diff --git a/monitoring_weekly/__init__.py b/monitoring_weekly/__init__.py
index 8b80925..aff037a 100644
--- a/monitoring_weekly/__init__.py
+++ b/monitoring_weekly/__init__.py
@@ -20,8 +20,9 @@ def main(mytimer: func.TimerRequest) -> None:
#run_script('weekly_sama_reporting')
#run_script('weekly_autolinker_100_links_audit')
#run_script('weekly_insights_brand_monitoring')
- run_script('weekly_new_brand_combos')
-
+ #run_script('weekly_new_brand_combos')
+ #run_script('weekly_new_store_monitoring')
+
def run_script(script_name):
script_path = os.path.join(os.path.dirname(__file__), f'{script_name}.py')
diff --git a/monitoring_weekly/weekly_new_brand_combos.py b/monitoring_weekly/weekly_new_brand_combos.py
index 760eb7f..63155b6 100644
--- a/monitoring_weekly/weekly_new_brand_combos.py
+++ b/monitoring_weekly/weekly_new_brand_combos.py
@@ -5,14 +5,12 @@
import time
from sqlalchemy import create_engine
+from sparkpost import SparkPost
import azure.functions as func
import pandas as pd
import sqlalchemy.dialects.sqlite
-from sparkpost import SparkPost
-
-
def main(mytimer: func.TimerRequest) -> None:
utc_timestamp = datetime.datetime.utcnow().replace(
@@ -144,7 +142,7 @@ def main(mytimer: func.TimerRequest) -> None:
"""
try:
sp.transmissions.send(
- recipients=['mlaferla@headset.io'],
+ recipients=['mfelipe@headset.io', 'rmontenigro@headset.io'],
html=msgHtml,
from_email='analytics-monitor@headset.io',
subject="New Brand Combos",
diff --git a/monitoring_weekly/weekly_new_store_monitoring.py b/monitoring_weekly/weekly_new_store_monitoring.py
new file mode 100644
index 0000000..6a09774
--- /dev/null
+++ b/monitoring_weekly/weekly_new_store_monitoring.py
@@ -0,0 +1,166 @@
+import datetime
+import logging
+import os
+import string
+import time
+
+from sparkpost import SparkPost
+from sqlalchemy import create_engine
+import azure.functions as func
+import pandas as pd
+import sqlalchemy.dialects.sqlite
+
+
+
+def main(mytimer: func.TimerRequest) -> None:
+ utc_timestamp = datetime.datetime.utcnow().replace(
+ tzinfo=datetime.timezone.utc).isoformat()
+
+ if mytimer.past_due:
+ logging.info('The timer is past due!')
+
+ logging.info('Python timer trigger function ran at %s', utc_timestamp)
+
+
+ logging.info("Weekly Monday New Store Monitoring")
+
+sp = SparkPost(os.environ["SPARKPOST_KEY"])
+
+dir_path = os.getcwd()
+
+
+engine = create_engine(
+ 'snowflake://{user}:{password}@{account}/'.format(
+ user=os.environ["SNOWFLAKE_USER"],
+ password=os.environ["SNOWFLAKE_PASSWORD"],
+ account=os.environ["SNOWFLAKE_ACCOUNT"],
+ )
+)
+
+
+usedb_string = "use FIVETRAN;"
+
+
+sql_string = """
+with chain as (
+ select company_id, count(distinct store_id) as num_stores_in_chain
+ from base.stores
+ where ACTIVE = 1
+ group by 1
+ )
+ , new_stores as (
+ select state
+ , company_id
+ , store_id
+ from base.stores s
+ where ACTIVE = 1
+ and date_created between current_date() - 7 and current_date() -1
+ )
+ , state_sales_T30days as (
+ select ps.state
+ , sum(base_price - discount) as state_sales
+ from staging.product_sales ps
+ where transaction_date_local between current_date - 30 and current_date -1
+ group by 1
+ )
+ , store_sales_T30days as (
+ select ps.state
+ , ps.COMPANY_ID
+ , ps.store_id
+ , sum(base_price-discount) as store_sales
+ , count(distinct case when ps.customer_key is not null
+ and gender in ('M', 'F')
+ and dob is not null
+ then receipt_id
+ else 0
+ end) as demographics_trxns
+ , count(distinct receipt_id) as num_trxns
+ , count(distinct case when is_delivery = 1 then receipt_id else null end) as delivery_trxns
+ , count(distinct transaction_date_local::date) as num_days
+ from staging.PRODUCT_SALES ps
+ join new_stores ns on ps.STORE_ID = ns.STORE_ID
+ join base.customers c on ps.CUSTOMER_KEY = c.CUSTOMER_KEY
+ where transaction_date_local between current_date - 30 and current_date -1
+ group by 1, 2, 3
+ )
+ , avg_store_sales as (
+ select
+ store.state
+ , store.COMPANY_ID
+ , store_id
+ , case when c.num_stores_in_chain > 1 then 'Y' else 'N' end as is_chain
+ , c.num_stores_in_chain
+ , store_sales / num_days as avg_daily_store_sales
+ , (state_sales/30) as avg_daily_state_sales
+ , avg_daily_store_sales / avg_daily_state_sales as avg_daily_store_mkt_share
+ , demographics_trxns / num_trxns as perc_demo_trxns
+ , delivery_trxns / num_trxns as perc_delivery
+ from store_sales_T30days store
+ join state_sales_T30days state on store.state = state.state
+ left join chain c on c.COMPANY_ID = store.COMPANY_ID
+ )
+ select * from avg_store_sales
+ where avg_daily_store_mkt_share > 0.05
+ or perc_demo_trxns > 0.25
+ or perc_delivery > 0.1
+ or num_stores_in_chain > 1
+ order by 6 desc
+"""
+
+try:
+ #create connection to DB and tell to use Fivetran
+ connection = engine.connect()
+ connection.execute(usedb_string)
+
+ print("executing query")
+ sql_df = pd.read_sql_query(sql_string, connection)
+
+finally:
+ connection.close()
+ engine.dispose()
+
+
+
+filename = dir_path+r'\new_store_monitoring_results.csv'
+sql_df.to_csv(filename, index = False)
+
+
+# # print(data_to_email)
+if len(sql_df.count()) > 0:
+
+ msgHtml = """
+
+ Hello, friend.
+ See attached for your data:
+ Regards,
+ Me
+
+ """
+ try:
+ sp.transmissions.send(
+ recipients=['mlaferla@headset.io'],
+ html=msgHtml,
+ from_email='analytics-monitor@headset.io',
+ subject="New Store Monitoring",
+ attachments=[
+ {
+ "name": filename.split('\\')[-1],
+ "type": "text/csv",
+ "filename": filename
+ }
+ ]
+ )
+ except SparkPostAPIException as err:
+ # http response status code
+ print(err.status)
+ # python requests library response object
+ # http://docs.python-requests.org/en/master/api/#requests.Response
+ print(err.response.json())
+ # list of formatted errors
+ print(err.errors)
+
+
+# Finally, remove files
+os.remove(filename)
+
+print("finished")
\ No newline at end of file