YJL

http://[BLOG_ID]_[HASH].blogspot.com/b/post-preview?token=[TOKEN]&type=POST

Keep in mind that changes made to profiles may take up to a couple of hours to update in Real-Time reports. We're working on reducing this latency.

  <b:include data='blog' name='google-analytics'/>
</body>

We found no clickthroughs for this page. Try adjusting the date range or select another page.

<script src="https://gist.github.com/raw/1713067/ga-wr.js"></script>
<script>
function init_page() {
  var gawr_options = {
    target: 'ga-wr',
    UA: 'UA-XXXXXXXX-X',
    report_options: [
      {
        title: 'Image is not loaded'
      },
      {
        title: 'Link is broken'
      },
      {
        title: 'Other'
      }
      ]
    };
  new GAWR(gawr_options);
}
$(init_page);
</script>
<div id="ga-wr"></div>

After I posted my first try of using Google Analytics Data Export API, I realized that I didnt need to send two requests for calculating visits change, one is enough. Moreover, I could also make a chart.

=== General ===

125 |                                                          #
    |                      #           ##      ##            ####
    |                      #           ###     ##     ##    #####
    | ##                  ###   ##  # ######   ## #  ####   #####
    |####  # #    # #  # #####  ############  ##### ###### ######
    |#### #####   # ## ##########################################
    |###########  ###############################################
    |########### ################################################
    |############################################################
    |############################################################
    |############################################################
  0 +------------------------------------------------------------

  116 visits (  -7.20%)
  Average time on site: 122.655172414 seconds (  55.75%)</pre>

I wonder if there is a popular Python library or common CLI tool to make an ASCII chart.

DAYS = 60
date = (dt.datetime.now() - dt.timedelta(days=1)).strftime('%Y-%m-%d')
date_start = (dt.datetime.now() - dt.timedelta(days=DAYS)).strftime('%Y-%m-%d')

# General
###########
data_query = gdata.analytics.client.DataFeedQuery({
    'ids': table_id,
    'start-date': date_start,
    'end-date': date,
    'dimensions': 'ga:date',
    'sort': 'ga:date',
    'metrics': 'ga:visits,ga:avgTimeOnSite'})
feed = my_client.GetDataFeed(data_query)
visits = [int(entry.metric[0].value) for entry in feed.entry]
max_visits = max(visits)
print '=== General ==='
print
CHART_HEIGHT = 10
VISIT_WIDTH = len(str(max_visits))
for y in range(CHART_HEIGHT, -1, -1):
  if y == CHART_HEIGHT:
    sys.stdout.write('%d |' % max_visits)
  else:
    sys.stdout.write('%s |' % (' '*VISIT_WIDTH))
  for x in range(-DAYS, 0):
    vst = visits[x]
    # vst / max_visits >= y / CHART_HEIGHT
    if vst * CHART_HEIGHT >= y * max_visits:
      sys.stdout.write('#')
    else:
      sys.stdout.write(' ')
  sys.stdout.write('\n')
  sys.stdout.flush()
print '%s0 +%s' % (' '*(VISIT_WIDTH-1), '-'*DAYS)
print
visits_change = 100.0 * (visits[-1] - visits[-2]) / visits[-2]
avg_time = float(feed.entry[-1].metric[1].value)
avg_time_before = float(feed.entry[-2].metric[1].value)
avg_time_change = 100.0 * (avg_time - avg_time_before) / avg_time_before
print '  %s visits (%7.2f%%)' % (visits[-1], visits_change)
print '  Average time on site: %s seconds (%7.2f%%)' % (avg_time, avg_time_change)
print

I finally tried to use Google Analytics API to generate a report which in a format I prefer to read. Its simple but it has everything I am interested.

About a couple of weeks ago, I noticed a few strange pageviews which have URL paths did not match Blogger blog URL structure and one word particularly got my attention, atheism.

If you are a Blogger blogger, you will be immediately aware that definitely not come from your blog. You wont see links like /blog/ or /YYYY/MM/DD/blah in your blog. The question is where did they come from?

At first thought, I believed that site owner mistyped a digit of his¹ own UA number² or something like that. But its obviously not because the UA number very different than mine. I began to think the owner was trying to fake pageviews and drew me to check out the owners website. However, I dismissed that thought very quickly, because that website doesnt seem to fit in and usually spammers only target a subject for a very short period of time. Often its one-time spamming only, but its been at least one day when I noticed.

My index finger slowly moved to point at Google Analytics system, some big flaw in the system I would guess. Ha! I will be the first one to expose this! I ecstatically enjoyed my glorious moment. Well, that moment didnt come. I put it aside because I didnt believe Google would have such flaw, either.

Finally, I decided to check help forums to see if anyone has encountered same situation. I found one useful, the problem is I still didnt think my UA number was being used by someone. I decided to do a final check on the websites source code, which was my second time. Still got nothing.

I brought up Firefox 4s Web Control and left Net and JavaScript on only, reloaded the page and read the logs. One thing more weird came to my eyes:

The page loaded Disqus script, its no big deal even that website doesnt use Disqus at all. The eye-bulging part is "yjlv", thats my blogs Disqus ID. I double-checked with Chromium because I just didnt believe, Chromiums Developer Tools Resources tab affirmed.

Alright, this whole thing is extremely confusing. Its as if the weirdness not only be doubled but actually is squared. Firstly, my UA number could be used by someone. And now, even Disqus? What the heck is going on? I asked myself.

I checked the source code for the third time, I still got nothing. I almost gave up and decided to write a post on help forums, then I clicked on the websites local copy of jQuery. I did the search, BINGO!

I wouldnt believe when I saw my code was in the end of file and more than just UA number and Disqus parts, it seems to include this entirely.

I dont know which part of my code the website owner is actually using. That JavaScript is written for this blog and I doubt it would work out-of-the-box on other website. I remember somewhere I read long ago, copy-and-pasting the code you dont understand is a very bad habit. If I was a very bad person and that website does have <pre><code>...</code></pre>, then I could send a different version of highlight.pack.js if my GAE app detects the visitor is from that website. Who knows what I would put in that fake JavaScript?

Right after I publish this post, I am going to find the contact information and shoot the owner an email with a link to this post. I hope its About or Contact page isnt written in Korean.

Anyway, I am really tired of writing an email to detail everything. So, here is the message body to the website owner:

Hi!

Dont worry, you didnt violate any copyright law. Just please remove parts you dont need from your /js/jquery.js, especially the part contains my Google Analytics UA. You contributed 600+ page views into my Google Analytics report, I am really appreciated for the generosity.

Sincerely yours, P.

PS. If possible, please tell me which part of my code you intend to use? collapse_pre()?

I really dont want to write a post anytime, but I also dont want to see any more data which dont belong to me. If you are going to suggest me creating a filter for preventing from this kind of thing happened again, thanks! But no, I wont do that. Covering eyes isnt a solution.

And please readers, though I decided not to mask that websites name and domain in screenshots, but please DO NOT visit that website anytime soon, or my Google Analytics account would have more **kindly contributed* data. Besides, you know most of you guys dont read Korean right, please dont say Google Translate, I am begging you!*

$ sqlite3 cookies.sqlite 
SQLite version 3.6.23.1
Enter ".help" for instructions
Enter SQL statements terminated with a ";"
sqlite> select count(name) from moz_cookies where name like '\_\_ut%' escape '\';
148
sqlite> select count(name) from moz_cookies;
456

127.0.0.1 google-analytics.com www.google-analytics.com ssl.google-analytics.com

I have a project called BRPS, which has an old client script brps.js. Whenever this client request data from BRPS server, the server will increase the requests count and it has a statistics page for showing the count. Recently, a new client is implemented, gas.js. This new client doesnt communicate with BRPS server, I need to find a way to get a statistic number about how many requests it has been made. I dont want to write more code on my server to log those requests. So, Google Analytics is the best option for me.

function _track() {
  try {
    var pageTracker = _gat._getTracker("UA-#######-#");
    pageTracker._setDomainName("none");
    pageTracker._setAllowLinker(true);
    pageTracker._trackPageview();
    }
  catch(err) {
    }
  }
if (window._gat) {
  _track();
  }
else {
  $.getScript(('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js', function(){
      _track();
      });
  }

2   Filters

I created a new profile and two more based on the first one. The last two are using filter each. The first filter is

Custom filter	Advanced
FieldA	Hostname	(.*)
FieldB	Request URI	(.*)
Output	Request URI	$A1$B1

The profile with this filter can see results like example.com/foobar. A sample output:

The second one is

Custom filter	Advanced
FieldA	Hostname	(.*)
FieldB	unused
Output	Request URI	$A1

The profile with this filter can see results like example.com, I would like to know which websites are top users. A sample output:

function _track() {
  var _gaq = window._gaq || [];
  _gaq.push(['_setAccount', 'UA-#######-#']);
  _gaq.push(['_setDomainName', 'none']);
  _gaq.push(['_setAllowLinker', 'true']);
  _gaq.push(['_trackPageview']);
  if (!window._gaq)
    window._gaq = _gaq;
  }

A standard asynchronous Google Analytics tracking code would look like:

<script type="text/javascript">

  var _gaq = _gaq || [];
  _gaq.push(['_setAccount', 'UA-#######-#']);
  _gaq.push(['_trackPageview']);

  (function() {
    var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
    ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
    var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
  })();

</script>

I didnt like how they look, so I decided to re-write with jQuery:

if (window._gat) {
  _gat._getTracker("UA-#######-#")._trackPageview();
  }
else {
  $.ajaxSetup({cache: true});
  $.getScript(('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js', function () {
      _gat._getTracker("UA-#######-#")._trackPageview();
      });
  $.ajaxSetup({cache: false});
  }

It checks if there already is a Google Analytics script included. The script is the same and reusable, some websites might have multiple tracking code being executed. There is no need to create many <script>. If the script isnt included, then it loads it using jQuerys getScript(). Within the callback, it logs the pageview. You might also want to put _gat... into a try {} catch.... The older non-asynchronous tracking code does that.

You can also see it uses $.ajaxSetup() to set up cache use. By default, jQuery appends a timestamp like _=1234567890 as a query parameter after the URL of the script you want to load, that timestamp is called cachebuster, which causes web server sends same content to client even the content isnt modified. I discovered this behavior when I was adding new code on this blog.

In normal request, your web browser will check with server. If server returns 304, then browser will use the ga.js it already has in hand. With cachebuster, that wont happen, browser receives same content again and again. Using ajaxSetup() is to ensure cache is in use.

The only part I dont like in my code is how it decides the script link, it doesnt look pretty to me.