example.yaml

apiVersion: argoproj.io/v1alpha1
kind: Workflow
metadata:
  generateName: hera-example-
  annotations:
    workflows.argoproj.io/description: |-
      Replicates the functionality of
      example.yaml
    workflows.argoproj.io/title: example remade via hera
    workflows.diamond.ac.uk/repository: https://github.com/DiamondLightSource/python-interface-to-workflows
  labels:
    workflows.diamond.ac.uk/science-group-examples: 'true'
spec:
  entrypoint: workflowentry
  templates:
  - name: workflowentry
    dag:
      tasks:
      - name: install
        template: install-dependencies
      - name: params
        template: generate-parameters
        arguments:
          parameters:
          - name: png
            value: 'True'
          - name: jpg
            value: 'True'
          - name: jpeg
            value: 'True'
          - name: tif
            value: 'True'
          - name: tiff
            value: 'True'
      - name: create-image
        depends: install && params
        template: create-image
        withParam: '{{tasks.params.outputs.parameters.out-parameters}}'
        arguments:
          parameters:
          - name: width
            value: '{{item.width}}'
          - name: height
            value: '{{item.height}}'
          - name: weights
            value: '{{item.weights}}'
          - name: extension
            value: '{{item.extension}}'
      - name: to-hdf5
        depends: create-image
        template: to-hdf5
        arguments:
          parameters:
          - name: paths
            value: '{{tasks.create-image.outputs.parameters.out-paths}}'
  - name: install-dependencies
    script:
      image: python:3.10
      source: |-
        import os
        import sys
        sys.path.append(os.getcwd())
        import subprocess
        print('creating venv')
        subprocess.check_call(['python', '-m', 'venv', '/tmp/venv'])
        subprocess.check_call(['/tmp/venv/bin/pip', 'install', 'pillow', 'h5py', 'numpy', 'hera'])
      command:
      - python
      volumeMounts:
      - name: tmpdir
        mountPath: /tmp
  - name: generate-parameters
    inputs:
      parameters:
      - name: png
      - name: jpg
      - name: jpeg
      - name: tif
      - name: tiff
    outputs:
      parameters:
      - name: out-parameters
        valueFrom:
          path: /tmp/parameters.json
    script:
      image: python:3.10
      source: |-
        import os
        import sys
        sys.path.append(os.getcwd())
        import json
        try: jpeg = json.loads(r'''{{inputs.parameters.jpeg}}''')
        except: jpeg = r'''{{inputs.parameters.jpeg}}'''
        try: jpg = json.loads(r'''{{inputs.parameters.jpg}}''')
        except: jpg = r'''{{inputs.parameters.jpg}}'''
        try: png = json.loads(r'''{{inputs.parameters.png}}''')
        except: png = r'''{{inputs.parameters.png}}'''
        try: tif = json.loads(r'''{{inputs.parameters.tif}}''')
        except: tif = r'''{{inputs.parameters.tif}}'''
        try: tiff = json.loads(r'''{{inputs.parameters.tiff}}''')
        except: tiff = r'''{{inputs.parameters.tiff}}'''

        import json
        params: list[dict[str, int | list[int] | str] | None] = [{'width': 500, 'height': 500, 'weights': [255, 1, 100], 'extension': 'png'} if png.lower() == 'true' else None, {'width': 600, 'height': 200, 'weights': [100, 150, 100], 'extension': 'jpg'} if jpg.lower() == 'true' else None, {'width': 300, 'height': 400, 'weights': [100, 150, 100], 'extension': 'jpeg'} if jpeg.lower() == 'true' else None, {'width': 300, 'height': 200, 'weights': [230, 100, 1], 'extension': 'tif'} if tif.lower() == 'true' else None, {'width': 200, 'height': 300, 'weights': [230, 100, 1], 'extension': 'tiff'} if tiff.lower() == 'true' else None]
        params_to_write: list[dict[str, int | list[int] | str]] = [image_params for image_params in params if image_params is not None]
        with open('/tmp/parameters.json', 'w') as f:
            json.dump(params_to_write, f)
      command:
      - python
      volumeMounts:
      - name: tmpdir
        mountPath: /tmp
  - name: create-image
    inputs:
      parameters:
      - name: width
      - name: height
      - name: weights
      - name: extension
    outputs:
      artifacts:
      - name: '{{inputs.parameters.extension}}-image'
        path: /tmp/{{inputs.parameters.extension}}-image.{{inputs.parameters.extension}}
        archive:
          none: {}
      parameters:
      - name: out-paths
        valueFrom:
          path: /tmp/{{inputs.parameters.extension}}-path.json
    script:
      image: python:3.10
      source: |-
        import os
        import sys
        sys.path.append(os.getcwd())
        import json
        try: extension = json.loads(r'''{{inputs.parameters.extension}}''')
        except: extension = r'''{{inputs.parameters.extension}}'''
        try: height = json.loads(r'''{{inputs.parameters.height}}''')
        except: height = r'''{{inputs.parameters.height}}'''
        try: weights = json.loads(r'''{{inputs.parameters.weights}}''')
        except: weights = r'''{{inputs.parameters.weights}}'''
        try: width = json.loads(r'''{{inputs.parameters.width}}''')
        except: width = r'''{{inputs.parameters.width}}'''

        import json
        from PIL import Image

        def create_pattern(width: int, height: int, weights: tuple[int, int, int]) -> Image.Image:
            print(f'width: {width}')
            print(f'height: {height}')
            print(f'RBG weights: {weights}')
            image = Image.new('RGB', (width, height))
            pixels = image.load()
            for i in range(width):
                for j in range(height):
                    pixels[i, j] = ((i + j * 50) % weights[0], weights[1], (i * 300 + j) % weights[2])
            return image
        image = create_pattern(width, height, weights)
        path = f'/tmp/{extension}-image.{extension}'
        image.save(path)
        with open(f'/tmp/{extension}-path.json', 'w') as f:
            json.dump(path, f)
      command:
      - /tmp/venv/bin/python
      volumeMounts:
      - name: tmpdir
        mountPath: /tmp
  - name: to-hdf5
    inputs:
      parameters:
      - name: paths
    outputs:
      artifacts:
      - name: hdf5output
        path: /tmp/images.hdf5
        archive:
          none: {}
    script:
      image: python:3.10
      source: |-
        import os
        import sys
        sys.path.append(os.getcwd())
        import json
        try: paths = json.loads(r'''{{inputs.parameters.paths}}''')
        except: paths = r'''{{inputs.parameters.paths}}'''

        import h5py
        import numpy as np
        from PIL import Image
        print('creating hdf5 file')
        with h5py.File('/tmp/images.hdf5', 'w') as f:
            for i, path in enumerate(paths):
                path = path.strip('"')
                print(f'Got {path}')
                with Image.open(path) as image:
                    arr = np.array(image)
                    f.create_dataset(f'image_{i}', data=arr, dtype=arr.dtype)
        print('done')
      command:
      - /tmp/venv/bin/python
      volumeMounts:
      - name: tmpdir
        mountPath: /tmp
  volumeClaimTemplates:
  - metadata:
      name: tmpdir
    spec:
      accessModes:
      - ReadWriteOnce
      resources:
        requests:
          storage: 1Gi