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|
%global _empty_manifest_terminate_build 0
Name: python-jupyter-plotly-dash
Version: 0.4.3
Release: 1
Summary: Interactive Jupyter use of plotly dash apps
License: MIT
URL: https://github.com/GibbsConsulting/jupyter-plotly-dash
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/70/9c/020dd6bad01e4ecbdcdb1c92af68b831774cb06f2276f892bc3cb358278b/jupyter-plotly-dash-0.4.3.tar.gz
BuildArch: noarch
Requires: python3-aiohttp
Requires: python3-django-bootstrap4
Requires: python3-django-plotly-dash
Requires: python3-dpd-components
Requires: python3-dpd-static-support
Requires: python3-jupyter
Requires: python3-nbserverproxy
%description
# jupyter-plotly-dash
[](https://badge.fury.io/py/jupyter-plotly-dash)
[](https://img.shields.io/pypi/dw/jupyter-plotly-dash.svg)
[](https://coveralls.io/github/GibbsConsulting/jupyter-plotly-dash?branch=master)
[](https://jupyter-plotly-dash.readthedocs.io/en/latest/?badge=latest)
Allow use of [plotly dash](https://plot.ly/products/dash/) applications within Jupyter notebooks, with the management of both session and internal state.
See the source for this project here:
<https://github.com/GibbsConsulting/jupyter-plotly-dash>
Try me here in your browser: [](https://mybinder.org/v2/gh/GibbsConsulting/jupyter-plotly-dash/master)
More detailed information
can be found in the online documentation at
<https://readthedocs.org/projects/jupyter-plotly-dash>
## Installation
Install the package. Use of a `virtualenv` environment is strongly recommended.
pip install jupyter_plotly_dash
Now the package is installed, it can be used within a Jupyter notebook.
## Simple use
After installation, launch a python Jupyter notebook server using `jupyter notebook` or `jupyter lab` as desired. Create a `Dash` application, using
the `JupyterDash` class instead of `dash.Dash` for the application, and copy the following into a code cell and evaluate it.
```python
from jupyter_plotly_dash import JupyterDash
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
app = JupyterDash('SimpleExample')
app.layout = html.Div([
dcc.RadioItems(
id='dropdown-color',
options=[{'label': c, 'value': c.lower()}
for c in ['Red', 'Green', 'Blue']],
value='red'
),
html.Div(id='output-color'),
dcc.RadioItems(
id='dropdown-size',
options=[{'label': i, 'value': j}
for i, j in [('L','large'), ('M','medium'), ('S','small')]],
value='medium'
),
html.Div(id='output-size')
])
@app.callback(
dash.dependencies.Output('output-color', 'children'),
[dash.dependencies.Input('dropdown-color', 'value')])
def callback_color(dropdown_value):
return "The selected color is %s." % dropdown_value
@app.callback(
dash.dependencies.Output('output-size', 'children'),
[dash.dependencies.Input('dropdown-color', 'value'),
dash.dependencies.Input('dropdown-size', 'value')])
def callback_size(dropdown_color, dropdown_size):
return "The chosen T-shirt is a %s %s one." %(dropdown_size,
dropdown_color)
app
```
The last line causes the dash application to be rendered. All callbacks are invoked asynchronously, so the display of an
application does not prevent other notebook cells from being evaluated. Multiple instances of the same dash application
can be rendered at the same time within a single notebook.
## Binder use
To launch a binder
image, visit [](https://mybinder.org/v2/gh/GibbsConsulting/jupyter-plotly-dash/master) to
run Jupyter notebooks using the latest version on the master branch of the main repository.
%package -n python3-jupyter-plotly-dash
Summary: Interactive Jupyter use of plotly dash apps
Provides: python-jupyter-plotly-dash
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-jupyter-plotly-dash
# jupyter-plotly-dash
[](https://badge.fury.io/py/jupyter-plotly-dash)
[](https://img.shields.io/pypi/dw/jupyter-plotly-dash.svg)
[](https://coveralls.io/github/GibbsConsulting/jupyter-plotly-dash?branch=master)
[](https://jupyter-plotly-dash.readthedocs.io/en/latest/?badge=latest)
Allow use of [plotly dash](https://plot.ly/products/dash/) applications within Jupyter notebooks, with the management of both session and internal state.
See the source for this project here:
<https://github.com/GibbsConsulting/jupyter-plotly-dash>
Try me here in your browser: [](https://mybinder.org/v2/gh/GibbsConsulting/jupyter-plotly-dash/master)
More detailed information
can be found in the online documentation at
<https://readthedocs.org/projects/jupyter-plotly-dash>
## Installation
Install the package. Use of a `virtualenv` environment is strongly recommended.
pip install jupyter_plotly_dash
Now the package is installed, it can be used within a Jupyter notebook.
## Simple use
After installation, launch a python Jupyter notebook server using `jupyter notebook` or `jupyter lab` as desired. Create a `Dash` application, using
the `JupyterDash` class instead of `dash.Dash` for the application, and copy the following into a code cell and evaluate it.
```python
from jupyter_plotly_dash import JupyterDash
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
app = JupyterDash('SimpleExample')
app.layout = html.Div([
dcc.RadioItems(
id='dropdown-color',
options=[{'label': c, 'value': c.lower()}
for c in ['Red', 'Green', 'Blue']],
value='red'
),
html.Div(id='output-color'),
dcc.RadioItems(
id='dropdown-size',
options=[{'label': i, 'value': j}
for i, j in [('L','large'), ('M','medium'), ('S','small')]],
value='medium'
),
html.Div(id='output-size')
])
@app.callback(
dash.dependencies.Output('output-color', 'children'),
[dash.dependencies.Input('dropdown-color', 'value')])
def callback_color(dropdown_value):
return "The selected color is %s." % dropdown_value
@app.callback(
dash.dependencies.Output('output-size', 'children'),
[dash.dependencies.Input('dropdown-color', 'value'),
dash.dependencies.Input('dropdown-size', 'value')])
def callback_size(dropdown_color, dropdown_size):
return "The chosen T-shirt is a %s %s one." %(dropdown_size,
dropdown_color)
app
```
The last line causes the dash application to be rendered. All callbacks are invoked asynchronously, so the display of an
application does not prevent other notebook cells from being evaluated. Multiple instances of the same dash application
can be rendered at the same time within a single notebook.
## Binder use
To launch a binder
image, visit [](https://mybinder.org/v2/gh/GibbsConsulting/jupyter-plotly-dash/master) to
run Jupyter notebooks using the latest version on the master branch of the main repository.
%package help
Summary: Development documents and examples for jupyter-plotly-dash
Provides: python3-jupyter-plotly-dash-doc
%description help
# jupyter-plotly-dash
[](https://badge.fury.io/py/jupyter-plotly-dash)
[](https://img.shields.io/pypi/dw/jupyter-plotly-dash.svg)
[](https://coveralls.io/github/GibbsConsulting/jupyter-plotly-dash?branch=master)
[](https://jupyter-plotly-dash.readthedocs.io/en/latest/?badge=latest)
Allow use of [plotly dash](https://plot.ly/products/dash/) applications within Jupyter notebooks, with the management of both session and internal state.
See the source for this project here:
<https://github.com/GibbsConsulting/jupyter-plotly-dash>
Try me here in your browser: [](https://mybinder.org/v2/gh/GibbsConsulting/jupyter-plotly-dash/master)
More detailed information
can be found in the online documentation at
<https://readthedocs.org/projects/jupyter-plotly-dash>
## Installation
Install the package. Use of a `virtualenv` environment is strongly recommended.
pip install jupyter_plotly_dash
Now the package is installed, it can be used within a Jupyter notebook.
## Simple use
After installation, launch a python Jupyter notebook server using `jupyter notebook` or `jupyter lab` as desired. Create a `Dash` application, using
the `JupyterDash` class instead of `dash.Dash` for the application, and copy the following into a code cell and evaluate it.
```python
from jupyter_plotly_dash import JupyterDash
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
app = JupyterDash('SimpleExample')
app.layout = html.Div([
dcc.RadioItems(
id='dropdown-color',
options=[{'label': c, 'value': c.lower()}
for c in ['Red', 'Green', 'Blue']],
value='red'
),
html.Div(id='output-color'),
dcc.RadioItems(
id='dropdown-size',
options=[{'label': i, 'value': j}
for i, j in [('L','large'), ('M','medium'), ('S','small')]],
value='medium'
),
html.Div(id='output-size')
])
@app.callback(
dash.dependencies.Output('output-color', 'children'),
[dash.dependencies.Input('dropdown-color', 'value')])
def callback_color(dropdown_value):
return "The selected color is %s." % dropdown_value
@app.callback(
dash.dependencies.Output('output-size', 'children'),
[dash.dependencies.Input('dropdown-color', 'value'),
dash.dependencies.Input('dropdown-size', 'value')])
def callback_size(dropdown_color, dropdown_size):
return "The chosen T-shirt is a %s %s one." %(dropdown_size,
dropdown_color)
app
```
The last line causes the dash application to be rendered. All callbacks are invoked asynchronously, so the display of an
application does not prevent other notebook cells from being evaluated. Multiple instances of the same dash application
can be rendered at the same time within a single notebook.
## Binder use
To launch a binder
image, visit [](https://mybinder.org/v2/gh/GibbsConsulting/jupyter-plotly-dash/master) to
run Jupyter notebooks using the latest version on the master branch of the main repository.
%prep
%autosetup -n jupyter-plotly-dash-0.4.3
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-jupyter-plotly-dash -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.4.3-1
- Package Spec generated
|
