https://github.com/rekcurd/python-client
Project for integrating ML module. It can connect the Rekcurd service on Kubernetes.
https://github.com/rekcurd/python-client
drucker grpc kubernetes ml rekcurd
Last synced: 8 months ago
JSON representation
Project for integrating ML module. It can connect the Rekcurd service on Kubernetes.
- Host: GitHub
- URL: https://github.com/rekcurd/python-client
- Owner: rekcurd
- License: apache-2.0
- Created: 2018-07-17T01:28:18.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2019-07-31T05:14:59.000Z (over 6 years ago)
- Last Synced: 2024-11-19T01:42:17.280Z (over 1 year ago)
- Topics: drucker, grpc, kubernetes, ml, rekcurd
- Language: Python
- Homepage:
- Size: 88.9 KB
- Stars: 7
- Watchers: 4
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# rekcurd-client
[](https://travis-ci.com/rekcurd/python-client)
[](https://badge.fury.io/py/rekcurd-client)
[](https://codecov.io/gh/rekcurd/python-client "Non-generated packages only")
[](https://pypi.python.org/pypi/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](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
(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.