ml-wrappers

library0.6.3pypypi✓ verified 80d ago

Machine Learning Wrappers SDK for Python (v0.6.3) provides wrapper classes to unify model outputs for interpretability and fairness tools. Active development by Microsoft.

ai-ml

pip install ml-wrappers

github ↗package ↗

INSTALL

IMPORT

SIG · ML-WRAPPERS

ml-wrappers

ai-mlpythonv0.6.3

Install

14.1s avg

Import

—

Disk

355MB

Pass rate

5/ 10

Env Coverage5 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.6.3 · 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

build_error

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 14.1s · import 0.000s · 342MB

355MB installed

● package 355MB

Code

Verified usage

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

DatasetWrapper

✓ from ml_wrappers import DatasetWrapper

✗ from ml_wrappers import ModelWrapper

wrap_model

✓ from ml_wrappers import wrap_model

✗ from ml_wrappers import ModelWrapper

Wrap a ML model with ModelWrapper to unify predict/predict_proba outputs.

from ml_wrappers import ModelWrapper import pandas as pd model = ... # your trained model X_test = pd.DataFrame({'feature': [1, 2, 3]}) wrapped = ModelWrapper(model=model, model_task='classification') # wrapped.predict(X_test) # returns structured output

Debug

Known issues

breakingIn v0.6.0, numpy and pandas were updated to >2.0. Older versions of these libraries may cause compatibility issues.

fix

Upgrade numpy to >=1.24 and pandas to >=2.0.

affects: >=0.6.0

breakingscikit-learn OneHotEncoder parameter changed from 'sparse' to 'sparse_output' in later scikit-learn versions. ml-wrappers v0.5.6+ handles this, but older versions may break.

fix

Update ml-wrappers to >=0.5.6 or manually adjust scikit-learn version.

affects: <0.5.6

deprecatedTensorFlow 1.x support is deprecated. TensorFlow wrapper may fail with TF 2.x if protobuf is incompatible.

fix

Use TensorFlow 2.x with compatible protobuf (e.g., protobuf <4.0).

affects: all

gotchaOpenAI wrapper in v0.5.x requires openai <1.0.0 for compatibility. v0.5.4 fixed this, but v0.5.3 and earlier break with openai >=1.0.0.

fix

Use openai<1.0.0 or upgrade ml-wrappers to >=0.5.4.

affects: >=0.5.0, <0.5.4

Upgrade

Version history

0.6.3latest on PyPI · released Mar 17, 2026

Audit

Dependencies

numpyrequiredCore dependency for array operations

pandasrequiredCore dependency for DataFrame handling

scikit-learnoptionalOptional but used for model wrappers

torchoptionalOptional for PyTorch model wrappers

tensorflowoptionalOptional for TensorFlow model wrappers

Agent activity

6 hits · last 30 days

node

Resources

githubhttps://github.com/microsoft/ml-wrappers ↗

packagehttps://pypi.org/project/ml-wrappers/ ↗