Metadata-Version: 1.0
Name: pyoos
Version: 0.5
Summary: A Python library for collecting Met/Ocean observations
Home-page: https://github.com/asascience-open/pyoos
Author: Kyle Wilcox
Author-email: kwilcox@sasascience.com
License: GPLv3
Description: # Pyoos - A Python library for collecting Met/Ocean observations
        
        *Note: Pyoos is very much a work in progress and should considered experimental until a 1.0 release is made!*
        
        Pyoos attempts to fill the need for a high level data collection library for met/ocean data publically available through many different websites and webservices.
        
        Pyoos will collect and parse the following data services into the [Paegan](https://github.com/asascience-open/paegan#paegan---the-python-cdm-for-metocean-data) Discrete Geometry CDM:
        
        * NERRS Observations - SOAP
        * NDBC Observations - IOOS SWE SOS 1.0
        * CO-OPS Observations - IOOS SWE SOS 1.0
        * STORET Water Quality - WqxOutbound via REST (waterqualitydata.us)
        * USGS NWIS Water Quality - WqxOutbound via REST (waterqualitydata.us)
        * USGS Instantaneous Values - WaterML via REST
        * NWS AWC Observations - XML via REST (http://www.aviationweather.gov)
        * HADS (http://www.nws.noaa.gov/oh/hads/ - limited to 7 day rolling window of data)
        
        ## Common Interface
        
        ### Filtering data
        
        #### Geo
        ##### Filter by bbox
        ```python
        # (minx, miny, maxx, maxy)
        collector.filter(bbox=(-74, 30, -70, 38))
        ```
        #### Time
        
        ##### Filter from a datetime (the 'start' parameter)
        ```python
        from dateime import dateime, timedelta
        collector.filter(start=datetime.utcnow() - timedelta(hours=1))
        ```
        ##### Filter until a datetime (the 'end' parameter)
        ```python
        from dateime import dateime
        collector.filter(end=datetime.utcnow())
        ```
        
        ##### Filter a datetime range (both 'start' and 'end' parameters)
        ```python
        from dateime import dateime, timedelta
        collector.filter(start=datetime.utcnow - timedelta(hours=24), end=datetime.utcnow())
        ```
        
        #### Feature(s)
        It is highly dependent on the data provider how they identify unique features/stations/objects.
        Pyoos does its best job to figure out what you are passing in.  For example,
        you may pass WMO ID's to the NDBC collector and Pyoos will request the correct complete URN to the NDBC SOS.
        
        ##### Retrieve a list of unique features available to filter
        ```python
        collector.list_features()
        ```
        ##### Filter by unique feature
        ```python
        # Any iterable of strings
        collector.filter(features=["21KY-BSW004"])
        ```
        
        #### Variable(s)
        Pyoos does its best job to format any string into the correct format for the actual request.  For example,
        you may pass typical standard_name string from CF-1.6 to the NDBC collector and Pyoos will turn it into a complete MMI URI.
        
        ##### Retreive a list of unique variables available to filter
        ```python
        collector.list_variables()
        ```
        
        ##### Filter by variable name
        ```python
        # Any iterable of strings
        collector.filter(variables=["sea_water_temperature"])
        ```
        
        #### Clear active filters
        ```python
        collector.clear()
        ```
        
        ## Filter Chaining
        You may chain many `filter` calls together (it returns a collector object)
        ```python
        collection.filter(bbox=(-74, 30, -70, 38)).filter(end=datetime.utcnow())
        ```
        You may also combine many filter types into one call to `filter`
        ```python
        collection.filter(bbox=(-74, 30, -70, 38), end=datetime.utcnow())
        ```
        
        ## Get Data
        
        ### As Paegan CDM objects
        ```python
        collector.collect()
        ```
        
        ### As raw response from provider
        ```python
        collector.raw()
        ```
        
        
        ## Specific functionality
        
        Each collector may implement a set of functions specific to that collection.  Please see the Wiki for an explanation of this type of functionality.
        
        
        ## Setup
        You are using `virtualenv`, right?
        
        1. Install [virtualenv-burrito](https://github.com/brainsik/virtualenv-burrito)
        2. Create virtualenv named "pyoos-dev": `mkvirtualenv -p your_python_binary pyoos-dev`
        3. Start using your new virtualenv: `workon pyoos-dev`
        
        
        ## Installation
        Pyoos requires python 2.7.x and is available on PyPI.
        
        The best way to install Pyoos is through pip:
        
        ```bash
        pip install pyoos
        ```
        
        Pyoos requires the following python libraries which will be downloaded and installed through `pip`:
        
        * Paegan>=0.9.9
          * numpy>=1.7.0
          * scipy
          * netCDF4>=1.0.2
          * Shapely>=1.2.15
          * pytz
          * python-dateutil>=1.5
        * OWSLib (install from git with `pip install git+http://github.com/geopython/OWSLib.git`)
        * requests
        * Fiona==0.16.1
        * beautifulsoup4==4.2.1
        * lxml>=3.2.0
        
        If your NetCDF4 and HDF5 libraries are in non-typical locations, you will need to pass the locations to the `pip` command:
        ```bash
        NETCDF4_DIR=path HDF5_DIR=path pip install pyoos
        ```
        
        There seems to be a problem installing numpy through `pip` dependency chains so you may need to install numpy before doing any of the above:
        
        ```bash
        pip install numpy==1.7.0
        ```
        
        ## Roadmap
        * Development of a standardized Metadata concept, possibly through SensorML and/or ISO 19115-2
        
        
        ## Use Cases
        Submit a PR with your use case!
        
        
        ## Troubleshooting
        If you are having trouble getting any of the pyoos functionality to work, try running the tests:
        
        ```bash
        git clone git@github.com:asascience-open/pyoos.git
        cd pyoos
        python setup.py test
        ```
        
        ## Contributors
        * Kyle Wilcox <kwilcox@asascience.com>
        * Sean Cowan <scowan@asascience.com>
        * Alex Crosby <acrosby@asascience.com>
        * Dave Foster <dfoster@asascience.com>
        
        
        Copyright and licence
        ---------------------
        
        Copyright (C) 2012, 2013  Applied Science Associates
        Copyright (C) 2012, 2013  Kyle Wilcox <wilcox.kyle@gmail.com>
        
        This file is part of Pyoos.
        
        Pyoos is free software: you can redistribute it and/or modify it under
        the terms of the GNU Lesser General Public License as published by the
        Free Software Foundation, either version 3 of the License, or
        (at your option) any later version.
        
        Pyoos is distributed in the hope that it will be useful,
        but WITHOUT ANY WARRANTY; without even the implied warranty of
        MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
        GNU Lesser General Public License for more details.
        
        You should have received a copy of the GNU Lesser General Public License
        along with Pyoos.  If not, see <http://www.gnu.org/licenses/>.
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
