adding physical db management

README.md

@@ -34,10 +34,11 @@ You can access the hosted version of the app at [https://davmelchi-db-query.hf.s
 
 ## TODO
 
-- [*] check if required sheets exist in the dump file
-- [*] Add a download button for all databases
-- [*] Add option to download Neighbors database
+- [x] check if required sheets exist in the dump file
+- [x] Add a download button for all databases
+- [x] Add option to download Neighbors database
 - [ ] Add dashboards for each database (Count of NE)
 - [ ] Add the ability to select columns
 - [ ] Error handling
-- [ ] Add option to update physical db
+- [x] Add page to update physical db
+- [x] Add Core dump checking App

app.py

@@ -4,6 +4,7 @@ pages = {
     "Apps": [
         st.Page("apps/database_page.py", title="Generate Databases"),
         st.Page("apps/core_dump_page.py", title="Check dump core"),
+        st.Page("apps/import_physical_db.py", title="Physical Database Management"),
     ],
     "Documentations": [
         st.Page("documentations/database_doc.py", title="Databases Documentation"),

apps/import_physical_db.py

@@ -0,0 +1,75 @@
+import os
+
+import pandas as pd
+import streamlit as st
+
+# Define the folder path where the physical database will be stored
+physical_db_folder = "physical_db"
+physical_db_file = os.path.join(physical_db_folder, "physical_database.csv")
+
+# Ensure the folder exists
+if not os.path.exists(physical_db_folder):
+    os.makedirs(physical_db_folder)
+
+# Streamlit app title
+st.title("Physical Database Management")
+
+# Step 1: Upload a new CSV file
+uploaded_file = st.file_uploader(
+    "Upload a CSV file of new physical database", type="csv"
+)
+
+if uploaded_file is not None:
+    # Step 2: Check if the file contains the required columns
+    df = pd.read_csv(uploaded_file)
+    required_columns = [
+        "CODE",
+        "sector",
+        "Code_Sector",
+        "Azimut",
+        "Longitude",
+        "Latitude",
+        "Hauteur",
+    ]
+
+    if not all(col in df.columns for col in required_columns):
+        st.error(
+            f"Error: The file must contain the following columns: {', '.join(required_columns)}"
+        )
+    elif len(df) <= 500:
+        st.error("Error: The file must contain more than 500 rows.")
+    else:
+        st.success("File successfully validated.")
+
+        # Display the DataFrame
+        st.write(df)
+
+        # Step 6: Add button to save the new file
+        if st.button("Save the new physical database file", type="primary"):
+            # Step 4: Remove everything in the folder physical_db/
+            for file in os.listdir(physical_db_folder):
+                os.remove(os.path.join(physical_db_folder, file))
+
+            # Step 5: Rename and save the new file
+            df.to_csv(physical_db_file, index=False)
+            st.success(f"New physical database saved Successfully.")
+
+
+# # Step 7: Add button to download the existing physical_database.csv file
+# if os.path.exists(physical_db_file):
+#     st.subheader("Download the existing physical_database.csv file")
+#     with open(physical_db_file, "rb") as f:
+#         st.download_button(
+#             label="Download physical_database.csv",
+#             data=f,
+#             file_name="physical_database.csv",
+#         )
+
+# Step 8: Add button to show the existing physical_database.csv file
+if os.path.exists(physical_db_file):
+    st.subheader("Show the existing physical_database file")
+    if st.button("Show actual physical database"):
+        df_existing = pd.read_csv(physical_db_file)
+        st.dataframe(df_existing)
+else:
+    st.warning("No physical_database.csv file found in the physical_db/ folder.")