Fixed so that the total median is now calculated using all the reques…

…ted URLs' median and request count values. This fixes issue #7.

locust/example.py

@@ -7,13 +7,16 @@ def login(l):
 def index(l):
     l.client.get("/")
 
+def stats(l):
+    l.client.get("/stats/requests")
+
 @require_once(login)
 def profile(l):
     l.client.get("/profile")
 
 class WebsiteUser(Locust):
     host = "http://127.0.0.1:8089"
     #tasks = [(index, 2), (profile, 1)]
-    tasks = [index]
+    tasks = [index, stats]
     min_wait=2000
     max_wait=5000

locust/stats.py

@@ -115,18 +115,7 @@ def median_response_time(self):
         if not self.response_times:
             return 0
 
-        def median(total, count):
-            """
-            total is the number of requests made
-            count is a dict {response_time: count}
-            """
-            pos = (total - 1) / 2
-            for k in sorted(count.iterkeys()):
-                if pos < count[k]:
-                    return k
-                pos -= count[k]
-
-        return median(self.num_reqs, self.response_times)
+        return median_from_dict(self.num_reqs, self.response_times)
 
     @property
     def current_rps(self):
@@ -250,6 +239,17 @@ def sum_stats(cls, name="Total", full_request_history=False):
 def avg(values):
     return sum(values, 0.0) / max(len(values), 1)
 
+def median_from_dict(total, count):
+    """
+    total is the number of requests made
+    count is a dict {response_time: count}
+    """
+    pos = (total - 1) / 2
+    for k in sorted(count.iterkeys()):
+        if pos < count[k]:
+            return k
+        pos -= count[k]
+
 # TODO Use interpolation or not?
 def percentile(N, percent, key=lambda x:x):
     """

locust/web.py

@@ -4,11 +4,12 @@
 import os.path
 from time import time
 from itertools import chain
+from collections import defaultdict
 
 from gevent import wsgi
 from flask import Flask, make_response, request, render_template
 
-from locust.stats import RequestStats
+from locust.stats import RequestStats, median_from_dict
 from locust import version
 
 DEFAULT_CACHE_TIME = 2.0
@@ -128,6 +129,7 @@ def request_stats():
     if not _request_stats_context_cache or _request_stats_context_cache["last_time"] < time() - _request_stats_context_cache.get("cache_time", DEFAULT_CACHE_TIME):
         cache_time = _request_stats_context_cache.get("cache_time", DEFAULT_CACHE_TIME)
         now = time()
+
         stats = []
         for s in chain(_sort_stats(locust_runner.request_stats), [RequestStats.sum_stats("Total")]):
             stats.append({
@@ -152,6 +154,17 @@ def request_stats():
                     report["fail_ratio"] = 100
                 else:
                     report["fail_ratio"] = 0
+
+            # since generating a total response times dict with all response times from all
+            # urls is slow, we make a new total response time dict which will consist of one
+            # entry per url with the median response time as key and the numbe fo requests as
+            # value
+            response_times = defaultdict(int) # used for calculating total median
+            for i in xrange(len(stats)-1):
+                response_times[stats[i]["median_response_time"]] += stats[i]["num_reqs"]
+
+            # calculate total median
+            stats[len(stats)-1]["median_response_time"] = median_from_dict(stats[len(stats)-1]["num_reqs"], response_times)
 
         is_distributed = isinstance(locust_runner, MasterLocustRunner)
         if is_distributed: