Bike sharing prediction model

Usage

To install the library:

$ # pip install ie_bike_model  # To upload to PyPI, which is not intended.
$ pip install .

Basic usage:

>>> import datetime as dt
>>> from ie_bike_model.model import train_and_persist, predict
>>> train_and_persist()  # Trains the model and saves it to `model.pkl`
>>> predict({
...     "date": dt.datetime(2011, 1, 1, 0, 0, 0),
...     "weathersit": 1,
...     "temperature_C": 9.84,
...     "feeling_temperature_C": 14.395,
...     "humidity": 81.0,
...     "windspeed": 0.0,
... })
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Development

To install a development version of the library:

$ flit install

To run the tests:

$ pytest