![]() Pythonista ( ) for the iPhone and iPad and now also the new Computable ( ) which brings the iPython Notebook interface plus numpy, sympy, pandas, etc. If you’re an iOS user, there are a couple great Python environments there too. 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. I now do basically all my calculation and ad-hoc computing in support of my development work inside Notebooks. 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. ![]() 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).Īnaconda installs in a single directory and makes it easy to have multiple versions and multiple python versions installed. 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). It just works, and it gives you everything you need on all three major platforms to do virtually anything out of the box. Install the Anaconda build, preferably 32 bit (as some libraries aren’t available for 64 bit, and you will get library clashes).Īnaconda might be the most powerful (and free!) software package for general end-user computing that there is. Stop struggling with Python on Windows. Avoid distributions with fancy install methods (I’m looking at you, ActiveState). If there is no Conda package, try pip, and then compiling from source (but never use easy_install). To install new packages, first try to use Conda install. But it’s a lot better than anything out there, and the only one I would recommend, at least on Windows Uninstalling it is easy and works.Ĭonda isn’t perfect, as I couldn’t get its environment system to work. Second, it does not put important stuff in hidden folders (as far as I can see). For one, it comes with all the scientific libraries like numpy, scipy etc preinstalled, so you don’t have to worry about messing with compiling them yourself. Recently, I discovered Anaconda, and that’s what I recommend now.īased on the open source Conda packaging system, Anaconda is the best Python distribution I have found till now. Why am I telling you this? To show you how hard getting Python running can be on Windows. I had to reinstall ActiveState Python, remove the libraries, and then uninstall it again. The path to Python libraries must have been put in the registry or something, because even when I deleted the folders, it still looked for them in the Roaming folders. I finally realised that ActiveState was to blame. I blamed Conda and spent weeks investigating obtuse error messages. Anyway, even after installing a different Python build (from Conda, see below), I kept getting library clashes which I couldn’t trace. These libraries take precedence over the local files (maybe due it being higher on the path hierarchy). I decided to re-install Python, and that’s when I hit problems.įor some stupid reason, ActiveState install libraries in the C:\users\\roaming\ region. ![]() But then I tried to install OpenCv, and got problems with versions. It also makes it easy to install packages, and for a long time, this is what I used. The version from ActiveState: ActiveState have a version of Python, and it’s a lot more stable than the official version. I didn’t find it very stable, and even installing basic things like Virtualenv gave me problems.Ģ. The official from : Especially on Windows, this is good only for learning. Here are some of the few Python versions I’ve tried:ġ. For my upcoming course on Python, I needed a lot of third party libraries, and I found that Python’s packaging system is really broken. All I meant was, in this day and age, it’s a shame there is no good packager for Python on Windows).īut I found that as soon as you try to do anything more complicated, like install libraries which need to be compiled (like numpy or scipy), the official build starts falling down. It is not, and I apologise if it came out that way. (Note: Lots of people have taken the previous sentence as an insult. ![]() If you plan to just stick to solving Project Euler or other such toy problems, then the official site is good enough. “But Mr T,” you say, “what’s the problem? You go to and just download it. If you have every tried to use Python beyond toy problems on Windows, you will have struggled with library clashes, 32/64 bit versions, ghost libraries (that seemed to be installed, but can’t be called).Īs someone who uninstalled and reinstalled Python eight times in the last four weeks, let me tell you, getting Python working perfectly on Windows isn’t easy. ![]()
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