Metadata-Version: 2.1
Name: td_ml_probabilistic_unification
Version: 0.0.5
Summary: Probabilistic Unification
Project-URL: Homepage, https://github.com/treasure-data-ps/td_ml_datamodel_create
Project-URL: Bug Tracker, https://github.com/treasure-data-ps/td_ml_datamodel_create
Author-email: Gurbaksh Sharma <gurumail10@gmail.com>
License: Copyright © 2022 Treasure Data, Inc. (or its affiliates). All rights reserved
License-File: LICENSE
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.8
Description-Content-Type: text/markdown

# td-ml-probabilistic-unification

## Introduction
Python package for Probabilistic Unification

##### Declare ENV Variables from YML file
- **apikey** = os.environ['TD_API_KEY']
- **tdserver** = os.environ['TD_API_SERVER']
- **sink_database** = os.environ['SINK_DB']
- **output_table** = os.environ['OUTPUT_TABLE

#####----Defining Variables-------#####
TD_SINK_DATABASE=os.environ.get('TD_SINK_DATABASE')
TD_API_KEY=os.environ.get('TD_API_KEY')
TD_API_SERVER=os.environ.get('TD_API_SERVER')

id_col=os.environ.get('id_col')
cluster_col_name=os.environ.get('cluster_col_name')
convergence_threshold=float(os.environ.get('convergence_threshold'))
cluster_threshold=float(os.environ.get('cluster_threshold'))
string_type=os.environ.get('string_type')
fill_missing=os.environ.get('fill_missing')
feature_dict=json.loads(os.environ.get('feature_dict'))
blocking_table=os.environ.get('blocking_table')
output_table=os.environ.get('output_table')

record_limit=int(os.environ.get('record_limit'))
lower_limit=int(os.environ.get('lower_limit'))
upper_limit=int(os.environ.get('upper_limit'))
range_index=os.environ.get('range_index')
paralelism = os.environ.get('paralelism')

input_table=blocking_table

## Expected Input Table


`Copyright © 2022 Treasure Data, Inc. (or its affiliates). All rights reserved`
