decanter-ai-core-sdk 1.0.0

Decanter AI Core SDK for the easy use of Decanter Core API.

MoBagel Decanter AI Core SDK

Decanter AI Core SDK allows you to call Decanter's API with more easy-to-use functions in Python.

It makes actions such like upload data, train models, predict results run more efficiently and handles hard to get results more accessible. It also supports running in jupyter notebook.

Installing

Install and update using pip:

pip install decanter-ai-core-sdk

Simple Example

from decanter import core

core.enable_default_logger()
context = core.Context.create(
        username='{usr}', password='{pwd}', host='{decanter-core-server}')
client = core.CoreClient()

train_file = open(train_file_path , 'r')
train_data = client.upload(file=train_file, name="train")

# In jupyter notebook just run the block no need to call context.run()
context.run()

train_data.show()

$ python -m path_to_file.file
15:50:09 [    INFO] [Context] no event loop to close
15:50:09 [    INFO] [Context] connect healty :)
Progress UploadTask_train:  55%|█████████████████████████████████████████

Contributing

For guidance on setting up a development environment and how to make a contribution to Decanter AI Core SDK, see the contributing guidelines.

Links

For details on design, guidance on setting up a development environment and how to make a contribution to MoBagel Decanter Core SDK.

• Code: https://github.com/MoBagel/decanter-ai-core-sdk