numpy (some of the underlying maths packages have more tuning than pip does) and pip/pipenv for the pure python bits. Historically I used macports for the bootstrap and compile any C libraries e.g. I now use conda as this seems to provide more and is self contained. Just install python, pip and maybe pipenv from this package manager. I think to install pip you need to bootstrap off macports or homebrew, the pipenv page shows homebrew. pip needs to compile those which the others will have a more robust compiler setup and usually will provide a compiled binary. 2.7, 3.7 3.8 in the others you need to use version specific pip for python versions.Īnother difference is in parts of a package that have non python dependencies. This option will install the library into /.local using. To install it using the port package manager, run: sudo port install p圓9-spyder Linux ¶ Spyder can be installed via third-party distro packages on most common Linux distributions. You can install a Python package into your home directory using pip with the -user option. Pip (with pipenv) and conda also provide python virtual environments which basically allow different sets of libraries for each project and allows you to set a different version of python for each project. To install it using the brew package manager, run: brew install -cask spyder It is also available as a a port through MacPorts. It seems to have expanded its scope to cover other languages. There is also conda which is python but does some general purpose stuff as well. Macports and Homebrew are general package managers for all languages. create -n nameofmyenv python activate nameofmyenv nameofmyenv install pandas install pandas0.20.3 install ipython install anaconda install pip. Note things change the last time I really looked at setiups was 3 years ago, I don't think much has changed but pip etc does gain more functionality as time goes on. The easiest way to install Python packages, and OpenSesame plugins/ extensions is through pip, the PyPA-recommended tool for installing Python packages. In general use one package manager at a time.
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