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I am learning Python, and I saw Dive Into Python and it looks cool and all, but it was released in 2004. So, what I am wondering is if Python 2.x has changed enough since 2004 that Dive Into Python has become so obsolete. And are there any more recent online textbooks like that for Python that can get me to become an awesome programmer?
Well, there is Dive Into Python 3...
Dive Into Python 3 covers Python 3 and its differences from Python 2. Compared to Dive Into Python, it’s about 20% revised and 80% new material.
There's a new version of Dive into Python that focuses on 3.x.
No, it is not obsolete. It is still a good resource which can teach you effective python programming.
You might also like to read Dive Into Python 3 by the same author, as he adapts the book for the python3 language.
Switch over to Dive into Python 3
Also see, What's new in Dive into Python 3 ?
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I'm trying to 'learn me some python packaging,' but keep getting bogged down in all the different ways of doing things. So far I have encountered setuptools, easy-install, requirements.txt, setup.py, poetry, and just now I found out about something called PEAK ("python enterprise application kit"). Regarding the latter: is this even still relevant? The website appears to be from about 2004. Looks comprehensive, but I don't want to invest a bunch of time assimilating a methodology that is outdated.
P.S. I do not care about Python 2.X, as I am only using Python 3.7+. So that might be another factor.
I never heard of it. Found this site http://peak.telecommunity.com/ where it appears after 13 years of silence. Package PEAK on PyPI was not updated since 2004. Last realse looks to be made By Phillip J. Eby Thursday, 01 May, 2003 And
this at the end of release note
You can also find current and in-development source code at Github.
links to https://github.com/PEAK-Legacy/. So I would to assume it's dead except maybe some inner developmnet at some corporation
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I have begun programming and I have faced a dilemma that do I need to learn everything about a particular language or do i need to learn the main concepts
It's impossible to learn literally everything about a programming language. Using python for example, there are so many packages, and new ones packages are being developed every week, nobody knows them all. It's more important to know the main concept. If you're using python for data science, for example, you'll need to know Numpy, pandas, matplotlib, scikit learn as your basics.
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I never went too far into NetLogo, and being a novice in Python I started looking into the turtle module, aiming towards ABM. I have seen some simple implementations of the turtle module (turtledemo and YouTube) but none were comparable to NetLogo library's examples. I went over (once) the mesa tutorials and it seemed interesting but, as it says, more advanced stuff require Javascript. I've also read that NetLogo is fast to pick up.
Considering the above, and adding your own experience, could NetLogo be a better choice than Python? Could you estimate how hard each path would be? Do you have any other suggestions?
I teach ABM. I used to use Python for my course,
using a module that provides some NetLogo-like functionality:
https://raw.githubusercontent.com/alan-isaac/econpy/master/abm/gridworld/gridworld.py
I gave that up. Although Python is a great language for
teaching programming, NetLogo is a much better language for
teaching ABM. (Both started out as teaching languages,
very roughly speaking, and became much more.) It is very
easy to get started with NetLogo. It's builtin facilities
also support very sophisticated model building. These facilities
can be extended when needed.
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I'm returning Python developer. I was working with 2.7 last time. And i want to read full list of new things and changes in 3.3 since 2.7. Does anyone know something good?
PS: Yeah, i know that there it is for me in the documentation, but i want a single article with some author's thoughts about these changes.
http://docs.python.org/3/whatsnew/3.0.html
This article explains the new features in Python 3.0, compared to 2.6.
I found this pdf very informative. It is a free 4-page cheat sheet of differences provided by the publisher of "Programming in Python 3" book by Mark Summerfield.
In response to your PS, this is not an article, but a very easy to grasp categorized list of differences.
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What datastructures should a junior python developer study first?
UPDATE:
I mean common datastructures, not python list, dict and tuple...
The best reference for learning python is the python standard library itself. As for data structures, if you want to go deeper than the standard python type, you can study the collections module. Have a look at the docs and see how it is implemented.
For instance with IPython, you can access the documentation of any object or module by appending "?" and the code by appending "??" (without the quotes).
To go beyond the standard library you can explore PyPI which is the Python package Index, a repository of community contributed Python modules.
Pick packages with high weights and not marked alpha if possible.
For instance, on data structures you have :
http://pypi.python.org/pypi/data-structures/0.1.2
http://pypi.python.org/pypi/structures/0.5
I think that looking at real code is the best to learn real programming.