Metadata-Version: 1.1
Name: phenodata
Version: 0.3.0
Summary: phenodata is a data acquisition and manipulation toolkit for open access phenology data
Home-page: https://github.com/hiveeyes/phenodata
Author: Andreas Motl
Author-email: andreas@hiveeyes.org
License: AGPL 3
Description: .. image:: https://img.shields.io/badge/Python-2.7-green.svg
            :target: https://pypi.org/project/phenodata/
        
        .. image:: https://img.shields.io/pypi/v/phenodata.svg
            :target: https://pypi.org/project/phenodata/
        
        .. image:: https://img.shields.io/github/tag/hiveeyes/phenodata.svg
            :target: https://github.com/hiveeyes/phenodata
        
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        #################################################
        phenodata - phenology data acquisition for humans
        #################################################
        
        
        *****
        About
        *****
        phenodata is a data acquisition and manipulation toolkit for open access phenology data.
        It is written in Python.
        
        Currently, it implements data wrappers for acquiring phenology observation data published
        on the DWD Climate Data Center (CDC) FTP server operated by »Deutscher Wetterdienst« (DWD).
        
        Under the hood, it uses the fine Pandas_ data analysis library for data mangling, amongst others.
        
        .. _Pandas: https://pandas.pydata.org/
        
        
        ***************
        Acknowledgments
        ***************
        Thanks to the many observers, »Deutscher Wetterdienst«,
        the »Global Phenological Monitoring programme« and all people working behind
        the scenes for their commitment in recording the observations and for making
        the excellent datasets available to the community. You know who you are.
        
        
        ***************
        Getting started
        ***************
        
        Install
        =======
        If you know your way around Python, installing this software is really easy::
        
            pip install phenodata --upgrade
        
        Please refer to the `virtualenv`_ page about further recommendations how to install and use this software.
        
        .. _virtualenv: https://github.com/hiveeyes/phenodata/blob/master/doc/virtualenv.rst
        
        
        Usage
        =====
        ::
        
            $ phenodata --help
            Usage:
              phenodata info
              phenodata list-species --source=dwd
              phenodata list-phases --source=dwd
              phenodata list-stations --source=dwd --dataset=immediate
              phenodata list-quality-levels --source=dwd
              phenodata list-quality-bytes --source=dwd
              phenodata list-filenames --source=dwd --dataset=immediate --partition=recent [--files=Hasel,Schneegloeckchen] [--years=2017 | --forecast]
              phenodata list-urls --source=dwd --dataset=immediate --partition=recent [--files=Hasel,Schneegloeckchen] [--years=2017 | --forecast]
              phenodata observations --source=dwd --dataset=immediate --partition=recent [--files=Hasel,Schneegloeckchen] [--stations=164,717 | --regions=berlin,brandenburg] [--species=hazel,snowdrop] [--phases=flowering] [--years=2017 | --forecast]
              phenodata --version
              phenodata (-h | --help)
        
            Data acquisition options:
              --source=<source>         Data source. Currently "dwd" only.
              --dataset=<dataset>       Data set. Use "immediate" or "annual" for --source=dwd.
              --partition=<dataset>     Partition. Use "recent" or "historical" for --source=dwd.
        
            Data filtering options:
              --files=<files>           Filter by files (comma-separated list)
              --years=<years>           Filter by years (comma-separated list)
              --stations=<stations>     Filter by station ids (comma-separated list)
              --regions=<regions>       Filter by region names (comma-separated list)
              --species=<species>       Filter by species names (comma-separated list)
              --phases=<phases>         Filter by phase names (comma-separated list)
        
        
        .. note::
        
            For most acquisition tasks, you must choose from one of two different datasets: `annual-reporters`_ and `immediate-reporters`_.
        
        .. _annual-reporters: https://www.dwd.de/DE/klimaumwelt/klimaueberwachung/phaenologie/daten_deutschland/jahresmelder/jahresmelder_node.html
        .. _immediate-reporters: https://www.dwd.de/DE/klimaumwelt/klimaueberwachung/phaenologie/daten_deutschland/sofortmelder/sofortmelder_node.html
        
        
        Examples
        ========
        
        
        Metadata
        --------
        
        Display list of species::
        
            phenodata list-species --source=dwd
        
        Display list of phases::
        
            phenodata list-phases --source=dwd
        
        Display list of stations::
        
            phenodata list-stations --source=dwd --dataset=immediate
        
        Display list of file names of recent observations by the annual reporters::
        
            phenodata list-urls --source=dwd --dataset=annual --subset=recent
        
        Display list of urls to recent observations by the annual reporters and apply filter criteria::
        
            phenodata list-urls --source=dwd --dataset=annual --subset=recent --files=Hasel,Schneegloeckchen
        
        
        Observations
        ------------
        
        Display observations of hazel and snowdrop::
        
            phenodata observations --source=dwd --dataset=annual --files=Hasel,Schneegloeckchen --partition=recent
        
        Display observations of hazel and snowdrop for stations 164 and 717::
        
            phenodata observations --source=dwd --dataset=annual --files=Hasel,Schneegloeckchen --partition=recent --stations=164,717
        
        Display all observations for stations 164 and 717 in 2016 and 2017::
        
            phenodata observations --source=dwd --dataset=annual --partition=recent --stations=164,717 --years=2016,2017
        
        
        Todo
        ----
        .. warning:: These commands are not implemented yet.
        
        Display regular flowering events for hazel and snowdrop around Berlin and Brandenburg (Germany) in 2017::
        
            phenodata calendar --source=dwd --dataset=immediate --regions=berlin,brandenburg --species=hazel,snowdrop --phases=flowering --partition=recent --years=2017
        
            phenodata calendar --source=dwd --dataset=immediate --regions=berlin,brandenburg --species=hazel,snowdrop --phases=flowering --partition=historical --years=1958
        
        Display forecast for "beginning of flowering" events for canola and sweet cherry around Thüringen and Bayern (Germany)::
        
            phenodata calendar --source=dwd --dataset=immediate --subset=annual --regions=thüringen,bayern --species=raps,süßkirsche --phases-bbch=60 --forecast
        
        To improve data acquisition performance, you can e.g. use ``--files=Hasel,Schneegloeckchen``
        to apply yet another filter based on file name matching. Only files matching the designated names
        will be retrieved.
        
        
        *******************
        Project information
        *******************
        
        About
        =====
        The "phenodata" program is released under the AGPL license.
        The code lives on `GitHub <https://github.com/hiveeyes/phenodata>`_ and
        the Python package is published to `PyPI <https://pypi.org/project/phenodata/>`_.
        You might also want to have a look at the `documentation <https://hiveeyes.org/docs/phenodata/>`_.
        
        The software has been tested on Python 2.7.
        
        If you'd like to contribute you're most welcome!
        Spend some time taking a look around, locate a bug, design issue or
        spelling mistake and then send us a pull request or create an issue.
        
        Thanks in advance for your efforts, we really appreciate any help or feedback.
        
        Code license
        ============
        Licensed under the AGPL license. See LICENSE file for details.
        
        Data license
        ============
        The DWD has information about their re-use policy in German and English.
        Please refer to the respective Disclaimer
        (`de <https://www.dwd.de/DE/service/disclaimer/disclaimer_node.html>`__,
        `en <https://www.dwd.de/EN/service/disclaimer/disclaimer.html>`__)
        and Copyright
        (`de <https://www.dwd.de/DE/service/copyright/copyright_node.html>`__,
        `en <https://www.dwd.de/EN/service/copyright/copyright_artikel.html>`__)
        information.
        
        Disclaimer
        ==========
        The project and its authors are not affiliated with DWD, USA-NPN or any
        other data provider in any way. It is a sole project from the community
        for making data more accessible in the spirit of open data.
        
Keywords: dwd usa-npn phenology phenometrics opendata bulk data download information research search
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Environment :: Web Environment
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU Affero General Public License v3
Classifier: Natural Language :: English
Classifier: Natural Language :: German
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python
Classifier: Topic :: Database
Classifier: Topic :: Education
Classifier: Topic :: Internet :: File Transfer Protocol (FTP)
Classifier: Topic :: Internet :: WWW/HTTP
Classifier: Topic :: Internet :: WWW/HTTP :: Indexing/Search
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Atmospheric Science
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: System :: Archiving
Classifier: Topic :: Text Processing :: Filters
Classifier: Topic :: Text Processing :: Indexing
Classifier: Topic :: Utilities
