gabiteodoru-qpython 2.0.0

kdb+ interfacing library for Python

qPython (NumPy 2.0 Compatible Fork)

This is a fork of finos/qPython with NumPy 2.0 compatibility fixes applied.

Changes made:

• Date: 2025-01-24

• Fix: Replaced all numpy.string_ with numpy.bytes_ for NumPy 2.0 compatibility, also NaN with nan, etc

• Original qPython version: Latest from finos/qPython as of fork date

For the original project and full documentation, see: https://github.com/finos/qPython

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qPython (Original README below)

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.

Building package

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