Update backend.py

backend.py

@@ -1,10 +1,9 @@
 import json
-import csv
 import io
 import requests
 import html  # For escaping HTML characters
 from bs4 import BeautifulSoup
-import pandas as pd  # Add pandas for Excel export
+import pandas as pd  # Added pandas for Excel export
 
 # Initialize OpenAI API with Nvidia's Llama model
 client = OpenAI(
@@ -89,42 +88,22 @@ def generate_testcases(user_story):
         print(f"API request failed: {str(e)}")
         return []
 
-def export_test_cases(test_cases, format='json'):
+def export_test_cases(test_cases):
     if not test_cases:
         return "No test cases to export."
 
-    # Convert test cases (which are currently strings) into a structured format for CSV
-    structured_test_cases = [{'Test Case': case} for case in test_cases]
-
-    if format == 'json':
-        # Improve JSON export to be line-by-line formatted
-        return json.dumps(test_cases, indent=4, separators=(',', ': '))  # More readable format
-    elif format == 'csv':
-        if isinstance(test_cases, list) and isinstance(test_cases[0], dict):
-            output = io.StringIO()
-            csv_writer = csv.DictWriter(output, fieldnames=test_cases[0].keys(), quoting=csv.QUOTE_ALL)
-            csv_writer.writeheader()
-            csv_writer.writerows(test_cases)
-            return output.getvalue()
-        else:
-            raise ValueError("Test cases must be a list of dictionaries for CSV export.")
-
-def save_test_cases_as_file(test_cases, format='json'):
+    # Use pandas to export the test cases to Excel
+    df = pd.DataFrame(test_cases)
+    output = io.BytesIO()
+    df.to_excel(output, index=False)
+    output.seek(0)
+    return output.getvalue()
+
+def save_test_cases_as_file(test_cases):
     if not test_cases:
         return "No test cases to save."
 
-    if format == 'json':
-        with open('test_cases.json', 'w') as f:
-            json.dump(test_cases, f)
-    elif format == 'csv':
-        with open('test_cases.csv', 'w', newline='') as file:
-            dict_writer = csv.DictWriter(file, fieldnames=test_cases[0].keys())
-            dict_writer.writeheader()
-            dict_writer.writerows(test_cases)
-    elif format == 'excel':
-        # Use pandas to export the test cases to Excel
-        df = pd.DataFrame(test_cases)
-        df.to_excel('test_cases.xlsx', index=False)
-    else:
-        return f"Unsupported format: {format}"
-    return f'{format} file saved'
+    # Use pandas to save the test cases to an Excel file
+    df = pd.DataFrame(test_cases)
+    df.to_excel('test_cases.xlsx', index=False)
+    return 'excel file saved'