Remote Python Execution Functionality

Functionality for the generation and management of remote Python function execution.

Warning

This functionality is provided in it's present form as a BETA Feature and is subject to change. To enable this functionality for testing please following configuration instructions here setting PYKX_BETA_FEATURES='true'

session

session()

A session refers to a connection to a remote kdb+/q process against which users are defining/registering Python Functions which will return results to a Python session.

add_library

add_library(*args)

Add a list of Python libraries which will be imported prior to definition of a remote Python function, this allows users for example to import numpy and use it as a defined library within a remote function.

Parameters:

Name	Type	Description	Default
*args		A list of strings denoting the packages which are to be imported for use by a remote function.	()

Returns:

Type	Description
	Returns a None type object on successful invocation.

>>> from pykx.remote import session
>>> remote_session = session()
>>> remote_session.add_library('numpy', 'pandas')

create

create(
    host="localhost",
    port=None,
    *,
    username="",
    password="",
    timeout=0.0,
    large_messages=True,
    tls=False
)

Populate a session for use when generating a function for remote execution. This session will be backed by a SyncQConnection instance, note that only one session can be associated with a given instance of a session class.

Parameters:

Name	Type	Description	Default
host	Union[str, bytes]	The host name to which a connection is to be established.	'localhost'
port	int	The port to which a connection is to be established.	None
username	Union[str, bytes]	Username for q connection authorization.	''
password	Union[str, bytes]	Password for q connection authorization.	''
timeout	float	Timeout for blocking socket operations in seconds. If set to 0, the socket will be non-blocking.	0.0
large_messages	bool	Whether support for messages >2GB should be enabled.	True
tls	bool	Whether TLS should be used.	False

Returns:

Type	Description
	Returns a None type object on successful connection creation

• Connect to a q session on localhost at port 5050

  >>> from pykx.remote import session
  >>> remote_session = session()
  >>> remote_session.create(port = 5050)

• Connect to a user-password protected q session at a defined port

  >>> from pykx.remote import session
  >>> remote_session = session()
  >>> remote_session.create_session(port=5001, username='username', password='password')

clear

clear()

Reset/clear the session and libraries associated with a defined session information

Example:

>>> from pykx.remote import session
>>> remote_session = session()
>>> remote_session.create(port = 5050)
>>> remote_session.add_library('numpy')
>>> {'session': session._session, 'libraries': session._libraries}
{'session': pykx.QConnection(port=5001), 'libraries': ['numpy']}
>>> remote_session.clear()
>>> {'session': session._session, 'libraries': session._libraries}
{'session': None, 'libraries': []}

function

function(remote_session, *args)

This decorator allows users to tag functions which will be executed on a remote server defined by a kx.remote.session instance.

Parameters:

Name	Type	Description	Default
remote_session		Valid kx.remote.session object used to interact with external q process	required
*args		When invoked the decorated function will be passed supplied arguments	()

Returns:

Type	Description
	When invoked the decorated function will return the result as a PyKX object to the
	calling process

Examples:

• Call a basic decorated function on a remote process

  >>> from pykx.remote import session, function
  >>> remote_session = session()
  >>> session.create(port = 5050)
  >>> @function(session)
  ... def func(x):
  ...    return x+1
  >>> func(1)
  pykx.LongAtom(pykx.q('2'))

• Apply a function making use of a named library

  >>> from pykx.remote import session, function
  >>> remote_session = session()
  >>> session.create(port = 5050)
  >>> session.add_library('numpy')
  >>> @function(session)
  ... def func(start, stop, count):
  ...     return numpy.linspace(start, stop, count)
  >>> func(0, 10, 5)
  pykx.FloatVector(pykx.q('0 2.5 5 7.5 10'))