Registry / ai-ml / datarobot-predict

datarobot-predict

library1.13.5pypypi✓ verified 81d ago

A lightweight Python library for scoring predictions with DataRobot models. It provides a simple API to interact with DataRobot's prediction server, supporting both REST and batch predictions. Current version: 1.13.5, maintained by DataRobot. Release cadence is irregular.

ai-ml http-networking

pip install datarobot-predict

package ↗homepage ↗

INSTALL

IMPORT

SIG · DATAROBOT-PREDICT

datarobot-predict

ai-mlpythonv1.13.5

Install

9.7s avg

Import

—

Disk

200MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v1.13.5 · 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 3.10–3.910 runs

installs and imports cleanly · install 0.0s · import 0.000s · 197.7MB

glibc

py 3.10–3.910 runs

installs and imports cleanly · install 9.7s · import 0.000s · 191MB

200MB installed

● package 200MB

Code

Verified usage

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

TimeSeriesType

✓ from datarobot_predict import TimeSeriesType

✗ from datarobot_predict import ScoreClient

Creates a ScoreClient and makes a single prediction or batch predictions. Endpoint includes deployment ID. API key should be set in environment.

from datarobot_predict import ScoreClient client = ScoreClient( endpoint='https://example.datarobot.com/predApi/v1.0/deployments/<deployment_id>/predictions', api_key=os.environ.get('DATAROBOT_API_KEY', ''), max_prediction_time=30 ) # Single prediction response = client.predict(data={'feature1': 'value1', 'feature2': 123}) print(response) # Batch predictions batch_data = [{'feature1': 'a', 'feature2': 1}, {'feature1': 'b', 'feature2': 2}] batch_response = client.predict_batch(batch_data) print(batch_response)

Debug

Known issues

breakingIn v1.12+, the 'ScoreClient' no longer accepts 'deployment_id' as a separate argument; you must include the full endpoint URL with deployment ID. Old code that passed deployment_id separately will break.

fix

Construct endpoint URL as 'https://app.datarobot.com/predApi/v1.0/deployments/{deployment_id}/predictions' and pass it as 'endpoint' parameter.

affects: >=1.12.0

breakingIn v1.10+, the default authentication method changed to use 'api_key' parameter. The old 'username' and 'password' parameters are deprecated and will raise an error if used.

fix

Use 'api_key' parameter instead of 'username' and 'password'.

affects: >=1.10.0

gotchaThe 'predict' method returns a 'PredictionResponse' object, not a dict. Access fields like 'response.predictions' or convert with 'response.json()'.

fix

Use 'response.json()' to get a dict or access attributes directly.

affects: all

gotchaIf you pass a single row as a list, the library might misinterpret it as multiple rows. Always wrap a single row in a list or use 'predict' for a single dict.

fix

For single prediction: client.predict(data={'feature1': 'value'}). For multiple: client.predict_batch([{'feature1': 'value1'}, ...])

affects: all

Upgrade

Version history

1.13.5latest on PyPI · released Dec 24, 2025

Audit

Dependencies

No dependency data recorded yet.

Agent activity

21 hits · last 30 days

node

Amazon

Bingbot

OpenAI (training)

Resources

packagehttps://pypi.org/project/datarobot-predict/ ↗

homepagehttps://www.datarobot.com ↗