If you need such a package, you can use a virtual machine or a computer with the appropriate operating system. Note that not all packages are pre-packaged for all platforms (or will build on all platforms).
Intel MKL support, which can boost performance. It is preferable to use enpkg/conda, since the packages are often built with things you may not have at home, e.g. If you are using Anaconda, start by using conda and failing that, use pip. If you are using Canopy, start by using enpkg and failing that, use pip.
#Install jupyter notebook mac 2017 mac os x
XCode on Mac OS X or the “Development Tools” option on many Linux distributions or appropriate version of Microsoft Visual Studio and/or MinGW on Microsoft Windows) to use pip.Īll three methods (enpkg, conda, pip) will resolve dependencies. Note that you may need a development toolchain (e.g. Once installed, you can open a terminal and run (*nix/Mac OS X users)įor the current user. We still recommend you install and use Canopy or Anaconda, as the system install of Python will not come with many of the packages we will need for this course and may change depending on operating system updates. If you are a *nix or Mac OS X user, note that your system likely ships with a Python install. You may need you to manually install some packages using the built-in package manager (detailed below). These Python distributions contain most of what you will need for the course.
#Install jupyter notebook mac 2017 how to
We recommend you either install Enthought Canopy with the free academic license or Continuum Anaconda with Python 2 (do not install the Python 3 version or miniconda – they are not suitable for this course if you have the Python 3 version installed, see the Anaconda documentation on how to setup a Python 2 environment).
The /1.6.1 refers to the version of Canopy loaded at time of writing, the default is 1.4.1, and 1.6.1 is the latest available version. You can also install Anaconda to your home directory.
Note that there are occasionally file locking issues with IPython on network shares (or possibly other reasons), so it may be preferable to install Canopy/Anaconda on your home computer rather than use the EWS machines. If it does not, look for output in the terminal for a statement like “The IPython Notebook is running at: (address)” and visit address in your browser (typically You can also use this at home via FastX. After a few seconds, your web browser should open to the IPython/Jupyter Notebook environment.
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