converted weekly new brand combos script

Headset · Jul 3, 2023 · 45edda4 · 45edda4
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diff --git a/monitoring_weekly/weekly_autolinker_100_links_audit.py b/monitoring_weekly/weekly_autolinker_100_links_audit.py
@@ -78,7 +78,7 @@ def main(mytimer: func.TimerRequest) -> None:
 
 
 if len(sql_df.count()) >0:
-    filename = dir_path+r'\azure_results\autolinker_100_sample_audit.csv'
+    filename = dir_path+r'\autolinker_100_sample_audit.csv'
     sql_df.to_csv(filename, index = False)
 
     msgHtml = """

diff --git a/monitoring_weekly/weekly_new_brand_combos.py b/monitoring_weekly/weekly_new_brand_combos.py
@@ -0,0 +1,177 @@
+import datetime
+import logging
+import os
+import string
+import time
+
+from sqlalchemy import create_engine
+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(
+        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 Wednesday New Brand Combos")
+
+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_s1 = """
+create or replace temp table lizland.public.new_state as
+select --b.category,
+        d.state,
+        c.name as brand,
+        min(link_date) as link_dt
+from staging.imported_products a
+join staging.products b
+on a.product_id = b.product_id
+join insights.dim_brand c
+on b.brand_id = c.brand_id
+join base.stores d
+on a.store_id = d.store_id
+group by 1, 2
+having min(link_date) >= current_date()-7;"""
+
+sql_string_s2 = """
+--new brands in a state file
+select bb.*, listagg(imported_product_id, ', ') as variations
+from staging.imported_products a
+join staging.products b
+on a.product_id = b.product_id
+join insights.dim_brand c
+on b.brand_id = c.brand_id
+join base.stores d
+on a.store_id = d.store_id
+join lizland.public.new_state bb
+on d.state = bb.state
+and c.name = bb.brand
+group by 1, 2, 3
+order by state;
+"""
+
+sql_string_c1 = """
+create or replace temp table lizland.public.new_cat as
+select b.category,
+        --d.state,
+        c.name as brand,
+        min(link_date) as link_dt
+from staging.imported_products a
+join staging.products b
+on a.product_id = b.product_id
+join insights.dim_brand c
+on b.brand_id = c.brand_id
+join base.stores d
+on a.store_id = d.store_id
+group by 1, 2
+having min(link_date) >= current_date()-7;
+"""
+
+sql_string_c2 = """
+--new brand in a category file
+select bb.*, listagg(imported_product_id, ', ') as variations
+from staging.imported_products a
+join staging.products b
+on a.product_id = b.product_id
+join insights.dim_brand c
+on b.brand_id = c.brand_id
+join lizland.public.new_cat bb
+on b.category = bb.category
+and c.name = bb.brand
+group by 1, 2, 3
+order by category;
+"""
+
+
+try:
+    #create connection to DB and tell to use Fivetran
+    connection = engine.connect()
+    connection.execute(usedb_string) 
+
+    print("executing query")
+    connection.execute(sql_string_c1)
+    connection.execute(sql_string_s1)
+    state_df = pd.read_sql_query(sql_string_s2, connection)
+    cat_df = pd.read_sql_query(sql_string_c2, connection)
+    print("query executed")
+
+finally:
+    connection.close()
+    engine.dispose()
+
+
+filename_s = dir_path+r'\new_store_brand_state_combos.csv'
+filename_c = dir_path+r'\new_store_brand_cat_combos.csv'
+state_df.to_csv(filename_s, index = False)
+cat_df.to_csv(filename_c, index = False)
+
+
+if len(state_df.count()) > 0 or len(cat_df.count()) > 0:
+    msgHtml = """
+        <html>
+    <body><p>Hello, friend.</p>
+    <p>See attached for your data:</p>
+    <p>Regards,</p>
+    <p>Me</p>
+    </body></html>
+    """
+    try:
+        sp.transmissions.send(
+        recipients=['mlaferla@headset.io'],
+        html=msgHtml,
+        from_email='analytics-monitor@headset.io',
+        subject="New Brand Combos",
+        attachments=[
+            {
+                "name": filename_c.split('\\')[-1],
+                "type": "text/csv",
+                "filename": filename_c
+            }
+            , {
+                "name": filename_s.split('\\')[-1],
+                "type": "text/csv",
+                "filename": filename_s
+            }
+        ]
+        )
+    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_s)
+os.remove(filename_c)       
+
+print("finished")