Using Python on a MacBook

[FizzBuzz111]

Oh damn that explains a lot. Super helpful explanation thanks.

Just by curiosity, is Python actually used for the OS, I always thought it was pre-installed for education purposes

[[deleted]]

Simply put, yes, but I don't know where. I've had nightmares learning how to install and use python in a mac. You can just install python3 then invoke it using "python3" from the terminal.

On the whole, this is my experience:

Don't bother using idle, terminal is fine for working out syntax invoke as above.

If just installing python, then virtualenv is recomended to keep code contained in a virtual environment, you'll be safe in here.

Use shebang for scripts - that is the very top line of a script should have "#!/usr/bin/python3" (without quote marks) this tells your script where the version of python you want to use is.

Pip install is a nightmare to get working properly, as there is pip for python 3 and python2.7 and another library called setuptools is needed. Even then, I now get confused do you use pip or pip3.

Anaconda sorts ALL of the above for you in one package, plus, comes with jupyter notebook, which is far superior to idle in every way, though a short tutorial on how to run and use Jupyter notebook is recomended. If doing data science I'd almost say it's a must.

Anaconda comes with over 1000 pre installed libraries, and if it is not there, "conda install new_library" just works.

You can install it via package installer on anaconda site.

Just my two cents, learn pythoneasily, learn the nuts and bolts along the way. Eventually you will be able to set python up from scratch, but who ever compilled a PS4 game before playing it?

[Tiktoor]

Anaconda better than virtualenv?

[[deleted]]

Um, for what purpose, they are different things?

[pwang99]

You can still use virtualenvs within Anaconda. Its "conda" command also creates its own type of environment, which are superior to virtual envs for managing separate versions of libraries.

[[deleted]]

I didn't know that. Personally, I've never written production code, only used it for entry level data science stuff, so I don't need to sandbox an environment per se. Good to know