Installation¶
Dependencies¶
sdmx
is a pure Python package requiring Python 3.7 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:
pandas for data structures,
pydantic to implement the IM,
requests for HTTP requests, and
lxml for XML processing.
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 requests-mock.
Instructions¶
(optional) If using Anaconda, use
source activate [ENV]
to activate the environment in which to installsdmx
.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 respository:
$ 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:
$ py.test
By default, tests that involve retrieving data over the network are skipped. To also run these tests, use:
$ py.test --remote-data
pytest offers many command-line options to control test invocation; see py.test --help
or the documentation.