hkube-python-wrapper 2.6.0.dev19

Hkube Python Wrapper

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

key	type	description
input	Array	algorithm input as defined in the pipeline descriptor
jobId	string	The job ID of the pipeline run
taskId	string	The task ID of the algorithm invocation
nodeName	string	The name of the node in the pipeline descriptor
pipelineName	string	The name of the pipeline
batchIndex	int	For batch instance, the index in the batch array
parentNodeName	string	For child (code-api) algorithm. The name of the invoking node
info.rootJobId	string	for sub-pipeline, the jobId of the invoking pipeline

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)