pd-auto-ml 0.4.0

Pd auto_ml provides a pandas dataframe accessor to allow using dataframes with MindsDB (either the local native library or a local or remote mindsdb server)

Python MindsDB SDK

It enables you to connect to a midnsDB server and use it in a similar way to mindsb_native.

Install

pip install mindsdb_sdk

Example of usage

from mindsdb_sdk import SDK

# connect
mdb = SDK('http://localhost:47334')

# upload datasource
mdb.datasources['home_rentals_data'] = {'file' : 'home_rentals.csv'}

# create a new predictor and learn to predict
predictor = mdb.predictors.learn(
    name='home_rentals',
    datasource='home_rentals_data',
    to_predict='rental_price'
)

# predict
result = predictor.predict({'initial_price': '2000','number_of_bathrooms': '1', 'sqft': '700'})

Tests

Before run tests, change SERVER and CREDENTIAL constants in tests/test.py. After that, run python3 tests/test.py
Test file - is a good place where you can find some examples of api usage.

API Reference(WIP)

class MindsDB(server: str, params: dict)

class DataSources()

class DataSource()

class Predictors()

class Predictor()

class Proxy()