ANN: pandaSDMX 0.3.0 released

[Dr. Leo]

Hi,

I am excited to announce the release of pandaSDMX 0.3.0, a major feature
release. The API has been streamlined. When requesting datasets, the key
to select columns may now be passed as a dict rather than obscure
string such as '...DE+FR.M'. Now you can simply type:

from pandasdmx import Request
une_resp = Request('ESTAT').get('data', 'une_rt_a', key={'GEO':
'EL+ES+IE', 'FREQ': 'A'},
params={'startPeriod': '2006'})

New features and improvements in v0.3.0:

* 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

See the documentation including an extensive tutorial at
pandasdmx.readthedocs.org


What it is:
=============

pandaSDMX is an Apache 2.0-licensed Python package aimed at becoming the
most intuitive and versatile tool to retrieve and acquire statistical
data and metadata disseminated in SDMX
format. It works well with the SDMX services of the European statistics
office (Eurostat) and the European Central Bank (ECB). Other agencies
may be supported as they adopt the XML flavour SDMX v2.1. While
pandaSDMX is extensible to cater any output format, it currently
supports only pandas.

Main features:

Liste mit 10 Einträgen
• intuitive API inspired by
requests
• support for many SDMX features including
Liste mit 4 Einträgen Verschachtelung 1
◦ generic datasets
◦ data structure definitions, code lists and concept schemes
◦ dataflow definitions and content-constraints
◦ categorisations and category schemes
Listenende Verschachtelung 1
• 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
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
Listenende

Enjoy!

Leo