{ "info": { "author": "Justin Crown", "author_email": "justincrown1@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "License :: OSI Approved :: MIT License", "Natural Language :: English", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3" ], "description": "=========\nHaralyzer\n=========\n\n.. image:: https://badge.fury.io/py/haralyzer.svg\n :target: http://badge.fury.io/py/haralyzer\n\n.. image:: https://travis-ci.org/mrname/haralyzer.svg?branch=master\n :target: https://travis-ci.org/mrname/haralyzer\n\n.. image:: https://coveralls.io/repos/mrname/haralyzer/badge.svg?branch=master\n :target: https://coveralls.io/r/mrname/haralyzer?branch=master\n\n.. image:: https://readthedocs.org/projects/haralyzer/badge/?version=latest\n :target: http://haralyzer.readthedocs.org/en/latest/\n\nA Python Framework For Using HAR Files To Analyze Web Pages.\n\nOverview\n--------\n\nThe haralyzer module contains two classes for analyzing web pages based\non a HAR file. ``HarParser()`` represents a full file (which might have\nmultiple pages), and ``HarPage()`` represents a single page from said file.\n\n``HarParser`` has a couple of helpful methods for analyzing single entries\nfrom a HAR file, but most of the pertinent functions are inside of the page\nobject.\n\n``haralyzer`` was designed to be easy to use, but you can also access more\npowerful functions directly.\n\nQuick Intro\n-----------\n\nHarParser\n+++++++++\n\nThe ``HarParser`` takes a single argument of a ``dict`` representing the JSON\nof a full HAR file. It has the same properties of the HAR file, EXCEPT that each\npage in HarParser.pages is a HarPage object::\n\n import json\n from haralyzer import HarParser, HarPage\n\n with open('har_data.har', 'r') as f:\n har_parser = HarParser(json.loads(f.read()))\n\n print har_parser.browser\n # {u'name': u'Firefox', u'version': u'25.0.1'}\n\n print har_parser.hostname\n # 'humanssuck.net'\n\n for page in har_parser.pages:\n assert isinstance(page, HarPage, None)\n # returns True for each\n\nHarPage\n+++++++\n\nThe ``HarPage`` object contains most of the goods you need to easily analyze a\npage. It has helper methods that are accessible, but most of the data you need is\nin properties for easy access. You can create a HarPage object directly by giving\nit the page ID (yes, I know it is stupid, it's just how HAR is organized), and either\na ``HarParser`` with `har_parser=parser`, or a ``dict`` representing the JSON of a full HAR\nfile (see example above) with `har_data=har_data`::\n\n import json\n From haralyzer import HarPage\n\n with open('har_data.har', 'r') as f:\n har_page = HarPage('page_3', har_data=json.loads(f.read()))\n\n ### GET BASIC INFO\n har_page.hostname\n # 'humanssuck.net'\n har_page.url\n $ 'http://humanssuck.net/about/'\n\n ### WORK WITH LOAD TIMES (all load times are in ms) ###\n\n # Get image load time in milliseconds as rendered by the browser\n har_page.image_load_time\n # prints 713\n\n # We could do this with 'css', 'js', 'html', 'audio', or 'video'\n\n ### WORK WITH SIZES (all sizes are in bytes) ###\n\n # Get the total page size (with all assets)\n har_page.page_size\n # prints 2423765\n\n # Get the total image size\n har_page.image_size\n # prints 733488\n # We could do this with 'css', 'js', 'html', 'audio', or 'video'\n\n # Get duplicate requests (requests to the same URL 2 or more times) if any\n har_page.duplicate_url_request\n # Returns a dict where the key is a string of the URL and the value is an int of the number\n # of requests to that URL. Only requests with 2 or more are included.\n # {'https://test.com/': 3}\n\n # Get the transferred sizes (works only with HAR files, generated with Chrome)\n har_page.page_size_trans\n har_page.image_size_trans\n har_page.css_size_trans\n har_page.text_size_trans\n har_page.js_size_trans\n har_page.audio_size_trans\n har_page.video_size_trans\n\n*IMPORTANT NOTE* - Technically, the `page_id` attribute of a single entry in a\nHAR file is optional. As such, if your HAR file contains entries that do not map\nto a page, an additional page will be created with an ID of `unknown`. This\n\"fake page\" will contain all such entries. Since it is not a real page, it does\nnot have attributes for things like time to first byte or page load, and will\nreturn `None`.\n\nMultiHarParser\n++++++++++++++\n\nThe ``MutliHarParser`` takes a ``list`` of ``dict``, each of which represents the JSON\nof a full HAR file. The concept here is that you can provide multiple HAR files of the\nsame page (representing multiple test runs) and the ``MultiHarParser`` will provide\naggregate results for load times::\n\n import json\n from haralyzer import HarParser, HarPage\n\n test_runs = []\n with open('har_data1.har', 'r') as f1:\n test_runs.append( (json.loads( f1.read() ) )\n with open('har_data2.har', 'r') as f2:\n test_runs.append( (json.loads( f2.read() ) )\n\n multi_har_parser = MultiHarParser(har_data=test_runs)\n\n # Get the mean for the time to first byte of all runs in MS\n print multi_har_parser.time_to_first_byte\n # 70\n\n # Get the total page load time mean for all runs in MS\n print multi_har_parser.load_time\n # 150\n\n # Get the javascript load time mean for all runs in MS\n print multi_har_parser.js_load_time\n # 50\n\n # You can get the standard deviation for any of these as well\n # Let's get the standard deviation for javascript load time\n print multi_har_parser.get_stdev('js')\n # 5\n # We can also do that with 'page' or 'ttfb' (time to first byte)\n print multi_har_parser.get_stdev('page')\n # 11\n print multi_har_parser.get_stdev('ttfb')\n # 10\n\n ### DECIMAL PRECISION ###\n\n # You will notice that all of the results are above. That is because\n # the default decimal precision for the multi parser is 0. However, you\n # can pass whatever you want into the constructor to control this.\n\n multi_har_parser = MultiHarParser(har_data=test_runs, decimal_precision=2)\n print multi_har_parser.time_to_first_byte\n # 70.15\n\n\nAdvanced Usage\n==============\n\n``HarPage`` includes a lot of helpful properties, but they are all\neasily produced using the public methods of ``HarParser`` and ``HarPage``::\n\n import json\n from haralyzer import HarPage\n\n with open('har_data.har', 'r') as f:\n har_page = HarPage('page_3', har_data=json.loads(f.read()))\n\n ### ACCESSING FILES ###\n\n # You can get a JSON representation of all assets using HarPage.entries #\n for entry in har_page.entries:\n if entry['startedDateTime'] == 'whatever I expect':\n ... do stuff ...\n\n # It also has methods for filtering assets #\n # Get a collection of entries that were images in the 2XX status code range #\n entries = har_page.filter_entries(content_type='image.*', status_code='2.*')\n # This method can filter by:\n # * content_type ('application/json' for example)\n # * status_code ('200' for example)\n # * request_type ('GET' for example)\n # * http_version ('HTTP/1.1' for example)\n # * load_time__gt (Takes an int representing load time in milliseconds.\n # Entries with a load time greater than this will be included in the\n # results.)\n # Parameters that accept a string use a regex by default, but you can also force a literal string match by passing regex=False\n\n # Get the size of the collection we just made #\n collection_size = har_page.get_total_size(entries)\n\n # We can also access files by type with a property #\n for js_file in har_page.js_files:\n ... do stuff ....\n\n ### GETTING LOAD TIMES ###\n\n # Get the BROWSER load time for all images in the 2XX status code range #\n load_time = har_page.get_load_time(content_type='image.*', status_code='2.*')\n\n # Get the TOTAL load time for all images in the 2XX status code range #\n load_time = har_page.get_load_time(content_type='image.*', status_code='2.*', asynchronous=False)\n\nThis could potentially be out of date, so please check out the sphinx docs.\n\n\nMore.... Advanced Usage\n=======================\n\nAll of the HarPage methods above leverage stuff from the HarParser,\nsome of which can be useful for more complex operations. They either\noperate on a single entry (from a HarPage) or a ``list`` of entries::\n\n import json\n from haralyzer import HarParser\n\n with open('har_data.har', 'r') as f:\n har_parser = HarParser(json.loads(f.read()))\n\n for page in har_parser.pages:\n for entry in page.entries:\n ### MATCH HEADERS ###\n if har_parser.match_headers(entry, 'Content-Type', 'image.*'):\n print 'This would appear to be an image'\n ### MATCH REQUEST TYPE ###\n if har_parser.match_request_type(entry, 'GET'):\n print 'This is a GET request'\n ### MATCH STATUS CODE ###\n if har_parser.match_status_code(entry, '2.*'):\n print 'Looks like all is well in the world'\n\n\nAsset Timelines\n+++++++++++++++\n\nThe last helper function of ``HarParser`` requires it's own section, because it\nis odd, but can be helpful, especially for creating charts and reports.\n\nIt can create an asset timeline, which gives you back a ``dict`` where each\nkey is a ``datetime`` object, and the value is a ``list`` of assets that were\nloading at that time. Each value of the ``list`` is a ``dict`` representing\nan entry from a page.\n\nIt takes a ``list`` of entries to analyze, so it assumes that you have\nalready filtered the entries you want to know about::\n\n import json\n from haralyzer import HarParser\n\n with open('har_data.har', 'r') as f:\n har_parser = HarParser(json.loads(f.read()))\n\n ### CREATE A TIMELINE OF ALL THE ENTRIES ###\n entries = []\n for page in har_parser.pages:\n for entry in page.entries:\n entries.append(entry)\n\n timeline = har_parser.create_asset_timeline(entries)\n\n for key, value in timeline.items():\n print(type(key))\n # \n print(key)\n # 2015-02-21 19:15:41.450000-08:00\n print(type(value))\n # \n print(value)\n # Each entry in the list is an asset from the page\n # [{u'serverIPAddress': u'157.166.249.67', u'cache': {}, u'startedDateTime': u'2015-02-21T19:15:40.351-08:00', u'pageref': u'page_3', u'request': {u'cookies':............................\n\n\nWith this, you can examine the timeline for any number of assets. Since the key is a ``datetime``\nobject, this is a heavy operation. 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