semvec/pypi-packages huggingface dataset:
ServeIt 0.0.9
Machine learning prediction serving
Keywords: machine learning model deployment serving API RESTful

ServeIt
=======

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version|

ServeIt lets you serve model predictions and supplementary information
from a RESTful API using your favorite Python ML library in as little as
one line of code:

.. code:: python

    from serveit.server import ModelServer
    from sklearn.linear_model import LogisticRegression
    from sklearn.datasets import load_iris

    # fit logistic regression on Iris data
    clf = LogisticRegression()
    data = load_iris()
    clf.fit(data.data, data.target)

    # initialize server with a model and start serving predictions
    ModelServer(clf, clf.predict).serve()

Your new API is now accepting ``POST`` requests at
``localhost:5000/predictions``! Please see the `examples <examples>`__
directory for detailed examples across domains (e.g., regression, image
classification), including live examples.

Features
^^^^^^^^

Current ServeIt features include:

1. Model inference serving via RESTful API endpoint
2. Extensible library for inference-time data loading, preprocessing,
   input validation, and postprocessing
3. Supplementary information endpoint creation
4. Automatic JSON serialization of responses
5. Configurable request and response logging (work in progress)

Supported libraries
^^^^^^^^^^^^^^^^^^^

The following libraries are currently supported: \* Scikit-Learn \*
Keras \* PyTorch

Installation: Python 2.7 and Python 3.6
---------------------------------------

Installation is easy with pip: ``pip install serveit``

Building
--------

You can build locally with: ``python setup.py``

License
-------

`MIT <LICENSE.md>`__

Please consider buying me a coffee if you like my work:

.. |Build Status| image:: https://travis-ci.org/rtlee9/serveit.svg?branch=master
   :target: https://travis-ci.org/rtlee9/serveit
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.. |PyPI version| image:: https://badge.fury.io/py/ServeIt.svg
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