5_1_read_and_sentimental_analysis.py

# MIT License
#
# Copyright (c) 2019 Jaehyeuk Oh, Hyperconnect
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.

from __future__ import absolute_import

import logging
import json

import apache_beam as beam
from apache_beam.options.pipeline_options import PipelineOptions


def run(argv=None):
    pipeline_options = PipelineOptions(["--runner=DirectRunner", "--streaming"])
    p = beam.Pipeline(options=pipeline_options)

    # read
    topic_path = "projects/qwiklabs-gcp-34125c5e4e40e9e3/topics/pycon30-tweet"  # replace topic with yours
    lines = (p | 'read' >> beam.io.ReadFromPubSub(topic=topic_path)
                | 'Load into JSON' >> beam.Map(json.loads)
                | 'out' >> beam.Map(lambda x: logging.info(x)))

    result = p.run()
    result.wait_until_finish()

if __name__ == '__main__':
    logging.getLogger().setLevel(logging.INFO)
    run()