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the_reading_machine.py
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import os
from airflow import DAG
from airflow import configuration as conf
from airflow.operators.bash_operator import BashOperator
from airflow.operators.dummy_operator import DummyOperator
from airflow.operators.email_operator import EmailOperator
from datetime import datetime, timedelta
# Load configuration
process_directory = os.path.join(conf.get('core', 'process_folder'))
# Set configure
default_args = {
'owner': 'michael',
'depends_on_past': False,
'start_date': datetime(2017, 4, 24),
'email': ['mkao006@gmail.com'],
'email_on_failure': True,
'email_on_retry': False,
'retries': 3,
'retry_delay': timedelta(minutes=1),
'catchup_by_default': False
}
# Create dag
dag = DAG('the_reading_machine',
default_args=default_args,
schedule_interval=None)
########################################################################
# Create nodes
########################################################################
# Article scrapping
# --------------------
scraper_dir = os.path.join(process_directory, 'article_scraper')
article_scraper_command = 'cd {}; python processor.py'.format(scraper_dir)
article_scraper = BashOperator(bash_command=article_scraper_command,
task_id='article_scraper',
params=default_args,
dag=dag)
db_raw_article = DummyOperator(task_id='db_raw_article', dag=dag)
# Article processing
# --------------------
article_processing_script_path = os.path.join(
process_directory, 'article_processing/processor.py')
article_processing_command = 'python {}'.format(
article_processing_script_path)
article_processing = BashOperator(bash_command=article_processing_command,
task_id='article_processing',
params=default_args,
dag=dag)
db_processed_article = DummyOperator(task_id='db_processed_article', dag=dag)
# Price Extraction
# --------------------
price_scraper_script_path = os.path.join(
process_directory, 'price_extraction/processor.py')
price_scraper_command = 'python {}'.format(
price_scraper_script_path)
price_scraper = BashOperator(bash_command=price_scraper_command,
task_id='price_extraction',
params=default_args,
dag=dag)
db_raw_price = DummyOperator(task_id='db_raw_price', dag=dag)
# Sentiment scoring
# --------------------
sentiment_scoring_script_path = os.path.join(
process_directory, 'sentiment_scoring/processor.py')
sentiment_scoring_command = 'python {}'.format(
sentiment_scoring_script_path)
sentiment_scoring = BashOperator(bash_command=sentiment_scoring_command,
task_id='sentiment_scoring',
params=default_args,
dag=dag)
db_sentiment_scoring = DummyOperator(task_id='db_sentiment_scoring', dag=dag)
# Topic Modelling
# --------------------
topic_modelling_script_path = os.path.join(
process_directory, 'topic_modelling/processor.py')
topic_modelling_command = 'python {}'.format(
topic_modelling_script_path)
topic_modelling = BashOperator(bash_command=topic_modelling_command,
task_id='topic_modelling',
params=default_args,
dag=dag)
db_topic_modelling = DummyOperator(task_id='db_topic_modelling', dag=dag)
# Geo_Tagging
# --------------------
geo_tagging_script_path = os.path.join(
process_directory, 'geo_tagging/processor.py')
geo_tagging_command = 'python {}'.format(
geo_tagging_script_path)
geo_tagging = BashOperator(bash_command=geo_tagging_command,
task_id='geo_tagging',
params=default_args,
dag=dag)
db_geo_tagging = DummyOperator(task_id='db_geo_tagging', dag=dag)
# Commodity tagging
# --------------------
commodity_tagging_script_path = os.path.join(
process_directory, 'commodity_tagging/processor.py')
commodity_tagging_command = 'python {}'.format(
commodity_tagging_script_path)
commodity_tagging = BashOperator(bash_command=commodity_tagging_command,
task_id='commodity_tagging',
params=default_args,
dag=dag)
db_commodity_tagging = DummyOperator(task_id='db_commodity_tagging', dag=dag)
# Data harmonisation
# --------------------
data_harmonisation_script_path = os.path.join(
process_directory, 'data_harmonisation/processor.py')
data_harmonisation_command = 'python {}'.format(
data_harmonisation_script_path)
data_harmonisation = BashOperator(bash_command=data_harmonisation_command,
task_id='data_harmonisation',
params=default_args,
dag=dag)
db_data_harmonisation = DummyOperator(task_id='db_data_harmonisation', dag=dag)
# Build price model
# --------------------
price_modelling_script_path = os.path.join(
process_directory, 'price_modelling/processor.py')
price_modelling_command = 'python {}'.format(
price_modelling_script_path)
price_modelling = BashOperator(bash_command=price_modelling_command,
task_id='price_modelling',
params=default_args,
dag=dag)
db_price_forecast = DummyOperator(task_id='db_price_forecast', dag=dag)
# Sent email
# --------------------
# send_success_email = EmailOperator(
# task_id='send_success_email',
# to=default_args['email'],
# subject='The Reading Machine executed successfully',
# html_content='',
# dag=dag)
########################################################################
# Create dependency
########################################################################
db_raw_article.set_upstream(article_scraper)
db_raw_price.set_upstream(price_scraper)
article_processing.set_upstream(db_raw_article)
db_processed_article.set_upstream(article_processing)
sentiment_scoring.set_upstream(db_processed_article)
topic_modelling.set_upstream(db_processed_article)
geo_tagging.set_upstream(db_processed_article)
commodity_tagging.set_upstream(db_processed_article)
db_sentiment_scoring.set_upstream(sentiment_scoring)
db_topic_modelling.set_upstream(topic_modelling)
db_geo_tagging.set_upstream(geo_tagging)
db_commodity_tagging.set_upstream(commodity_tagging)
data_harmonisation.set_upstream(db_sentiment_scoring)
data_harmonisation.set_upstream(db_topic_modelling)
data_harmonisation.set_upstream(db_geo_tagging)
data_harmonisation.set_upstream(db_commodity_tagging)
db_data_harmonisation.set_upstream(data_harmonisation)
price_modelling.set_upstream(db_raw_price)
price_modelling.set_upstream(db_data_harmonisation)
db_price_forecast.set_upstream(price_modelling)
# send_success_email.set_upstream(db_price_model)