npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

deephaven-ipywidgets

v0.1.0

Published

Deephaven ipython widget library

Downloads

2

Readme

deephaven-ipywidgets

Deephaven Community IPython Widget Library

Installation

You can install using pip:

pip install deephaven-ipywidgets

If you are using Jupyter Notebook 5.2 or earlier, you may also need to enable the nbextension:

jupyter nbextension enable --py [--sys-prefix|--user|--system] deephaven-ipywidgets

Usage

Starting the server

First you'll need to start the Deephaven server.

# Start up the Deephaven Server
from deephaven_server import Server
s = Server(port=8080)
s.start()

Display Tables

Pass the table into a DeephavenWidget to display a table:

# Create a table and display it
from deephaven import empty_table
t = empty_table(1000).update("x=i")
display(DeephavenWidget(t))

You can also pass in the size you would like the widget to be:

# Specify a size for the table
display(DeephavenWidget(t, width=100, height=250))

Development Installation

Before starting, you will need python3, node, and yarn installed.

Create and source a dev python venv environment:

export JAVA_HOME=/Library/Java/JavaVirtualMachines/openjdk-11.jdk/Contents/Home
python3 -m venv .venv
source .venv/bin/activate
pip install --upgrade pip setuptools
pip install deephaven_server jupyter jupyterlab jupyter-packaging

After initial installation/creation, you can just do

source .venv/bin/activate

Install the python. This will also build the TS package.

pip install -e ".[test, examples]"

When developing your extensions, you need to manually enable your extensions with the notebook / lab frontend. For lab, this is done by the command:

jupyter labextension develop --overwrite .
yarn run build

For classic notebook, you need to run:

jupyter nbextension install --sys-prefix --symlink --overwrite --py deephaven_ipywidgets
jupyter nbextension enable --sys-prefix --py deephaven_ipywidgets

Note that the --symlink flag doesn't work on Windows, so you will here have to run the install command every time that you rebuild your extension. For certain installations you might also need another flag instead of --sys-prefix, but we won't cover the meaning of those flags here.

For running in VS Code, you need to run the classic notebook steps, as well as set up the VS Code environment:

  1. Create a .env file with your JAVA_HOME variable set, e.g.
JAVA_HOME=/Library/Java/JavaVirtualMachines/openjdk-11.jdk/Contents/Home
  1. Create a new notebook (.ipynb) or open an existing notebook file (such as example.ipynb)
  2. In the notebook, make sure your .venv Python environment is selected - either use the dropdown menu in the top right, or hit Ctrl + P then type > Select Kernel and select the Notebook: Select Notebook Kernel option and choose .venv.

How to see your changes

Typescript:

If you use JupyterLab to develop then you can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the widget.

# Watch the source directory in one terminal, automatically rebuilding when needed
yarn run watch
# Run JupyterLab in another terminal
jupyter lab

After a change wait for the build to finish and then refresh your browser and the changes should take effect.

Python:

If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.