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https://github.com/deephaven/deephaven-ipywidgets

Deephaven Community IPython Widget Library
https://github.com/deephaven/deephaven-ipywidgets

Last synced: 27 days ago
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Deephaven Community IPython Widget Library

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README 

        
# deephaven-ipywidgets



Deephaven Community IPython Widget Library



## Installation



You can install using `pip`. 



If running with the embedded server (`deephaven-server`), install with the following:

```shell

pip install "deephaven-ipywidgets[server]"

```

This installs the embedded server.



If connecting to a server running elsewhere (`pydeephaven`), install with the following:

```bash

pip install "deephaven-ipywidgets[client]"

```



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

the nbextension:



```bash

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

```



## Usage



### Starting the server



First, if you are using the embedded server, you'll need to start the [Deephaven server](https://github.com/deephaven/deephaven-core/blob/d73ef01cdf6fda43f7d03110995add26d16d4eae/py/embedded-server/README.md).



```python

# 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:



```python

# 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:



```python

# Specify a size for the table

display(DeephavenWidget(t, width=100, height=250))

```



### Connecting to a Remote Server



If you are using the client to connect to an already running server, create a `pydeephaven` session.

See the [pydeephaven documentation](https://deephaven.io/core/docs/tutorials/pyclient-quickstart/) for more information.

```python

from pydeephaven import Session



client_session = Session(

    host="deephaven.local",

    port=10000,

    auth_type="io.deephaven.authentication.psk.PskAuthenticationHandler",

    auth_token="YOUR_PASSWORD_HERE",

)

```



### Displaying Tables from a Remote Server



The session can be used to create objects such as tables on the server and then display them in the widget.

```python

t = client_session.time_table("PT1s")

from deephaven_ipywidgets import DeephavenWidget

display(DeephavenWidget(t))

```



You can also reference objects already created on the server. This code assumes a table named `t` exists on the server.

```python

display(DeephavenWidget("t", session=client_session))

```



### 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`.



```python

import os

os.environ["DEEPHAVEN_IPY_URL"] = "http://localhost:1234"

```



## Development Installation



Before starting, you will need [python3](https://www.python.org/downloads/), [node](https://nodejs.org/en/download/), and [yarn](https://classic.yarnpkg.com/lang/en/docs/install/) installed.



Create and source a dev python venv environment:



```bash

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



```bash

source .venv/bin/activate

```



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



```bash

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.



```bash

JAVA_HOME=/Library/Java/JavaVirtualMachines/openjdk-11.jdk/Contents/Home

```



2. Create a new notebook (.ipynb) or open an existing notebook file (such as [example.ipynb](./example.ipynb))

3. 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.



```bash

# 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 the `eslint` tests. Then run `yarn 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:

  ```bash

  npm login

  npm publish

  ```

- Install publish dependencies:



```bash

pip install build twine

```



- Build the assets and publish

  ```bash

  python -m build .

  twine check dist/*

  twine upload dist/*

  ```

- Tag the release commit (`git tag `)

- 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` and `git push --tags`.