Check python version jupiter notebook

Python how to check version in jupyter notebook

Here are some step that user must follow to get its current running version of the python interpreter:- Open cmd/terminal/windows powershell Write ‘python’ and press enter key to move into python interpreter Write the same command given in the input box below, and in the result, the user will get the current interpreter version. For this method, the user must open the Python shell and write the following command as given below, with this command the user will get the current working version of the python interpreter in the form of a string.

Check the Version of the Python Interpreter

Under this article, we will get to know the current version of python interpreter in the system. Getting the version of the interpreter is really important as the python interpreter is widely used throughout the industries for computer programming and source coding. It takes an interactive command and executes it.

As the interpreter is the one which takes the code and helps in execution. Sometimes due to the old version of the interpreter making command doesn’t work properly and as we know the language python comes with frequent update vision with some added new features, so the user must update the interpreter with the latest release version.

To get the Version of the python Interpreter; They are listed as follows:

• Using sys.version method
• Using python_version() function
• Using python -V command

1. Using sys.version method:

For this method, the user needs to import the sys library and from sys.version command which will return the user’s current python version in the use. For this method, the user must open the Python shell and write the following command as given below, with this command the user will get the current working version of the python interpreter in the form of a string.

Here are some step that user must follow to get its current running version of the python interpreter:-

1. Open cmd/terminal/windows powershell
2. Write ‘python’ and press enter key to move into python interpreter
3. Write the same command given in the input box below, and in the result, the user will get the current interpreter version.

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How to Check Python Version in Jupyter Notebook: Ultimate Guide

Learn different methods to check Python version in Jupyter Notebook and how to change it if needed. Explore how to check Jupyter Notebook version, change kernel, and use Python 3.10 in Jupyter Notebook.

• How to Check the Python Version in Jupyter Notebook
• How to Check the Version of Jupyter Notebook
• Check Python Version From Jupyter Notebook
• How to Change the Python Version in Jupyter Notebook
• How to Change the Kernel in Jupyter Notebook
• How to Check the Python Version Used in Jupyter Notebook
• How to Check the Version of a Python Package in Jupyter Notebook
• Using Python 3.10 in Jupyter Notebook
• Additional Helpful Examples for Checking Python Version in Jupyter Notebook
• Conclusion
• What version of Python does Jupyter Notebook use?
• How to check the version of Python?
• How do I use Python 3.10 in Jupyter Notebook?

Python is a powerful programming language that is widely used in various fields such as data science, web development, and machine learning. Jupyter Notebook is a popular tool for data analysis and visualization, which allows users to write and execute Python code in a web-based environment. In this blog post, we will explore different methods for checking the Python version in Jupyter Notebook and how to change it if needed.

How to Check the Python Version in Jupyter Notebook

To check the Python version in Jupyter Notebook, there are multiple ways to do it. One way is to use the command !python —version in a code cell, which will display the installed Python version. Another way is to use the command import sys; print(sys.version) in a code cell, which will display more detailed information about the installed Python version. It is important to note that the commands for checking the Python version may vary depending on the operating system.

For example, to check the Python version on a Windows machine, open the command prompt and type python —version . This will display the installed Python version. Alternatively, you can type python to open the Python interpreter and then type import sys; print(sys.version) to display more detailed information about the installed Python version.

How to Check the Version of Jupyter Notebook

To find the version of Jupyter Notebook, use the command !jupyter —version in a code cell. This will display the version number of Jupyter Notebook installed on your system.

Check Python Version From Jupyter Notebook

This video talks about, how one can Check Python Version from Jupyter Notebook.Watch out Duration: 0:43

How to Change the Python Version in Jupyter Notebook

To change the Python version in Jupyter Notebook, it is recommended to use virtualenv and start Jupyter inside it. First, create a virtual environment for the desired Python version using the command virtualenv -p /path/to/python/version env_name . Then, activate the virtual environment using the command source env_name/bin/activate . Finally, start Jupyter Notebook inside the virtual environment using the command jupyter notebook . This will ensure that Jupyter Notebook is using the desired Python version.

Another way to change the Python version in Jupyter Notebook is to use Conda environments. To create a new Conda environment for the desired Python version, use the command conda create —name env_name python=X.X where X.X is the desired version of Python. Then, activate the Conda environment using the command conda activate env_name . Finally, start Jupyter Notebook using the command jupyter notebook . This will ensure that Jupyter Notebook is using the desired Python version.

How to Change the Kernel in Jupyter Notebook

To change the kernel in Jupyter Notebook, click on the “Kernel” tab, then select “Change kernel” and choose the desired Python version. This will change the kernel used by Jupyter Notebook to the selected Python version.

How to Check the Python Version Used in Jupyter Notebook

To check the Python version used in Jupyter Notebook, use the command !python -V in a code cell. This will display the Python version used by Jupyter Notebook.

How to Check the Version of a Python Package in Jupyter Notebook

To check the version of a Python package, use the command !pip show package_name in a code cell. This will display the package version installed in the Python environment used by Jupyter Notebook.

Using Python 3.10 in Jupyter Notebook

The latest version of Python is Python 3.10, and to use it in Jupyter Notebook, it is recommended to create a new Conda environment. First, create a new Conda environment for Python 3.10 using the command conda create —name env_name python=3.10 . Then, activate the Conda environment using the command conda activate env_name . Next, register the Conda environment with IPython using the command python -m ipykernel install —user —name env_name —display-name «Python 3.10» . Finally, start Jupyter Notebook using the command jupyter notebook , and select the “Python 3.10” kernel.

Additional Helpful Examples for Checking Python Version in Jupyter Notebook

In python, get python version jupyter code example

from platform import python_versionprint(python_version())

In python, check package version jupyter python code example

import packagename print(packagename.__version__)

In python, python version command notebook code example

import platform print(platform.python_version())

In python, find python version in jupyter notebook code example

from platform import python_versionprint(python_version()) 

Conclusion

Checking and changing the python version in jupyter notebook is an essential task for users who work with different Python versions. There are multiple ways to check the Python version in Jupyter Notebook, and each method has its advantages and disadvantages. Changing the Python version in Jupyter Notebook can be done using virtualenv or Conda environments, depending on the user’s preference. It is important to keep the Python environment up to date with the latest security patches and bug fixes to ensure a smooth workflow. By following these simple steps, users can easily check and change the Python version in Jupyter Notebook, enabling them to work with different versions of Python and take advantage of the latest features and improvements.

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Check python version jupiter notebook

Last updated: Apr 13, 2023
Reading time · 3 min

# How to check your Python version in Jupyter Notebook

The easiest way to check your Python version in Jupyter Notebook is to:

1. Import the python_version method from the platform module.
2. Call the python_version() method to print the Python version as a string.

Start Jupyter Notebook by issuing the jupyter-notebook command from your terminal.

Click on New and select Python 3 (ipykernel).

Now, import the python_version method from the platform module and call it.

Copied! 
from platform import python_version print(python_version()) 

Once you import and call the method, click on the Run button or press Ctrl + Enter .

The screenshot shows that my Python version is 3.11.3.

The code sample imports the python_version method from the platform module.

Unlike the sys.version attribute, the string always contains the patch component (even if it’s 0 ).

If you have virtual environments that you are trying to switch to from within Jupyter Notebook:

1. Click on Kernel.
2. Hover over Change kernel.
3. Select your virtual environment.

If you encounter any issues when switching virtual environments, restart the kernel.

If you need to create a new virtual environment in Jupyter Notebook, follow the instructions in this article.

# Check your Python interpreter in Jupyter Notebook using the sys module

You can use the sys module if you need to check your Python interpreter in Jupyter Notebook.

Copied! 
import sys print(sys.executable) # 👉️ /usr/bin/python3.11 

The sys.executable attribute returns the absolute path of the executable binary of the Python interpreter.

If Python can’t determine the path to the interpreter, then sys.executable returns an empty string or a None value.

There is also a sys.version attribute that returns a string containing:

• the version number of the Python interpreter
• additional information about the build number and the compiler

Copied! 
import sys print(sys.executable) # /usr/bin/python3.11 # 👇️ 3.11.3 (main, Apr 5 2023, 14:14:37) [GCC 11.3.0] print(sys.version) # 👇️ sys.version_info(major=3, minor=11, # micro=3, releaselevel='final', serial=0) print(sys.version_info) 

The sys.version_info attribute returns a tuple that contains five components of the version number:

All components except for the release level are integers.

The release level component can be one of the following:

You can access specific tuple elements at an index.

Copied! 
import sys # 👇️ sys.version_info(major=3, minor=11, # micro=3, releaselevel='final', serial=0) print(sys.version_info) print(sys.version_info[0]) # 3 print(sys.version_info[1]) # 11 print(sys.version_info[2]) # 3 print(sys.version_info[3]) # final 

# Using the !python —version command to check your version

You can also use the !python —version command to check your Python version in Jupyter Notebook.

Copied! 
!python --version # same as above !python -V 

The !python -V command is an alias of the !python —version command.

Notice that the command is prefixed with an exclamation mark.

This is necessary when issuing the command in a Jupyter cell.

The exclamation mark ! is used to run a shell command in Jupyter.

You can use the !jupyter —version command if you need to check your Jupyter version.

# Using the menu to check your Python version in Jupyter Notebook

You can also use the Help menu to check your Python version in Jupyter Notebook:

• The version of the notebook server
• The Python version that is run in Jupyter Notebook
• Additional information about the current kernel

If you encounter issues when checking your version, try restarting the kernel.

# Additional Resources

You can learn more about the related topics by checking out the following tutorials:

I wrote a book in which I share everything I know about how to become a better, more efficient programmer.

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