Adding Geo input and visualization

streamlit/view_groups.py

@@ -105,6 +105,36 @@
             },
         ],
     },
+
+    {
+        "title": "Alerts",
+        "views": [
+            {
+                "label": "List alerts",
+                "help": "List all alerts.",
+                "page": "views/alerts.py",
+                "icon": ":material/notifications_none:",
+            },
+        ],
+    },
+    {
+        "title": "Geo Visualization",
+        "views": [
+            {
+                "label": "Display Geo Input",
+                "help": "Display geo information on a map.",
+                "page": "views/maps_display.py",
+                "icon": ":material/globe:",
+            },
+              {
+                "label": "User Geo Input",
+                "help": "Enable users to select own geo input.",
+                "page": "views/maps_draw.py",
+                "icon": ":material/pin_drop:",
+            },
+        ],
+    },
+
     {
         "title": "Unity Catalog",
         "views": [
@@ -133,16 +163,4 @@
             },
         ],
     },
-
-    {
-        "title": "Unity Catalog",
-        "views": [
-            {
-                "label": "Get Catalogs",
-                "help": "Get meta data.",
-                "page": "views/unity_catalog_get.py",
-                "icon": ":material/lan:",
-            },
-        ],
-    }
 ]

streamlit/views/alerts.py

@@ -0,0 +1,41 @@
+import streamlit as st
+from databricks.sdk import WorkspaceClient
+import pandas as pd
+
+w = WorkspaceClient()
+
+def get_all_alerts(): 
+    alerts = [alert.__dict__ for alert in w.alerts.list()]
+    return pd.DataFrame(alerts)
+
+st.header("List alert", divider=True)
+st.subheader("Enable users to display all alerts")
+st.write("This receipt enables users to display all alerts.")
+
+tab_a, tab_b, tab_c = st.tabs(["**Try it**", "**Code snippet**", "**Requirements**"])
+
+with tab_a:
+    st.write("""### See all alerts""")
+    st.dataframe(get_all_alerts())
+
+table = [
+    {
+        "type": "Get alerts",
+        "param": "",
+        "description": "Get all alerts",
+        "code": """
+        ```python
+        def get_all_alerts(): 
+            alerts = [alert.__dict__ for alert in w.alerts.list()]
+            return pd.DataFrame(alerts)
+        ```
+        """,
+    },
+]
+
+
+with tab_b:
+    for i, row in enumerate(table):
+        with st.expander(f"**{row['type']} ({row['param']})**", expanded=(i == 0)):
+            st.markdown(f"**Description**: {row['description']}")
+            st.markdown(row["code"])

streamlit/views/maps_display.py

@@ -0,0 +1,130 @@
+
+import streamlit as st
+from databricks import sql
+from databricks.sdk.core import Config
+import pandas as pd
+
+
+st.header("Geo Visualization", divider=True)
+st.subheader("Read a table and display as a map")
+st.write("This receipt loads a table from a delta table and displays the data on a map.")
+
+cfg = Config()
+
+@st.cache_resource
+def get_connection(http_path):
+    return sql.connect(
+        server_hostname=cfg.host,
+        http_path=http_path,
+        credentials_provider=lambda: cfg.authenticate,
+    )
+
+
+def read_table(table_name, conn):
+    with conn.cursor() as cursor:
+        query = f"SELECT * FROM {table_name}"
+        cursor.execute(query)
+        return cursor.fetchall_arrow().to_pandas()
+
+cities = [
+    {"name": "New York", "latitude": 40.7128, "longitude": -74.0060},
+    {"name": "Los Angeles", "latitude": 34.0522, "longitude": -118.2437},
+    {"name": "London", "latitude": 51.5074, "longitude": -0.1278},
+    {"name": "Tokyo", "latitude": 35.6895, "longitude": 139.6917},
+    {"name": "Sydney", "latitude": -33.8688, "longitude": 151.2093},
+    {"name": "Paris", "latitude": 48.8566, "longitude": 2.3522},
+    {"name": "Dubai", "latitude": 25.276987, "longitude": 55.296249},
+    {"name": "Rio de Janeiro", "latitude": -22.9068, "longitude": -43.1729},
+    {"name": "Moscow", "latitude": 55.7558, "longitude": 37.6173},
+    {"name": "Cape Town", "latitude": -33.9249, "longitude": 18.4241}
+]
+
+data = pd.DataFrame(cities)
+
+
+tab_a, tab_b, tab_c, tab_d = st.tabs(["**Try it**","**Try it with a delta table**", "**Code snippet**", "**Requirements**"])
+
+with tab_a:
+    col1, col2 = st.columns(2)
+    with col1:
+        if st.button("Try It with a random sample"):
+            st.map(data, latitude="Latitude", longitude="Longitude")
+            st.dataframe(data)
+
+
+with tab_b:
+    col1, col2 = st.columns(2)
+    with col1:
+        http_path_input = st.text_input(
+            "Enter your Databricks HTTP Path:", placeholder="/sql/1.0/warehouses/xxxxxx"
+        )
+
+        table_name = st.text_input(
+            "Specify a Unity Catalog table name:", placeholder="catalog.schema.table"
+        )
+        st.info("For displaying a sample, please use the table samples.accuweather.forecast_daily_calendar_metric")
+
+        if http_path_input and table_name:
+            conn = get_connection(http_path_input)
+            df = read_table(table_name, conn)
+
+            st.dataframe(df)
+
+            if 'latitude' in df.columns and 'longitude' in df.columns:
+                df['latitude'] = pd.to_numeric(df['latitude'], errors='coerce')
+                df['longitude'] = pd.to_numeric(df['longitude'], errors='coerce')
+                df = df.dropna(subset=['latitude', 'longitude'])
+
+                if not df.empty:
+                    st.map(df, latitude="latitude", longitude="longitude")
+            else:
+                st.warning("no longitude, latitude found in the table")
+
+
+table = [
+    {
+        "type": "Get Tables",
+        "param": "Get long lat from the tables",
+        "description": "Get long lat from the tables.",
+        "code": """
+        ```python
+        def read_table(table_name, conn):
+            with conn.cursor() as cursor:
+                query = f"SELECT * FROM {table_name} LIMIT 1000"
+                cursor.execute(query)
+                return cursor.fetchall_arrow().to_pandas()
+        ```
+        """,
+    },
+    {
+        "type": "Display Maps",
+        "param": "Display pandas df as maü",
+        "description": "Display the streamlit map",
+        "code": """
+        ```python
+            conn = get_connection(http_path_input)
+            df = read_table(table_name, conn)
+
+            st.dataframe(df)
+
+            if 'latitude' in df.columns and 'longitude' in df.columns:
+                df['latitude'] = pd.to_numeric(df['latitude'], errors='coerce')
+                df['longitude'] = pd.to_numeric(df['longitude'], errors='coerce')
+                df = df.dropna(subset=['latitude', 'longitude'])
+
+                if not df.empty:
+                    st.map(df, latitude="latitude", longitude="longitude")
+            else:
+                st.warning("no longitude, latitude found in the table")
+
+
+        ```
+        """,
+    },
+]
+
+with tab_c:
+    for i, row in enumerate(table):
+        with st.expander(f"**{row['type']} ({row['param']})**", expanded=(i == 0)):
+            st.markdown(f"**Description**: {row['description']}")
+            st.markdown(row["code"])