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|
%global _empty_manifest_terminate_build 0
Name: python-dash-bio
Version: 1.0.2
Release: 1
Summary: Dash components for bioinformatics
License: MIT License
URL: http://github.com/plotly/dash-bio
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/7e/eb/5f12d4b0b91974e2457aaf344230010488453edadffb9e5c241eb9f02d34/dash_bio-1.0.2.tar.gz
BuildArch: noarch
%description
# Dash Bio
[](https://circleci.com/gh/plotly/dash-bio)
[](https://badge.fury.io/py/dash-bio)
Dash Bio is a suite of bioinformatics components built to work with
[Dash](https://github.com/plotly/dash/).
Announcement: https://medium.com/@plotlygraphs/announcing-dash-bio-ed8835d5da0c
Demo:
[https://dash-gallery.plotly.host/Portal/?search=Bioinformatics](https://dash-gallery.plotly.host/Portal/?search=Bioinformatics)
Documentation:
[https://dash.plotly.com/dash-bio](https://dash.plotly.com/dash-bio)
## Components
The Dash Bio components each fall into one of three categories:
- Custom chart types
- Sequence analysis tools
- 3D rendering tools
### Custom chart types
- Dash Circos
- Dash Clustergram
- Dash Manhattan Plot
- Dash Needle Plot
- Dash Volcano Plot
### Sequence analysis tools
- Dash Alignment Chart
- Dash Onco Print
- Dash Forna Container
- Dash Sequence Viewer
### Visualization tools
- Dash Mol2D
- Dash Mol3D
- Dash Speck
- Dash Ngl
## Using Dash Bio
It's easy to add a fully interactive chromosomal, molecular or genomic visualization to your Dash app by simply
including the Dash Bio component into your app layout as follows:
```python
import urllib.request as urlreq
from dash import Dash, html
import dash_bio as dashbio
app = Dash(__name__)
data = urlreq.urlopen(
'https://raw.githubusercontent.com/plotly/dash-bio-docs-files/master/alignment_viewer_p53.fasta'
).read().decode('utf-8')
app.layout = html.Div([
dashbio.AlignmentChart(
id='my-default-alignment-viewer',
data=data
)
])
if __name__ == '__main__':
app.run_server(debug=True)
```
See the [Dash Bio documentation](https://dash.plotly.com/dash-bio) for more components and examples.
## Run Dash Bio in a JupyterLab environment
1. Create a virtual environment:
The following steps require a virtual environment tool to be installed on your computer: `pip install virtualenv`
a. On macOS and Linux: `python3 -m venv env`
b. On Windows, enter: `py -m venv env`
2. Activate your new environment:
a. On macOS and Linux, enter: `source env/bin/activate`
b. On Windows, enter: `.\env\Scripts\activate`
3. Install required libraries (make sure you have pip installed with `pip help`):
```
pip install dash dash-bio pandas numpy Jupyterlab
```
4. To run Dash inside Jupyter lab:
a. Install jupyter-dash: `pip install jupyter-dash`
b. Enter `jupyter lab build`
(Note: This step requires Node.js and NPM installed on yourcomputer. To check if Node and NPM are installed, enter `node -v` and `npm -v` in your terminal. For install instructions see [nodejs.org](https://nodejs.org/en/).
5. To display Plotly figures in JupyterLab:
```
pip install jupyterlab "ipywidgets>=7.5”
jupyter labextension install jupyterlab-plotly@4.14.3
```
6. Start JupyterLab by typing: `jupyter lab`
Important: JupyterLab must be run within the virtual environment that was previously activated.
For more on running a Dash app in Jupyter Lab visit [Getting Started with Jupyter Dash](https://github.com/plotly/jupyter-dash/blob/master/notebooks/getting_started.ipynb).
## Dash
Learn more about Dash at
[https://plotly.com/products/dash/](https://plotly.com/products/dash/).
## Consulting and OEM
For inquiries about Dash app development, advanced OEM integration,
and more, please [reach
out](https://plotly.typeform.com/to/mH1Cpb).
## Contributing and Local Development
If you would like to contribute to this repository, or run demo apps and tests, please refer to
the [contributing
guidelines](https://github.com/plotly/dash-bio/blob/master/CONTRIBUTING.md).
%package -n python3-dash-bio
Summary: Dash components for bioinformatics
Provides: python-dash-bio
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-dash-bio
# Dash Bio
[](https://circleci.com/gh/plotly/dash-bio)
[](https://badge.fury.io/py/dash-bio)
Dash Bio is a suite of bioinformatics components built to work with
[Dash](https://github.com/plotly/dash/).
Announcement: https://medium.com/@plotlygraphs/announcing-dash-bio-ed8835d5da0c
Demo:
[https://dash-gallery.plotly.host/Portal/?search=Bioinformatics](https://dash-gallery.plotly.host/Portal/?search=Bioinformatics)
Documentation:
[https://dash.plotly.com/dash-bio](https://dash.plotly.com/dash-bio)
## Components
The Dash Bio components each fall into one of three categories:
- Custom chart types
- Sequence analysis tools
- 3D rendering tools
### Custom chart types
- Dash Circos
- Dash Clustergram
- Dash Manhattan Plot
- Dash Needle Plot
- Dash Volcano Plot
### Sequence analysis tools
- Dash Alignment Chart
- Dash Onco Print
- Dash Forna Container
- Dash Sequence Viewer
### Visualization tools
- Dash Mol2D
- Dash Mol3D
- Dash Speck
- Dash Ngl
## Using Dash Bio
It's easy to add a fully interactive chromosomal, molecular or genomic visualization to your Dash app by simply
including the Dash Bio component into your app layout as follows:
```python
import urllib.request as urlreq
from dash import Dash, html
import dash_bio as dashbio
app = Dash(__name__)
data = urlreq.urlopen(
'https://raw.githubusercontent.com/plotly/dash-bio-docs-files/master/alignment_viewer_p53.fasta'
).read().decode('utf-8')
app.layout = html.Div([
dashbio.AlignmentChart(
id='my-default-alignment-viewer',
data=data
)
])
if __name__ == '__main__':
app.run_server(debug=True)
```
See the [Dash Bio documentation](https://dash.plotly.com/dash-bio) for more components and examples.
## Run Dash Bio in a JupyterLab environment
1. Create a virtual environment:
The following steps require a virtual environment tool to be installed on your computer: `pip install virtualenv`
a. On macOS and Linux: `python3 -m venv env`
b. On Windows, enter: `py -m venv env`
2. Activate your new environment:
a. On macOS and Linux, enter: `source env/bin/activate`
b. On Windows, enter: `.\env\Scripts\activate`
3. Install required libraries (make sure you have pip installed with `pip help`):
```
pip install dash dash-bio pandas numpy Jupyterlab
```
4. To run Dash inside Jupyter lab:
a. Install jupyter-dash: `pip install jupyter-dash`
b. Enter `jupyter lab build`
(Note: This step requires Node.js and NPM installed on yourcomputer. To check if Node and NPM are installed, enter `node -v` and `npm -v` in your terminal. For install instructions see [nodejs.org](https://nodejs.org/en/).
5. To display Plotly figures in JupyterLab:
```
pip install jupyterlab "ipywidgets>=7.5”
jupyter labextension install jupyterlab-plotly@4.14.3
```
6. Start JupyterLab by typing: `jupyter lab`
Important: JupyterLab must be run within the virtual environment that was previously activated.
For more on running a Dash app in Jupyter Lab visit [Getting Started with Jupyter Dash](https://github.com/plotly/jupyter-dash/blob/master/notebooks/getting_started.ipynb).
## Dash
Learn more about Dash at
[https://plotly.com/products/dash/](https://plotly.com/products/dash/).
## Consulting and OEM
For inquiries about Dash app development, advanced OEM integration,
and more, please [reach
out](https://plotly.typeform.com/to/mH1Cpb).
## Contributing and Local Development
If you would like to contribute to this repository, or run demo apps and tests, please refer to
the [contributing
guidelines](https://github.com/plotly/dash-bio/blob/master/CONTRIBUTING.md).
%package help
Summary: Development documents and examples for dash-bio
Provides: python3-dash-bio-doc
%description help
# Dash Bio
[](https://circleci.com/gh/plotly/dash-bio)
[](https://badge.fury.io/py/dash-bio)
Dash Bio is a suite of bioinformatics components built to work with
[Dash](https://github.com/plotly/dash/).
Announcement: https://medium.com/@plotlygraphs/announcing-dash-bio-ed8835d5da0c
Demo:
[https://dash-gallery.plotly.host/Portal/?search=Bioinformatics](https://dash-gallery.plotly.host/Portal/?search=Bioinformatics)
Documentation:
[https://dash.plotly.com/dash-bio](https://dash.plotly.com/dash-bio)
## Components
The Dash Bio components each fall into one of three categories:
- Custom chart types
- Sequence analysis tools
- 3D rendering tools
### Custom chart types
- Dash Circos
- Dash Clustergram
- Dash Manhattan Plot
- Dash Needle Plot
- Dash Volcano Plot
### Sequence analysis tools
- Dash Alignment Chart
- Dash Onco Print
- Dash Forna Container
- Dash Sequence Viewer
### Visualization tools
- Dash Mol2D
- Dash Mol3D
- Dash Speck
- Dash Ngl
## Using Dash Bio
It's easy to add a fully interactive chromosomal, molecular or genomic visualization to your Dash app by simply
including the Dash Bio component into your app layout as follows:
```python
import urllib.request as urlreq
from dash import Dash, html
import dash_bio as dashbio
app = Dash(__name__)
data = urlreq.urlopen(
'https://raw.githubusercontent.com/plotly/dash-bio-docs-files/master/alignment_viewer_p53.fasta'
).read().decode('utf-8')
app.layout = html.Div([
dashbio.AlignmentChart(
id='my-default-alignment-viewer',
data=data
)
])
if __name__ == '__main__':
app.run_server(debug=True)
```
See the [Dash Bio documentation](https://dash.plotly.com/dash-bio) for more components and examples.
## Run Dash Bio in a JupyterLab environment
1. Create a virtual environment:
The following steps require a virtual environment tool to be installed on your computer: `pip install virtualenv`
a. On macOS and Linux: `python3 -m venv env`
b. On Windows, enter: `py -m venv env`
2. Activate your new environment:
a. On macOS and Linux, enter: `source env/bin/activate`
b. On Windows, enter: `.\env\Scripts\activate`
3. Install required libraries (make sure you have pip installed with `pip help`):
```
pip install dash dash-bio pandas numpy Jupyterlab
```
4. To run Dash inside Jupyter lab:
a. Install jupyter-dash: `pip install jupyter-dash`
b. Enter `jupyter lab build`
(Note: This step requires Node.js and NPM installed on yourcomputer. To check if Node and NPM are installed, enter `node -v` and `npm -v` in your terminal. For install instructions see [nodejs.org](https://nodejs.org/en/).
5. To display Plotly figures in JupyterLab:
```
pip install jupyterlab "ipywidgets>=7.5”
jupyter labextension install jupyterlab-plotly@4.14.3
```
6. Start JupyterLab by typing: `jupyter lab`
Important: JupyterLab must be run within the virtual environment that was previously activated.
For more on running a Dash app in Jupyter Lab visit [Getting Started with Jupyter Dash](https://github.com/plotly/jupyter-dash/blob/master/notebooks/getting_started.ipynb).
## Dash
Learn more about Dash at
[https://plotly.com/products/dash/](https://plotly.com/products/dash/).
## Consulting and OEM
For inquiries about Dash app development, advanced OEM integration,
and more, please [reach
out](https://plotly.typeform.com/to/mH1Cpb).
## Contributing and Local Development
If you would like to contribute to this repository, or run demo apps and tests, please refer to
the [contributing
guidelines](https://github.com/plotly/dash-bio/blob/master/CONTRIBUTING.md).
%prep
%autosetup -n dash-bio-1.0.2
%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-dash-bio -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.0.2-1
- Package Spec generated
|
