Dahu Package

You can have a look at the man pages of the CLi tool: dahu-reprocess and dahu_server which is the Tang-device server.

This is the public API of dahu.

dahu.job

Data Analysis RPC server over Tango:

Contains the Job class which handles jobs. A static part of the class contains statistics of the class

class Job(name='plugin.Plugin', input_data={})[source]

Bases: threading.Thread

Class Job

  • Each instance will be a job
  • Constructor takes an input data and generates the JobId
  • Each instance will gave a “getOutput” method with optional join
  • there could be a “join” method, waiting for the job to finish
  • Each instance will have a “execute” method and returning a JobId
  • Each instance will have a “setCallBack” method that stores the name of the external callback
  • provide status of a job
  • Each instance has an abort method which can be used to stop processing (or a server)

Static part: * keeps track of all jobs status * leave the time to job to initialize * static class retrieve job-instance, status, small-log … * does not manage workload of the computer, should be managed at the ExecPlugin level

Used for the tango binding

== class variables == dictPluginStatus[pluginName] = [“uninitialized”|”running”|”executed”|”failed”] dictJobs [JobId] = Job.Instance

== static methods == getJob(JobId)

RESERVED keywords from Thread: start, run, join, name, ident, is_alive, daemon

start is overridden with a call to the factory to instanciate the plugin

STATE_INEXISTANT = 'inexistant'
STATE_UNINITIALIZED = 'uninitialized'
STATE_STARTING = 'starting'
STATE_RUNNING = 'running'
STATE_SUCCESS = 'success'
STATE_FAILURE = 'failure'
STATE_ABORTED = 'aborted'
STATE = ['uninitialized', 'starting', 'running', 'success', 'failure', 'aborted']
start()[source]

We need to create the plugin before starting the new tread…

join(timeout=None)[source]

Wait until the thread terminates.

This blocks the calling thread until the thread whose join() method is called terminates – either normally or through an unhandled exception or until the optional timeout occurs.

When the timeout argument is present and not None, it should be a floating point number specifying a timeout for the operation in seconds (or fractions thereof). As join() always returns None, you must call is_alive() after join() to decide whether a timeout happened – if the thread is still alive, the join() call timed out.

When the timeout argument is not present or None, the operation will block until the thread terminates.

A thread can be join()ed many times.

join() raises a RuntimeError if an attempt is made to join the current thread as that would cause a deadlock. It is also an error to join() a thread before it has been started and attempts to do so raises the same exception.

abort()[source]

Tell the job to stop !

Needs to be implemented into the plugin !

run()[source]

Defines the sequence of execution of the plugin 1) the the state to “running” 2) sets the input data to the plugin 3) run the set-up 4) run the process 4) run the tear-down: always runs tear-down ! 5) run the call-backs

connect_callback(method=None)[source]
Parameters:method – function or method to be called - back
clean(force=False, wait=True)[source]

Frees the memory associated with the plugin

Parameters:
  • force – Force garbage collection after clean-up
  • wait – wait for job to be finished
synchronize(timeout=None)

Wait until the thread terminates.

This blocks the calling thread until the thread whose join() method is called terminates – either normally or through an unhandled exception or until the optional timeout occurs.

When the timeout argument is present and not None, it should be a floating point number specifying a timeout for the operation in seconds (or fractions thereof). As join() always returns None, you must call is_alive() after join() to decide whether a timeout happened – if the thread is still alive, the join() call timed out.

When the timeout argument is not present or None, the operation will block until the thread terminates.

A thread can be join()ed many times.

join() raises a RuntimeError if an attempt is made to join the current thread as that would cause a deadlock. It is also an error to join() a thread before it has been started and attempts to do so raises the same exception.

id
Returns:JobId

@rtype: integer

plugin
Returns:the processing instance

@rtype: python object

status
Returns:status of the Job

@rtype: string

input_data

Returns the job input data

output_data

Returns the job output data :param _bWait: shall we wait for the plugin to finish to retrieve output data: Yes by default. :type _bWait: boolean

getName()[source]
setName(name)[source]
name
classmethod synchronize_all()[source]

Wait for all jobs to finish.

classmethod synchronize_job(jobId, timeout=None)[source]

Wait for all a specific jobs to finish.

Parameters:
  • jobId – identifier of the job … intg
  • timeout – timeout in second to wait
Returns:

status of the job

classmethod getStatusFromID(jobId)[source]

Retrieve the job (hence the plugin) status

Parameters:jobId (int) – the Job identification number
Returns:the Job status

@rtype: string

classmethod getStatusFromId(jobId)

Retrieve the job (hence the plugin) status

Parameters:jobId (int) – the Job identification number
Returns:the Job status

@rtype: string

classmethod getJobFromID(jobId)[source]

Retrieve the job (hence the plugin)

Parameters:jobId – the Job identification number
Returns:the “Job instance”, which contains the plugin and the status

@rtype: a Python object, instance of Job.

classmethod getJobFromId(jobId)

Retrieve the job (hence the plugin)

Parameters:jobId – the Job identification number
Returns:the “Job instance”, which contains the plugin and the status

@rtype: a Python object, instance of Job.

classmethod cleanJobfromId(jobId, forceGC=True)[source]

Frees the memory associated with the top level plugin

Parameters:
  • jobId (int) – the Job identification number
  • forceGC (boolean) – Force garbage collection after clean-up
classmethod cleanJobfromID(jobId, forceGC=True)

Frees the memory associated with the top level plugin

Parameters:
  • jobId (int) – the Job identification number
  • forceGC (boolean) – Force garbage collection after clean-up
classmethod getDataOutputFromId(jobId, as_JSON=False)[source]

Returns the Plugin Output Data :param jobId: job idenfier :type jobId: int :return: Job.DataOutput JSON string

classmethod getDataOutputFromID(jobId, as_JSON=False)

Returns the Plugin Output Data :param jobId: job idenfier :type jobId: int :return: Job.DataOutput JSON string

classmethod getDataInputFromId(jobId, as_JSON=False)[source]

Returns the Plugin Input Data :param jobId: job idenfier :type jobId: int :return: Job.DataInput JSON string

classmethod getDataInputFromID(jobId, as_JSON=False)

Returns the Plugin Input Data :param jobId: job idenfier :type jobId: int :return: Job.DataInput JSON string

classmethod getErrorFromId(jobId)[source]

Returns the error messages from plugin :param jobId: job idenfier :type jobId: int :return: error message as a string

classmethod getErrorFromID(jobId)

Returns the error messages from plugin :param jobId: job idenfier :type jobId: int :return: error message as a string

classmethod stats()[source]

Retrieve some statistics and print them

dahu.plugin

Data Analysis RPC server over Tango:

Definiton of plugins

class Plugin[source]

Bases: object

A plugin is instanciated

  • Gets its input parameters as a dictionary from the setup method
  • Performs some work in the process
  • Sets the result as output attribute, should be a dictionary
  • The process can be an infinite loop or a server which can be aborted using the abort method
DEFAULT_SET_UP = 'setup'
DEFAULT_PROCESS = 'process'
DEFAULT_TEAR_DOWN = 'teardown'
DEFAULT_ABORT = 'abort'
REPROCESS_IGNORE = []
get_name()[source]
setup(kwargs=None)[source]

This is the second constructor to setup input variables and possibly initialize some objects

process()[source]

main processing of the plugin

teardown()[source]

method used to tear-down the plugin (close connection, files)

This is always run, even if process fails

get_info()[source]
abort()[source]

Method called to stop a server process

log_error(txt, do_raise=True)[source]

Way to log errors and raise error

log_warning(txt)[source]

Way to log warning

wait_for(job_id)[source]

Wait for another job to be finished …

Parameters:job_id – identifier for the job
Returns:the job object
class PluginFromFunction[source]

Bases: dahu.plugin.Plugin

Template class to build a plugin from a function

process()[source]

main processing of the plugin

plugin_from_function(function)[source]

Create a plugin class from a given function and registers it into the

Parameters:function – any function
Returns:plugin name to be used by the plugin_factory to get an instance

dahu.factory

Data Analysis RPC server over Tango:

Factory for the loading of plugins

load_source(module_name, file_path)[source]

Plugin loader which does not pollute sys.module

class Factory(workdir=None, plugin_path=None)[source]

Bases: object

This is a factory, it instanciates a plugin from it name

registry = {}
modules = {}
plugin_dirs = {'/home/tester/dahu/build/lib/dahu/plugins': ['id15v2', 'id02', 'bm29', 'focus', 'id15', 'id31', 'example', 'pyfai']}
reg_sem = <threading.Semaphore object>
add_directory(directory)[source]
search_plugin(plugin_name)[source]

Search for a given plugins … starting from the FQN package.class,

classmethod register(klass, fqn=None)[source]

Register a class as a plugin which can be instanciated.

This can be used as a decorator

@plugin_factor.register

@param klass: class to be registered as a plugin @param fqn: fully qualified name @return klass

dahu.server

dahu.cache

Data Analysis RPC server over Tango:

Class Cache for storing the data in a Borg

class DataCache(max_size=10)[source]

Bases: dict

This class is a Borg : always returns the same values regardless to the instance of the object it is used as data storage for images … with a limit on the number of images to keep in memory.

has_key(key)

D.__contains__(k) -> True if D has a key k, else False

get(key, default=None)[source]

get method with default answer implemented

keys()[source]

Returns the list of keys, ordered

pop(key)[source]

Remove a key for the dictionary and return it’s value

dahu.utils