#! /usr/bin/env python3
import apache_beam as beam
from apache_beam.options.pipeline_options import PipelineOptions

job_server = "3.84.135.13"
# expansion_service = "localhost:8096"
# Set up this host to point to 127.0.0.1 in /etc/hosts
# bootstrap_servers = "host.docker.internal:9092"
# kafka_consumer_group_id = "kafka_echo"
# input_topic = "echo-input"
# output_topic = "echo-output"


pipeline_options = {
    # MUST BE PortableRunner
    "runner": "PortableRunner",
    "job_name": "ftd_beam_test",
    "job_endpoint": f"{job_server}:8099",
    "artifact_endpoint": f"{job_server}:8098",
    "environment_type": "EXTERNAL",
    "environment_config": "localhost:50000",
    "streaming": True,
    "parallelism": 2,
    "experiments": ["use_deprecated_read"],
    "checkpointing_interval": "60000",
}
options = PipelineOptions([], **pipeline_options)


# options = PipelineOptions(
#    [
#        "--runner=FlinkRunner",
#        "--flink_version=1.16",
#        "--job_endpoint=3.95.212.26:8081",
#        #    "--environment_type=LOOPBACK" # loopback for local only?
#        #    "--environment_type=DOCKER"
#    ]
# )
# options = PipelineOptions(
#    [
#        "--runner=FlinkRunner",
#        #        "--flink_version=1.16",
#        "--job_endpoint=3.84.135.13:8099",
#        #    "--environment_type=LOOPBACK" # loopback for local only?
#        #    "--environment_type=DOCKER"
#    ]
# )

# From another example (https://python.plainenglish.io/apache-beam-flink-cluster-kubernetes-python-a1965f37b7cb)
#    options = PipelineOptions([
#        "--runner=FlinkRunner",
#        "--flink_version=1.10",
#        "--flink_master=localhost:8081",
#        "--environment_type=EXTERNAL",
#        "--environment_config=localhost:50000"
#    ])


with beam.Pipeline(options=options) as pipeline:
    elements = (
        pipeline
        | "Create elements"
        >> beam.Create(["Hello", "World", "Fred", "was", "here", "twice", "Fred"])
        | "Print Elements" >> beam.Map(print)
    )