Add URL log analysis and histogram visualization

python-scripts/url_search.py

@@ -0,0 +1,66 @@
+import re
+import matplotlib.pyplot as plt
+
+def analyze_log(log_file_path):
+    """
+    User will be asked to enter the URL substring interactively.
+    """
+
+    # Ask the user to enter a URL substring dynamically
+    url_keyword = input("Enter the URL substring to search: ").strip()
+
+    pattern = re.compile(
+        r'GET\s+(\S+)\s+=>.*?in\s+(\d+)\s+msecs',
+        re.IGNORECASE
+    )
+
+    times = []
+
+    # Read large log file efficiently
+    with open(log_file_path, "r", encoding="utf-8", errors="ignore") as f:
+        for line in f:
+            match = pattern.search(line)
+            if match:
+                url = match.group(1)
+                time = int(match.group(2))
+
+                if url_keyword in url:
+                    times.append(time)
+
+    if not times:
+        print(f"\n No matching entries found for: {url_keyword}")
+        return
+
+    min_time = min(times)
+    max_time = max(times)
+
+    print("\n========== ANALYSIS RESULT ==========")
+    print(f"URL Searched        : {url_keyword}")
+    print(f"Total Requests      : {len(times)}")
+    print(f"Min Response Time   : {min_time} ms")
+    print(f"Max Response Time   : {max_time} ms")
+    print("======================================\n")
+
+    # Histogram bins: 0–500, 500–1000, ...
+    max_bin = ((max_time // 500) + 1) * 500
+    bins = list(range(0, max_bin + 500, 500))
+
+    # Improve figure size so x-labels don't overlap
+    plt.figure(figsize=(14, 6))
+
+    plt.hist(times, bins=bins, edgecolor='black')
+    plt.title(f"Response Time Histogram for '{url_keyword}'")
+    plt.xlabel("Response Time (ms)")
+    plt.ylabel("Number of Requests")
+
+    # Rotate labels so they are visible
+    plt.xticks(bins, rotation=45, ha='right')
+
+    plt.grid(axis='y', linestyle='--', alpha=0.4)
+    plt.tight_layout()  # prevents clipping
+    plt.show()
+
+
+
+log_path = "./django_spoken.log"
+analyze_log(log_path)