A couple of useful git commands for styding big git repositories:

Rank contributors by contributed lines of code in HEAD

git grep --cached -zIle '' |\
     xargs -0n1 git blame -e |\
    sed  -n 's/^.*(<\([a-zA-Z.]*\)@.*/\1/p' |\
    sort|uniq -c|sort -rn >authors-by-line.txt

sort branches by last modified date in the remote repository

git for-each-ref --sort=-committerdate \
    --format='%(committerdate:short)%(authorname)%(refname:short)' refs/remotes >branches-by-date.txt

Whether you order designs from 99designs or from an in-house designer, use this simple rule of thumb:

Your most valuable content should be the most contrasted.

Here's why. Bad designs are wildly different, but all good designs share one thing in common: they put your content first. As I am writing this, I realize that the text I am typing appears in charcoal gray or #4d4f51 while the title is all black. This is inconsistent at best, but not everything is lost for LinkedIn — the list of my last posts on the right is in a lighter gray #96999c and the editor buttons are even lighter than that.

The poster boy of good design, Boston Globe, displays text as black #000000 on all-white background #ffffff while their menu items have varying levels of greyness, from a rather dark #464646 on white to the same dark #464646 on neutral gray #eeeeee. This is good design — the most important thing Boston Globe has is news, and their news enjoy the most contrast you can get: all black text on all white background.

However, many websites have their main content in a rather worn-out pale black, while surrounding elements are flashy and attractive. Check for instance BBC.co.uk, their content is shown in dark gray #404040 while the navigation is in all-black #00000.

We've already seen it in 2009. The European Commission could have built an exemplary anti-trust case against Microsoft for forcing manufacturers to bundle its operating system with the computers. Instead, it targeted a smaller issue of tying the web browser to the operating system. Since then, Microsoft lost the browser war on technical grounds, and Internet Explorer became known as a tool to download Google Chrome on a fresh computer. The only real impact of the 2009 Commission's decision on consumers was negative. A sudden drop in the quality of email rendering in Microsoft Outlook 2010 and all the later versions comes from the fact that Microsoft teared off the Internet Explorer's component from Microsoft Office and replaced it with a much older and less capable library developed in the early 80s and initially used to display RTF documents. So, whenever you see bulky fonts and ugly formatting in your Microsoft Outlook, don't blame the sender, blame the European Commission. This old story repeats with Google. They took on an irrelevant issue of Google Shopping search results, instead of picking one of the well-publicized issues of: * abuse of control over the Android ecosystem * Gmail interoperability with small independent mail servers * Gtalk and Google Hangouts interoperability with third-party XMPP servers * Google Single Sign-On interoperability with regards to industry standards …the list can go on and on.

Among the multitude of programming APIs provided by Google lies a jewel called Prediction API. It has a high-quality classifier that allows for continuous learning with model updates.

Let's quickly use it to automatically sort incoming mail into your existing labels. The most tedious part is configuration:

Configuration

1. Create a new Blank Project in Google Apps Script and enable Prediction API in the Resources/Advanced Google services… menu.
2. Sign up for the Google Developers Console and take the 300$ free credit. Then, create your first Developers Console project and enable Prediction API in its API & auth section.
3. Switch back to your newly created Google Apps Script and link it with your new Developers Console project through the Resources/Developers Console Project menu.

We are done configuring. Now, there are only two functions to implement: one to train the model and the other to classify incoming mail.

Train

The function GmailApp.getUserLabels() ❶ gets all labels that you defined in Gmail and disregards standard labels such as Inbox, All Mail or Spam. Mails in Gmail are organized by threads, so once you get a handle on a label, you have to get all of its threads ❷, then grab individual mails under that thread. We'll use the first email of a thread for this simple exercise ❸.

Objective

Select like-minded users from a local community website.

Pre-requisites

1. A Drupal website with the votingapi module enabled and at least a few dozen votes by registered users.
2. A working installation of the R language.

Exract data

For each user, select all other users that voted on same node and comments:

SELECT v1.uid uid1, v2.uid uid2, u1.name name1, u2.name name2,
  v2.entity_id entity_id, v1.value value1, v2.value value2
FROM votingapi_vote v1
JOIN (votingapi_vote v2, users u1, users u2)
 ON (v1.uid != v2.uid AND v1.entity_id=v2.entity_id
   AND v1.entity_type=v2.entity_type AND v1.uid=u1.uid AND v2.uid=u2.uid)
WHERE v1.uid 

This produces a table