Skip to main content

A light WMS server to visualise your NetCDf and Grib data

Project 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 inpterpret 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

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: $ python demo.py --path /path/to/mydata
  • The command line: $ skinny-wms --path /path/to/mydata

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/::

$ conda config --add channels conda-forge
$ conda install skinnywms

If you have Magics already installed you can use pip::

$ 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 developer:

  • Sylvie Lamy-Thepaut <https://github.com/sylvielamythepaut>_ - ECMWF

Main contributors:

  • Baudouin Raoult - ECMWF
  • Stephan Siemen <https://github.com/stephansiemen>_ - ECMWF
  • Milana Vuckovic- 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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

skinnywms-0.2.1.tar.gz (12.6 MB view details)

Uploaded Source

File details

Details for the file skinnywms-0.2.1.tar.gz.

File metadata

  • Download URL: skinnywms-0.2.1.tar.gz
  • Upload date:
  • Size: 12.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.4.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4

File hashes

Hashes for skinnywms-0.2.1.tar.gz
Algorithm Hash digest
SHA256 cdf098f8d43f86ce20bdf62ea4b098a81f7be56db8eb9501c7416ae43885bd7b
MD5 d9bc6b23eb297470df73f7d6d0ace7f1
BLAKE2b-256 ad341637d657c2cbb0483fa40ff07eb81819e7b14a52538295fac80d563c5dcc

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page