# einteract
> [!WARNING]
> This package has been deprecated and is no longer actively maintained. For improved interactive dashboards within Jupyter and to access future developments, we recommend migrating to [DashLab](https://github.com/asaboor-gh/dashlab).
[](https://asaboor-gh.github.io/einteract-docs/notebooks/index.html?path=einteract.ipynb)
[](https://mybinder.org/v2/gh/asaboor-gh/einteract/HEAD?urlpath=%2Fdoc%2Ftree%2Feinteract-demo.ipynb)
[](https://badge.fury.io/py/einteract)
[](https://pepy.tech/project/einteract)
An enhanced interactive widget that lets you observe any trait of widgets, observe multiple functions and build beautiful dashboards which can be turned into full screen. This is a wrapper library around interact functionality in [ipyslides](https://github.com/asaboor-gh/ipyslides) which also provides rich content representations.
## Installation
You can install einteract using pip:
```bash
pip install einteract
```
Or if you prefer to install from source, clone the repository and in its top folder, run:
```bash
pip install -e .
```
## Interactive Playground
**✨ Try it in your browser ✨**
| Jupyter Lab | Notebook | Binder |
|----|---|--- |
| [](https://asaboor-gh.github.io/einteract-docs/lab/index.html?path=einteract.ipynb) | [](https://asaboor-gh.github.io/einteract-docs/notebooks/index.html?path=einteract.ipynb) | [](https://mybinder.org/v2/gh/asaboor-gh/einteract/HEAD?urlpath=%2Fdoc%2Ftree%2Feinteract-demo.ipynb) |
## Features
- **InteractBase**: Create interactive dashboard applications with minimal code by extending the `InteractBase` class and defining methods with the `@callback` decorator.
- **Custom Widgets**:
- Included custom built widgets for enhanced interaction.
- Pass any DOMWidget as a parameter to `interact/interactive` functions unlike default `ipywidgets.interactive` behavior.
- Observe any trait of the widget by `'widget_name.trait_name'` where `'widget_name'` is assigned to a `widget`/`fixed(widget)` in control parameters, OR `'.trait_name'` if `trait_name` exists on instance of interactive.
- You can use '.fullscreen' to detect fullscreen change and do actions based on that.
- Add `ipywidgets.Button` to hold callbacks which use it as paramter for a click
- **Plotly Integration**: Modified plotly support with additional traits like `selected` and `clicked`
- **HTML support**:
- Any (supported) python object can be converted to html using `hstack` and `vstack` function.
- **JupyTimer**: A non-blocking widget timer for Jupyter Notebooks without threading/asyncio.
- **Event Callbacks**: Easy widget event handling with the `@callback` decorator inside the subclass of `InteractBase` or multiple functions in `interact/interactive` functions.
- **Full Screen Mode**: Transform your dashboards into full-screen applications by added button.
## Usage Example
```python
import numpy as np
import matplotlib.pyplot as plt
import ipywidgets as ipw
import pandas as pd
import plotly.graph_objects as go
import einteract as ei
dash = ei.Dashboard(
fig = ei.patched_plotly(go.FigureWidget()),
html = ipw.HTML('**Select Box/Lesso on figure traces**'),
A = (1,10), omega = (0,20), phi = (0,10),
sdata = 'fig.selected', cdata = 'fig.clicked', fs = '.isfullscreen',
)
@dash.callback('out-click', throttle = 200) # limit click rate by 200 ms
def on_click(cdata,html):
display(pd.DataFrame(cdata or {}))
@dash.callback('out-select')
def on_select(sdata, html):
plt.scatter(sdata.get('xs',[]),sdata.get('ys',[]))
plt.show()
@dash.callback('out-fs')
def detect_fs(fig, fs):
print("isfullscreen = ",fs)
fig.layout.autosize = False # double trigger
fig.layout.autosize = True
@dash.callback
def plot(fig:go.FigureWidget, A, omega,phi): # adding type hint allows auto-completion inside function
fig.data = []
x = np.linspace(0,10,100)
fig.add_trace(go.Scatter(x=x, y=A*np.sin(omega*x + phi), mode='lines+markers'))
dash.set_css({
'.left-sidebar':{'background':'whitesmoke'},
':fullscreen': {'height': '100vh'}}
)
dash.set_layout(
left_sidebar=['A','omega','phi','html','out-main'],
center=['fig','out-click'],
pane_widths=[3,7,0],
)
dash
```
## Comprehensive Examples
- Check out the [einteract-demo.ipynb](einteract-demo.ipynb) which demonstates subclassing `InteractBase`, using custom widgets, and observing multiple functions through the `@callback` decorator.
- See [Bandstructure Visualizer](https://github.com/asaboor-gh/ipyvasp/blob/d181ba9a1789368c5d8bc1460be849c34dcbe341/ipyvasp/widgets.py#L642) and [KPath Builder](https://github.com/asaboor-gh/ipyvasp/blob/d181ba9a1789368c5d8bc1460be849c34dcbe341/ipyvasp/widgets.py#L935) as comprehensive dashboards.
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"description": "\r\n# einteract\r\n\r\n> [!WARNING]\r\n> This package has been deprecated and is no longer actively maintained. For improved interactive dashboards within Jupyter and to access future developments, we recommend migrating to [DashLab](https://github.com/asaboor-gh/dashlab).\r\n\r\n[](https://asaboor-gh.github.io/einteract-docs/notebooks/index.html?path=einteract.ipynb)\r\n[](https://mybinder.org/v2/gh/asaboor-gh/einteract/HEAD?urlpath=%2Fdoc%2Ftree%2Feinteract-demo.ipynb)\r\n[](https://badge.fury.io/py/einteract)\r\n[](https://pepy.tech/project/einteract)\r\n\r\nAn enhanced interactive widget that lets you observe any trait of widgets, observe multiple functions and build beautiful dashboards which can be turned into full screen. This is a wrapper library around interact functionality in [ipyslides](https://github.com/asaboor-gh/ipyslides) which also provides rich content representations. \r\n\r\n\r\n\r\n## Installation\r\n\r\nYou can install einteract using pip:\r\n\r\n```bash\r\npip install einteract\r\n```\r\n\r\nOr if you prefer to install from source, clone the repository and in its top folder, run:\r\n\r\n```bash\r\npip install -e .\r\n```\r\n\r\n## Interactive Playground\r\n**\u2728 Try it in your browser \u2728**\r\n| Jupyter Lab | Notebook | Binder |\r\n|----|---|--- |\r\n| [](https://asaboor-gh.github.io/einteract-docs/lab/index.html?path=einteract.ipynb) | [](https://asaboor-gh.github.io/einteract-docs/notebooks/index.html?path=einteract.ipynb) | [](https://mybinder.org/v2/gh/asaboor-gh/einteract/HEAD?urlpath=%2Fdoc%2Ftree%2Feinteract-demo.ipynb) |\r\n\r\n## Features\r\n\r\n- **InteractBase**: Create interactive dashboard applications with minimal code by extending the `InteractBase` class and defining methods with the `@callback` decorator.\r\n- **Custom Widgets**: \r\n - Included custom built widgets for enhanced interaction. \r\n - Pass any DOMWidget as a parameter to `interact/interactive` functions unlike default `ipywidgets.interactive` behavior.\r\n - Observe any trait of the widget by `'widget_name.trait_name'` where `'widget_name'` is assigned to a `widget`/`fixed(widget)` in control parameters, OR `'.trait_name'` if `trait_name` exists on instance of interactive.\r\n - You can use '.fullscreen' to detect fullscreen change and do actions based on that.\r\n - Add `ipywidgets.Button` to hold callbacks which use it as paramter for a click\r\n- **Plotly Integration**: Modified plotly support with additional traits like `selected` and `clicked`\r\n- **HTML support**: \r\n - Any (supported) python object can be converted to html using `hstack` and `vstack` function.\r\n- **JupyTimer**: A non-blocking widget timer for Jupyter Notebooks without threading/asyncio.\r\n- **Event Callbacks**: Easy widget event handling with the `@callback` decorator inside the subclass of `InteractBase` or multiple functions in `interact/interactive` functions.\r\n- **Full Screen Mode**: Transform your dashboards into full-screen applications by added button.\r\n\r\n## Usage Example\r\n\r\n```python\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport ipywidgets as ipw\r\nimport pandas as pd\r\nimport plotly.graph_objects as go\r\nimport einteract as ei\r\n\r\ndash = ei.Dashboard(\r\n fig = ei.patched_plotly(go.FigureWidget()), \r\n html = ipw.HTML('**Select Box/Lesso on figure traces**'),\r\n A = (1,10), omega = (0,20), phi = (0,10),\r\n sdata = 'fig.selected', cdata = 'fig.clicked', fs = '.isfullscreen',\r\n)\r\n@dash.callback('out-click', throttle = 200) # limit click rate by 200 ms\r\ndef on_click(cdata,html):\r\n display(pd.DataFrame(cdata or {}))\r\n\r\n@dash.callback('out-select')\r\ndef on_select(sdata, html):\r\n plt.scatter(sdata.get('xs',[]),sdata.get('ys',[]))\r\n plt.show()\r\n\r\n@dash.callback('out-fs')\r\ndef detect_fs(fig, fs):\r\n print(\"isfullscreen = \",fs)\r\n fig.layout.autosize = False # double trigger\r\n fig.layout.autosize = True\r\n\r\n@dash.callback\r\ndef plot(fig:go.FigureWidget, A, omega,phi): # adding type hint allows auto-completion inside function\r\n fig.data = []\r\n x = np.linspace(0,10,100)\r\n fig.add_trace(go.Scatter(x=x, y=A*np.sin(omega*x + phi), mode='lines+markers'))\r\n\r\ndash.set_css({\r\n '.left-sidebar':{'background':'whitesmoke'},\r\n ':fullscreen': {'height': '100vh'}}\r\n)\r\ndash.set_layout(\r\n left_sidebar=['A','omega','phi','html','out-main'], \r\n center=['fig','out-click'], \r\n pane_widths=[3,7,0],\r\n)\r\n\r\ndash\r\n```\r\n\r\n\r\n## Comprehensive Examples\r\n- Check out the [einteract-demo.ipynb](einteract-demo.ipynb) which demonstates subclassing `InteractBase`, using custom widgets, and observing multiple functions through the `@callback` decorator.\r\n- See [Bandstructure Visualizer](https://github.com/asaboor-gh/ipyvasp/blob/d181ba9a1789368c5d8bc1460be849c34dcbe341/ipyvasp/widgets.py#L642) and [KPath Builder](https://github.com/asaboor-gh/ipyvasp/blob/d181ba9a1789368c5d8bc1460be849c34dcbe341/ipyvasp/widgets.py#L935) as comprehensive dashboards.\r\n\r\n\r\n",
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