arviz

library1.3.0pypypi✓ verified 24d ago

ArviZ is a Python package for exploratory analysis of Bayesian models. It provides tools for diagnostics, visualization, and inference data management, working with various probabilistic programming frameworks. Version 1.0.0 is the current major release, and the project has a regular, active release cadence.

ai-ml data

pip install arviz

github ↗package ↗homepage ↗docs ↗

INSTALL

IMPORT

SIG · ARVIZ

arviz

ai-mlpythonv1.3.0

Install

15.8s avg

Import

5296ms

Disk

385MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.23.4 · 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 4.394s · 428.1MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 15.8s · import 4.080s · 412MB

385MB installed

● package 385MB

Code

Verified usage

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

arviz

✓ import arviz as az

Commonly imported with the alias `az` for brevity and convention.

InferenceData

✓ import arviz as az idata = az.InferenceData(...)

The central data structure for ArviZ, usually accessed via `az` alias.

This quickstart demonstrates how to create a basic `InferenceData` object (often loaded from a model output) and use ArviZ to plot a trace and generate summary statistics. It uses `numpy` for data simulation and `arviz` for analysis and visualization.

import arviz as az import numpy as np # Simulate some data for demonstration np.random.seed(42) data = { 'theta': np.random.normal(0, 1, size=1000), 'phi': np.random.normal(5, 2, size=1000) } # Create a dummy InferenceData object (usually loaded from a model) id = az.InferenceData( posterior=az.dict_to_dataset(data), sample_stats=az.dict_to_dataset({'lp': np.random.normal(0, 1, size=1000)}) ) # Plot a trace of the posterior samples az.plot_trace(id, var_names=['theta']) # Print summary statistics print(az.summary(id, var_names=['theta']))

Debug

Known issues

breakingArviZ v1.0.0 and newer require Python 3.12 or higher. Users on older Python versions (e.g., 3.10, 3.11) must upgrade their Python environment to use ArviZ 1.x.

fix

Upgrade your Python environment to 3.12+ or use an older ArviZ version compatible with your Python (e.g., `pip install arviz<1.0`).

affects: >=1.0.0

breakingThe `rpy2` dependency and the `az.from_rpy2` function were removed in ArviZ v1.0.0 due to the internal refactor into a meta-package structure.

fix

Migrate any workflows relying on direct R-to-Python conversion via `from_rpy2` to alternative data transfer methods, or use an older ArviZ version if this functionality is critical.

affects: >=1.0.0

gotchaDefault values for several key plotting and analysis functions changed in ArviZ v0.13.0. For example, `az.plot_forest`'s `combined` argument, `az.plot_posterior`'s `kind` argument, and `az.loo`'s `pointwise` argument.

fix

Review release notes for v0.13.0 and explicitly specify arguments like `combined`, `kind`, `pointwise` if you relied on previous default behaviors to ensure consistent output.

affects: >=0.13.0

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'arviz'

ArviZ is not installed in the Python environment.

fix

Install ArviZ using pip: `pip install arviz`.

AttributeError: module 'arviz' has no attribute 'geweke'

The 'geweke' function has been removed in recent versions of ArviZ.

fix

Downgrade ArviZ to version 0.11.0 using conda: `conda install -c conda-forge arviz=0.11.0`.

AttributeError: module 'arviz' has no attribute 'plots'

The 'plots' module has been removed or restructured in recent versions of ArviZ.

fix

Ensure compatibility between PyMC3 and ArviZ versions, or update code to use the current ArviZ plotting functions.

AttributeError: module 'arviz' has no attribute 'extract'

The 'extract' function has been renamed to 'extract_dataset' in recent versions of ArviZ.

fix

Use 'az.extract_dataset()' instead of 'az.extract()'.

AttributeError: module 'pymc3' has no attribute 'traceplot'

PyMC3 has deprecated 'traceplot' in favor of ArviZ's 'plot_trace' function.

fix

Replace 'pm.traceplot()' with 'az.plot_trace()'.

Upgrade

Version history

1.3.0latest on PyPI · released Aug 11, 2026

Audit

Dependencies

No dependency data recorded yet.

Agent activity

55 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/arviz-devs/arviz ↗

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

homepagehttps://python.arviz.org ↗

docshttps://python.arviz.org ↗