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
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file pythonkdb-3.0.6.tar.gz
.
File metadata
- Download URL: pythonkdb-3.0.6.tar.gz
- Upload date:
- Size: 99.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.10.11
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | c367d010bf2e11b1962bfe4bb88c6061017673e317c64f2adf3619ae5f0f54d8 |
|
MD5 | 0d4d328013846b1454e33398498c5884 |
|
BLAKE2b-256 | a24c3908d285669afbdd6f2fb86bcb091268acb73424481e51573ad8f247a93b |
File details
Details for the file pythonKdb-3.0.6-cp310-cp310-win_amd64.whl
.
File metadata
- Download URL: pythonKdb-3.0.6-cp310-cp310-win_amd64.whl
- Upload date:
- Size: 71.6 kB
- Tags: CPython 3.10, Windows x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.10.11
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5ecbb7547286b13d24167fa125094b4282d39ca5c453adbc72ad32525838127e |
|
MD5 | 7a2229953c3ae76b2315dbfbd70cc3a9 |
|
BLAKE2b-256 | cb8a3e6f015e805ae1e96619b849dd2d871a2d8066fcb52e0ff70558ec086192 |