Metadata-Version: 1.1
Name: pandaSDMX
Version: 0.3.1
Summary: A Python- and pandas-powered client for Statistical Data and Metadata eXchange
Home-page: https://github.com/dr-leo/pandasdmx
Author: Dr. Leo
Author-email: fhaxbox66@gmail.com
License: UNKNOWN
Description: =============
        pandaSDMX
        =============
        
        
        
        
        pandaSDMX is an Apache 2.0-licensed `Python <http://www.python.org>`_ 
        package aimed at becoming the 
        most intuitive and versatile tool to retrieve and acquire statistical data and metadata
        disseminated in `SDMX <http://www.sdmx.org>`_ format. 
        It should work with all
        SDMX data providers supporting SDMX 2.1. Currently,
        this is tested for the European statistics office (Eurostat),
        and the European Central Bank (ECB) each providing hundreds of
        thousands of time series. 
        
        While pandaSDMX is extensible to 
        cater any output format, it currently supports only `pandas <http://pandas.pydata.org>`_, the gold-standard 
        of data analysis in Python. But from pandas you can export your data to Excel and friends. 
        
        Main features
        ---------------------
        
        * intuitive API inspired by `requests <https://pypi.python.org/pypi/requests/>`_  
        * support for many SDMX features including
        
          - generic datasets
          - data structure definitions, code lists and concept schemes
          - dataflow definitions and content-constraints
          - categorisations and category schemes
        
        * pythonic representation of the SDMX information model  
        * find dataflows by name or description in multiple languages if available
        * When requesting datasets, validate column selections against code lists 
          and content-constraints if available 
        * read and write SDMX messages to and from local files 
        * configurable HTTP connections
        * support for `requests-cache <https://readthedocs.org/projects/requests-cache/>`_ allowing to cache SDMX messages in 
          memory, MongoDB, Redis or SQLite  
        * writer transforming SDMX generic datasets into multi-indexed pandas DataFrames or Series of observations and attributes 
        * extensible through custom readers and writers for alternative input and output formats of data and metadata
        
        For further details including extensive code examples
        see the 
        `documentation <http://pandasdmx.readthedocs.org>`_ . 
        
        
        pandaSDMX Links
        -------------------------------
        
        * `Documentation <http://pandasdmx.readthedocs.org>`_
        * `Mailing list <https://groups.google.com/forum/?hl=en#!forum/sdmx-python>`_  
        * `github <https://github.com/dr-leo/pandaSDMX>`_
         
          
          
        Recent changes 
        ========================
        
        v0.3.0 (2015-09-22)
        -----------------------
        
        
        * support for `requests-cache <https://readthedocs.org/projects/requests-cache/>`_ allowing to cache SDMX messages in 
          memory, MongoDB, Redis or SQLite 
        * pythonic selection of series when requesting a dataset:
          Request.get allows the ``key`` keyword argument in a data request to be a dict mapping dimension names 
          to values. In this case, the dataflow definition and datastructure 
          definition, and content-constraint
          are downloaded on the fly, cached in memory and used to validate the keys. 
          The dotted key string needed to construct the URL will be generated automatically. 
        * The Response.write method takes a ``parse_time`` keyword arg. Set it to False to avoid
          parsing of dates, times and time periods as exotic formats may cause crashes.
        * The Request.get method takes a ``memcache`` keyward argument. If set to a string,
          the received Response instance will be stored in the dict ``Request.cache`` for later use. This is useful
          when, e.g., a DSD is needed multiple times to validate keys.
        * fixed base URL for Eurostat  
        * major refactorings to enhance code maintainability
        
        v0.2.2 (2015-05-19)
        -------------------------------
        
        * Make HTTP connections configurable by exposing the 
          `requests.get API <http://www.python-requests.org/en/latest/>`_ 
          through the ``pandasdmx.api.Request`` constructor.
          Hence, proxy servers, authentication information and other HTTP-related parameters consumed by ``requests.get`` can be
          set for an ``Request`` instance and used in subsequent requests. The configuration is
          exposed as a dict through the ``Request.client.config`` attribute.
        * Responses now have an ``http_headers`` attribute containing the headers returned by the SDMX server
        
        
        v0.2.1 (2015-04-22)
        ----------------------------------
        
        * API: add support for zip archives received from an SDMX server. 
          This is common for large datasets from Eurostat
        * incidentally get a remote resource if the footer of a received message
          specifies an URL. This pattern is common for large datasets from Eurostat.
        * allow passing a file-like object to api.Request.get() 
        * enhance documentation
        * make pandas writer parse more time period formats and increase its performance  
          
        v0.2.0 (2015-04-13)
        ------------------------------------
        
        
        This version is a quantum leap. The whole project has been redesigned and rewritten from
        scratch to provide robust support for many SDMX features. The new architecture is centered around
        a pythonic representation of the SDMX information model. It is extensible through readers and writers
        for alternative input and output formats. 
        Export to pandas has been dramatically improved. Sphinx documentation
        has been added.
        
        v0.1 (2014-09)
        ----------------
        
        Initial release
        
         
        
        
        
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Provides: pandasdmx
