This is a Python plugin for Deephaven generated from a deephaven-plugin template.
This is an experimental plugin that can create and embed simple jupyter notebooks within deephaven. It cannot show more complex resources like ipywidgets at this time.
The src directory contains the Python and JavaScript code for the plugin.
Within the src directory, the deephaven_plugin_notebook directory contains the Python code, and the js directory contains the JavaScript code.
The Python files have the following structure:
deephaven_plugin_notebook_object.py defines a simple Python class that can wrap a notebook
deephaven_plugin_notebook_type.py defines the Python type for the plugin (which is used for registration) and a simple message stream.
js_plugin.py defines the Python class that will be used to setup the JavaScript side of the plugin.
register.py registers the plugin with Deephaven.
The JavaScript files have the following structure:
DeephavenPluginNotebookPlugin.ts registers the plugin with Deephaven.
DeephavenPluginNotebookView.tsx defines the plugin panel and loads the notebook.
Additionally, the test directory contains Python tests for the plugin. This demonstrates how the embedded Deephaven server can be used in tests.
It's recommended to use tox to run the tests, and the tox.ini file is included in the project.
To build the plugin, you will need npm and python installed, as well as the build package for Python.
nvm is also strongly recommended, and an .nvmrc file is included in the project.
The python venv can be created and the recommended packages installed with the following commands:
cd deephaven_plugin_notebook
python -m venv .venv
source .venv/bin/activate
pip install --upgrade -r requirements.txtBuild the JavaScript plugin from the src/js directory:
cd src/js
nvm install
npm install
npm run buildThen, build the Python plugin from the top-level directory:
cd ../..
python -m build --wheelThe built wheel file will be located in the dist directory.
If you modify the JavaScript code, remove the build and dist directories before rebuilding the wheel:
rm -rf build distThe plugin can be installed into a Deephaven instance with pip install <wheel file>.
The wheel file is stored in the dist directory after building the plugin.
Exactly how this is done will depend on how you are running Deephaven.
If using the venv created above, the plugin and server can be created with the following commands:
pip install deephaven-server
pip install dist/deephaven_plugin_notebook-0.0.1.dev0-py3-none-any.whl
deephaven serverSee the plug-in documentation for more information.
After the initial setup, you can call
./rebuild.shwhich will reinstall and run the server.
Once the Deephaven server is running, the plugin should be available to use.
from deephaven_plugin_notebook import DeephavenPluginNotebookObject
obj = DeephavenPluginNotebookObject()Here is a simple example that uses dh.ui to make a simple notebook with input.
There are two cell types that reflect the two main jupyter cell types. Any "code" blocks are ran automatically, sequentially.
from deephaven_plugin_notebook import DeephavenPluginNotebookObject
from ipywidgets import IntSlider
import deephaven.ui as ui
def render_notebook(text):
notebook = [
{
"type": "markdown",
"source": "Hello, World!"
},
{
"type": "code",
"source": f"print('{text}')"
}
]
return DeephavenPluginNotebookObject(notebook)
@ui.component
def demo():
text, set_text = ui.use_state("Hello, World!")
print_input = ui.text_field(value=text, on_change=set_text)
rendered_notebook = ui.use_memo(lambda: render_notebook(text), [text])
return ui.flex(print_input, rendered_notebook, direction="column", width="100%")
notebook_input = demo()The function render_notebook could also be ran on it's own if not using dh.ui
To distribute the plugin, you can upload the wheel file to a package repository, such as PyPI.
The version of the plugin can be updated in the setup.cfg file.
There is a separate instance of PyPI for testing purposes. Start by creating an account at TestPyPI. Then, get an API token from account management, setting the “Scope” to “Entire account”.
To upload to the test instance, use the following commands:
python -m pip install --upgrade twine
python -m twine upload --repository testpypi dist/*Now, you can install the plugin from the test instance. The extra index is needed to find dependencies:
pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ deephaven_plugin_notebookFor a production release, create an account at PyPI. Then, get an API token from account management, setting the “Scope” to “Entire account”.
To upload to the production instance, use the following commands.
Note that --repository is the production instance by default, so it can be omitted:
python -m pip install --upgrade twine
python -m twine upload dist/*Now, you can install the plugin from the production instance:
pip install deephaven_plugin_notebookSee the Python packaging documentation for more information.