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@@ -0,0 +1 @@ +/lumen-0.5.1.tar.gz diff --git a/python-lumen.spec b/python-lumen.spec new file mode 100644 index 0000000..bee342f --- /dev/null +++ b/python-lumen.spec @@ -0,0 +1,305 @@ +%global _empty_manifest_terminate_build 0 +Name: python-lumen +Version: 0.5.1 +Release: 1 +Summary: A monitoring solution built on Panel. +License: BSD +URL: https://github.com/holoviz/lumen +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/c4/f8/a5dc48aa924fc2858d413a7927a3d3dc22984c7387665905e615826266ec/lumen-0.5.1.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-bokeh +Requires: python3-param +Requires: python3-panel +Requires: python3-pandas +Requires: python3-hvplot +Requires: python3-holoviews +Requires: python3-packaging +Requires: python3-intake +Requires: python3-jinja2 +Requires: python3-codecov +Requires: python3-fastparquet +Requires: python3-flake8 +Requires: python3-intake +Requires: python3-intake-sql +Requires: python3-msgpack-python +Requires: python3-nbsite +Requires: python3-pre-commit +Requires: python3-pydata-sphinx-theme +Requires: python3-pytest +Requires: python3-pytest-cov +Requires: python3-sphinx-copybutton +Requires: python3-sphinx-design +Requires: python3-toolz +Requires: python3-pydata-sphinx-theme +Requires: python3-nbsite +Requires: python3-sphinx-design +Requires: python3-sphinx-copybutton +Requires: python3-pytest +Requires: python3-flake8 +Requires: python3-intake +Requires: python3-intake-sql +Requires: python3-fastparquet +Requires: python3-msgpack-python +Requires: python3-toolz +Requires: python3-pytest-cov +Requires: python3-codecov +Requires: python3-pre-commit + +%description +# Lumen + +*Illuminate your data* + +<img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/diagram.png" width="100%"> + +| | | +| --- | --- | +| Build Status | [](https://github.com/holoviz/lumen/actions/workflows/test.yml) +| Coverage | [](https://codecov.io/gh/holoviz/lumen) | +| Latest dev release | [](https://github.com/holoviz/lumen/tags) [](https://pyviz-dev.github.io/lumen/) | +| Latest release | [](https://github.com/holoviz/lumen/releases) [](https://pypi.python.org/pypi/lumen) [](https://anaconda.org/pyviz/lumen) [](https://anaconda.org/conda-forge/lumen) [](https://anaconda.org/anaconda/lumen) | +| Docs | [](https://github.com/holoviz/lumen/tree/gh-pages) [](https://lumen.holoviz.org) | +| Support | [](https://discourse.holoviz.org/) | + +## Why Lumen? + +The Lumen project provides a framework for visual analytics, which allows users to build data-driven dashboards from a simple yaml specification. The power of Lumen comes from the ability to leverage the powerful data intake, data processing and data visualization libraries available in the PyData ecosystem. + +- **Data Intake**: A flexible system for declaring data sources with strong integration with [Intake](https://intake.readthedocs.io/en/latest/), allows Lumen to query data from a wide range of sources including many file formats such as CSV or Parquet but also SQL and many others. +- **Data Proccessing**: Internally Lumen stores data as DataFrame objects, allowing users to leverage familiar APIs for filtering and transforming data using [Pandas](https://pandas.pydata.org/) while also providing the ability to scale these transformations out to a cluster thanks to [Dask](https://dask.org/). +- **Data Visualization**: Since Lumen is built on [Panel](https://panel.holoviz.org) all the most popular plotting libraries and many other components such as powerful datagrids and BI indicators are supported. + +The core strengths of Lumen include: + +- **Flexibility**: The design of Lumen allows flexibly combining data intake, data processing and data visualization into a simple declarative pipeline. +- **Extensibility**: Every part of Lumen is designed to be extended letting you define custom Source, Filter, Transform and View components. +- **Scalability**: Lumen is designed with performance in mind and supports scalable Dask DataFrames out of the box, letting you scale to datasets larger than memory or even scale out to a cluster. +- **Security**: Lumen ships with a wide range of OAuth providers out of the box, making it a breeze to add authentication to your applications. + +## Examples + + <table> + <tr> + <td><a href="https://lumen.holoviz.org/gallery/bikes.html"><b>London Bike Points</b><br><img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/bikes.png" /></a></td> + <td><a href="https://lumen.holoviz.org/gallery/nyc_taxi.html"><b>NYC Taxi</b><br><img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/nyc_taxi.png" /></a></td> + </tr> + <tr> + <td><a href="https://lumen.holoviz.org/gallery/penguins.html"><b>Palmer Penguins</b><br><img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/penguins.png" /></a></td> + <td><a href="https://lumen.holoviz.org/gallery/precip.html"><b>Precipitation</b><br><img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/precip.png" /></a></td> + </tr> + <tr> + <td><a href="https://lumen.holoviz.org/gallery/seattle.html"><b>Seattle Weather</b><br><img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/seattle.png" /></a></td> + </tr> + </table> + +## Getting started + +Lumen works with Python 3 and above on Linux, Windows, or Mac. The recommended way to install Lumen is using the [`conda`](https://conda.pydata.org/docs/) command provided by [Anaconda](https://docs.continuum.io/anaconda/install) or [`Miniconda`](https://conda.pydata.org/miniconda.html): + + conda install -c pyviz lumen + +or using PyPI: + + pip install lumen + +Once installed you will be able to start a Lumen server by running: + + lumen serve dashboard.yaml --show + +This will open a browser serving the application or dashboard declared by your yaml file in a browser window. During development it is very helpful to use the `--autoreload` flag, which will automatically refresh and update the application in your browser window, whenever you make an edit to the dashboard yaml specification. In this way you can quickly iterate on your dashboard. + +Try it out! Click on one of the examples below, copy the yaml specification and launch your first Lumen application. + + + + +%package -n python3-lumen +Summary: A monitoring solution built on Panel. +Provides: python-lumen +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-lumen +# Lumen + +*Illuminate your data* + +<img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/diagram.png" width="100%"> + +| | | +| --- | --- | +| Build Status | [](https://github.com/holoviz/lumen/actions/workflows/test.yml) +| Coverage | [](https://codecov.io/gh/holoviz/lumen) | +| Latest dev release | [](https://github.com/holoviz/lumen/tags) [](https://pyviz-dev.github.io/lumen/) | +| Latest release | [](https://github.com/holoviz/lumen/releases) [](https://pypi.python.org/pypi/lumen) [](https://anaconda.org/pyviz/lumen) [](https://anaconda.org/conda-forge/lumen) [](https://anaconda.org/anaconda/lumen) | +| Docs | [](https://github.com/holoviz/lumen/tree/gh-pages) [](https://lumen.holoviz.org) | +| Support | [](https://discourse.holoviz.org/) | + +## Why Lumen? + +The Lumen project provides a framework for visual analytics, which allows users to build data-driven dashboards from a simple yaml specification. The power of Lumen comes from the ability to leverage the powerful data intake, data processing and data visualization libraries available in the PyData ecosystem. + +- **Data Intake**: A flexible system for declaring data sources with strong integration with [Intake](https://intake.readthedocs.io/en/latest/), allows Lumen to query data from a wide range of sources including many file formats such as CSV or Parquet but also SQL and many others. +- **Data Proccessing**: Internally Lumen stores data as DataFrame objects, allowing users to leverage familiar APIs for filtering and transforming data using [Pandas](https://pandas.pydata.org/) while also providing the ability to scale these transformations out to a cluster thanks to [Dask](https://dask.org/). +- **Data Visualization**: Since Lumen is built on [Panel](https://panel.holoviz.org) all the most popular plotting libraries and many other components such as powerful datagrids and BI indicators are supported. + +The core strengths of Lumen include: + +- **Flexibility**: The design of Lumen allows flexibly combining data intake, data processing and data visualization into a simple declarative pipeline. +- **Extensibility**: Every part of Lumen is designed to be extended letting you define custom Source, Filter, Transform and View components. +- **Scalability**: Lumen is designed with performance in mind and supports scalable Dask DataFrames out of the box, letting you scale to datasets larger than memory or even scale out to a cluster. +- **Security**: Lumen ships with a wide range of OAuth providers out of the box, making it a breeze to add authentication to your applications. + +## Examples + + <table> + <tr> + <td><a href="https://lumen.holoviz.org/gallery/bikes.html"><b>London Bike Points</b><br><img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/bikes.png" /></a></td> + <td><a href="https://lumen.holoviz.org/gallery/nyc_taxi.html"><b>NYC Taxi</b><br><img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/nyc_taxi.png" /></a></td> + </tr> + <tr> + <td><a href="https://lumen.holoviz.org/gallery/penguins.html"><b>Palmer Penguins</b><br><img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/penguins.png" /></a></td> + <td><a href="https://lumen.holoviz.org/gallery/precip.html"><b>Precipitation</b><br><img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/precip.png" /></a></td> + </tr> + <tr> + <td><a href="https://lumen.holoviz.org/gallery/seattle.html"><b>Seattle Weather</b><br><img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/seattle.png" /></a></td> + </tr> + </table> + +## Getting started + +Lumen works with Python 3 and above on Linux, Windows, or Mac. The recommended way to install Lumen is using the [`conda`](https://conda.pydata.org/docs/) command provided by [Anaconda](https://docs.continuum.io/anaconda/install) or [`Miniconda`](https://conda.pydata.org/miniconda.html): + + conda install -c pyviz lumen + +or using PyPI: + + pip install lumen + +Once installed you will be able to start a Lumen server by running: + + lumen serve dashboard.yaml --show + +This will open a browser serving the application or dashboard declared by your yaml file in a browser window. During development it is very helpful to use the `--autoreload` flag, which will automatically refresh and update the application in your browser window, whenever you make an edit to the dashboard yaml specification. In this way you can quickly iterate on your dashboard. + +Try it out! Click on one of the examples below, copy the yaml specification and launch your first Lumen application. + + + + +%package help +Summary: Development documents and examples for lumen +Provides: python3-lumen-doc +%description help +# Lumen + +*Illuminate your data* + +<img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/diagram.png" width="100%"> + +| | | +| --- | --- | +| Build Status | [](https://github.com/holoviz/lumen/actions/workflows/test.yml) +| Coverage | [](https://codecov.io/gh/holoviz/lumen) | +| Latest dev release | [](https://github.com/holoviz/lumen/tags) [](https://pyviz-dev.github.io/lumen/) | +| Latest release | [](https://github.com/holoviz/lumen/releases) [](https://pypi.python.org/pypi/lumen) [](https://anaconda.org/pyviz/lumen) [](https://anaconda.org/conda-forge/lumen) [](https://anaconda.org/anaconda/lumen) | +| Docs | [](https://github.com/holoviz/lumen/tree/gh-pages) [](https://lumen.holoviz.org) | +| Support | [](https://discourse.holoviz.org/) | + +## Why Lumen? + +The Lumen project provides a framework for visual analytics, which allows users to build data-driven dashboards from a simple yaml specification. The power of Lumen comes from the ability to leverage the powerful data intake, data processing and data visualization libraries available in the PyData ecosystem. + +- **Data Intake**: A flexible system for declaring data sources with strong integration with [Intake](https://intake.readthedocs.io/en/latest/), allows Lumen to query data from a wide range of sources including many file formats such as CSV or Parquet but also SQL and many others. +- **Data Proccessing**: Internally Lumen stores data as DataFrame objects, allowing users to leverage familiar APIs for filtering and transforming data using [Pandas](https://pandas.pydata.org/) while also providing the ability to scale these transformations out to a cluster thanks to [Dask](https://dask.org/). +- **Data Visualization**: Since Lumen is built on [Panel](https://panel.holoviz.org) all the most popular plotting libraries and many other components such as powerful datagrids and BI indicators are supported. + +The core strengths of Lumen include: + +- **Flexibility**: The design of Lumen allows flexibly combining data intake, data processing and data visualization into a simple declarative pipeline. +- **Extensibility**: Every part of Lumen is designed to be extended letting you define custom Source, Filter, Transform and View components. +- **Scalability**: Lumen is designed with performance in mind and supports scalable Dask DataFrames out of the box, letting you scale to datasets larger than memory or even scale out to a cluster. +- **Security**: Lumen ships with a wide range of OAuth providers out of the box, making it a breeze to add authentication to your applications. + +## Examples + + <table> + <tr> + <td><a href="https://lumen.holoviz.org/gallery/bikes.html"><b>London Bike Points</b><br><img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/bikes.png" /></a></td> + <td><a href="https://lumen.holoviz.org/gallery/nyc_taxi.html"><b>NYC Taxi</b><br><img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/nyc_taxi.png" /></a></td> + </tr> + <tr> + <td><a href="https://lumen.holoviz.org/gallery/penguins.html"><b>Palmer Penguins</b><br><img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/penguins.png" /></a></td> + <td><a href="https://lumen.holoviz.org/gallery/precip.html"><b>Precipitation</b><br><img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/precip.png" /></a></td> + </tr> + <tr> + <td><a href="https://lumen.holoviz.org/gallery/seattle.html"><b>Seattle Weather</b><br><img src="https://raw.githubusercontent.com/holoviz/lumen/main/doc/_static/seattle.png" /></a></td> + </tr> + </table> + +## Getting started + +Lumen works with Python 3 and above on Linux, Windows, or Mac. The recommended way to install Lumen is using the [`conda`](https://conda.pydata.org/docs/) command provided by [Anaconda](https://docs.continuum.io/anaconda/install) or [`Miniconda`](https://conda.pydata.org/miniconda.html): + + conda install -c pyviz lumen + +or using PyPI: + + pip install lumen + +Once installed you will be able to start a Lumen server by running: + + lumen serve dashboard.yaml --show + +This will open a browser serving the application or dashboard declared by your yaml file in a browser window. During development it is very helpful to use the `--autoreload` flag, which will automatically refresh and update the application in your browser window, whenever you make an edit to the dashboard yaml specification. In this way you can quickly iterate on your dashboard. + +Try it out! Click on one of the examples below, copy the yaml specification and launch your first Lumen application. + + + + +%prep +%autosetup -n lumen-0.5.1 + +%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-lumen -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.5.1-1 +- Package Spec generated @@ -0,0 +1 @@ +14ab1a8ec3055fa9f75e51b7b2cc16d3 lumen-0.5.1.tar.gz |