def build_email(**context):
with open('/tmp/pokupki.xlsx', mode='r') as file:
email_op = EmailOperator(
task_id='send_email',
to=['*****@*****.**','*****@*****.**', '*****@*****.**', '*****@*****.**', '*****@*****.**', '*****@*****.**', '*****@*****.**', '*****@*****.**', '*****@*****.**', '*****@*****.**', '*****@*****.**', '*****@*****.**', '*****@*****.**', '*****@*****.**', '*****@*****.**', '*****@*****.**', '*****@*****.**', '*****@*****.**'],
subject="Fortemarket покупки",
html_content='Hello, <br/>',
files=[file.name],
)
email_op.execute(context)
def build_email(**context):
with open('/tmp/BPM_report_new.xlsx', mode='r') as file:
email_op = EmailOperator(
task_id='send_email',
to=[
'*****@*****.**', '*****@*****.**', '*****@*****.**',
'*****@*****.**'
],
subject="Daily BPM report",
html_content='Hello, <br/>',
files=[file.name],
)
email_op.execute(context)
def build_email(**context):
with open('/tmp/fm_unrecognized.xlsx', mode='r') as file:
email_op = EmailOperator(
task_id='send_email',
to=[
'*****@*****.**', '*****@*****.**',
'*****@*****.**', '*****@*****.**', '*****@*****.**',
'*****@*****.**'
],
subject="fm_unrecognized",
html_content='Hello, <br/>',
files=[file.name],
)
email_op.execute(context)
def build_email(**context):
with open('/tmp/vipiski.xlsx', mode='r') as file:
email_op = EmailOperator(
task_id='send_email',
to=[
'*****@*****.**', '*****@*****.**',
'*****@*****.**', '*****@*****.**', '*****@*****.**',
'*****@*****.**', '*****@*****.**'
],
subject="Fortemarket выписка",
html_content='Hello, <br/>',
files=[file.name],
)
email_op.execute(context)
default_args=default_args,
schedule_interval="0 12 * * *")
run_this_first = DummyOperator(task_id='run_this_first', dag=dag)
branching = BranchPythonOperator(task_id='branching',
python_callable=lambda: 'source_count'
if datetime.now().day <= 7 and datetime.today(
).weekday() == 6 else 'ignore_not_sunday',
dag=dag)
branching.set_upstream(run_this_first)
esucc = EmailOperator(task_id='email_success_' + dag.dag_id,
to=email_addr,
subject=dag.dag_id + ' [success] on ' +
datetime.now().strftime('%Y-%m-%d'),
html_content='Congratulation!',
trigger_rule='all_success',
dag=dag)
source_count = BashOperator(
task_id='source_count',
bash_command='/disk1/source_data_count; ./daily_table_count.sh > out.log ',
dag=dag)
source_count.set_upstream(branching)
esucc.set_upstream(source_count)
ignore_not_sunday = DummyOperator(task_id='ignore_not_sunday', dag=dag)
ignore_not_sunday.set_upstream(branching)
'email_on_failure': True,
'email_on_retry': False,
'start_date': airflow.utils.dates.days_ago(1),
'retries': 1,
'retry_delay': timedelta(minutes=1),
'concurrency': 1,
'max_active_run': 4
}
dag = DAG('import_applog_mongodb',
default_args=default_args,
schedule_interval="10 5 * * *")
esucc = EmailOperator(task_id='email_success_' + dag.dag_id,
to=email_addr,
subject=dag.dag_id + ' [success] on {{ ds }} ',
html_content='Congratulation!',
trigger_rule='all_success',
dag=dag)
# add table here:
tables = [
'browser_history', 'account_list', 'event_ios', 'event_app',
'ios_deviceinfo', 'frequentlocation', 'coordinates', 'hardware',
'location', 'network', 'telephone', 'hardwareios'
]
# copy table to bi
#bitables = ['hardware', 'hardwareios']
bitables = []
for table in tables:
imp = BashOperator(
wrtr.writerow(['url', 'count'])
wrtr.writerows(cntr.most_common(5))
simple_search = PythonOperator(task_id='search_twitter',
provide_context=True,
python_callable=search_twitter,
dag=dag,
params={'query': '#python'})
move_tweets_to_sqlite = PythonOperator(task_id='csv_to_sqlite',
provide_context=True,
python_callable=csv_to_sqlite,
dag=dag)
id_popular = PythonOperator(task_id='identify_popular_links',
provide_context=True,
python_callable=identify_popular_links,
dag=dag)
email_links = EmailOperator(task_id='email_best_links',
to='*****@*****.**',
subject='Latest popular links',
html_content='Check out the latest!!',
files=['{}/latest_links.txt'.format(RAW_TWEET_DIR)],
dag=dag)
simple_search.set_downstream(move_tweets_to_sqlite)
id_popular.set_upstream(move_tweets_to_sqlite)
email_links.set_upstream(id_popular)
params={'rasterdir': RASTER_DIR},
on_success_callback=lambda c: set_perms(c['params']['rasterdir'],
default_args['owner']),
dag=dag)
make_raster_task = BashOperator(task_id='make_rasters',
bash_command=make_raster_cmd,
env={'PATH': ANACONDA_PATH},
params={
'postphydir': POSTPHY_DIR,
'ecanalysispath': ECANALYSIS_PATH,
'rasterdir': RASTER_DIR
},
dag=dag)
############ Report Completion
email_me = EmailOperator(task_id='email_me',
to=default_args['email'],
subject='%s is merged' % dag_id,
html_content='You may commence analysis.',
dag=dag)
rsync_task.set_upstream(make_postphy_dir_task)
merge_events_task.set_upstream(rsync_task)
kwik2pandas_task.set_upstream(merge_events_task)
email_me.set_upstream(kwik2pandas_task)
make_raster_dir_task.set_upstream(kwik2pandas_task)
make_raster_task.set_upstream(make_raster_dir_task)
globals()[dag_id] = dag
mv_kwik_bak_task = BashOperator(task_id='move_kwik_bak',
bash_command=mv_kwik_bak_cmd,
params={
'block': BLOCK,
'birdid': BIRD
},
dag=dag)
rsync_task = BashOperator(task_id='rsync',
bash_command=rsync_command,
params={'block': BLOCK},
dag=dag)
email_me = EmailOperator(
task_id='email_me',
to=default_args['email'],
subject='%s is complete' % dag_id,
html_content='you can now manually sort on niao',
dag=dag)
slack_it = SlackAPIPostOperator(task_id='slack_it',
token=SLACK_TOKEN,
text='%s is complete' % dag_id,
channel='#ephys',
dag=dag)
make_kwd_task.set_upstream(make_klusta_dir_task)
phy_task.set_upstream(make_kwd_task)
#merge_events_task.set_upstream(phy_task)
clear_phy_task.set_upstream(phy_task)
make_kwik_bak_dir_task.set_upstream(phy_task)
mv_kwik_bak_task.set_upstream(make_kwik_bak_dir_task)
send_processes_killed_email = EmailOperator(
task_id="send_processes_killed_email",
to=PROCESS_KILLED_EMAIL_ADDRESSES,
subject=PROCESS_KILLED_EMAIL_SUBJECT,
html_content="""
<html>
<body>
<h2>Dag Run Information</h2>
<table>
<tr><td><b> ID: </b></td><td>{{ dag_run.id }}</td></tr>
<tr><td><b> DAG ID: </b></td><td>{{ dag_run.dag_id }}</td></tr>
<tr><td><b> Execution Date: </b></td><td>{{ dag_run.execution_date }}</td></tr>
<tr><td><b> Start Date: </b></td><td>{{ dag_run.start_date }}</td></tr>
<tr><td><b> End Date: </b></td><td>{{ dag_run.end_date }}</td></tr>
<tr><td><b> Run ID: </b></td><td>{{ dag_run.run_id }}</td></tr>
<tr><td><b> External Trigger: </b></td><td>{{ dag_run.external_trigger }}</td></tr>
</table>
<h2>Task Instance Information</h2>
<table>
<tr><td><b> Task ID: </b></td><td>{{ task_instance.task_id }}</td></tr>
<tr><td><b> Execution Date: </b></td><td>{{ task_instance.execution_date }}</td></tr>
<tr><td><b> Start Date: </b></td><td>{{ task_instance.start_date }}</td></tr>
<tr><td><b> End Date: </b></td><td>{{ task_instance.end_date }}</td></tr>
<tr><td><b> Host Name: </b></td><td>{{ task_instance.hostname }}</td></tr>
<tr><td><b> Unix Name: </b></td><td>{{ task_instance.unixname }}</td></tr>
<tr><td><b> Job ID: </b></td><td>{{ task_instance.job_id }}</td></tr>
<tr><td><b> Queued Date Time: </b></td><td>{{ task_instance.queued_dttm }}</td></tr>
<tr><td><b> Log URL: </b></td><td><a href="{{ task_instance.log_url }}">{{ task_instance.log_url }}</a></td></tr>
</table>
<h2>Processes Killed</h2>
<ul>
{% for process_killed in task_instance.xcom_pull(task_ids='kill_halted_tasks', key='kill_halted_tasks.processes_to_kill') %}
<li>Process {{loop.index}}</li>
<ul>
{% for key, value in process_killed.iteritems() %}
<li>{{ key }}: {{ value }}</li>
{% endfor %}
</ul>
{% endfor %}
</ul>
</body>
</html>
""",
dag=dag)
dag = DAG(dag_id="connect_to_monary_and_email_operator", default_args=default_args, params=params)
def connect_to_monary_and_email_operator(ds, **kwargs):
m = Monary()
pipeline = [{"$group": {"_id": "$state", "totPop": {"$sum": "$pop"}}}]
states, population = m.aggregate("zips", "data", pipeline, ["_id", "totPop"], ["string:2", "int64"])
strs = list(map(lambda x: x.decode("utf-8"), states))
result = list("%s: %d" % (state, pop) for (state, pop) in zip(strs, population))
print(result)
run_this = PythonOperator(
task_id="connect_to_monary_and_email_operator",
provide_context=True,
python_callable=connect_to_monary_and_email_operator,
dag=dag,
)
send_email_notification_flow_successful = EmailOperator(
task_id="send_email_notification_flow_successful",
to="*****@*****.**",
subject="custom email from airflow",
html_content="{{ params['foo'](execution_date) }}",
params=params,
dag=dag,
)
send_email_notification_flow_successful.set_upstream(run_this)
dag = DAG('edmjnl_crawler11',
default_args=default_args,
schedule_interval='@hourly',
catchup=True)
t1 = BashOperator(
task_id='schedule_edmjnl_crawler',
bash_command=
"cd ~/airflow/edmjnl2 && scrapy runspider edmjnl.py -o file.csv -t csv",
dag=dag)
#For ^ I prefer: file_'{{ execution_date }}'.csv -t csv"
t2 = BashOperator(
task_id='schedule_edmjnl_crawler2',
bash_command=
"cd ~/airflow/edmjnl2 && scrapy runspider post.py -o file2.csv -t csv",
dag=dag)
t3 = EmailOperator(task_id='schedule_edmjnl_email',
to='*****@*****.**',
subject='Edmjnl Email',
html_content="HTML content",
files='file.csv',
dag=dag)
# For ^ I need something like ["home/antony/airflow/edmjnl/file_'{{ execution_date }}'.csv"]
t1 >> t2
'email': ['*****@*****.**'],
'email_on_failure': True,
'email_on_retry': True,
'retries': 0,
}
with DAG(
'PriceAlerter',
default_args=default_args,
schedule_interval='*/5 9-17 * * *',
catchup=False,
) as dag:
price_listener = PythonOperator(
task_id='listener',
python_callable=listener.listen,
)
email_trigger = ShortCircuitOperator(
task_id='email_trigger',
python_callable=lambda: True if listener.trigger else False,
trigger_rule=TriggerRule.NONE_FAILED,
)
email = EmailOperator(
task_id='email',
to=email_service.email_list,
subject=email_service.get_email_subject(listener.summary),
html_content=email_service.get_html_content(listener.summary),
)
price_listener.set_downstream(email_trigger)
email_trigger.set_downstream(email)
# task_id='make_mansort_dir',
# bash_command=as_user(make_mansort_dir_cmd, USER),
# params={'mansortdir': MANSORT_DIR},
# dag=dag)
# rsync_task = BashOperator(
# task_id='rsync',
# bash_command=as_user(rsync_command, USER),
# params={'klustadir': KLUSTA_DIR,
# 'mansortdir': MANSORT_DIR,
# 'mansorthost': MANSORT_HOST},
# dag=dag)
email_me = EmailOperator(
task_id='email_me',
to=default_args['email'],
subject='%s is complete' % dag_id,
html_content='You may now manually sort on NIAO',
dag=dag)
make_kwd_task.set_upstream(make_klusta_dir_task)
phy_task.set_upstream(make_kwd_task)
#merge_events_task.set_upstream(phy_task)
clear_phy_task.set_upstream(phy_task)
make_kwik_bak_dir_task.set_upstream(phy_task)
mv_kwik_bak_task.set_upstream(make_kwik_bak_dir_task)
# make_mansort_dir_task.set_upstream(phy_task)
# rsync_task.set_upstream(clear_phy_task)
# rsync_task.set_upstream(mv_kwik_bak_task)
# rsync_task.set_upstream(make_mansort_dir_task)
# email_me.set_upstream(rsync_task)
fill_search_terms = PythonOperator(task_id='fill_terms',
provide_context=True,
python_callable=fill_terms,
dag=dag)
gen_search_terms = BranchPythonOperator(task_id='generate_search_terms',
provide_context=True,
python_callable=generate_search_terms,
dag=dag)
email_links = EmailOperator(task_id='email_best_links',
to='*****@*****.**',
subject='Latest popular links',
html_content='Check out the latest!!',
files=['{}/latest_links.txt'.format(RAW_TWEET_DIR)],
dag=dag)
sub = SubDagOperator(subdag=subdag,
task_id='insert_and_id_pop',
trigger_rule='one_success',
dag=dag)
clear_latest = BashOperator(bash_command='rm -rf {}/latest_links.txt'.format(
RAW_TWEET_DIR), task_id='clear_latest', dag=dag)
gen_search_terms.set_upstream(fill_search_terms)
from datetime import datetime, timedelta
default_args = {
'owner': 'airflow',
'start_date': datetime.now() - timedelta(seconds=10),
'retries': 0
}
dag = DAG('Sales_Nov',
default_args=default_args,
start_date=datetime.now() - timedelta(seconds=10))
op1 = DummyOperator(task_id='File1_landing', dag=dag)
t1 = EmailOperator(task_id='Processing_File_1',
to='*****@*****.**',
subject="Airflow_report",
html_content="File 1 started",
dag=dag)
op2 = DummyOperator(task_id='File2_landing', dag=dag)
t2 = EmailOperator(task_id='Processing_File_2',
to='*****@*****.**',
subject="Airflow_report",
html_content="File 2 started",
dag=dag)
op3 = DummyOperator(task_id='Aggregating', dag=dag)
op4 = DummyOperator(task_id='Final_Table_Push', dag=dag)
t1.set_upstream(op1)
t2.set_upstream(op2)
op3.set_upstream(t1)
task_id='move_kwik_bak',
bash_command=mv_kwik_bak_cmd,
params={'klustadir': KLUSTA_DIR,
'kwikbakdir': KWIKBAK_DIR},
dag=dag)
rsync_task = BashOperator(
task_id='rsync',
bash_command=as_user(rsync_command, USER),
params={'klustadir': KLUSTA_DIR,
'mansortdir': MANSORT_DIR},
dag=dag)
email_me = EmailOperator(
task_id='email_me',
to=default_args['email'],
subject='%s is complete' % dag_id,
html_content='You may now manually sort on NIAO',
dag=dag)
slack_it = SlackAPIPostOperator(
task_id='slack_it',
token=SLACK_TOKEN,
text='%s is complete' % dag_id,
channel='#ephys',
dag=dag)
make_kwd_task.set_upstream(make_klusta_dir_task)
phy_task.set_upstream(make_kwd_task)
#merge_events_task.set_upstream(phy_task)
clear_phy_task.set_upstream(phy_task)
make_kwik_bak_dir_task.set_upstream(phy_task)
# The DAG object; we'll need this to instantiate a DAG
from airflow import DAG
from airflow.operators import EmailOperator
from datetime import datetime, timedelta
default_args = {
'owner': 'airflow',
'depends_on_past': False,
'start_date': datetime(2017, 3, 29),
'email_on_failure': True,
'email_on_retry': False,
'retries': 2,
'retry_delay': timedelta(minutes=5),
# 'queue': 'bash_queue',
# 'pool': 'backfill',
# 'priority_weight': 10,
'end_date': datetime(2016, 3, 31)
}
dag = DAG(
'once_hour', default_args=default_args, schedule_interval="0 * * * *"
)
# the schedule interval for the dag here is one day
t1 = EmailOperator(
to='*****@*****.**',
subject='Generic Subject')
'start_date': one_min_ago,
'retries': 500
}
dag = DAG('vs', default_args=default_args, schedule_interval='@once')
chem1_pdb_prot1_pdb = BashOperator(
task_id='chem1_pdb_prot1_pdb',
bash_command="(cd /working-directory; virtualScreening.py -l chem1.pdb -o result -p prot1.pdb) ",
dag=dag)
chem1_pdb_prot1_pdb_success_mail = EmailOperator(
task_id="chem1_pdb_prot1_pdb_success_mail",
to=[u'*****@*****.**'],
subject="chem1_pdb_prot1_pdb success",
html_content="chem1_pdb_prot1_pdb success",
dag=dag)
chem1_pdb_prot1_pdb_success_mail.set_upstream(chem1_pdb_prot1_pdb)
#chem1_pdb_prot1_pdb.set_upstream( )
chem1_pdb_prot2_pdb = BashOperator(
task_id='chem1_pdb_prot2_pdb',
bash_command="(cd /working-directory; virtualScreening.py -l chem1.pdb -o result -p prot2.pdb) ",
dag=dag)
chem1_pdb_prot2_pdb_success_mail = EmailOperator(
task_id="chem1_pdb_prot2_pdb_success_mail",
to=[u'*****@*****.**'],
fill_search_terms = PythonOperator(task_id='fill_terms',
provide_context=True,
python_callable=fill_terms,
dag=dag)
gen_search_terms = BranchPythonOperator(task_id='generate_search_terms',
provide_context=True,
python_callable=generate_search_terms,
dag=dag)
email_links = EmailOperator(
task_id='email_best_links',
to='*****@*****.**',
subject='Latest popular links',
html_content='Check out the latest!!',
files=['{}/latest_links.txt'.format(RAW_TWEET_DIR)],
dag=dag)
sub = SubDagOperator(subdag=subdag,
task_id='insert_and_id_pop',
trigger_rule='one_success',
dag=dag)
clear_latest = BashOperator(
bash_command='rm -rf {}/latest_links.txt'.format(RAW_TWEET_DIR),
task_id='clear_latest',
dag=dag)
gen_search_terms.set_upstream(fill_search_terms)
# task_id='make_mansort_dir',
# bash_command=as_user(make_mansort_dir_cmd, USER),
# params={'mansortdir': MANSORT_DIR},
# dag=dag)
# rsync_task = BashOperator(
# task_id='rsync',
# bash_command=as_user(rsync_command, USER),
# params={'klustadir': KLUSTA_DIR,
# 'mansortdir': MANSORT_DIR,
# 'mansorthost': MANSORT_HOST},
# dag=dag)
email_me = EmailOperator(
task_id='email_me',
to=default_args['email'],
subject='%s is complete' % dag_id,
html_content='You may now manually sort on NIAO',
dag=dag)
make_kwd_task.set_upstream(make_klusta_dir_task)
phy_task.set_upstream(make_kwd_task)
#merge_events_task.set_upstream(phy_task)
clear_phy_task.set_upstream(phy_task)
make_kwik_bak_dir_task.set_upstream(phy_task)
mv_kwik_bak_task.set_upstream(make_kwik_bak_dir_task)
# make_mansort_dir_task.set_upstream(phy_task)
# rsync_task.set_upstream(clear_phy_task)
# rsync_task.set_upstream(mv_kwik_bak_task)
# rsync_task.set_upstream(make_mansort_dir_task)
# email_me.set_upstream(rsync_task)
email_me.set_upstream(mv_kwik_bak_task)
simple_search = PythonOperator(task_id='search_twitter',
provide_context=True,
python_callable=search_twitter,
dag=dag,
params={'query': '#python'})
move_tweets_to_sqlite = PythonOperator(task_id='csv_to_sqlite',
provide_context=True,
python_callable=csv_to_sqlite,
dag=dag)
id_popular = PythonOperator(task_id='identify_popular_links',
provide_context=True,
python_callable=identify_popular_links,
dag=dag)
email_links = EmailOperator(task_id='email_best_links',
to='*****@*****.**',
subject='Latest popular links',
html_content='Check out the latest!!',
files=['{}/latest_links.txt'.format(RAW_TWEET_DIR)],
dag=dag)
simple_search.set_downstream(move_tweets_to_sqlite)
id_popular.set_upstream(move_tweets_to_sqlite)
email_links.set_upstream(id_popular)
dag = DAG(dag_id='connect_to_monary_and_email_operator',
default_args=default_args,
params=params)
def connect_to_monary_and_email_operator(ds, **kwargs):
m = Monary()
pipeline = [{"$group": {"_id": "$state", "totPop": {"$sum": "$pop"}}}]
states, population = m.aggregate("zips", "data", pipeline,
["_id", "totPop"], ["string:2", "int64"])
strs = list(map(lambda x: x.decode("utf-8"), states))
result = list("%s: %d" % (state, pop)
for (state, pop) in zip(strs, population))
print(result)
run_this = PythonOperator(task_id='connect_to_monary_and_email_operator',
provide_context=True,
python_callable=connect_to_monary_and_email_operator,
dag=dag)
send_email_notification_flow_successful = EmailOperator(
task_id='send_email_notification_flow_successful',
to="*****@*****.**",
subject='custom email from airflow',
html_content="{{ params['foo'](execution_date) }}",
params=params,
dag=dag)
send_email_notification_flow_successful.set_upstream(run_this)
params={'rasterdir': RASTER_DIR},
on_success_callback = lambda c: set_perms(c['params']['rasterdir'],default_args['owner']),
dag=dag)
make_raster_task = BashOperator(
task_id='make_rasters',
bash_command=make_raster_cmd,
env={'PATH': ANACONDA_PATH},
params={'postphydir': POSTPHY_DIR,
'ecanalysispath': ECANALYSIS_PATH,
'rasterdir': RASTER_DIR},
dag=dag)
############ Report Completion
email_me = EmailOperator(
task_id='email_me',
to=default_args['email'],
subject='%s is merged' % dag_id,
html_content='You may commence analysis.',
dag=dag)
rsync_task.set_upstream(make_postphy_dir_task)
merge_events_task.set_upstream(rsync_task)
kwik2pandas_task.set_upstream(merge_events_task)
email_me.set_upstream(kwik2pandas_task)
make_raster_dir_task.set_upstream(kwik2pandas_task)
make_raster_task.set_upstream(make_raster_dir_task)
globals()[dag_id] = dag