Поменять версию python в jupiter

Change Python Version for Jupyter Notebook

Three ways to do it- sometimes package dependencies force analysts and developers to require older versions of Python use conda to downgrade Python version (if Anaconda installed already) conda install python=3.5.0 Hat tip- http://chris35wills.github.io/conda_python_version/ https://docs.anaconda.com/anaconda/faq#how-do-i-get-the-latest-anaconda-with-python-3-5 2. you download the latest version of Anaconda and then make a Python 3.5 environment. To create the new environment for Python 3.6, … Continue reading “Change Python Version for Jupyter Notebook”

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Changing the Python version Jupyter uses

Sometimes you want to change the version of Python that Jupyter is using! Often this is because you want to make your command-line python command match the version that Jupyter is using.

Jupyter doesn’t use the PATH variable to figure out which Python to use, it uses specific settings called kernels. As a result, if you upgrade or change Pythons on the command line, Jupyter might still be stuck in the past!

You can read more about how this causes libraries to go missing, but we’re just going to jump into changing it here. Our process is only three quick steps:

1. Confirm our Python version
2. Install the ipykernel package for managing Jupyter settings
3. Use ipykernel to change our default Jupyter

 $ python --version Python 3.10.0 $ python -m pip install ipykernel $ python -m ipykernel install --user Installed kernelspec python3 in /Users/soma/Library/Jupyter/kernels/python3

This kernel or kernelspec is the settings file that Jupyter uses to figure out what Python it should point to. Now it’s updated, so everything should work great! Shut down your Jupyter notebook server, start a new one, and you’ll be good to go.

When I say “shut down your Jupyter notebook server,” I don’t mean close your notebook tab: that isn’t enough! You need to actually turn off and restart the entire Jupyter server. Use Ctrl+C to shut it down from the command line.

Double-checking the kernel installed correctly

If we’re nosy or suspicious, we could actually look at the kernel’s details. Read the last line of the output to see where the kernelspec (kernel specification) lives:

$ python -m ipykernel install --user Installed kernelspec python3 in /Users/soma/Library/Jupyter/kernels/python3

The settings are stored in a file called kernel.json inside of this folder. To check up on the details, we can use the cat command.

 $ cat /Users/soma/Library/Jupyter/kernels/python3/kernel.json  "argv": [ "/Users/soma/.pyenv/versions/3.10.0/bin/python", "-m", "ipykernel_launcher", "-f", "" ], "display_name": "Python 3 (ipykernel)", "language": "python", "metadata":  "debugger": true > >

The important part here is /Users/soma/.pyenv/versions/3.10.0/bin/python — that’s the exact Python file that Jupyter will be running!

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Русские Блоги

Поскольку Anaconda3 поставляется с Python3 (этот пример 3.7.5) в каталоге установки, откройте jupyter, по умолчанию будет ядро ​​Python 3 (которое было изменено на py3).

Проверьте, что его номер версии 3.7.5

———————————————-Разделительная линия— ———————————————

Что если вам нужно установить другую версию python, такую ​​как python3.6.5 (также возможно python2.7, не выгружайте ее снова после ее установки), и вам нужно использовать эту версию python в jupyter?

Step by step:

1 Сначала откройте терминал подсказки Anaconda3, введите

Посмотреть установленную версию Python

2 Создайте виртуальную среду py3.6.5, установите эту версию python в каталог env anaconda3

conda create --name py3.6.5 python=3.6.5 

3 cmd в каталог py3.6.5 (подойдет cmd, поставляемый с windows), введите

(Установка Baidu без pip-инструментария) В каталоге скриптов будет создан ряд инструментов

4 Найдите здесь, сделайте копию существующего проекта, переименуйте в python3.6.5

Открыть, чтобы изменить, как показано ниже

5 Вы сделали

Открыть Jupyter

ввод

import sys print(sys.version) 

Посмотреть используемый номер версии Python

Справочный блог:
https://www.cnblogs.com/wayland/p/10938756.html

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How do I change which Python is used? #169

How do I change which Python is used? #169

Comments

My apologies if this is not specific to Jupyterlab App.

in a notebook within Jupyterlab App, when I run:

I would like it to return
‘/usr/local/anaconda3/bin/python’

How do I specify which python Jupyterlab App uses?

The text was updated successfully, but these errors were encountered:

On MacOS, I can add new kernels by adding them to the ~/Library/Jupyter/kernels folder (https://jupyter-client.readthedocs.io/en/stable/kernels.html)

Environments should be built with repo2docker or at least REES: Reproducible Execution Environment Specification IMHO. That adds a container system dependency, but it’s cross platform and reproducible.

I put together some notes for an «nbhandler» app awhile back:
westurner/nbhandler#1

Launch a notebook server locally from a link or a downloaded file; like BinderHub for the desktop

[. ] https://github.com/machine-learning-apps/repo2docker-action is a GitHub Action that runs repo2docker and uploads to dockerhub. This is useful for projects that don’t need to be built by end users if there’s already an image to just pull

To discover local conda envs, nb_conda_kernels works. From https://github.com/Anaconda-Platform/nb_conda_kernels :

nb_conda_kernels
This extension enables a Jupyter Notebook or JupyterLab application in one conda environment to access kernels for Python, R, and other languages found in other environments. When a kernel from an external environment is selected, the kernel conda environment is automatically activated before the kernel is launched. This allows you to utilize different versions of Python, R, and other languages from a single Jupyter installation.

The package works by defining a custom KernelSpecManager that scans the current set of conda environments for kernel specifications. It dynamically modifies each KernelSpec so that it can be properly run from the notebook environment. When you create a new notebook, these modified kernels will be made available in the selection list.

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Jupyter lab: how to use different versions of Python

If you have jupyter notebook, but you do not have jupyter lab, you can install it like this:

from the windows 10 command line or Powershell.

Once you installed it, you can run Jupyter lab from any folder, writing in powershell:

Then, something like this will appear.

How to use a different version of Python in Jupyter lab

Jupyter lab, evolution of Jupyter notebook is a great tool to use Python code inside the browser, with a lot of enhancement that you can use to join coding in Python with markdown and with the chance to use html and also javascript inside the same page to better explain what you are doing with the code. It is a sort of IDE inside the browser that can also show inside the page widgets, graphics from matplotlib, tables from pandas etc.

Running different version on Python in Jupyter lab

You could have different versions of Python on your computer. If you do not do anything, Jupyter lab will run the default version of Python. Let’s say there is a new version of Python and you install it, making it the default one. If you need to run a different, older, version of Python in Jupyter Lab, you can do write the code that you see in the next image.

On my computer, for example, I have the version 3.6 (as default version) and also the new 3.7 version. Here is an example of use of the new dataclassee in Python 3.7, that I can’t use in versio 3.6.

%%script C:\Users\Utente\AppDAta\Local\Programs\Python\Python37\python.exe from dataclasses import dataclass @dataclass class Data: name: str age: int def printData(self): print(f'I am ') print(f'My age is ') a1 = Data("John", 35) a1.printData()

Video

Here is the video that shows you how to start different version of Python in Jupyter lab.

%

New features in Python 3.6

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