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.

To install qPython from PyPI:

$ pip install qpython3

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

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.

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

Instructions:

• Execute: python setup.py build_ext --inplace

Instructions:

• Execute: python setup.py bdist

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

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

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

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