Metadata-Version: 2.4
Name: jupyterlab_nvdashboard
Version: 0.14.0
Dynamic: Keywords
Summary: A JupyterLab extension for displaying GPU usage dashboards
Project-URL: Homepage, https://github.com/rapidsai/jupyterlab-nvdashboard
Project-URL: Bug Tracker, https://github.com/rapidsai/jupyterlab-nvdashboard/issues
Project-URL: Repository, https://github.com/rapidsai/jupyterlab-nvdashboard.git
Author: NV Dashboard contributors
License-Expression: BSD-3-Clause
License-File: LICENSE
Classifier: Framework :: Jupyter
Classifier: Framework :: Jupyter :: JupyterLab
Classifier: Framework :: Jupyter :: JupyterLab :: 4
Classifier: Framework :: Jupyter :: JupyterLab :: Extensions
Classifier: Framework :: Jupyter :: JupyterLab :: Extensions :: Prebuilt
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.11
Requires-Dist: jupyterlab>=4.0.0
Requires-Dist: nvidia-ml-py>=12
Requires-Dist: psutil
Requires-Dist: tornado
Provides-Extra: test
Requires-Dist: pytest; extra == 'test'
Requires-Dist: pytest-jupyter[server]>=0.6.0; extra == 'test'
Description-Content-Type: text/markdown

# JupyterLab NVdashboard

NVDashboard is a JupyterLab extension for displaying GPU usage dashboards. It enables JupyterLab users to visualize system hardware metrics within the same interactive environment they use for development. Supported metrics include:

- GPU-compute utilization
- GPU-memory consumption
- PCIe throughput
- NVLink throughput

## Demo

![JupyterLab-nvdashboard Demo](https://raw.githubusercontent.com/rapidsai/jupyterlab-nvdashboard/HEAD/docs/_images/screencast1.gif)

## Table of Contents

- [New Features](#new-features)
  - [Brush for Time Series Charts](#brush-for-time-series-charts)
  - [Synced Tooltips](#synced-tooltips)
  - [Theme Compatibility](#theme-compatibility)
  - [GPU Accelerators](#gpu-accelerators)
- [Version Compatibility](#version-compatibility)
- [Requirements](#requirements)
- [Installation](#installation)
- [Troubleshoot](#troubleshoot)
- [Contributing](#contributing-developers-guide)
- [Future Improvements](#future-improvements)

## New Features

JupyterLab-nvdashboard v4 brings a host of new features, improved backend architecture, and enhanced frontend components for an even better user experience.
Explore the exciting updates below.

### Brush for Time Series Charts

Introducing a powerful brushing feature for time series charts. Users can easily inspect past events by selecting a specific time range, providing more granular control over data exploration.

![JupyterLab-nvdashboard Demo1](https://raw.githubusercontent.com/rapidsai/jupyterlab-nvdashboard/HEAD/docs/_images/screencast2.gif)

### Synced Tooltips

For pages with multiple charts, JupyterLab-nvdashboard now offers synchronized tooltips for timestamps across all charts. This feature enhances the user's ability to analyze data cohesively and understand relationships between different data points.

![JupyterLab-nvdashboard Demo4](https://raw.githubusercontent.com/rapidsai/jupyterlab-nvdashboard/HEAD/docs/_images/screenshot3.png)

### Theme Compatibility

Seamless integration with JupyterLab themes is now a reality. The extension adapts its colors and aesthetics based on whether the user is in a light or dark theme, ensuring a consistent and visually appealing experience.

#### Light Theme

![JupyterLab-nvdashboard Demo3](https://raw.githubusercontent.com/rapidsai/jupyterlab-nvdashboard/HEAD/docs/_images/screenshot2.png)

#### Dark Theme

![JupyterLab-nvdashboard Demo2](https://raw.githubusercontent.com/rapidsai/jupyterlab-nvdashboard/HEAD/docs/_images/screenshot1.png)

### GPU Accelerators

A GPU accelerator activator button that lets you enable GPU-backed execution with **zero code changes**. When active, your existing **pandas** code runs on the GPU (via cudf-pandas), and/or your **scikit-learn** code runs on the GPU (via cuml-accel). Accelerators are shown only when the corresponding dependencies are installed: **cuDF** for pandas acceleration and **cuML** for scikit-learn acceleration.

## Version Compatibility

JupyterLab-nvdashboard v4 is designed exclusively for JupyterLab v4 and later versions.

## Installation

### Conda

```bash
# nightly version
conda install -c rapidsai-nightly -c conda-forge jupyterlab-nvdashboard

# stable version
conda install -c rapidsai -c conda-forge jupyterlab-nvdashboard
```

### PyPI

```bash
# nightly version
pip install --extra-index-url https://pypi.anaconda.org/rapidsai-wheels-nightly/simple 'jupyterlab-nvdashboard>=0.14.0a0'

# stable version
pip install jupyterlab-nvdashboard
```

## Troubleshoot

If you are seeing the frontend extension, but it is not working, check
that the server extension is enabled:

```bash
jupyter server extension list
```

If the server extension is installed and enabled, but you are not seeing
the frontend extension, check the frontend extension is installed:

```bash
jupyter labextension list
```

## Contributing Developers Guide

For more details, check out the [contributing guide](./CONTRIBUTING.md).
