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kdb+ interfacing library for Python

Project description

qPython

qPython is a Python library providing support for interprocess communication between Python and kdb+ processes, it offers:

  • Synchronous and asynchronous queries
  • Convenient asynchronous callbacks mechanism
  • Support for kdb+ protocol and types as of kdb+ v4.0
  • Uncompression of the IPC data stream
  • Internal representation of data via numpy arrays (lists, complex types) and numpy data types (atoms)
  • Supported on Python 3.4/3.5/3.6 and numpy 1.8+

For more details please refer to the documentation_.

Installation

To install qPython from PyPI:

$ pip install qpython3

Please do not use old PyPI package name: qpython or exxeleron-qpython.

To install qPython from internal PyPI:

``$ pip install --trusted-host pypi.dts.corp.local --extra-index-url https://pypi.dts.corp.local/root/citizen/+simple/ qpython

Building package

``$ python setup.py sdist bdist_wheel

Documentation


qPython documentation is generated with help of `Sphinx`_ document generator.
In order to build the documentation, including the API docs, execute:
``make html`` from the doc directory.

Documentation is built into the: ``doc/build/html/`` directory.


Compile Cython extensions

qPython utilizes Cython_ to tune performance critical parts of the code.

Instructions:

  • Execute: python setup.py build_ext --inplace

Build binary distribution


Instructions:

- Execute: ``python setup.py bdist``


Testing
~~~~~~~

qPython uses py.test as a test runner for unit tests.

Instructions:

- Make sure that top directory is included in the ``PYTHONPATH``
- Execute: ``py.test``


CVE Scanning
~~~~~~~~~~~~

Configured GitHub Action as per the "Python" section of:

- https://github.com/maoo/security-scanning


Requirements
~~~~~~~~~~~~

qPython requires numpy 1.8 to run.

Optional requirements have to be met to provide additional features:

- tune performance of critical parts of the code:

  - Cython 0.20.1

- support serialization/deserialization of ``pandas.Series`` and ``pandas.DataFrame``

  - pandas 0.14.0

- run Twisted sample:

  - Twisted 13.2.0

- build documentation via Sphinx:

  - Sphinx 1.2.3
  - mock 1.0.1

Required libraries can be installed using `pip`_.

To install all the required dependencies, execute:
``pip install -r requirements.txt``

Minimal set of required dependencies can be installed by executing:
``pip install -r requirements-minimal.txt``

.. _Cython: http://cython.org/
.. _Sphinx: http://sphinx-doc.org/
.. _pip: http://pypi.python.org/pypi/pip
.. _documentation: http://qpython.readthedocs.org/en/latest/

Project details


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