JupyterLab
Overview
JupyterLab is an interactive development environment used to create, run, and manage computational work, mainly in Python.
It provides access to notebooks, terminals, and files through a web interface.
Getting Started
- Access the JupyterLab web interface or install it locally
- Log in to the neurethic server if required
- Navigate the file system using the interface
- Open or create notebooks and other files
- Select the appropriate kernel and start working
Key Concepts
- Workspace: The interface where you organize notebooks, files, and tools.
- Notebook integration: JupyterLab allows you to create and edit notebook files (.ipynb).
- Kernel: The engine that executes code (e.g., Python).
- Remote server: A machine that runs computations remotely.
- File browser: Interface to manage project files and directories.
Main Uses
- Access and use remote computing resources
- Create and manage Jupyter Notebooks
- Run Python scripts and analyses
- Organize project files and workflows
Why It Matters
- Provides a unified environment for development and computation
- Enables the use of powerful remote machines
- Centralizes files, notebooks, and tools in one interface
- Supports reproducible and organized workflows
When You Will Use It
- Accessing the lab’s computational resources
- Creating or editing notebooks
- Running data analysis or heavy computations
- Managing project files remotely
Good Practices
- Keep files and folders well organized
- Use clear naming conventions for notebooks and scripts
- Shut down unused kernels to free resources
- Regularly save your work