@deephaven/ipywidgets
v0.4.0
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Deephaven ipython widget library
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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 on port 8080 with token `iris`
from deephaven_server import Server
s = Server(port=8080, jvm_args=["-Dauthentication.psk=iris"])
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
from deephaven_ipywidgets import DeephavenWidget
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))
Alternate Deephaven Server URL
By default, the Deephaven server is located at http://localhost:{port}
, where {port}
is the port set in the Deephaven server creation call. If the server is not there, such as when running a Jupyter notebook in a Docker container, modify the DEEPHAVEN_IPY_URL
environmental variable to the correct URL before creating a DeephavenWidget
.
import os
os.environ["DEEPHAVEN_IPY_URL"] = "http://localhost:1234"
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:
- Create a
.env
file with yourJAVA_HOME
variable set, e.g.
JAVA_HOME=/Library/Java/JavaVirtualMachines/openjdk-11.jdk/Contents/Home
- Create a new notebook (.ipynb) or open an existing notebook file (such as example.ipynb)
- In the notebook, make sure your
.venv
Python environment is selected - either use the dropdown menu in the top right, or hitCtrl + P
then type> Select Kernel
and select theNotebook: 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.
Testing your changes
There are separate test suites for the python and TypeScript code.
- Python: To run the python tests, run
pytest
in the root directory of the repository. - TypeScript: To run the TypeScript tests, run
yarn run lint:check
in the root directory of the repository to run theeslint
tests. Then runyarn run test
to run the rest of the unit tests.
Releasing your initial packages:
- Add tests
- Ensure tests pass locally and on CI. Check that the coverage is reasonable.
- Make a release commit, where you remove the
, 'dev'
entry in_version.py
. - Update the version in
package.json
- Relase the npm packages:
npm login npm publish
- Install publish dependencies:
pip install build twine
- Build the assets and publish
python -m build . twine check dist/* twine upload dist/*
- Tag the release commit (
git tag <python package version identifier>
) - Update the version in
_version.py
, and put it back to dev (e.g. 0.1.0 -> 0.2.0.dev). Update the versions of the npm packages (without publishing). - Commit the changes.
git push
andgit push --tags
.