What are available tools/libraries to integrate Python
with kdb
?
Python and kdb integration [closed]
I guess you found bitbucket.org/halotis/qpy? –
Raffarty
I also found http://www.kx.com/a/k/connect/python/, along with http://bitbucket.org/halotis/qpy. I haven't used either.
I will add this one, and it even has some docs :) code.kx.com/trac/wiki/Contrib/PyQ#Releases –
Drubbing
kx.com/a/k/connect/python is a link to older releases of pyk - Python for kdb (not kdb+!). The latest (but still old) code for pyk can be found at code.kx.com/wsvn/code/contrib/serpent.speak/trunk/K. PyQ is a successor to pyk and provides Python for kdb+. –
Inconsistency
The timestored website has a guide to the python apis for kdb complete with videos. https://www.timestored.com/kdb-guides/python-api
To summarize your options:
- qPython - Newest API, supporting Python 2.7
- Dan Nugents Python Library - Still maintained API for pulling data into Python <=v2.6 from a kdb server. Faster than qpy.
- qpy - Original API that was based on kx.com's java API. Slower than Dans but nicer formatting of tables when printed.
- PyQ - Gone? - Brings Python and Q interpreters into the same process and allows code written in either of the languages to operate on the same data. Supports Python 2.7 and 3.x and all versions of kdb+.
- PyKX - Commercial
I also found http://www.kx.com/a/k/connect/python/, along with http://bitbucket.org/halotis/qpy. I haven't used either.
I will add this one, and it even has some docs :) code.kx.com/trac/wiki/Contrib/PyQ#Releases –
Drubbing
kx.com/a/k/connect/python is a link to older releases of pyk - Python for kdb (not kdb+!). The latest (but still old) code for pyk can be found at code.kx.com/wsvn/code/contrib/serpent.speak/trunk/K. PyQ is a successor to pyk and provides Python for kdb+. –
Inconsistency
there's also Dan Nugent's https://github.com/DannoHung/q
also note that, as with perl, sometimes the formatted export over the web socket is sufficient -- just GET http://SERVER.example:PORT/FMT?QUERY
, where FMT is any of csv/txt/xml/xls (e.g. http://localhost:5050/csv?table
)
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