I want to dwell on #4 for a moment.
The Python community actually has a Code of Conduct. We try to stick by it and conferences will have reporting mechanisms in place so we can educate folks who are being inconsiderate or disrespectful.
The consequence of this is a welcoming and intentionally helpful community. It's hard to emphasize the "intentionally helpful" enough. We don't have much patience for snark. And we're willing to call each other out on being unhelpful.
In my Day Job, we have an in-house Slack channel with well over 1,000 Python folks. The single most common class of questions is a variation on "My Corporate Firewall Setup Doesn't Let Me Use PIP." This is ubiquitous. And confusing. And frustrating for folks who are surprised there is a corporate firewall.
We have a number of pinned answers in Slack for this. And -- perhaps once a week -- someone will patiently repeated the pinned answers for someone who's truly and deeply in over their head trying to get pip to work. (We have an in-house PyPI, also, but it requires doing something in addition to typing `pip install whatever` at the command line, and that can require hand-holding.)
As Python2 winds to a close, and we uncover folks working with Python 2, we have to issue guidance. I've switched tone from "please consider rewriting your app/tool/framework" to "we strongly recommend you start using Python 3." In June, I'm plan to switch to "You have only six months to convert whatever you're working on."
We've had some sidebar conversations on making sure I'm being properly positive, supportive, considerate, and respectful of the folks who think Python2 might be useful.
The point of the Python community is to help each other. We're actively and intentionally trying to be helpful and inclusive.
Technical Sidebar -- Conda and Virtual EnvironmentsWhat about the trickle of people trying to make use of the built-in Python2 in Mac OS X or the Python2 that comes with Linux on a cloud-based server?
Some important coaching: Don't Use The OS Default Python.
This is kind of negative. It helps to state this positively. Always Use A Virtual Environment.
Because we have a *large* community of data scientists, this becomes: Always Use A Conda Environment.
And yes, there are some packages that also require a pip install. And yes, XKCD 1987 describes the consequence of the rapid growth of Python and the variety of ways it can be made to work. (While all the strands of spaghetti look like a negative, they reflect the variety of clever solutions, all of which work without any problems.)
1. conda create --name=working python=3.7 --file conda_install.txt
2. conda activate working
3. python3 -m pip install pip_install.txt
The absolute worst case is a project with two lists of requirements, one in a conda conda_install.txt and some extra stuff in a pip conda_install.txt. We're able to use `python3 -m pip install requirements.txt` for almost everything.
If you're just starting out, you can use miniconda to bootstrap everything else you might need.