haralyzer 1.6.0

哈帕瑟

HarParser接受一个表示json的dict参数 一个完整的har文件。它与har文件具有相同的属性，除了 pages是一个harpage对象：

import json
from haralyzer import HarParser, HarPage

with open('har_data.har', 'r') as f:
    har_parser = HarParser(json.loads(f.read()))

print har_parser.browser
# {u'name': u'Firefox', u'version': u'25.0.1'}

print har_parser.hostname
# 'humanssuck.net'

for page in har_parser.pages:
    assert isinstance(page, HarPage, None)
    # returns True for each

竖琴

HarPage对象包含您需要轻松分析 第页。它有可访问的helper方法，但您需要的大多数数据是 在属性中方便访问。您可以直接通过提供 它是页面id（是的，我知道它很愚蠢，只是har是如何组织的），或者 一个HarParser和一个表示完整har的json的dict。 文件（见上面的示例），其中包含har-data=har-data：

import json
From haralyzer import HarPage

with open('har_data.har', 'r') as f:
    har_page = HarPage('page_3', har_data=json.loads(f.read()))

### GET BASIC INFO
har_page.hostname
# 'humanssuck.net'
har_page.url
$ 'http://humanssuck.net/about/'

### WORK WITH LOAD TIMES (all load times are in ms) ###

# Get image load time in milliseconds as rendered by the browser
har_page.image_load_time
# prints 713

# We could do this with 'css', 'js', 'html', 'audio', or 'video'

### WORK WITH SIZES (all sizes are in bytes) ###

# Get the total page size (with all assets)
har_page.page_size
# prints 2423765

# Get the total image size
har_page.image_size
# prints 733488
# We could do this with 'css', 'js', 'html', 'audio', or 'video'

# Get the transferred sizes (works only with HAR files, generated with Chrome)
har_page.page_size_trans
har_page.image_size_trans
har_page.css_size_trans
har_page.text_size_trans
har_page.js_size_trans
har_page.audio_size_trans
har_page.video_size_trans

important note-从技术上讲，在 har文件是可选的。因此，如果har文件包含未映射的条目 对于一个页面，将创建一个ID为未知的附加页面。这个 “假页”将包含所有此类条目。既然不是真正的一页 没有时间到第一个字节或页面加载之类的属性，并且将 return无。

多弹琴手

MutliHarParser接受一个list的dict，每个代表json 一个完整的har文件。这里的概念是您可以提供 相同的页面（表示多个测试运行）和MultiHarParser将提供 加载时间的聚合结果：

import json
from haralyzer import HarParser, HarPage

test_runs = []
with open('har_data1.har', 'r') as f1:
    test_runs.append( (json.loads( f1.read() ) )
with open('har_data2.har', 'r') as f2:
    test_runs.append( (json.loads( f2.read() ) )

multi_har_parser = MultiHarParser(har_data=test_runs)

# Get the mean for the time to first byte of all runs in MS
print multi_har_parser.time_to_first_byte
# 70

# Get the total page load time mean for all runs in MS
print multi_har_parser.load_time
# 150

# Get the javascript load time mean for all runs in MS
print multi_har_parser.js_load_time
# 50

# You can get the standard deviation for any of these as well
# Let's get the standard deviation for javascript load time
print multi_har_parser.get_stdev('js')
# 5
# We can also do that with 'page' or 'ttfb' (time to first byte)
print multi_har_parser.get_stdev('page')
# 11
print multi_har_parser.get_stdev('ttfb')
# 10

### DECIMAL PRECISION ###

# You will notice that all of the results are above. That is because
# the default decimal precision for the multi parser is 0. However, you
# can pass whatever you want into the constructor to control this.

multi_har_parser = MultiHarParser(har_data=test_runs, decimal_precision=2)
print multi_har_parser.time_to_first_byte
# 70.15

import json
from haralyzer import HarPage

with open('har_data.har', 'r') as f:
    har_page = HarPage('page_3', har_data=json.loads(f.read()))

### ACCESSING FILES ###

# You can get a JSON representation of all assets using HarPage.entries #
for entry in har_page.entries:
    if entry['startedDateTime'] == 'whatever I expect':
        ... do stuff ...

# It also has methods for filtering assets #
# Get a collection of entries that were images in the 2XX status code range #
entries = har_page.filter_entries(content_type='image.*', status_code='2.*')
# This method can filter by:
# * content_type ('application/json' for example)
# * status_code ('200' for example)
# * request_type ('GET' for example)
# * http_version ('HTTP/1.1' for example)
# It will use a regex by default, but you can also force a literal string match by passing regex=False

# Get the size of the collection we just made #
collection_size = har_page.get_total_size(entries)

# We can also access files by type with a property #
for js_file in har_page.js_files:
    ... do stuff ....

### GETTING LOAD TIMES ###

# Get the BROWSER load time for all images in the 2XX status code range #
load_time = har_page.get_load_time(content_type='image.*', status_code='2.*')

# Get the TOTAL load time for all images in the 2XX status code range #
load_time = har_page.get_load_time(content_type='image.*', status_code='2.*', asynchronous=False)

import json
from haralyzer import HarParser

with open('har_data.har', 'r') as f:
    har_parser = HarParser(json.loads(f.read()))

for page in har_parser.pages:
    for entry in page.entries:
        ### MATCH HEADERS ###
        if har_parser.match_headers(entry, 'Content-Type', 'image.*'):
            print 'This would appear to be an image'
        ### MATCH REQUEST TYPE ###
        if har_parser.match_request_type(entry, 'GET'):
            print 'This is a GET request'
        ### MATCH STATUS CODE ###
        if har_parser.match_status_code(entry, '2.*'):
            print 'Looks like all is well in the world'

资产时间表

HarParser的最后一个helper函数需要它自己的节，因为它 很奇怪，但可能会有帮助，特别是在创建图表和报告时。

它可以创建一个资产时间轴，它给您返回一个dict，其中每个 key是一个datetime对象，值是 当时正在装货。list的每个值都是表示 页面上的条目。

它需要list个条目来分析，因此它假设您 已经筛选了您想知道的条目：

import json
from haralyzer import HarParser

with open('har_data.har', 'r') as f:
    har_parser = HarParser(json.loads(f.read()))

### CREATE A TIMELINE OF ALL THE ENTRIES ###
entries = []
for page in har_parser.pages:
    for entry in page.entries:
        entries.append(entry)

timeline = har_parser.create_asset_timeline(entries)

for key, value in timeline.items():
    print(type(key))
    # <type 'datetime.datetime'>
    print(key)
    # 2015-02-21 19:15:41.450000-08:00
    print(type(value))
    # <type 'list'>
    print(value)
    # Each entry in the list is an asset from the page
    # [{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':............................

这样，您就可以检查任意数量资产的时间线。因为密钥是datetime 对象，这是一个繁重的操作。我们可以在将来改变，但现在， 将此方法提供的资源限制为只需要检查的内容。