Adding inventory units

apps/database_page.py

@@ -7,6 +7,7 @@ from st_aggrid import AgGrid, ColumnsAutoSizeMode
 from apps.dump_analysis import dump_analysis_space
 from queries.process_all_db import process_all_tech_db, process_all_tech_db_with_stats
 from queries.process_gsm import process_gsm_data_to_excel
+from queries.process_invunit import process_invunit_data_to_excel
 from queries.process_lte import process_lte_data_to_excel
 
 # from queries.process_mal import process_mal_data_to_excel
@@ -51,15 +52,12 @@ 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 == "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 == "INVUNIT":
+        data = UtilsVars.final_invunit_database
+        file_name = f"INVUNIT database_{datetime.now()}.xlsx"
     st.download_button(
         type="primary",
         label=f"Download {database_type} Database File",
@@ -111,6 +109,7 @@ if uploaded_file is not None:
             and Technology.neighbors == False
             and Technology.trx == False
             and Technology.mrbts == False
+            and Technology.invunit == False
         ):
             st.error(
                 """
@@ -121,7 +120,7 @@ if uploaded_file is not None:
                     "neighbors": ["ADCE", "ADJS", "ADJI", "ADJG", "ADJW", "BTS", "WCEL"],
                     "trx": ["TRX", "BTS"],
                     "mrbts": ["MRBTS"],
-                    "mal": ["MAL"],
+                    "invunit": ["INVUNIT"]
                 """
             )
 
@@ -131,7 +130,7 @@ if uploaded_file is not None:
             and Technology.lte == True
             and Technology.trx == True
             and Technology.mrbts == True
-            and Technology.mal == True
+            and Technology.invunit == True
         ):
             DumpType.full_dump = True
             with col1:
@@ -159,14 +158,6 @@ 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.mrbts == True:
             with col5:
                 st.button(
@@ -175,15 +166,17 @@ if uploaded_file is not None:
                         process_mrbts_data_to_excel, "MRBTS"
                     ),
                 )
+        if Technology.invunit == True:
+            with col6:
+                st.button(
+                    "Generate INVUNIT",
+                    on_click=lambda: process_database(
+                        process_invunit_data_to_excel, "INVUNIT"
+                    ),
+                )
 
-        # 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 col6:
+            with col7:
                 st.button(
                     "Generate NEI DB",
                     on_click=lambda: process_database(

queries/process_all_db.py

@@ -1,4 +1,5 @@
 from queries.process_gsm import combined_gsm_database, gsm_analaysis
+from queries.process_invunit import process_invunit_data
 from queries.process_lte import lte_fdd_analaysis, lte_tdd_analaysis, process_lte_data
 from queries.process_mrbts import process_mrbts_data
 from queries.process_wcdma import process_wcdma_data, wcdma_analaysis
@@ -16,6 +17,7 @@ def all_dbs(filepath: str):
     process_wcdma_data(filepath)
     process_lte_data(filepath),
     process_mrbts_data(filepath)
+    process_invunit_data(filepath)
 
 
 def process_all_tech_db(filepath: str):
@@ -23,7 +25,7 @@ def process_all_tech_db(filepath: str):
 
     UtilsVars.final_all_database = convert_dfs(
         UtilsVars.all_db_dfs,
-        ["GSM", "MAL", "TRX", "WCDMA", "LTE_FDD", "LTE_TDD", "MRBTS"],
+        ["GSM", "MAL", "TRX", "WCDMA", "LTE_FDD", "LTE_TDD", "MRBTS", "INVUNIT"],
     )
 
 
@@ -41,5 +43,5 @@ def process_all_tech_db_with_stats(
     lte_tdd_analaysis(filepath)
     UtilsVars.final_all_database = convert_dfs(
         UtilsVars.all_db_dfs,
-        ["GSM", "MAL", "TRX", "WCDMA", "LTE_FDD", "LTE_TDD", "MRBTS"],
+        ["GSM", "MAL", "TRX", "WCDMA", "LTE_FDD", "LTE_TDD", "MRBTS", "INVUNIT"],
     )

queries/process_invunit.py

@@ -0,0 +1,93 @@
+import pandas as pd
+
+from utils.convert_to_excel import convert_dfs, save_dataframe
+from utils.extract_code import extract_code_from_mrbts
+from utils.utils_vars import UtilsVars
+
+
+def create_invunit_summary(df: pd.DataFrame) -> pd.DataFrame:
+    """
+    Creates a summary string column in the given DataFrame by concatenating non-NaN values of all columns except the first one (MRBTS) into a single string with '/' as separator.
+
+    Args:
+        df (pd.DataFrame): The DataFrame to process.
+
+    Returns:
+        pd.DataFrame: The DataFrame with the added "invunit_summary" column.
+    """
+
+    def process_row(row):
+        values = []
+        for col in df.columns[1:]:  # Exclude 'MRBTS'
+            if pd.notna(row[col]):  # Check if value is not NaN
+                values.append(f"{int(row[col])} {col}")  # Format as 'count column_name'
+        return "/".join(values) if values else ""
+
+    df["invunit_summary"] = df.apply(process_row, axis=1)
+    return df
+
+
+def process_invunit_data(file_path: str) -> pd.DataFrame:
+    """
+    Process data from the specified file path.
+
+    Args:
+        file_path (str): The path to the file.
+    """
+    dfs = pd.read_excel(
+        file_path,
+        sheet_name=["INVUNIT"],
+        engine="calamine",
+        skiprows=[0],
+    )
+    # Parse INVUNIT
+    df_invunit = dfs["INVUNIT"]
+    df_invunit.columns = df_invunit.columns.str.replace(r"[ ]", "", regex=True)
+
+    df_invunit = df_invunit[df_invunit["MRBTS"].apply(lambda x: str(x).isnumeric())]
+    df_invunit["CODE"] = df_invunit["MRBTS"].apply(extract_code_from_mrbts)
+    df_invunit = df_invunit[["MRBTS", "inventoryUnitType"]]
+
+    df_invunit = (
+        df_invunit.groupby(["MRBTS", "inventoryUnitType"])
+        .size()
+        .unstack(fill_value=None)
+        .reset_index()
+    )
+    # Rename columns
+    df_invunit = df_invunit.rename(
+        columns={
+            "ABIA AirScale Capacity": "ABIA",
+            "AMIA AirScale Indoor Subrack": "AMIA",
+            "AMOB AirScale Outdoor Subrack": "AMOB",
+            "ASIA AirScale Common": "ASIA",
+            "ASIB AirScale Common": "ASIB",
+            "BB Extension Outdoor Sub-Module FBBA": "FBBA",
+            "CORE_ASIA AirScale Common": "CORE_ASIA",
+            "CORE_ASIB AirScale Common": "CORE_ASIB",
+            "CORE_Flexi System Module Outdoor FSMF": "CORE_FSMF",
+            "CORE_SMOD": "CORE_SMOD",
+            "Flexi Baseband Sub-Module FBBC": "FBBC",
+            "Flexi System Module Outdoor FSMF": "FSMF",
+            "Not available": "NOT_AVAILABLE",
+            "SingleAntennaDevice": "SAD",
+        }
+    )
+    df_invunit = create_invunit_summary(df_invunit)
+    df_invunit["CODE"] = df_invunit["MRBTS"].apply(extract_code_from_mrbts)
+    df_invunit = df_invunit[["MRBTS", "CODE", "invunit_summary"]]
+
+    UtilsVars.all_db_dfs.append(df_invunit)
+    UtilsVars.all_db_dfs_names.append("INVUNIT")
+    return df_invunit
+
+
+def process_invunit_data_to_excel(file_path: str) -> None:
+    """
+    Process data from the specified file path and save it to a excel file.
+
+    Args:
+        file_path (str): The path to the file.
+    """
+    invunit_df = process_invunit_data(file_path)
+    UtilsVars.final_invunit_database = convert_dfs([invunit_df], ["INVUNIT"])

utils/check_sheet_exist.py

@@ -13,6 +13,7 @@ class Technology:
     trx = False
     mrbts = False
     mal = False
+    invunit = False
 
 
 # Dictionary of sheet groups to check
@@ -24,6 +25,7 @@ sheets_to_check = {
     "trx": ["TRX", "BTS"],
     "mrbts": ["MRBTS"],
     "mal": ["MAL", "BTS"],
+    "invunit": ["INVUNIT"],
 }
 
 
@@ -76,6 +78,7 @@ def execute_checks_sheets_exist(file_path):
     Technology.neighbors = False
     Technology.trx = False
     Technology.mrbts = False
+    Technology.invunit = False
     Technology.mal = False
     DumpType.full_dump = False
     for tech_attr, sheets in sheets_to_check.items():

utils/utils_vars.py

@@ -52,6 +52,7 @@ class UtilsVars:
     final_wcdma_database = ""
     final_trx_database = ""
     final_mrbts_database = ""
+    final_invunit_database = ""
     final_mal_database = ""
     gsm_dfs = []
     wcdma_dfs = []