Metadata-Version: 2.1
Name: skinnywms
Version: 0.7.0
Summary: A light WMS server to visualise your NetCDf and Grib data
Home-page: https://github.com/sylvielamythepaut/skinnywms
Author: European Centre for Medium-Range Weather Forecasts (ECMWF)
Author-email: software.support@ecmwf.int
License: Apache License Version 2.0
Description: 
        The skinny WMS is a small WMS server that will help you to visualise your NetCDF and Grib Data.
        The principle is simple: skinny will browse the directory, or the single file passed as argument, and try to interpret each NetCDF or GRIB files. From the metadata, it will be built the getCapabilities document, and find a relevant style to plot the data.
        
        [![build](https://img.shields.io/travis/ecmwf/skinnywms/master.svg)](https://travis-ci.org/ecmwf/skinnywms/branches)
        [![Docker Build Status](https://img.shields.io/docker/cloud/build/ecmwf/skinnywms.svg)](https://hub.docker.com/r/ecmwf/skinnywms)
        [![Docker Pulls](https://img.shields.io/docker/pulls/ecmwf/skinnywms)](https://hub.docker.com/r/ecmwf/skinnywms)[![PyPI version](https://badge.fury.io/py/skinnywms.svg)](https://badge.fury.io/py/skinnywms) [![Anaconda-Server Badge](https://anaconda.org/conda-forge/skinnywms/badges/version.svg)](https://anaconda.org/conda-forge/skinnywms) [![Anaconda-Server Badge](https://anaconda.org/conda-forge/skinnywms/badges/downloads.svg)](https://anaconda.org/conda-forge/skinnywms)
        
        Features:
        ---------
        SkinnyWMS implements 3 of the WMS endpoints:
        - **getCapabilities**: Discover the data, build an XML Document presenting each identified parameter in the file(s) as a layer with the list of their predefined styles. (There is always a default style)
        - **getMap** : Return the  selected layer suing the selected style.
        - **getLegendGraphic**: Return the legend.
        
        
        Usage:
        -----
        There are 2 ways to start using it, they both will start a small Flask server.
        Once running, a small leaflet client is accessible [http://127.0.0.1:5000/]
        
        * The demo:
        
        ```bash
        python demo.py --path /path/to/mydata
        ```
        
        * The command line:
        
        ```bash
        skinny-wms --path /path/to/mydata
        ```
        
        * Or with uwsgi:
        
        ```bash
        uwsgi --http localhost:5000 --master --process 20 --mount /=skinnywms.wmssvr:application --env SKINNYWMS_DATA_PATH=/path/to/mydata
        ```
        Run using Docker
        ----------------
        
        ```bash
         docker run --rm -p 5000:5000 -i -t ecmwf/skinnywms 
         ```
         Now you can try the leaflet demo at http://localhost:5000/
        
        
        Installation
        ------------
        
        SkinnyWMS  depends on the ECMWF *Magics* library.
        
        If you do not have *Magics* installed on your platform, skinnywms is available on conda forge https://conda-forge.org/
        
        ```bash
        conda config --add channels conda-forge
        conda install skinnywms
        ```
        
        If you have *Magics* already installed you can use pip:
        
        ```bash
        pip install skinnywms
        ```
        
        Limitations:
        ------------
        - SkinnyWMS will perform better on well formatted and documented NetCDF and GRIB.
        
        - development stage: **Alpha**,
        
        
        Add your own styles:
        --------------------
        
        Multi-process
        -------------
        
        Cache
        -----
        
        
        How to install Magics
        -----------------------
        
        that must be installed on the system and accessible as a shared library.
        Some Linux distributions ship a binary version that may be installed with the standard package manager.
        
        
        As an alternative you may install the official source distribution
        by following the instructions at
        https://software.ecmwf.int/magics/Installation+Guide
        Magics is available on github https://github.com/ecmwf/magics
        
        Note that *Magics* support for the Windows operating system is experimental.
        
        
        
        
        Contributing
        ------------
        
        The main repository is hosted on GitHub,
        testing, bug reports and contributions are highly welcomed and appreciated:
        
        https://github.com/ecmwf/skinnywms
        https://github.com/ecmwf/magics-python
        https://github.com/ecmwf/magics
        
        
        Please see the CONTRIBUTING.rst document for the best way to help.
        
        Lead developers:
        
        - `Sylvie Lamy-Thepaut <https://github.com/sylvielamythepaut>`_ - ECMWF
        - `Baudouin Raoult <https://github.com/b8raoult>` - ECMWF
        
        Main contributors:
        
        - `Stephan Siemen <https://github.com/stephansiemen>`_ - ECMWF
        - `Milana Vuckovic <https://github.com/milanavuckovic>` - ECMWF
        
        
        License
        -------
        
        Copyright 2017-2019 European Centre for Medium-Range Weather Forecasts (ECMWF).
        
        Licensed under the Apache License, Version 2.0 (the "License");
        you may not use this file except in compliance with the License.
        You may obtain a copy of the License at: http://www.apache.org/licenses/LICENSE-2.0.
        Unless required by applicable law or agreed to in writing, software
        distributed under the License is distributed on an "AS IS" BASIS,
        WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
        See the License for the specific language governing permissions and
        limitations under the License.
        
        
Keywords: magics grib WMS visualisation NetCDF climate meteorology
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
