Installation¶
Dependencies¶
sdmx
is a pure Python package requiring Python 3.9 or higher, which can be installed:
from the Python website, or
using a scientific Python distribution that includes other packages useful for data analysis, such as Anaconda, Canopy, or others listed on the Python wiki.
sdmx
also depends on:
Optional dependencies for extra features¶
for
cache
, allowing the caching of SDMX messages in memory, MongoDB, Redis, and more: requests-cache.for
tests
, to run the test suite: pytest and others.
Instructions¶
(optional) If using Anaconda, use source activate [ENV] to activate the environment in which to install
sdmx
.From the command line, issue:
$ pip install sdmx1
To also install optional dependencies, use commands like:
$ pip install sdmx1[cache] # just requests-cache $ pip install sdmx1[cache,docs,tests] # all extras
From source¶
Download the latest code:
from Github as a ZIP archive, or
by cloning the Github repository:
$ git clone git@github.com:khaeru/sdmx.git
In the package directory, issue:
$ pip install --editable .
or:
$ python setup.py install
To also install optional dependencies, use commands like:
$ pip install --editable .[cache] # just requests-cache $ pip install --editable .[cache,docs,tests] # all extras
Note
The pip --editable flag is recommended for development, so that changes to your code are reflected the next time sdmx
is imported.
Running tests¶
Install from source, including the tests
optional dependencies.
Then, in the package directory, issue:
$ pytest
By default, tests of the many supported data sources are skipped, because they involve retrieving data over a network connection, and some queries are large, so they can be slow to run. To also run these tests, use:
$ pytest -m source
Pytest offers many command-line options to control test invocation; see pytest --help or the documentation.