I was having lunch at the recent LinuxCon and Plumbers conference with a colleague, bragging as usual about how much I love my home near Portland, Oregon.
A traditional compiler translates a high-level computer program into machine code for the CPU you want to run it on. An interpreted language translates a high-level language into the machine code for some imaginary CPU. For historical reasons, this imaginary CPU is called a "virtual machine" and its instructions are called "byte code." One advantage of this approach is development speed: creating...
The server world has really embraced Python in a big way. For example, the OpenStack project is a very popular Infrastructure as a Service offering, and most of it is written in Python. This makes Python a leader for Software Defined Infrastructure (SDI), Software Defined Storage (SDS) and Software Defined Networking (SDN).
My current job is to lead our company's work on dynamic server languages, such as performance optimization and feature enabling. Besides PHP and HHVM, we want to improve Python. There is a huge amount of Python code in use out there, for example running OpenStack, Swift, DropBox and many others. What I didn't realize when I took the job was that much of this use is in a "dead" language.