Skip to main content

MonitorAI SDK

The Official Python SDK for Monitoring Machines Lab. MonitorAI is an observabiltiy framework designed for tabular ML to GenAI offering root cause analysis and decision intelligence allowing a linkup between ML and decision making for organizations that rely and use ML for solutions.

Getting started with monitorai sdk for feature drift :

  • Install the package:
pip install monitorai
import pandas as pd
from monitorai import MonitorAI
from monitorai.drift.feature import CategoricalFeatureDrift

client=MonitorAI(api_key="***")

ref_df=pd.DataFrame({
"color":["red","red","blue","blue","red","yellow","yellow","red","blue"],
"social":["twitter","twitter","facebook","facebook","twitter","insta","insta","insta","insta"]})
    
analysis_df=pd.DataFrame({
"color":["red","red","red","blue","blue","yellow"],
"social":["twitter","twitter","facebook","insta","insta","insta"]
})


## create feature drift variable:
feature_drift=CategoricalFeatureDrift(ref_data=ref_df,analysis_data=analysis_df)

## get the bhattacharrya coefficients
bhatta_coeff_social=feature_drift.bhatta_coeff(feature="social")
bhatta_coeff_color=feature_drift.bhatta_coeff(feature="color")

## cauchy schwartz distance:
cauchy_schwartz_social=feature_drift.cauchy_schwartz_dist(feature="social")
cauchy_schwartz_color=feature_drift.cauchy_schwartz_dist(feature="color")

## euclidean distance:
euclid_social=feature_drift.euclidean_dist(feature="social")
euclid_color=feature_drift.euclidean_dist(feature="color")

## hellinger distance:
hellinger_social=feature_drift.hellinger_dist(feature="social")
hellinger_color=feature_drift.hellinger_dist(feature="color")

## jensen-shannon divergence:
js_social=feature_drift.js_divergence(feature="social")
js_color=feature_drift.js_divergence(feature="social")

## kl-divergence:
kl_social=feature_drift.kl_divergence(feature="social")
kl_color=feature_drift.kl_divergence(feature="color")

##psi:
psi_social=feature_drift.psi(feature="social")
psi_color=feature_drift.psi(feature="color")

Citing monitorai

If you use monitorai in your research, please cite it:

@software{monitorai,
  title = {monitorai: A Root Cause and Decision Intelligence Kit For Machine Learning},
  author = {Monitoring Machines Lab},
  year = {2026},
  url = {https://github.com/MasemeneMatlakanaBenny/monitorai},
  doi = {10.5281/zenodo.19646175},
  license = {MIT},
}

Metadata

Release files for monitor-aii 0.1.48

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for monitor-aii 0.1.48
File Size Uploaded
monitor_aii-0.1.48.tar.gz 6.7 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for monitor-aii 0.1.48
File Interpreter ABI Platform
monitor_aii-0.1.48-py3-none-any.whl Python 3 none any Details

Total release size: 18.2 kB

Release files / monitor_aii-0.1.48.tar.gz

Download URL monitor_aii-0.1.48.tar.gz
Size 6.7 kB
Tags Source
SHA-256 checksum
How to use checksums
df86fa3111c88a38a2ca9af8900d07c308e0e0279a72dc0f315a6e485a80e127
BLAKE2b-256 checksum
How to use checksums
296eff1c393cbc58a7de0bf42bd9aef20f3a8bf985dc59632cf43eb624db61d6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.3

Release files / monitor_aii-0.1.48-py3-none-any.whl

Download URL monitor_aii-0.1.48-py3-none-any.whl
Size 11.6 kB
Tags Python 3
SHA-256 checksum
How to use checksums
610d48966fa6e10e8f7f1f1f77ec1c7f9782a37c821171a82004d0841036e98e
BLAKE2b-256 checksum
How to use checksums
76733b5414bd70ce5b9d89dfebd60a46faf8ef63138fc3ad8611855096f0fc62
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.3

Release history Release notifications | RSS feed

This release

0.1.48 This release

2 release files

0.1.4

2 release files

0.1.3

2 release files

0.1.2

2 release files

0.1.1

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page