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Developer Productivity
During the great Internet boom of the mid-to-late 1990s, it was difficult to find enough programmers to implement software projects; developers were asked to implement systems as fast as the Internet evolved. Today, in an era of layoffs and economic recession, the picture has shifted. Programming staffs are often now asked to accomplish the same tasks with even fewer people.
In both of these scenarios, Python has shined as a tool that allows programmers to get more done with less effort. It is deliberately optimized for speed of development—its simple syntax, dynamic typing, lack of compile steps, and built-in toolset allow programmers to develop programs in a fraction of the time needed when using some other tools. The net effect is that Python typically boosts developer productivity many times beyond the levels supported by traditional languages. That’s good news in both boom and bust times, and everywhere the software industry goes in between.
[2] For a more complete look at the Python philosophy, type the command import this at any Python interactive prompt (you’ll see how in Chapter 2). This invokes an “Easter egg” hidden in Python—a collection of design principles underlying Python. The acronym EIBTI is now fashionable jargon for the “explicit is better than implicit” rule.
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