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Sample model

Unit tests

Test repo for hands-on part of the first MLOps lecture.

How to use it

from mlops_models import ConstantPredictionModel

model = ConstantPredictionModel(0)
model.predict("")
> 0
from mlops_models import ConstantPredictionModel

model = ConstantPredictionModel(1)
model.predict("")
> 1

How to build it

To build a python package, run the following command:

python setup.py sdist bdist_wheel

This will generate a dist folder with the following structure:

mlops_models-0.1.0-py3-none-any.whl
mlops_models-0.1.0.tar.gz

How to test it

To run the tests, run the following command:

python -m pytest

How to install it

To install the package, run the following command:

pip install mlops_models-0.1.0-py3-none-any.whl

To install it in development mode, run the following command:

pip install -e .

How to run it

To run the package, run the following command:

python -m mlops_models

How to publish it

To publish the package, run the following command:

python -m twine upload dist/*

To publish package in GitHub, run the following command:

python -m github-release upload --tag v0.1.0 --user FRI-Machine-Learning-Operations-22-23 --repo mlops-01-hands-on --name "mlops_models-0.1.0-py3-none-any.whl" --file dist/mlops_models-0.1.0-py3-none-any.whl

How to contribute

To contribute, run the following commands:

git clone

Release files for mlops-models 1.0.5

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

Source distribution (sdist)

Source distribution for mlops-models 1.0.5
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Built distribution (wheel)

Table of built distributions (wheels) for mlops-models 1.0.5
File Interpreter ABI Platform
mlops_models-1.0.5-py3-none-any.whl Python 3 none any Details

Total release size: 57.1 kB

Release files / mlops-models-1.0.5.tar.gz

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