Update app.py

app.py

@@ -3,7 +3,7 @@ import pandas as pd
 import requests
 import base64
 
-def get_backlinks(api_login, api_key, target_url, filters, include_subdomains):
+def get_backlinks(api_login, api_key, target_url, filters):
     # Encoding credentials
     encoded_credentials = base64.b64encode(f"{api_login}:{api_key}".encode()).decode()
 
@@ -18,8 +18,7 @@ def get_backlinks(api_login, api_key, target_url, filters, include_subdomains):
             "target": target_url,
             "limit": 1000,
             "mode": "as_is",
-            "filters": filters,
-            "include_subdomains": include_subdomains  # Adding the include_subdomains filter
+            "filters": filters
         }
     }
 
@@ -80,7 +79,7 @@ is_lost = st.sidebar.checkbox("Is Lost", value=False)
 dofollow = st.sidebar.checkbox("Dofollow", value=True)
 backlink_spam_score = st.sidebar.slider("Backlink Spam Score ≤", 0, 100, 10)
 page_from_language = st.sidebar.selectbox("Page From Language", ['en', 'other'])
-include_subdomains = st.sidebar.checkbox("Include Subdomains", value=True)  # New filter
+is_broken = st.sidebar.checkbox("Is Broken", value=False)  # Added is_broken filter
 
 # Prepare filters for API call
 filters = []
@@ -98,6 +97,10 @@ if dofollow:
     filters.append(["dofollow", "=", dofollow])
     filters.append("and")
 
+if is_broken:
+    filters.append(["is_broken", "=", is_broken])
+    filters.append("and")
+
 filters.append(["backlink_spam_score", "<=", backlink_spam_score])
 filters.append("and")
 filters.append(["page_from_language", "=", page_from_language])
@@ -120,7 +123,7 @@ df = None
 
 # Generate CSV and download button
 if generate_button and target_url:
-    df = get_backlinks(api_login, api_key, target_url, filters, include_subdomains)
+    df = get_backlinks(api_login, api_key, target_url, filters)
     if df is not None:
         csv = convert_df_to_csv(df)
         st.download_button(