Update main.py

main.py

@@ -1,10 +1,11 @@
 from fastapi import FastAPI, File, UploadFile
 from fastapi.responses import HTMLResponse
 import csv
+from typing import List
+from io import StringIO
 
 app = FastAPI()
 
-# Dictionaries to store URLs, API counts, and associated names
 url_counts = {}
 api_counts = {}
 url_names = {}
@@ -18,22 +19,34 @@ async def upload_csv(file: UploadFile):
         total_records = 0
 
         csvreader = csv.reader(content)
-        header = next(csvreader)  # Skip the header row
+        header = next(csvreader)
         for row in csvreader:
-            # ... (rest of the processing code remains the same)
+            url = row[3]
+            api = row[4]
+            url_name = row[2]
+            api_name = row[6]
+            total_records += 1
+
+            if url in url_counts:
+                url_counts[url] += 1
+            else:
+                url_counts[url] = 1
+                url_names[url] = url_name
+
+            if api in api_counts:
+                api_counts[api] += 1
+            else:
+                api_counts[api] = 1
+                api_names[api] = api_name
 
-        # Find redundant URLs and APIs with counts greater than 1
         redundant_urls = [url for url, count in url_counts.items() if count > 1]
         redundant_apis = [api for api, count in api_counts.items() if count > 1]
 
-        # Calculate the percentage of redundant URLs
         percentage_redundant_urls = (len(redundant_urls) / total_records) * 100 if total_records > 0 else 0
 
-        # Construct the summary string
         summary_string = f"<b>Total GET Records:</b> {total_records}<br>" \
                          f"<b>% of Redundant GET Requests:</b> {round(percentage_redundant_urls, 2)}%<br>"
 
-        # Create an HTML table in the desired format
         html_table = "<table>"
         html_table += "<tr><th>GET Request</th><th>Count of Repetition</th></tr>"
         for url in redundant_urls:
@@ -41,9 +54,7 @@ async def upload_csv(file: UploadFile):
             html_table += f"<tr><td>{url}</td><td>{count}</td></tr>"
         html_table += "</table>"
 
-        # Return both JSON and HTML responses
         return HTMLResponse(content=f"<h2>Analysis Results:</h2>{summary_string}{html_table}",
                             status_code=200)
     else:
         return {"error": "Invalid file format. Please upload a CSV file."}
-