feat: add domain as a filter for top list

app.py

@@ -15,7 +15,8 @@ PASS = os.getenv("PASSWORD")
 list_iface = gr.Interface(fn=compute_offer,
             inputs=[gr.File(label="Upload CSV", type="file"),
                     gr.Slider(1, 365, value=30, step=1, label="Days", info="Number of days to look back"),
-                    gr.Slider(5000, 100000, value=15000, step=1, label="Minimum Sent", info="Minimum number of emails sent")
+                    gr.Slider(5000, 100000, value=15000, step=1, label="Minimum Sent", info="Minimum number of emails sent"),
+                    gr.Dropdown(["Comcast", "Yahoo", "Hotmail", "Aol"], value="Comcast", label="Domain")
                     ],
             outputs="dataframe")
 

utils/gradio_utils.py

@@ -231,7 +231,7 @@ def generate_ips_per_subclass(ip_subclasses: str, num_of_ips: int) -> str:
 
 
 ### GENERATE TOP LISTS ###
-def compute_offer(csv_file, days_lookback, min_sent):
+def compute_offer(csv_file, days_lookback, min_sent, domain):
     # cmp_list = ['MSP', 'HOM', 'NTU', 'HCK', 'DDS', 'MNP', 'PSC', 'DTL', 'GVS', 'ANP', 'WDR', 'BSG']   #1
 
     #raw_df = pd.read_csv('tools/data/30.08.2023.gabriel.sabau.campanii.csv', parse_dates=['Data'])
@@ -244,7 +244,7 @@ def compute_offer(csv_file, days_lookback, min_sent):
     # comcast_df = raw_df[raw_df['Nume'].str.contains('|'.join(cmp_list))]  #1
     # comcast_df = comcast_df[comcast_df['Domeniu'] == 'Comcast'] #2
     exclude_list = comcast_df[(comcast_df['Data'] > (pd.Timestamp('now') - pd.Timedelta(days=days_lookback))) \
-                            & (comcast_df['Domeniu'] == 'Comcast')]['Oferta'].unique()
+                            & (comcast_df['Domeniu'] == domain)]['Oferta'].unique()
     comcast_df = comcast_df[~comcast_df['Oferta'].isin(exclude_list)]
     
     comcast_df = comcast_df[comcast_df['Send'] > int(min_sent)]