Seive Testing

tests/random_readwrite.py

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+import requests
+import random
+import json
+from tqdm import tqdm
+import time
+
+baseurl = "http://localhost:8000"
+
+endpoints = {
+    "/user/{user_id}": 0.8,  # 80% read operations
+    "/update_user/?user_id={user_id}&name=Test&followers=100&bio=Updated&posts=Updated": 0.2  # 20% write operations
+}
+
+# Fetch all user IDs
+user_ids = json.loads(requests.get(baseurl + "/users").content)["ids"]
+
+random.seed(0)
+
+def generate_random():
+    """Randomly generate a read or write request, favoring cache hits."""
+    endpoint = random.choices(list(endpoints.keys()), list(endpoints.values()))[0]
+    if endpoint == "/user/{user_id}":
+        # Favor frequently accessed user IDs to increase hit ratio
+        if len(user_ids) > 0:
+            # Sample from a subset of user IDs to simulate frequent access
+            frequent_users = user_ids[:int(len(user_ids) * 0.2)]  # 20% frequent users
+            random_user = str(random.choice(frequent_users)) if random.random() < 0.7 else str(random.choice(user_ids))
+        else:
+            random_user = str(random.choice(user_ids))
+    else:
+        random_user = str(random.choice(user_ids))
+    return baseurl + endpoint.replace("{user_id}", random_user)
+
+times = []
+hits = []
+
+# Warm-up phase
+# for _ in tqdm(range(1000)):
+#     url = generate_random()
+#     requests.get(url)
+
+# Main testing phase
+start = time.time()
+for i in tqdm(range(10000)):
+    url = generate_random()
+    response = requests.get(url)
+
+    try:
+        content = json.loads(response.content)
+        
+        if "time_ms" in content:  # Only process if "time_ms" exists
+            times.append(content["time_ms"])
+            hits.append(content["source"] == "cache")
+
+    except json.JSONDecodeError:
+        print(f"Error decoding JSON: {response.content}")
+        exit(1)
+    except KeyError:
+        print(f"Unexpected response format: {content}")
+        exit(1)
+
+end = time.time()
+
+hits_count = sum(hits)
+miss_count = len(hits) - hits_count
+
+hits_time = sum(times[i] for i in range(len(times)) if hits[i])
+miss_time = sum(times[i] for i in range(len(times)) if not hits[i])
+total_time = hits_time + miss_time
+
+print(f"hits: {hits_count} misses: {miss_count} ratio: {hits_count / (hits_count + miss_count):.2f}")
+print(f"average response time (ms)           : {total_time / len(times):.2f}")
+print(f"average cache hit response time (ms) : {hits_time / hits_count if hits_count else 0:.2f}")
+print(f"average cache miss response time (ms): {miss_time / miss_count if miss_count else 0:.2f}")
+print(f"cache throughput (requests / ms)     : {len(times) / total_time:.2f}")
+print(f"real throughput  (requests / ms)     : {len(times) / (end - start) / 1000:.2f}")