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dtreeviz

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library2.3.2pypypi✓ verified 85d ago

A Python 3 library for visualizing decision trees from scikit-learn, XGBoost, LightGBM, Spark, and TensorFlow. Version 2.3.2 supports AI chat integration for sklearn, categorical variables, and various tree model backends. Releases are frequent, approximately every few months.

pip install dtreeviz
INSTALL
IMPORT
SIG · DTREEVIZ
D
dtreeviz
ai-mlpythonv2.3.2
Install
18.2s avg
Import
6774ms
Disk
443MB
Pass rate
5/ 10
Env Coverage5 / 10
glibc
3.93.13
musl
3.93.13
Install & Compatibility
Where this runs
tested against v2.3.2 · 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 3.103.95 runs
build_error
glibc
py 3.103.95 runs
installs and imports cleanly · install 18.2s · import 6.774s · 426MB
443MB installed
● package 443MB
Code
Verified usage

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

dtreeviz
from dtreeviz import dtreeviz
import dtreeviz
The main function is inside the dtreeviz module. Using 'import dtreeviz' then calling dtreeviz.dtreeviz(...) is also valid but less common.
model
from sklearn.tree import DecisionTreeRegressor

Train a simple decision tree regressor and visualize it with dtreeviz.

from sklearn.datasets import load_diabetes from sklearn.tree import DecisionTreeRegressor from dtreeviz import dtreeviz diabetes = load_diabetes() X = diabetes.data y = diabetes.target regr = DecisionTreeRegressor(max_depth=3) regr.fit(X, y) viz = dtreeviz(regr, X, y, target_name='diabetes', feature_names=diabetes.feature_names) viz.view()
Debug
Known issues
breakingVersion 2.1.0 introduced a major refactoring. Functions like 'ctree_feature_space' changed signature; older code may break.
fix
Update function calls to match new signatures. Refer to changelog for specific changes.
affects: <2.1.0 → >=2.1.0
gotchaWhen using categorical features, ensure they are numeric-encoded. dtreeviz does not handle string categories natively in older versions; supported from 2.2.0 onward.
fix
Upgrade to >=2.2.0 or encode categories as integers before fitting.
affects: <2.2.0
Errors
Common errors & fixes
TypeError: dict() argument after ** must be a mapping, not float
Incompatibility with newer versions of numpy or other dependencies, fixed in 2.2.1.
fix
Upgrade dtreeviz to >=2.2.1 or pin numpy to a compatible version.
KeyError when using decision_boundaries function
Bug in version 2.0.x, fixed in 2.1.0.
fix
Upgrade dtreeviz to >=2.1.0.
Upgrade
Version history
2.3.2latest on PyPI · released Jan 2, 2026
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Dependencies

No dependency data recorded yet.

Agent activity
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Amazon
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OpenAI (training)
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Resources
dtreeviz — pip install dtreeviz · libregistry