I'm a fan of WinPython, though it's only for Windows. It let me get started quickly, while also providing access to the standard tools such as pip. For virtuall

I'm a fan of WinPython, though it's only for Windows. It let me get started quickly, while also providing access to the standard tools such as pip. For virtually everything I've done, either pip or "python setup.py install" have been successful. The nicest thing about WinPython is that if I mess it up, I can just erase it and start over. I can also test my code on a "clean" distribution, to make sure that my installation instructions are valid. The practice in my team is that you can start out any way you want, but you're expected to begin learning batter practices as your projects mature. And we have a couple people who can teach you. Though I was the one who introduced Python to my work site, I'm also one of the ones who needs to continue learning better programming practices. It's sad that there is virtually no decent training for scientists who want to be better programmers. There's certainly a cacophony of advice, much of it conflicting or too complicated to be credible. Maybe it's not widespread, but when "scientific" programming is mentioned, there are always a lot of comments to the effect that we shouldn't be programming at all without a license. Likewise for the use of Excel. Instead, scientists are left to figure things out for ourselves, like we've been doing anyway since the dawn of time.