Metadata-Version: 2.1
Name: jupyterflow
Version: 0.0.1
Summary: Run your ML workflow with jupyterflow
Home-page: https://github.com/hongkunyoo/jupyterflow
Author: hongkunyoo
Author-email: hongkunyoo@gmail.com
License: BSD 3-Clause
Description: # jupyterflow
        
        Run workflow on JupyterHub
        
        ## What is jupyterflow
        
        Run [Argo Workflow](https://argoproj.github.io/argo) pipeline on JupyterHub with single command!
        
        #### For Users
        - No Kubernetes knowledge (YAML) need.
        - No container build & push or deploy.
        - Just run pipeline with single command `jupyterflow`!
        
        #### For MLOps Engineer
        
        Although, You need to know Kubernetes to set its up, But it is...
        
        - Easy to deploy ML jobs.
        - 
        
        
        
        ## Get Started
        
        ### Prerequisite
        
        
        
        
        ### Install jupyterflow
        
        
        
        ### Run Workflow
        
        ```bash
        jupyterflow create -c "python main.py >> python train.py"
        ```
        
        ```bash
        jupyterflow create -f workflow.yaml
        ```
        
        
        ```yaml
        # workflow.yaml
        jobs:
        - python input.py 
        - python train.py
        
        dags:
        - 1 >> 2
        ```
        
        ### Go to Argo Workflow Web
        
        ![]()
        
        
        ## How does it work?
        
        그럼 넣기
        
        
        
        
        
        ## Configuration
        
        ```yaml
        # $HOME/.jupyterflow.yaml
        workflow:
          name: jupyterflow
        singleuser:
          image:
            name: jupyter/datascience-notebook:latest
            pullPolicy: Always
            secret: "default"
          resources:
            requests:
              cpu: 400m
              memory: 400Mi
            limits:
              cpu: 400m
              memory: 400Mi
          env:
            CUSTOM_ENV: "value"
          runAsUser: 1000
          runAsGroup: 100
          fsGroup: 100
          nodeSelector: {}
          serviceAccountName: default
          storage:
            homePvcName: claim-{username}
            homeMountPath: /home/jovyan
            extraVolumes:
            - name: nas001
              persistentVolumeClaim:
                claimName: nas001
            extraVolumeMounts:
            - name: nas001
              mountPath: /nas001
        ```
        
        
        ### `workflow`
        
        - `name`: jupyterflow
        
        ### `singlueuser`
        
        - `image.name`: current JupyterHub Server image
        - `image.pullPolicy`: Always
        - `image.secret`: default
        - `resources.requests`: None
        - `resources.limits`: None
        - `storage.homePvcName`: `claim-{username}`
        - `storage.homeMountPath`: `/home/jovyan`
        - `storage.extraVolumes`: 
            - `Pod` Volumes Spec
        - `storage.extraVolumeMounts`: 
            - `name`:
            - `mountPath`: 
        - `env`: 
            - `name`:
            - `value`:
        - `nodeSelector`: {}
        - `runAsUser`: 1000
        - `runAsGroup`: 100
        - `fsGroup`: 100
        - `serviceAccountName`: default
        
        
Keywords: ctl,jupyterhub,pipeline,ML
Platform: UNKNOWN
Description-Content-Type: text/markdown
