I was using the Anaconda 3.5distro in a Windows 10 machine. Due to dependencies in libraries that I want to work with, I had to have the 2.7 version installed as well.

The good news is that the libraries I needed can now work with the 2.7 version smoothly and Visual Studio 2015 automagically detected my new Python environment.

The problem comes when using the command line. Upon issuing the command

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I get

i.e. a single environment (to my understanding and search so far, according to this I should see two envs listed). This means I can't use conda to acquire new packages for my Python3.5 installation, at least not at the command line as I used to since conda only refers to Python2.7. The same goes for the GUI version, Anaconda navigator (I'm not very fond of the GUI version but I tried it out).

There's also no way of launching python3 from the command line since

always fires up python2.7 and issuing $python3 or $python3.5 in the command line doesn't seem to work (nor would adding the path of python3 to the system since the actual executable has the same name as python2 i.e. python.exe)

Is my system taken over by Python2.7? Is anyone here using them both smoothly and if so could you please elaborate on how to do that? Was it a 'no no' move to install both versions of Anaconda?

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3 Answers

You can make Python 3.5 environment with your Anaconda 2.7:

Now, activate it:

Finally you can install the desired packages:

or, the whole anaconda:

Adobe reader for windows 7 official site. The advantage of this approach is that you can also create Python 3.4 or 3.6 environments. Furthermore, you can create environments with different combinations and versions of libraries.

Actually, it makes sense to create a new environment for each larger project.

I also despise the virtual environment switch that Anaconda tries to force on us. I prefer to have both executables always instantly available from the command line. I'm pretty sure I had this working on a Windows machine once:

1. Install Anaconda2 and Anaconda3 to the C: drive as 'C:Anaconda2' and 'C:Anaconda3' respectively.
2. Edit your 'Path' environment variable (Control Panel -> System and Security -> System -> Advanced system settings -> Environment Variables) and make sure that 'C:Anaconda2;C:Anaconda2Scripts;C:Anaconda2Librarybin' is in front of 'C:Anaconda3;C:Anaconda3Scripts;C:Anaconda3Librarybin'.
3. Copy and rename the file 'C:Anaconda3python.exe' to 'C:Anaconda3python3.exe'.
4. Copy and rename the file 'C:Anaconda3Scriptsconda.exe' to 'C:Anaconda3Scriptsconda3.exe'
5. Copy and rename any other scripts you might use in 'C:Anaconda3Scripts', such as 'pip.exe' to 'pip3.exe', etc.

Now, when you type 'python' or 'conda' at the command line you will get the python2 version, and when you type 'python3' or 'conda3', etc. at the command line you will get the python3 version.

The best way to use both Python 2.7x and Python 3.5x together is Jupyter Notebook.

You will be able to work on your browser with IPython Notebook style interface which is great for working with scripting languages.

I found some of these videos on YouTube very informative:

1) https://www.youtube.com/watch?v=HW29067qVWk

2) https://www.youtube.com/watch?v=e9cSF3eVQv0

Besides Python 2.7 and 3.5, there are a bunch of other languages that you will be able run with your Jupyter Notebook. The various Kernels are available in this link below:

After installation, as you start your Jupyter Notebook, your browser will open up a new page showing your Home Directory. Among the 4 tabs (Files Running Clusters Conda):

1) The Files tab shows all the files in your Home Directory.

2) Running tab shows all the Notebooks that are running.

3) Clusters tab is provided by IPython parallel.

4) Conda tab is where you need to add the Python version 3.5 (and other languages if needed) to your Jupyter Notebook (If Python 2.7 is default).

If you are interested to try C++ with your Jupyter Notebook, there are a couple of Kernels available.

1) JupyRoot - https://github.com/root-mirror/root/tree/master/bindings/pyroot/JupyROOT

2) Cling - https://github.com/root-mirror/cling

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