- Introduction on How to Open a Jupyter Notebook using command line in CMD App
- Installing and Execute Jupyter Notebook using a script and How to Launch it:
- Using the Command Line:
- Troubleshooting The Jupyter Notebook Interface
Introduction on How to Open a Jupyter Notebook using command line in CMD App
Jupyter Notebook is a popular web application that allows users to create and share documents that contain live code, equations, visualizations, and narrative or interactive text. It's widely used for data analysis or output, scientific computing, and machine learning, among other things.
While Jupyter can be launched through a graphical user interface (GUI), opening it from the command line can be more efficient and convenient, especially for advanced users. This tutorial will explain how to launch Jupyter from the command prompt on different operating systems, including Windows, macOS, and Linux.
This will be a good summary for you to learn how to modify, set up and enable Jupyter on your computer. Whether you're a beginner or an experienced software user, learning how to use the command line to launch Jupyter Notebook app can save you time and help you streamline your workflow.
Read through this whole module, and it will make your life easier.
Installing and Execute Jupyter Notebook using a script and How to Launch it:
Before you can open the notebook in the terminal, you must install it on your computer. If you don't already have it installed, you can follow these steps to install it:
First, make sure you have Python installed on your computer. It requires Python 3.3 or greater, but it's recommended to use Python 3.6 or later as we will use Python code.
launch a terminal or command prompt window on your computer.
Type the following command to install Jupyter Notebook using pip (Python's package manager):
pip install jupyter
Depending on your system configuration, you may need to run the command with administrator privileges (e.g. using sudo on Linux or macOS).
Once the installation is complete, you can verify that it is installed by typing the following command:
jupyter notebook --version
- This should display the version number of Jupyter that is installed on your computer.
That's it! Once it is installed, you can proceed to the next section to learn how to open it from the command line.
Using the Command Line:
Once Jupyter Notebook is installed on your computer, you can open it from the command line by following these steps:
Open a terminal or command prompt window on your computer.
Navigate to the directory where you want to create or open a Jupyter Notebook. You can use the
cdcommand to change directories. For example, if you want to create a new Notebook in a directory called "my_notebooks", you would navigate to that directory by typing:
Once you're in the correct directory, type the following command to start Jupyter Notebook:
This should launch Jupyter Notebook in your default web browser. If your browser doesn't launch automatically, you can manually navigate to
http://localhost:8888/treeon your browser.
From here, you can create a new Notebook by clicking the "New" button in the upper right corner of the screen or launch an existing Notebook by clicking on its filename.
When you finish using Jupyter Notebook, you can stop the server by returning to the command prompt window and pressing
That's it! By using the command line to launch Jupyter Notebook, you can quickly create and edit Notebooks without navigating through menus or using a graphical user interface.
Troubleshooting The Jupyter Notebook Interface
Launching Jupyter Notebook from the command line is usually straightforward, but you may encounter some issues along the way. Here are some common problems and solutions:
"Command not found" error: If you receive this message that says "jupyter: command not found", it means that Jupyter Notebook is not in your system's PATH environment variable. To fix this, you can add the directory where Jupyter Notebook is installed to your PATH variable. Alternatively, you can specify the full location to the
jupyterexecutable when you run the command.
Port already in use error: If you see this message that says "Port 8888 is already in use", it means that another process on your computer is already using that port. To fix this, you can either stop the other process (if you know what it is) or specify a different port when you start Jupyter Notebook. For example, you can use the command
jupyter notebook --port 8889to start the server on port 8889 instead.
"SSL error" when using HTTPS: If you're trying to access Jupyter Notebook using HTTPS and you receive a message that says "SSL error", it may mean that your browser is not trusting the self-signed SSL certificate that Jupyter Notebook generates by default. To fix this, you can either use HTTP instead of HTTPS or add the certificate to your browser's trusted certificates list.
Notebook not appearing in browser: If you start Jupyter Notebook from the command line but the Notebook doesn't appear in your browser, it may mean that your browser is not compatible with Jupyter Notebook. Make sure you're using a modern, up-to-date browser like Chrome, Firefox, or Safari.
Other issues: If you encounter other issues when launching Jupiter Notebook from the command line, you can search online for solutions or ask for help on forums like Stack Overflow or the Jupyter community forums.
You can quickly get back to using Jupyter Notebook from the command line without too much hassle by troubleshooting common issues like these.
Launching Jupyter Notebook from the command line is a powerful way to quickly create and edit Notebooks without having to navigate through menus or use a graphical user interface. By following the steps outlined in this article, you can install Jupyter Notebook on your computer and start using it from the command line in just a few minutes.
Remember, if you encounter any issues along the way, don't be afraid to search online for solutions or ask for help on forums like Stack Overflow or the Jupyter community forums. With a little troubleshooting, you can quickly get back to using Jupyter Notebook and enjoy its many benefits for data science, machine learning, and more.