Metadata-Version: 2.1
Name: automl-streams
Version: 0.0.2
Summary: AutoML framework for implementing automated machine learning on data streams.
Home-page: https://github.com/AlexImb/automl-streams
Author: Alexandru-Ionut Imbrea
Author-email: aleximbrea@gmail.com
License: mit
Project-URL: Documentation, https://github.com/AlexImb/automl-streams
Platform: any
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Programming Language :: Python
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: scikit-learn (>=0.22.1)
Requires-Dist: scikit-multiflow (>=0.4.1)
Requires-Dist: kafka-python (>=1.4.7)
Requires-Dist: pymfe (>=0.2.0)
Provides-Extra: docs
Requires-Dist: sphinx ; extra == 'docs'
Provides-Extra: testing
Requires-Dist: pytest ; extra == 'testing'
Requires-Dist: pytest-cov ; extra == 'testing'


# AutoML Streams

An AutoML framework for implementing automated machine learning on data streams 
architectures in production environments.

# Installation

From `pip`

```shell
pip install -U automl-streams
```

or `conda`:

```shell
conda install automl-streams
```

# Usage

```py
from skmultiflow.trees import HoeffdingTree
from skmultiflow.evaluation import EvaluatePrequential
from automlstreams.streams import KafkaStream

stream = KafkaStream(topic, bootstrap_servers=broker)
stream.prepare_for_use()
ht = HoeffdingTree()
evaluator = EvaluatePrequential(show_plot=True,
                                pretrain_size=200,
                                max_samples=3000)

evaluator.evaluate(stream=stream, model=[ht], model_names=['HT'])
```

More demonstrations available in the [demos](./demos) directory.

# Development

Create and activate a `virtualenv` for the project:

```shell
$ virtualenv .venv
$ source .venv/bin/activate
```

Install the `development` dependencies:

```shell
$ pip install -e . 
```

Install the app in "development" mode:
```shell
$ python setup.py develop  
```






