rekcurd-client

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: Project for serving ML module.
• Rekcurd-dashboard: Project for managing ML model and deploying ML module.
• Rekcurd-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 directly:

pip install rekcurd_client

How to use

Example is available here.

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 (required)	input: option	output: label (required)	output: score (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. False (default): Print the input and output to the log message.