictly positive (e.g., remove zeros and negative values before fitting).

affects: all

Errors

Common errors & fixes

AttributeError: module 'powerlaw' has no attribute 'Fit'

Old code that imported a submodule incorrectly or used an outdated import pattern.

fix

Use `import powerlaw` and then `fit = powerlaw.Fit(data)`.

TypeError: Fit() got an unexpected keyword argument 'xmin'

The API changed in v2.0; `xmin` is no longer a direct argument to `Fit`; use `Fit(data, xmin=value)` may still work but check docs.

fix

Use `fit = powerlaw.Fit(data, xmin=...)` and refer to v2.0 docs; if using v2.0, the argument is still supported but check for other changes.

ValueError: Data must be positive

Power law fitting requires all data points > 0.

fix

Filter your data: `data = data[data > 0]` before fitting.

Upgrade

Version history

2.0.0latest on PyPI · released Jan 2, 2026

Audit

Dependencies

No dependency data recorded yet.

Agent activity

8 hits · last 30 days

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Resources

packagehttps://pypi.org/project/powerlaw/ ↗