Toptal runs the article “One Size Fits Some: A Guide to Responsive Web Design Image Solutions“, which discusses one of the trickiest problems of today’s web design and development – responsive images. They cover several tools and approaches – from HTML5 elements to on-the-fly image resizing and source shuffling.
I don’t deal with Unicode and other character encoding on the daily basis, but when I do, I need every piece of information that has been written on the subject. Hence the link to this interesting issue :
As long as you stick to precomposed Unicode characters, and Western scripts, things are relatively straightforward. Whether it’s A or Å, S or Š – so long as there are no combining marks, you can count a single Unicode code point as one character width. So the following works:
Nice and neat, right?
Unfortunately, problems appear with Asian characters. When displayed in monospace, many Asian characters occupy two character widths.
I’m saving this here for current and future generations of programmers:
Latency Comparison Numbers
L1 cache reference 0.5 ns
Branch mispredict 5 ns
L2 cache reference 7 ns 14x L1 cache
Mutex lock/unlock 25 ns
Main memory reference 100 ns 20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy 3,000 ns
Send 1K bytes over 1 Gbps network 10,000 ns 0.01 ms
Read 4K randomly from SSD* 150,000 ns 0.15 ms
Read 1 MB sequentially from memory 250,000 ns 0.25 ms
Round trip within same datacenter 500,000 ns 0.5 ms
Read 1 MB sequentially from SSD* 1,000,000 ns 1 ms 4X memory
Disk seek 10,000,000 ns 10 ms 20x datacenter roundtrip
Read 1 MB sequentially from disk 20,000,000 ns 20 ms 80x memory, 20X SSD
Send packet CA->Netherlands->CA 150,000,000 ns 150 ms
1 ns = 10-9 seconds
1 ms = 10-3 seconds
* Assuming ~1GB/sec SSD
By Jeff Dean: http://research.google.com/people/jeff/
Originally by Peter Norvig: http://norvig.com/21-days.html#answers
Some updates from: https://gist.github.com/2843375
Great 'humanized' comparison version: https://gist.github.com/2843375
Visual comparison chart: http://i.imgur.com/k0t1e.png
Nice animated presentation of the data: http://prezi.com/pdkvgys-r0y6/latency-numbers-for-programmers-web-development/
This is a copy-paste of this gist, referenced from this blog post. Read and share both, for the better world.
I came across a collection of free data science books:
Pulled from the web, here is a great collection of eBooks (most of which have a physical version that you can purchase on Amazon) written on the topics of Data Science, Business Analytics, Data Mining, Big Data, Machine Learning, Algorithms, Data Science Tools, and Programming Languages for Data Science.
Most notably, there are introductory books, handbooks, Hadoop guide, SQL books, social media data mining stuff, and d3 tips and tricks. There’s also plenty on artificial intelligence and machine learning, but that’s too far out for me.
“Logging with Monolog: From Devtools to Slack” is a handy quick article for anybody who wants to use Monolog for logging in PHP applications. After all, monolog/monolog is one of the most popular libraries on Packagist.