In that case, I would just remove Anaconda installation from the path, delete folder and re-install. The fact that a full explanation took so many words and touched so many concepts, I think, indicates a real usability issue for the Jupyter ecosystem, and so I proposed a few possible avenues that the community might adopt to try to streamline the experience for users. . I think this warning leads to confusion. For Python kernels, this will point to a particular Python version, but Jupyter is designed to be much more general than this: Jupyter has for languages including Python 2, Python 3, Julia, R, Ruby, Haskell, and even C++ and Fortran! So it's not a full solution to the problem by any means, but if Python kernels could be designed to do this sort of shell initialization by default, it would be far less confusing to users:! I was using conda 4. But that leaves us in an undesireable place, as it increases the learning curve for novice users who may want to do something they rightly presume should be simple: install a package and then use it.
I have a few ideas, some of which might even be useful: Potential Changes to Jupyter As I mentioned, the fundamental issue is a mismatch between Jupyter's shell environment and compute kernel. Just launch a fresh command prompt, type conda info --envs, and the base env will show with an asterisk, meaning it's the current one and, I assume, is thus activated. In that case, I would just remove Anaconda installation from the path, delete folder and re-install. After proposing some simple solutions that can be used today, I went into a detailed explanation of why these solutions are necessary: it comes down to the fact that in Jupyter, the kernel is disconnected from the shell. For many users, the choice between pip and conda can be a confusing one.
When the installation is complete, use which to verify the location of the main binary: which python3 python3 -V The output of the above command should be similar to: Check Python Version in Linux To exit the Python prompt, simply type. Fundamentally the problem is usually rooted in the fact that the Jupyter kernels are disconnected from Jupyter's shell; in other words, the installer points to a different Python version than is being used in the notebook. If you are using older Windows version than Windows 10 and latest system updates are not installed, might be also required. The root of the issue is this: the shell environment is determined when the Jupyter notebook is launched, while the Python executable is determined by the kernel, and the two do not necessarily match. I had the same issue. But if the base env is not activated by default, then conda info --envs should be amended not to show the asterisk for the base env, unless it is explicitly activated. So I don't know how to do it.
A Jupyter kernel is a set of files that point Jupyter to some means of executing code within the notebook. Install Anaconda Download Anaconda from. But if they are implemented carefully, I think it would lead to a much nicer overall user experience. The reason is simple: this allows us to have the latest stable release of the language 3. Have a question about this project? We can see this by printing the sys. I'm not too familiar with the current build-recipes in use.
How can I install cvxpy with conda and python 3. In the simplest contexts this issue does not arise, but when it does, debugging the problem requires knowledge of the intricacies of the operating system, the intricacies of Python package installation, and the intricacies of Jupyter itself. In this case pip install will install packages to a path inaccessible to the python executable. . Is that what is proposed? For day-to-day Python usage, you should isolate your packages from the system Python, using either or — I personally prefer conda for this, but I know many colleagues who prefer virtualenv. Ah, well your conda thing is probably a different issue.
There is no uninstall step. You need to activate the base env like any other. To preserve my Environments, I shared each environment as 'environment. You can try removing offending packages like this: conda remove argcomplete conda-manager Sometime this will keep showing new offending packages. I know the new version of conda is a big win , but it I'm not ready for it yet if it's going to give me strange errors like: 'python' is not recognized as an internal or external command, operable program or batch file. Install packages if they are available.
Doing this can have bad consequences, as often the operating system itself depends on particular versions of packages within that Python installation. Reply to this email directly, view it on GitHub , or mute the thread. I always assumed that if I launch Python interpreter without activating any environment, it would use the base env by default. So, could we massage kernel specifications such that they force the two to match? A: If the import fails on Windows, make sure you have Visual C++ redistributable 201x menstion above choose according to your python version installed. I currently have Python 3. One thing should keep in mind that , the supported package of numpy an opencv for specific version of python is important to match.
But When I used Python version 3. This is why a simple! This issue is a perrennial source of StackOverflow questions e. The version I downloaded is 2018. Reply to this email directly, view it on GitHub , or mute the thread. How your operating system locates executables When you're using the terminal and type a command like python, jupyter, ipython, pip, conda, etc.
I'm trying to upgrade to Python 3. Details how to do it: — Mar 26 '18 at 17:45. Have a question about this project? You are likely to overwrite packages maintained by your system package manager yum, apt, etc. But When I used Python version 3. Note If you followed the instructions to install a Python 3 environment, you can skip this section. It is about creating a Python 3 environment when your default environment is Python 2.