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63 lines
1.8 KiB
Python
63 lines
1.8 KiB
Python
# Tests latency and hit rate of endpoints. Can be configured with weighted averages for various endpoints.
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import requests
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import random
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import json
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from tqdm import tqdm
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import time
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baseurl = "http://localhost:8000"
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chance_of_selecting_friend = 0.7
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user_friends = json.loads(requests.get(baseurl + "/users_and_friends").content)
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user_ids = json.loads(requests.get(baseurl + "/users").content)["ids"]
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random.seed(0)
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def fetch_friend(prob):
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return random.random() < prob
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def generate_random():
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random_user = str(random.choice(user_ids))
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return random_user
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def generate_random_friend(user):
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next_user = str(random.choice(user_friends[user]))
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return next_user
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times = []
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hits = []
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start = time.time()
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curr_user = generate_random()
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for i in tqdm(range(10000)):
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url = baseurl + "/user/" + curr_user
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response = requests.get(url)
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content = json.loads(response.content)
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times.append(content["time_ms"])
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hits.append(content["source"] == "cache")
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if fetch_friend(chance_of_selecting_friend):
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curr_user = generate_random_friend(curr_user)
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else:
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curr_user = generate_random()
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end = time.time()
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hits_count = sum(hits)
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miss_count = len(hits) - hits_count
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hits_time = 0
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miss_time = 0
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for i in range(len(times)):
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if hits[i]:
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hits_time += times[i]
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else:
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miss_time += times[i]
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total_time = hits_time + miss_time
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print(f"hits: {hits_count} misses: {miss_count} ratio: { hits_count / (hits_count + miss_count)}")
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print(f"average response time (ms) : {total_time / len(times)}")
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print(f"average cache hit response time (ms) : {hits_time / hits_count}")
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print(f"average cache miss response time (ms): {miss_time / miss_count}")
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print(f"cache throughput (requests / ms) : { len(times) / total_time}")
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print(f"real throughput (requests / ms) : { len(times) / (end - start) / 1000}") |