get python version jupyter with code examples

In this article, we will discuss how to get the version of Python in Jupyter. Jupyter is an open-source web-based interactive environment that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. It is often used for data science and scientific computing.

The easiest way to get the version of Python in Jupyter is to use the sys module. The sys module provides information about the Python interpreter and its environment. To get the version of Python in Jupyter, you can use the sys.version attribute.

import sys
print(sys.version)

This will output the version of Python that is currently being used by Jupyter. For example, if you are using Python 3.8, the output will be 3.8.x.

Another way to get the version of Python in Jupyter is to use the platform module. The platform module provides information about the underlying platform, such as the version of Python. To get the version of Python in Jupyter, you can use the platform.python_version() function.

import platform
print(platform.python_version())

This will output the version of Python that is currently being used by Jupyter. For example, if you are using Python 3.8, the output will be 3.8.x.

You can also use the !python3 -V command in Jupyter Notebook.

!python3 -V

This will give the version of python3 installed on your system.

In addition to these methods, you can also use the !pip show <package_name> command in Jupyter Notebook to check the version of a specific package.

!pip show pandas

This will give you the version of pandas package installed on your system.

In conclusion, there are several ways to get the version of Python in Jupyter, such as using the sys module, the platform module, or by using the command line. Each method has its own advantages, but they all provide the same information.

In addition to getting the version of Python in Jupyter, there are also several other useful features and tools that can be used in Jupyter. One such feature is the ability to create and run Jupyter notebooks.

A Jupyter notebook is a web-based interactive environment that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. To create a new Jupyter notebook, you can use the jupyter notebook command in the command line. This will open a new browser window with the Jupyter interface, where you can create a new notebook by clicking the "New" button and selecting "Python 3" as the kernel.

Once you have created a new notebook, you can begin to enter code and run it by clicking the "Run" button or by pressing Shift+Enter. You can also add text and markdown to your notebook to provide additional context and explanations for your code.

Another useful feature in Jupyter is the ability to use magic commands. Magic commands are special commands that are prefixed with a % symbol and are used to perform various tasks, such as running shell commands, controlling the environment, and more. For example, the %run magic command can be used to run a Python script within a Jupyter notebook.

%run my_script.py

In addition to these features, Jupyter also has a wide variety of useful extensions that can be installed to add additional functionality. Some popular extensions include the ability to add a table of contents, spell checker, and the ability to use interactive widgets. To install an extension, you can use the !pip install command in a Jupyter notebook or terminal.

!pip install jupyter_contrib_nbextensions

Jupyter also offers the ability to use interactive widgets, which allows you to create interactive visualizations and user interfaces within a Jupyter notebook. One popular library for creating interactive widgets is the ipywidgets library. To use this library, you will need to install it and then import it into your notebook.

!pip install ipywidgets
import ipywidgets as widgets

In conclusion, Jupyter is a powerful tool for data science and scientific computing. In addition to getting the version of Python, it offers a wide variety of features and tools, such as creating and running Jupyter notebooks, using magic commands, installing useful extensions, and using interactive widgets. These features and tools can help you to be more productive and efficient when working with data and code in Jupyter.

Popular questions

1. How can I get the version of Python in Jupyter?

• You can use the sys.version attribute or the platform.python_version() function to get the version of Python in Jupyter.

2. How do I create a new Jupyter notebook?

• To create a new Jupyter notebook, you can use the jupyter notebook command in the command line. This will open a new browser window with the Jupyter interface, where you can create a new notebook by clicking the "New" button and selecting "Python 3" as the kernel.

3. What are magic commands in Jupyter and what can they be used for?

• Magic commands in Jupyter are special commands that are prefixed with a % symbol and are used to perform various tasks, such as running shell commands, controlling the environment, and more.

4. How can I install and use interactive widgets in Jupyter?

• To use interactive widgets in Jupyter, you will need to install the ipywidgets library and import it into your notebook. You can then use the widgets in the library to create interactive visualizations and user interfaces within your Jupyter notebook.

5. How do I check the version of a specific package in Jupyter?

• You can use the !pip show <package_name> command in Jupyter Notebook to check the version of a specific package. For example, to check the version of the pandas package, you can use the command !pip show pandas.

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Python