由于Python版本的变化很少，我总是忘记我是如何用最新的Python为Jupyter Notebook创建了一个新的Conda环境的，所以我想我应该把它列出来，以便下次使用。从StackOverflow中，有一些答案不再起作用，下面是我在StackOverflow上找到的命令的汇编，这些命令对我来说是有效的，2022年11月29日。下面的这些指令是针对Windows的，和使用Powershell（尽管它们也可以用于普通的命令行cmd.exe）

# make sure you are in the base env

    # update conda
    conda update conda

    # to allow support for powershell
    conda init --all

    # The conda-forge repository seems to have at least the latest
    # stable Python version, so we will get Python from there.
    # add conda-forge to channels of conda.
    conda config --add channels conda-forge

    conda update jupyter
    # to fix 500 internal server error when trying to open a notebook later
    pip3 install --upgrade --user nbconvert

    # nb_conda_kernels enables a Jupyter Notebook or JupyterLab
    # application in one conda environment to access kernels for Python,
    # R, and other languages found in other environments.

    conda install nb_conda_kernels

    # I will now create a new conda env for Python 3.11 and name it as Python3.11
    conda create -n python3.11 python=3.11

    # check that it was created
    conda info --envs

    conda activate python3.11

    # Once installed, need to install ipykernel so Jupyter notebook can
    # see the new environment python3.11. 
    conda install -n python3.11 ipykernel

    # install ipywidgets as well for some useful functionalities 
    conda install -n python3.11 ipywidgets

    # Since I use R too, I'll also add a note here on R
    # To utilize an R environment, it must have the r-irkernel package; e.g.
    # conda install -n r_env r-irkernel

    # example to install a package in the new env, if desired
    # conda install --update-all --name python3.11 numpy

    #conda list will show the env's packages, versions, and where they came from too
    conda activate python3.11
    conda list
    conda deactivate

    # Now to check if the new environment can be selected in Jupyter
    # Notebook.  I change to the root directory first so jupyter 
    # notebook can see every folder.  Note that we are in base
    # environment, although no problem if in another environment 
    cd\
    jupyter notebook

    # If I open an existing notebook for example, I can tap on Kernel,
    # then Change kernel, and I should now be able to select the kernel
    # from the new environment I created, shown as "Python [conda env:python3.11]".
    #
    # There will also be another entry showing just the name of the env,
    # in this case, python3.11.  Just ignore this, select the entries
    # starting with "Python [conda env" ...   
    # 
    # If I tapped on New instead when Jupyter Notebook opened, it will
    # also show the list of envs. 

    # to check version, either use :
    !python --version

    # or

    from platform import python_version
    print(python_version()) 

    # both will show the Python version of whatever kernel is in use
    # by Jupyter notebook

    # to test Python 3.10 or 3.11 for example... from 3.10, an optional
    # strict parameter for zip has been added and can be used to
    # generate an error if lists' lengths are not the same

    a = [1,2,3,4]
    b = ['a', 'b', 'c']
    for val1, val2 in zip(a,b, strict = True):
        print(val1, val2)
    
    # this should appear - ValueError: zip() argument 2 is shorter than argument 1

还有别的办法吗？