![]() They are mostly simple and intuitive, however any help is always useful.Ĥ. Assuming that you have installed anaconda from above, use this cheat sheet to familiarise yourself with the common commands. To make life easy add a link to the anaconda command prompt on your desktop for ease of access.ģ. You can have both Python 3 and Python 2.7 running on your machine if you want to make things more complex (see xkcd cartoon above) – but unless you have to, don’t. Why? The Python 2.7 clock is ticking – don’t get caught out in 2020 as 2.7 will no longer be maintained. Use the link below to download.Īnaconda comes with a whole heap of useful stuff including Jupyter Notebook and Spyder (an interactive development environment).Ģ. I have found, if you are completely starting from scratch, that anaconda is the best place to start. This post is a series of steps to how I would set up Python 3 today, with Windows 10 as my operating system. There will be a second post that will give an introduction to Jupyter Notebooks. This blog post is for anyone who is new to programming with Python. If you have not used Python before and you are looking to get started here are a few recommendations to get you up and running. If you find it valuable, I would really appreciate it if you could spread the word and recommend it to others.I have written a lot in the past about using Python for GIS and Earth Observation. If you are looking for a way to support me and my work, consider purchasing one of my books or subscribing to the paid version of my free AI newsletter. Twitter and LinkedIn where I share more content related to machine learning and AI. If you liked this article, you can also find me on Should I use Python 2 or Python 3 for my development activity?ġ0 awesome features of Python that you can’t use because you refuse to upgrade to Python 3Įverything you did not want to know about Unicode in Python 3 Here is a list of some good articles concerning Python 2 and 3 that I would recommend as a follow-up. More articles about Python 2 and Python 3 # In Python 3, the range() was implemented like the xrange() function so that a dedicated xrange() function does not exist anymore ( xrange() raises a NameError in Python 3). However, in contrast to 1-time iterations, it is not recommended if you repeat the iteration multiple times, since the generation happens every time from scratch! Thanks to its “lazy-evaluation”, the advantage of the regular range() is that xrange() is generally faster if you have to iterate over it only once (e.g., in a for-loop). The behavior was quite similar to a generator (i.e., “lazy evaluation”), but here the xrange-iterable is not exhaustible - meaning, you could iterate over it infinitely. The usage of xrange() is very popular in Python 2.x for creating an iterable object, e.g., in a for-loop or list/set-dictionary-comprehension. TypeError: Can't convert 'bytes' object to str implicitly > 1 'note that we cannot add a string' + b'bytes for data' TypeError Traceback (most recent call last) For example, if we want Python 3.x’s integer division behavior in Python 2, we can import it via ![]() It is recommended to use _future_ imports it if you are planning Python 3.x support for your code. Python 3.x introduced some Python 2-incompatible keywords and features that can be imported via the in-built _future_ module in Python 2.
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