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You describe my experience about 9 months ago! I’ve become so frustrated I am now getting myself a Mac – I have issues with Ruby, PHP and Node on Windows as well. The main program installers work without much bother but as soon as you start playing with third party libraries you will get issues. I’ve not tried Anaconda but I’ve just had a look and it has an impressive set of libraries out the box, I’ll try it out. You might want to have a look at this site (if you haven’t already): It’s an impressive up to date list of Windows binaries for Python packages and I’ve installed a few with good results! Regards, Matt 😉. Many people struggle, but there is a macho attitude in the community “Just be a big boy and get on with it”, which is why I decided to write this post.
Spyder is a powerful scientific environment written in Python, for Python,. Edit a dateframe or Numpy array, sort a collection, dig into nested objects,. Of our supported platforms is to download it as part of the Anaconda distribution,.
It’s not just a Python issue- as you mention, other frameworks, most notably Ruby have had problems as well. I was looking at a job posting by a famous company for Ruby developers, and the advert basically said “You must be good with Linux, as Ruby doesn’t work on Windows” (their words, not mine).
Yes, I’ve seen that link, even tried a few libraries from it. While they work, my problem is the same: I’d rather have a centralised package manager than having to install/uninstall libraries from a dozen locations. That’s what I like about Conda. It makes it easier to manage once you have more than a dozen libraries. I did try Linux but I find you have to do a fair bit of heavy lifting with it. For example, Node has a Mac installer (and Windows) but you have to build it with Linux. That’s fine for a production server but when you want to tinker around with stuff (as I do) it gets a bit inconvenient.
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I use C# a lot and building that on Linux is a mission – on a Mac it just works out the box. Because Windows and Mac aren’t free means they get targeted for the professional dev tools. I know there are some lovers of Linux out there and I’m not knocking you! Anaconda might be the most powerful (and free!) software package for general end-user computing that there is. It just works, and it gives you everything you need on all three major platforms to do virtually anything out of the box. I too recommend: for those Windows things you might need that are not available as conda packages (like Postgres and MySQL database drives to go with SQL Alchemy). The installers from there integrate well with anaconda (it will find all Python environments registered on the machine, let you pick one, and then install into the correct places).
Anaconda installs in a single directory and makes it easy to have multiple versions and multiple python versions installed. It comes with the Spyder IDE, and all the iPython stuff, including what’s probably the most impressive component of the Python eco-system these days, the iPython Notebook interface. I now do basically all my calculation and ad-hoc computing in support of my development work inside Notebooks. Honestly everyone who does any form of “computing” using their computer needs to have the anaconda system, and Python is the #1 language/tool to learn because you can do and drive basically anything and everything with it. If you’re an iOS user, there are a couple great Python environments there too. Pythonista for the iPhone and iPad and now also the new Computable which brings the iPython Notebook interface plus numpy, sympy, pandas, etc.
An interesting article and I recognise some of the challenges of Python on Windows but have to say that it doesn’t accord with my experience. I’ve found the ActiveState 32bit Python 2.7 to be stable and with pypm it is trivial to install 95% of what I need – matplotlib, numpy, scipy, ipython, pandas, nmap, etc, etc. OpenCV was easy to install too – the install instructions on the website work perfectly – you do read the instructions, don’t you?
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П˜‰ If you really want a command line package manager for the OS you can always install Chocolatey. I’ve spent many years working with various Linux distros too and could write a similar article on the challenges posed by that OS. The time I’ve spent getting CUPS to work with my printer easily outweighs any time spent fiddling with Windows to get Python to work nicely. I think that it’s quite realistic to develop with Python on Windows or.nix but you should expect in either OS that you sometimes have to get under the hood in order to get things to work! Thanks for the post! I’ve been programming on both pylin and pywin for a number of few years now, bouncing between machines, vms, oses, and ides, virtualenvs / enviros for different projects.
And yeah, it’s an elephant in the room for a mostly love-blinded python convert from 10 or so years back, but I’ve kinda gotten used to the open-pit-toilet of the std pywin experience. If my primary win box ever gains enough space i’ll be sure to give ana a crack, like I should have some time ago. But when you’re walking over a spaghetti bridge high above a croc-infested-turd-river filled with sharp rocks, the changes happen slowly and carefully. П˜‰ Oh, and yes, your point is well made. Just because i do have wizard powers (including lightning from fingers) and have gotten through all the hellish hurdles to make things work, that doesn’t make me a clever-clogs because so little of the struggle was time well spent. Rather, it was time spent being an I-can’t-let-things-go-nerd, to my own detriment. Shame, Mr Impractial-pants, shame.
Hi all, i came here because I had a strange situation when working on anaconda with windows. At first everything worked perfectly but since i created a separate virtual env and loaded it to run a separate code from terminal in this new environment, I have been having issues running code on jupyter notebook. I was just not able to read a simple hdf file that returned a value error but the point is I cannot comprehend what happened and now after uninstalling and reinstalling anaconda, I am still having the same problem. I also noticed that after uninstalling anaconda, I still have the anaconda folder in my directory.
I want to know if it is safe to manually delete it?