dispy version 4.12.3 has been released. Major changes since previous release are:
dispynode under Windows doesn't force daemon mode. Command line now can be used to see the
status of computations, change CPUs, quit disypynode etc.
It is possible now to use client and nodes with different versions of Python 3 even if pickle
protocol versions are different. See pycos configuration variable PickleProtocolVersion; dispy
uses pycos for communication so setting this variable appropriately will allow serialization /
deserialization even if different Python versions use different default protocol versions (e.g.,
Python 3.7 and 3.8 use different protocol versions). Note that this will not work between Python
3 and Python 2.... read more
dispy version 4.12.2 has been released. In this version
dispy version 4.12.1 has been released. In this version
setup
only client uses this feature; otherwise, dispynode crashes. With this programs that don't use setup
, includingsample.py
in examples, work now.dispy version 4.12.0 has been released. In this version
resetup_node
method to JobCluster
. This method can be used to run cleanup
and setup
function with different depends and arguments to prepare the node for a new run of jobs. This is useful to, e.g., replace in-memory data to run jobs with data. pulse_interval
can now be set to as small as 0.1 (seconds).dispy version 4.11.1 has been released. In this version
dispy version 4.11.0 has been released. In this version
node_port
, dispyscheduler with scheduler_port
etc.), now only base dispy port (61590) needs to be given to all of them.config.py
module in dispy for convenience (useful in site-wide configuration).--admin_secret
option, nodes can be controlled with dispyadmin; otherwise, nodes are shown in the web interface but can't be managed.dispy.py
command line program to dispy_cmd.py
.depends
and setup_args
optional parameters to NodeAllocate
. This feature can be used to send node and computation specific dependent files and to use node and computation spefiic arguments to run setup function. setup
and cleanup
functions can no longer be partial functions.relay
optional parameter to dispy_provisional_result
and dispy_send_file
functions (that can be used in computation functions). If this parameter is False (default), results and files are sent from nodes to client directly, even if SharedJobCluster
is used. If this parameter is True, they are sent via dispyscheduler, which is required if nodes can't communicate with client directly (e.g., if secret between dispyscheduler and nodes is different from that between dispyscheduler and client or SSL setup is different).dispy version 4.10.6 has been released. In this version
submit_job_id
and submit_job_id_node
methods to cluster. These methods take 'id' argument that is set to job's id
attribute when job is created by scheduler so that when callback methods are called, the id
can be used by those methods. If id
is initialized by client after submit methods return job instance, the callback may be called before client can initialize (as dispy and callback run in other threads).id
attribute of jobs to distinguish jobs instead of the job instance itself; if jobs need to be stored in a dictionary, for example, they should be managed with id
attribute (which should be unique for each job created) and not job itself.suid
feature is used (so one computation doesn't access another computation's files).dispy version 4.10.5 has been released. In this version
DispyNode
instances now have tx
and rx
attributes that maintain amount data sent to / received from that node. print_status
method and web interface now show this information.dispy version 4.10.4 has been released. In this release
dispy version 4.10.3 has been released. In this release
submit_node
.discover_nodes
method to JobCluster
that clients can use to establish communication with nodes that may not be found when cluster initialized.dispy version 4.10.2 has been released. In this version
force_cleanup
to dispynode so all files transferred or created by computation are removed when computation is closed, even if computation disables cleanup.close_node
method.dispy version 4.10.1 has been released. In this release
dispy version 4.10.0 has been released. In this version
--unsafe_setup
option to dispynode to run setup and cleanup functions in main dispynode process, as used to be the case until 4.10.0 release.SharedJobCluster
so accept remote address as scheduler_node
parameter.dispy version 4.9.1 has been released. In this version
dispy version 4.9.0 has been released. In this release
dispy version 4.8.9 has been released. In this version
ext_ip_addr
option so even if netifaces module is available; in 4.8.8 this option didn't work if netifaces module is available.ipv4_udp_multicast
and daemon
options to dispynetrelay.dispy version 4.8.8 has been released. In this version
ipv4_udp_multicast
option to control whether to use multicast or broadcast for UDP (to discover nodes) with IPv4.dispy version 4.8.7 has been released. Changes since last release are:
dispy version 4.6.8 has been released. In this version
deallocate_node
and close_node
methods to cluster.dispy version 4.8.5 has been released. In this version
dispy version 4.8.4 has been released. In this version
SharedJobCluster
is closed with Python 3.dispy version 4.8.3 has been released. In this version
ext_ip_addr
option to dispynode.recover_jobs
function (which can be used for fault-recovery in case client crashes or loses network connection to nodes).recover_file
option to recover_jobs
is now optional; if this option is not given, latest file with prefix _dispy_
is used (default falut-recovery files are of the form _dispy_*
).dispy version 4.8.2 has been released. In this version,
dispy version 4.8.1 has been released. In this version crash with dispyscheduler (due to conflicts of names of variables and methods with change from asyncoro to pycos) has been fixed.
dispy version 4.8.0 has been released. In this release asyncoro module has been replaced with pycos module.