Merge pull request #7 from mrname/numpy

Numpy

.travis.yml

@@ -2,7 +2,6 @@ language: python
 matrix:
   fast_finish: true
   allow_failures:
-  - python: "3.2"
   - python: "nightly"
 python:
   - "2.6"

README.rst

@@ -251,8 +251,3 @@ already filtered the entries you want to know about::
 With this, you can examine the timeline for any number of assets. Since the key is a ``datetime``
 object, this is a heavy operation. We could always change this in the future, but for now,
 limit the assets you give this method to only what you need to examine.
-
-Known Issues
-------------
-
-The `haralyzer` module is currently not compatible with python 3.2. This is due to the fact that it leverages the `statistics` backport, which is not compatible with python 3.2. We will be working on a fix as soon as possible, feel free to submit a pull request in the meantime.

docs/conf.py

@@ -60,9 +60,9 @@
 # built documents.
 #
 # The short X.Y version.
-version = '1.2'
+version = '1.3'
 # The full version, including alpha/beta/rc tags.
-release = '1.2.2'
+release = '1.3.1'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

haralyzer/assets.py

@@ -7,9 +7,9 @@
 import dateutil
 # I know this import is stupid, but I cannot use dateutil.parser without it
 from dateutil import parser
+import numpy
 assert parser
 import re
-import statistics
 
 from haralyzer.compat import iteritems
 
@@ -214,7 +214,8 @@ def get_stdev(self, asset_type):
         else:
             load_times = self.get_load_times(asset_type)
 
-        return round(statistics.stdev(load_times), self.decimal_precision)
+        return round(numpy.std(load_times, ddof=1),
+                     self.decimal_precision)
 
     @property
     def pages(self):
@@ -247,15 +248,15 @@ def time_to_first_byte(self):
         ttfb = []
         for page in self.pages:
             ttfb.append(page.time_to_first_byte)
-        return round(statistics.mean(ttfb), self.decimal_precision)
+        return round(numpy.mean(ttfb), self.decimal_precision)
 
     @cached_property
     def page_load_time(self):
         """
         The average total load time for all runs (not weighted).
         """
         load_times = self.get_load_times('page')
-        return round(statistics.mean(load_times), self.decimal_precision)
+        return round(numpy.mean(load_times), self.decimal_precision)
 
     @cached_property
     def js_load_time(self):
@@ -266,47 +267,47 @@ def js_load_time(self):
         total load time or the browser load time
         """
         load_times = self.get_load_times('js')
-        return round(statistics.mean(load_times), self.decimal_precision)
+        return round(numpy.mean(load_times), self.decimal_precision)
 
     @cached_property
     def css_load_time(self):
         """
         Returns aggregate css load time for all pages.
         """
         load_times = self.get_load_times('css')
-        return round(statistics.mean(load_times), self.decimal_precision)
+        return round(numpy.mean(load_times), self.decimal_precision)
 
     @cached_property
     def image_load_time(self):
         """
         Returns aggregate image load time for all pages.
         """
         load_times = self.get_load_times('image')
-        return round(statistics.mean(load_times), self.decimal_precision)
+        return round(numpy.mean(load_times), self.decimal_precision)
 
     @cached_property
     def html_load_time(self):
         """
         Returns aggregate html load time for all pages.
         """
         load_times = self.get_load_times('html')
-        return round(statistics.mean(load_times), self.decimal_precision)
+        return round(numpy.mean(load_times), self.decimal_precision)
 
     @cached_property
     def audio_load_time(self):
         """
         Returns aggregate audio load time for all pages.
         """
         load_times = self.get_load_times('audio')
-        return round(statistics.mean(load_times), self.decimal_precision)
+        return round(numpy.mean(load_times), self.decimal_precision)
 
     @cached_property
     def video_load_time(self):
         """
         Returns aggregate video load time for all pages.
         """
         load_times = self.get_load_times('video')
-        return round(statistics.mean(load_times), self.decimal_precision)
+        return round(numpy.mean(load_times), self.decimal_precision)
 
 
 class HarPage(object):

requirements.txt

@@ -1,5 +1,5 @@
-statistics; python_version <= '2.7'
+cached-property
+numpy
 python-dateutil
 pytest-cov
 python-coveralls
-cached-property

setup.py

@@ -7,14 +7,14 @@
 
 
 install_reqs = ['cached-property',
-                'python-dateutil',
-                'statistics', ]
+                'numpy',
+                'python-dateutil', ]
 
 readme = open('README.rst').read()
 
 setup(
     name='haralyzer',
-    version='1.2.2',
+    version='1.3',
     description='A python framework for getting useful stuff out of HAR files',
     long_description=readme,
     author='Justin Crown',