combined mal and trx into gsm database

apps/database_page.py

@@ -6,10 +6,12 @@ import streamlit as st
 from queries.process_all_db import process_all_tech_db
 from queries.process_gsm import process_gsm_data_to_excel
 from queries.process_lte import process_lte_data_to_excel
-from queries.process_mal import process_mal_data_to_excel
+
+# from queries.process_mal import process_mal_data_to_excel
 from queries.process_mrbts import process_mrbts_data_to_excel
 from queries.process_neighbors import process_neighbors_data_to_excel
-from queries.process_trx import process_trx_with_bts_name_data_to_excel
+
+# from queries.process_trx import process_trx_with_bts_name_data_to_excel
 from queries.process_wcdma import process_wcdma_data_to_excel
 from utils.check_sheet_exist import Technology, execute_checks_sheets_exist
 from utils.utils_vars import UtilsVars
@@ -46,15 +48,15 @@ def download_button(database_type):
     elif database_type == "NEI":
         data = UtilsVars.neighbors_database
         file_name = f"Neighbors databases_{datetime.now()}.xlsx"
-    elif database_type == "TRX":
-        data = UtilsVars.final_trx_database
-        file_name = f"TRX database_{datetime.now()}.xlsx"
+    # elif database_type == "TRX":
+    #     data = UtilsVars.final_trx_database
+    #     file_name = f"TRX database_{datetime.now()}.xlsx"
     elif database_type == "MRBTS":
         data = UtilsVars.final_mrbts_database
         file_name = f"MRBTS database_{datetime.now()}.xlsx"
-    elif database_type == "MAL":
-        data = UtilsVars.final_mal_database
-        file_name = f"MAL database_{datetime.now()}.xlsx"
+    # elif database_type == "MAL":
+    #     data = UtilsVars.final_mal_database
+    #     file_name = f"MAL database_{datetime.now()}.xlsx"
     st.download_button(
         type="primary",
         label=f"Download {database_type} Database File",
@@ -135,16 +137,16 @@ if uploaded_file is not None:
                     "Generate LTE DB",
                     on_click=lambda: process_database(process_lte_data_to_excel, "LTE"),
                 )
-        if Technology.trx == True:
-            with col5:
-                st.button(
-                    "Generate TRX DB",
-                    on_click=lambda: process_database(
-                        process_trx_with_bts_name_data_to_excel, "TRX"
-                    ),
-                )
+        # if Technology.trx == True:
+        #     with col5:
+        #         st.button(
+        #             "Generate TRX DB",
+        #             on_click=lambda: process_database(
+        #                 process_trx_with_bts_name_data_to_excel, "TRX"
+        #             ),
+        #         )
         if Technology.mrbts == True:
-            with col6:
+            with col5:
                 st.button(
                     "Generate MRBTS",
                     on_click=lambda: process_database(
@@ -152,14 +154,14 @@ if uploaded_file is not None:
                     ),
                 )
 
-        if Technology.mal == True:
-            with col7:
-                st.button(
-                    "Generate MAL",
-                    on_click=lambda: process_database(process_mal_data_to_excel, "MAL"),
-                )
+        # if Technology.mal == True:
+        #     with col7:
+        #         st.button(
+        #             "Generate MAL",
+        #             on_click=lambda: process_database(process_mal_data_to_excel, "MAL"),
+        #         )
         if Technology.neighbors == True:
-            with col8:
+            with col6:
                 st.button(
                     "Generate NEI DB",
                     on_click=lambda: process_database(

queries/process_all_db.py

@@ -1,8 +1,6 @@
-from queries.process_gsm import process_gsm_data
+from queries.process_gsm import combined_gsm_database
 from queries.process_lte import process_lte_data
-from queries.process_mal import process_mal_with_bts_name
 from queries.process_mrbts import process_mrbts_data
-from queries.process_trx import process_trx_with_bts_name
 from queries.process_wcdma import process_wcdma_data
 from utils.convert_to_excel import convert_dfs
 from utils.utils_vars import UtilsVars
@@ -10,14 +8,12 @@ from utils.utils_vars import UtilsVars
 
 def process_all_tech_db(filepath: str):
     UtilsVars.all_db_dfs.clear()
-    process_gsm_data(filepath)
+    combined_gsm_database(filepath)  # for gsm,mal,trx
     process_wcdma_data(filepath)
-    process_lte_data(filepath)
-    process_trx_with_bts_name(filepath)
+    process_lte_data(filepath),  # for LTE_FDD, LTE_TDD
     process_mrbts_data(filepath)
-    process_mal_with_bts_name(filepath)
 
     UtilsVars.final_all_database = convert_dfs(
         UtilsVars.all_db_dfs,
-        ["GSM", "WCDMA", "LTE_FDD", "LTE_TDD", "TRX", "MRBTS", "MAL"],
+        ["GSM", "MAL", "TRX", "WCDMA", "LTE_FDD", "LTE_TDD", "MRBTS"],
     )

queries/process_gsm.py

@@ -1,7 +1,7 @@
 import pandas as pd
 
-from queries.process_mal import process_mal_data
-from queries.process_trx import process_trx_data
+from queries.process_mal import process_mal_data, process_mal_with_bts_name
+from queries.process_trx import process_trx_data, process_trx_with_bts_name
 from utils.config_band import config_band
 from utils.convert_to_excel import convert_dfs, save_dataframe
 from utils.utils_vars import UtilsVars
@@ -154,12 +154,21 @@ def process_gsm_data(file_path: str):
     # save_dataframe(df_trx, "trx")
     # df_2g2 = save_dataframe(df_2g, "2g")
 
-    UtilsVars.all_db_dfs.append(df_2g)
+    # UtilsVars.all_db_dfs.append(df_2g)
     # UtilsVars.final_gsm_database = convert_dfs([df_2g], ["GSM"])
     # UtilsVars.final_gsm_database = [df_2g]
     return df_2g
 
 
+def combined_gsm_database(file_path: str):
+    gsm_df = process_gsm_data(file_path)
+    mal_df = process_mal_with_bts_name(file_path)
+    trx_df = process_trx_with_bts_name(file_path)
+
+    UtilsVars.all_db_dfs.extend([gsm_df, mal_df, trx_df])
+    return [gsm_df, mal_df, trx_df]
+
+
 def process_gsm_data_to_excel(file_path: str):
     """
     Process data from the specified file path and save it to a excel file.
@@ -167,5 +176,5 @@ def process_gsm_data_to_excel(file_path: str):
     Args:
         file_path (str): The path to the file.
     """
-    gsm_dfs = process_gsm_data(file_path)
-    UtilsVars.final_gsm_database = convert_dfs([gsm_dfs], ["GSM"])
+    gsm_dfs = combined_gsm_database(file_path)
+    UtilsVars.final_gsm_database = convert_dfs(gsm_dfs, ["GSM", "MAL", "TRX"])

queries/process_mal.py

@@ -70,7 +70,7 @@ def process_mal_with_bts_name(file_path: str):
     df_mal_bts_name = pd.merge(mal_df, df_bts, on="ID_MAL", how="left")
     df_mal_bts_name = df_mal_bts_name[MAL_BTS_COLUMNS]
 
-    UtilsVars.all_db_dfs.append(df_mal_bts_name)
+    # UtilsVars.all_db_dfs.append(df_mal_bts_name)
     return df_mal_bts_name
 
 

queries/process_trx.py

@@ -120,24 +120,12 @@ def process_trx_with_bts_name(file_path: str):
     df_gsm_trx = process_brute_trx_data(file_path=file_path).copy()
     df_gsm_trx.drop(["name"], axis=1, inplace=True)
 
-    # Process TRX data
-    # dfs = pd.read_excel(
-    #     file_path,
-    #     sheet_name=["BTS"],
-    #     engine="calamine",
-    #     skiprows=[0],
-    # )
-    # df_bts = dfs["BTS"]
     df_bts = process_small_bts_data(file_path=file_path)
-    # df_bts.columns = df_bts.columns.str.replace(r"[ ]", "", regex=True)
-    # df_bts["code"] = df_bts["name"].str.split("_").str[0].astype(int)
-    # df_bts["ID_BTS"] = df_bts[["BSC", "BCF", "BTS"]].astype(str).apply("_".join, axis=1)
-    # df_bts = df_bts[["ID_BTS", "code", "name"]]
 
     df_trx_bts_name = pd.merge(df_gsm_trx, df_bts, on="ID_BTS", how="left")
     df_trx_bts_name = df_trx_bts_name[TRX_BTS_COLUMNS]
 
-    UtilsVars.all_db_dfs.append(df_trx_bts_name)
+    # UtilsVars.all_db_dfs.append(df_trx_bts_name)
 
     return df_trx_bts_name