add ami reporter

renamed fmrest_barcode
add box info

ami_scripts/ami_record_exporter_and_analyzer.py

@@ -0,0 +1,150 @@
+#!/usr/bin/env python3
+
+import argparse
+import csv
+import os
+import re
+import pandas as pd
+from fmrest import Server
+from collections import defaultdict
+
+# Define command line arguments
+parser = argparse.ArgumentParser(description="Script to read SPEC AMI IDs from a CSV or Excel file and process them using a Filemaker database.")
+parser.add_argument('-u', '--username', help="The username for the Filemaker database.", required=True)
+parser.add_argument('-p', '--password', help="The password for the Filemaker database.", required=True)
+parser.add_argument('-i', '--input', help="The path to the input file containing SPEC AMI IDs.", required=True)
+parser.add_argument('-o', '--output', help="The path to the output CSV file for exporting barcodes.", required=True)
+args = parser.parse_args()
+
+# Environment variables
+server = os.getenv('FM_SERVER')
+database = os.getenv('FM_DATABASE')
+layout = os.getenv('FM_LAYOUT')
+
+if not all([server, database, layout]):
+    print("Server, database, and layout need to be set as environment variables.")
+    exit(1)
+
+# Function to connect to Filemaker database
+def connect_to_filemaker(server, username, password, database, layout):
+    url = f"https://{server}"
+    api_version = 'v1'
+    fms = Server(url, database=database, layout=layout, user=username, password=password, verify_ssl=True, api_version=api_version)
+    try:
+        fms.login()
+        print("Successfully connected to the FileMaker database.")
+        return fms
+    except Exception as e:
+        print(f"Failed to connect to Filemaker server: {e}")
+        return None
+
+# Function to read SPEC AMI IDs from input file
+def read_spec_ami_ids(file_path):
+    ids = []
+    try:
+        if file_path.endswith('.csv'):
+            with open(file_path, mode='r', encoding='utf-8') as file:
+                reader = csv.reader(file)
+                first_row = next(reader, None)
+                if first_row and any(not item.isdigit() for item in first_row):
+                    column_index = first_row.index('SPEC_AMI_ID') if 'SPEC_AMI_ID' in first_row else 0
+                else:
+                    column_index = 0  # Assume the ID is in the first column
+                    if re.match(r"^\d{6}$", first_row[0]):
+                        ids.append(first_row[0])
+                for row in reader:
+                    if re.match(r"^\d{6}$", row[column_index]):
+                        ids.append(row[column_index])
+        elif file_path.endswith('.xlsx'):
+            df = pd.read_excel(file_path, sheet_name=None)
+            for sheet_name, sheet_df in df.items():
+                if 'SPEC_AMI_IDs' in sheet_name or re.search(r"spec_ami_ids", sheet_name, re.IGNORECASE):
+                    if 'SPEC_AMI_ID' in sheet_df.columns:
+                        ids.extend(sheet_df['SPEC_AMI_ID'].dropna().astype(str).tolist())
+    except Exception as e:
+        print(f"Failed to read input file: {e}")
+    return ids
+
+if __name__ == "__main__":
+    fms = connect_to_filemaker(server, args.username, args.password, database, layout)
+    if fms:
+        spec_ami_ids = read_spec_ami_ids(args.input)
+        ami_id_details = []
+        box_summary = {}
+
+        for ami_id in sorted(spec_ami_ids):
+            print(f"Attempting to find: {ami_id}")
+            query = [{"ref_ami_id": ami_id}]
+            found_records = fms.find(query)
+
+            for record in found_records:
+                record_data = record.to_dict()
+                barcode = record_data.get('id_barcode', None)
+                migration_status = record_data.get('OBJECTS_MIGRATION_STATUS_active::migration_status', None)
+                box_name = str(record_data.get('OBJECTS_parent_from_OBJECTS::name_d_calc', ''))
+                box_barcode = str(record_data.get('OBJECTS_parent_from_OBJECTS::id_barcode', ''))
+                container_location = str(record_data.get('OBJECTS_parent_from_OBJECTS::ux_loc_active_d', ''))
+                item_location = str(record_data.get('ux_loc_active_d', ''))
+                format3 = record_data.get('format_3', '')
+
+                ami_id_details.append({
+                    'AMI ID': ami_id,
+                    'Barcode': barcode,
+                    'Format': format3,
+                    'Migration Status': migration_status,
+                    'Item Location': item_location,
+                    'Box Name': box_name,
+                    'Box Barcode': box_barcode,
+                    'Box Location': container_location
+                })
+                print(f"Found and added details for AMI ID: {ami_id}")
+
+                if box_name:
+                    if box_name not in box_summary:
+                        box_summary[box_name] = {
+                            'Box Barcode': box_barcode,
+                            'Box Location': container_location,
+                            'Total Count': 0,
+                            'Formats': {}
+                        }
+                    box_summary[box_name]['Total Count'] += 1
+                    if format3 in box_summary[box_name]['Formats']:
+                        box_summary[box_name]['Formats'][format3] += 1
+                    else:
+                        box_summary[box_name]['Formats'][format3] = 1
+
+        # Convert list to DataFrame
+        details_df = pd.DataFrame(ami_id_details)
+
+        # Prepare summary data for Excel
+        summary_overview = []
+        summary_formats = []
+
+        for box_name, details in box_summary.items():
+            summary_overview.append({
+                'Box Name': box_name,
+                'Box Barcode': details['Box Barcode'],
+                'Box Location': details['Box Location'],
+                'Total Requested Items': details['Total Count']
+            })
+
+            for format_name, count in details['Formats'].items():
+                summary_formats.append({
+                    'Box Name': box_name,
+                    'Format': format_name,
+                    'Count': count
+                })
+
+        overview_df = pd.DataFrame(summary_overview)
+        formats_df = pd.DataFrame(summary_formats)
+
+        # Write to Excel
+        with pd.ExcelWriter(args.output, engine='openpyxl') as writer:
+            details_df.to_excel(writer, sheet_name='AMI ID Details', index=False)
+            overview_df.to_excel(writer, sheet_name='Box Summary', index=False)
+            formats_df.to_excel(writer, sheet_name='Box Summary', startrow=len(overview_df) + 3, index=False)
+
+        print(f"Exported details to {args.output} with sheets: 'AMI ID Details' and 'Box Summary'.")
+        fms.logout()
+    else:
+        print("Failed to connect to the Filemaker server.")