# Copyright 2020 kubeflow.org
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.


import kfp.dsl as dsl
from kubernetes.client import V1Volume, V1SecretVolumeSource, V1VolumeMount, V1EnvVar
from kfp import components

OP1_STR = """
name: download
outputs:
  - {name: downloaded, type: String}
implementation:
  container:
    image: google/cloud-sdk
    command:
    - sh
    - -c
    args:
    - |
      set -e
      ls | tee $0
    - {outputPath: downloaded}
"""

OP2_STR = """
name: echo
inputs:
  - {name: msg, type: String}
implementation:
  container:
    image: library/bash
    command:
    - sh
    - -c
    args:
    - |
      set -e
      echo
    - {inputValue: msg}
"""

op1_op = components.load_component_from_text(OP1_STR)
op2_op = components.load_component_from_text(OP2_STR)


@dsl.pipeline(
    name='volume',
    description='A pipeline with volume.'
)
def volume_pipeline():
    op1 = op1_op()

    op1.add_volume(V1Volume(name='gcp-credentials',
                            secret=V1SecretVolumeSource(secret_name='user-gcp-sa')))
    op1.container.add_volume_mount(V1VolumeMount(mount_path='/secret/gcp-credentials',
                                                 name='gcp-credentials'))
    op1.container.add_env_variable(V1EnvVar(name='GOOGLE_APPLICATION_CREDENTIALS',
                                            value='/secret/gcp-credentials/user-gcp-sa.json'))
    op1.container.add_env_variable(V1EnvVar(name='Foo', value='bar'))

    op2 = op2_op(op1.output)


if __name__ == '__main__':
    from kfp_tekton.compiler import TektonCompiler
    TektonCompiler().compile(volume_pipeline, __file__.replace('.py', '.yaml'))