Datarisk MLOps - SDK
A Python SDK for interacting with the MLOps API, providing tools for training, deploying, and monitoring machine learning models.
Table of Contents
Installation
pip install datarisk-mlops-codex
Getting started
To use the SDK, you must be logged in to the application. This can be done by importing one of the provided clients, as shown in the example below
from mlops_codex.model import MLOpsModelClient
client = MLOpsModelClient()
Example of usage
PATH = './samples/asyncModel/'
# Deploying a new model
model = client.create_model(
model_name='Teste notebook Async',
model_reference='score',
source_file=PATH+'app.py',
model_file=PATH+'model.pkl',
requirements_file=PATH+'requirements.txt',
schema=PATH+'schema.csv',
python_version='3.9',
operation="Async",
input_type='csv',
group='datarisk'
)
PATH = './samples/asyncModel/'
execution = model.predict(data=PATH+'input.csv', group_token='TODO', wait_complete = False)
There's also some example notebooks.
Support
- For help or questions, visit the documentation
Contributing
- To learn more about making a contribution to datarisk-mlops-codex, please see our Contributing guide.
2 maintainers
Metadata
2 maintainers
Release files for datarisk-mlops-codex 4.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| datarisk_mlops_codex-4.0.2.tar.gz | 117.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| datarisk_mlops_codex-4.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 180.5 kB
Release files / datarisk_mlops_codex-4.0.2.tar.gz
| Download URL | datarisk_mlops_codex-4.0.2.tar.gz |
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Release files / datarisk_mlops_codex-4.0.2-py3-none-any.whl
| Download URL | datarisk_mlops_codex-4.0.2-py3-none-any.whl |
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| Size | 63.0 kB |
| Tags | Python 3 |
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