HKube Python Wrapper

Hkube python wrapper provides a simple interface for integrating algorithm in HKube

For general information on HKube see hkube.io

Installation

pip install hkube-python-wrapper

Download hkubectl latest version.

curl -Lo hkubectl https://github.com/kube-HPC/hkubectl/releases/download/$(curl -s https://api.github.com/repos/kube-HPC/hkubectl/releases/latest | grep -oP '"tag_name": "\K(.*)(?=")')/hkubectl-linux \
&& chmod +x hkubectl \
&& sudo mv hkubectl /usr/local/bin/

For mac replace with hkubectl-macos
For Windows download hkubectl-win.exe

Config hkubectl with your running Kubernetes.

hkubectl config # and follow the prompts

Basic Usage (using hkube build feature)

create a file for the algorithm entry-points (alg.py)

from typing import Dict
from hkube_python_wrapper import Algorunner, HKubeApi
def start(args: Dict, hkubeApi: HKubeApi):
    return 1

build the algorithm with hkubectl

hkubectl algorithm apply algorithm-name  --codePath ./folder_of_alg_py --codeEntryPoint alg.py --env python --setCurrent

Basic Usage (manual build)

from typing import Dict
from hkube_python_wrapper import Algorunner, HKubeApi
def start(args: Dict, hkubeApi: HKubeApi):
    return 1
if __name__ == "__main__":
    Algorunner.Run(start=start)

The start method accepts two arguments:

args: dict of invocation input

hkubeApi: instance of HKubeApi for code-api operations

Class HKubeApi

Method start_algorithm

def start_algorithm(
    self,
    algorithmName,
    input=[],
    includeResult=True,
    blocking=False
)

Starts an invocation of algorithm with input, and optionally waits for results

Args

algorithmName: string : The name of the algorithm to start.

input :array : Optional input for the algorithm.

includeResult :bool : if True, returns the result of the algorithm execution.
default: True

blocking :bool : if True, blocks until the algorithm finishes, and returns the results. If False, returns an awaiter object, that can be awaited (blocking) at a later time
default: False

Returns

if blocking==False, returns an awaiter. If true, returns the result of the algorithm

Example:

hkubeApi.start_algorithm('some_algorithm',input=[3], blocking=True)

Method start_stored_subpipeline

def start_stored_subpipeline(
    self,
    name,
    flowInput={},
    includeResult=True,
    blocking=False
)

Starts an invocation of a sub-pipeline with input, and optionally waits for results

Args

name : string : The name of the pipeline to start.

flowInput : dict : Optional flowInput for the pipeline.

includeResult :bool : if True, returns the result of the pipeline execution.
default: True

blocking : bool : if True, blocks until the pipeline finishes, and returns the results. If False, returns an awaiter object, that can be awaited (blocking) at a later time
default: False

Returns

if blocking==False, returns an awaiter. If true, returns the result of the pipeline

Example:

hkubeApi.start_stored_subpipeline('simple',flowInput={'foo':3},blocking=True)

Method start_raw_subpipeline

def start_raw_subpipeline(
    self,
    name,
    nodes,
    flowInput,
    options={},
    webhooks={},
    includeResult=True,
    blocking=False
)

Starts an invocation of a sub-pipeline with input, nodes, options, and optionally waits for results

Args

name : string : The name of the pipeline to start.

nodes : string : Array of nodes. See example below.

flowInput : dict : FlowInput for the pipeline.

options : dict : pipeline options (like in the pipeline descriptor).

webhooks : dict : webhook options (like in the pipeline descriptor).

includeResult :bool : if True, returns the result of the pipeline execution.
default: True

blocking : bool : if True, blocks until the pipeline finishes, and returns the results. If False, returns an awaiter object, that can be awaited (blocking) at a later time
default: False

Returns

if blocking==False, returns an awaiter. If true, returns the result of the pipeline

Example:

nodes=[{'nodeName': 'd1', 'algorithmName': 'green-alg', 'input': ['@flowInput.foo']}]
flowInput={'foo':3}
hkubeApi.start_raw_subpipeline('ddd',nodes, flowInput,webhooks={}, options={}, blocking=True)