I currently have scikit-learn 0.19 installed. I'd like to test my code using the latest development version as there seems to be a fix for Incremental PCA.
How do I go about installing this new version if I've previously installed scikit-learn using anaconda?
Also, how would I revert back to the stable release in the event that 0.20 does not solve my problem?
I am in need of some hand holding here, as I've read the docs on the website and not sure I completely understand the process (especially being able to revert back to the stable version if needed).
The whole point of the Anaconda Python distribution (apart from the convenience of having a bunch of useful packages included) is that you get the conda
environment manager, which exists to meet exactly this sort of requirement.
What you want to do is to create a new conda environment by launching the Anaconda prompt and typing
conda create -n myenv scikit-learn other-package other-package2 etc
where myenv
is the name you want to give the new environment and other-package other-package2 etc
are the names of any other packages you will want to use (import) in your code. conda will figure out any dependencies of these packages and show you a list of what is going to be installed before it proceeds.
If you want to specify that a package should be a particular version, add that to the package name eg other-package=1.1.0
, otherwise conda will install the latest versions of each package that are mutually compatible. You can also specify a particular version of Python by including it in the package list, eg python=3.4
. You can check what versions of a package are available with conda search package-name
(where package-name is the name of the package you want, obviously).
To run your code in the newly created environment, first activate
the environment at the Anaconda prompt. If you use the Spyder IDE, launch it after activating the correct environment, or use the start menu shortcut specific to that environment if you have one. Other IDEs may have their own method of selecting a specific environment to work in.
To revert to the version(s) you were using before, activate
the environment containing those versions - if you've never created a new environment before, that'll be root
.
Just in case someone comes here looking for a solution without conda
:
The website recommends that you download the latest code via
git clone git://github.com/scikit-learn/scikit-learn.git
and then include it in pip via (after changing to the directory)
pip install --editable .
You can also add the --user
flag to have pip
install to a local directory. Then, uninstalling should be as easy as pip uninstall sklearn
.
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