Metadata-Version: 2.1
Name: logicplum
Version: 1.0.0
Summary: This client library is designed to support the LogicPlum API.
Home-page: https://github.com/LogicPlum/logicplum_v3
Author: LogicPlum, Inc.
Author-email: message@logicplum.com
License: MIT
Keywords: logicplum machine-learning AI automl prediction model
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: requests (>=2.25.1)
Requires-Dist: pandas (>=1.2.1)
Requires-Dist: twine (>=3.3.0)

# LogicPlum
LogicPlum is a client library for working with the LogicPlum platform APIs.


Example
------------
```
>>> import pandas as pd
>>> from logicplum import LogicPlum
>>>
>>>
>>> lp = LogicPlum("YOUR-API-KEY")
>>>
>>> # New Project
>>> project_id = lp.create_project("PROJECT-NAME", "PROJECT-DESCRIPTION")
>>> print(project_id)
>>>
>>> # Data Training
>>> train_df = pd.read_csv("datatotrain.csv")
>>> target = "TARGET-COLUMN-NAME"
>>> x = lp.train(project_id, train_df, target)
>>> print(x)
>>>
>>> # Check data training status
>>> training_status = lp.train_status(project_id)
>>> print(training_status)
>>>
>>> # List models
>>> models = lp.model_list(project_id)
>>> print(models)
>>>
>>> # Deploy a model
>>> model_id = "MODEL-ID-TO-DEPLOY"
>>> deployment_id = lp.deploy(project_id, model_id)
>>> print(deployment_id)
>>> 
>>> # List deployed models
>>> deployments = lp.deployment_list(project_id)
>>> print(deployments)
>>>
>>> # Predictions
>>> score_df = pd.read_csv('datatoscore.csv')
>>> scores = lp.score(deployment_id, score_df)
>>> print(scores)
>>>
```


