Metadata-Version: 1.1
Name: rekcurd_client
Version: 1.0.0a0
Summary: A Python gRPC client for Rekcurd.
Home-page: https://github.com/rekcurd/python-client
Author: Rekcurd team and contributors
Author-email: rekcurd.developers@gmail.com
License: Apache License Version 2.0
Description: # rekcurd-client
        
        [![Build Status](https://travis-ci.com/rekcurd/python-client.svg?branch=master)](https://travis-ci.com/rekcurd/python-client)
        [![PyPI version](https://badge.fury.io/py/rekcurd-client.svg)](https://badge.fury.io/py/rekcurd-client)
        [![codecov](https://codecov.io/gh/rekcurd/python-client/branch/master/graph/badge.svg)](https://codecov.io/gh/rekcurd/python-client "Non-generated packages only")
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        Rekcurd client is the project for integrating ML module. Any Rekcurd service is connectable. It can connect the Rekcurd service on Kubernetes.
        
        
        ## Parent Project
        https://github.com/rekcurd/community
        
        
        ## Components
        - [Rekcurd](https://github.com/rekcurd/rekcurd-python): Project for serving ML module.
        - [Rekcurd-dashboard](https://github.com/rekcurd/dashboard): Project for managing ML model and deploying ML module.
        - [Rekcurd-client](https://github.com/rekcurd/python-client): Project for integrating ML module.
        
        
        ## Installation
        From source:
        
        ```
        git clone --recursive https://github.com/rekcurd/python-client.git
        cd python-client
        python setup.py install
        ```
        
        From [PyPi](https://pypi.org/project/rekcurd_client/) directly:
        
        ```
        pip install rekcurd_client
        ```
        
        ## How to use
        Example is available [here](https://github.com/rekcurd/rekcurd-client-example). 
        
        
        ## Unittest
        ```
        $ python -m unittest
        ```
        
        ## Method definition
        You need to use an appropriate method for your Rekcurd service. The methods are generated according to the input and output formats. *V* is the length of feature vector. *M* is the number of classes. If your algorithm is a binary classifier, you set *M* to 1. If your algorithm is a multi-class classifier, you set *M* to the number of classes.
        
        |method |input: data<BR>(required) |input: option |output: label<BR>(required) |output: score<BR>(required) |output: option |
        |:---|:---|:---|:---|:---|:---|
        |run_predict_string_string |string |string (json) |string |double |string (json) |
        |run_predict_string_bytes |string |string (json) |bytes |double |string (json) |
        |run_predict_string_arrint |string |string (json) |int[*M*] |double[*M*] |string (json) |
        |run_predict_string_arrfloat |string |string (json) |double[*M*] |double[*M*] |string (json) |
        |run_predict_string_arrstring |string |string (json) |string[*M*] |double[*M*] |string (json) |
        |run_predict_bytes_string |bytes |string (json) |string |double |string (json) |
        |run_predict_bytes_bytes |bytes |string (json) |bytes |double |string (json) |
        |run_predict_bytes_arrint |bytes |string (json) |int[*M*] |double[*M*] |string (json) |
        |run_predict_bytes_arrfloat |bytes |string (json) |double[*M*] |double[*M*] |string (json) |
        |run_predict_bytes_arrstring |bytes |string (json) |string[*M*] |double[*M*] |string (json) |
        |run_predict_arrint_string |int[*V*] |string (json) |string |double |string (json) |
        |run_predict_arrint_bytes |int[*V*] |string (json) |bytes |double |string (json) |
        |run_predict_arrint_arrint |int[*V*] |string (json) |int[*M*] |double[*M*] |string (json) |
        |run_predict_arrint_arrfloat |int[*V*] |string (json) |double[*M*] |double[*M*] |string (json) |
        |run_predict_arrint_arrstring |int[*V*] |string (json) |string[*M*] |double[*M*] |string (json) |
        |run_predict_arrfloat_string |double[*V*] |string (json) |string |double |string (json) |
        |run_predict_arrfloat_bytes |double[*V*] |string (json) |bytes |double |string (json) |
        |run_predict_arrfloat_arrint |double[*V*] |string (json) |int[*M*] |double[*M*] |string (json) |
        |run_predict_arrfloat_arrfloat |double[*V*] |string (json) |double[*M*] |double[*M*] |string (json) |
        |run_predict_arrfloat_arrstring |double[*V*] |string (json) |string[*M*] |double[*M*] |string (json) |
        |run_predict_arrstring_string |string[*V*] |string (json) |string |double |string (json) |
        |run_predict_arrstring_bytes |string[*V*] |string (json) |bytes |double |string (json) |
        |run_predict_arrstring_arrint |string[*V*] |string (json) |int[*M*] |double[*M*] |string (json) |
        |run_predict_arrstring_arrfloat |string[*V*] |string (json) |double[*M*] |double[*M*] |string (json) |
        |run_predict_arrstring_arrstring |string[*V*] |string (json) |string[*M*] |double[*M*] |string (json) |
        
        The input "option" field needs to be a json format. Any style is Ok but we have some reserved fields below.
        
        |Field |Type |Description |
        |:---|:---|:---|
        |suppress_log_input |bool |True: NOT print the input and output to the log message. <BR>False (default): Print the input and output to the log message.
        
Keywords: Rekcurd,Kubernetes,Python client,gRPC
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Web Environment
Classifier: Topic :: Software Development :: Libraries :: Application Frameworks
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
