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# parallel.client.view

## Module: `parallel.client.view`

Inheritance diagram for `IPython.parallel.client.view`:

Views of remote engines.

Authors:

- Min RK

## Classes

### `DirectView`

class `IPython.parallel.client.view.``DirectView`(client=None, socket=None, targets=None)

  Bases: `IPython.parallel.client.view.View`

  Direct Multiplexer View of one or more engines.

  These are created via indexed access to a client:

      >>> dv_1 = client[1]
      >>> dv_all = client[:]
      >>> dv_even = client[::2]
      >>> dv_some = client[1:3]

  This object provides dictionary access to engine namespaces:

  # push a=5: >>> dv[‘a’] = 5 # pull ‘foo’: >>> db[‘foo’]

  `__init__`(client=None, socket=None, targets=None)
  `abort`(jobs=None, targets=None, block=None)

    Abort jobs on my engines.

    Parameters : | jobs : None, str, list of strs, optional if None: abort all jobs. else: abort specific msg_id(s).

  `activate`()

    Make this View active for parallel magic commands.

    IPython has a magic command syntax to work with MultiEngineClient objects. In a given IPython session there is a single active one. While there can be many Views created and used by the user, there is only one active one. The active View is used whenever the magic commands %px and %autopx are used.

    The activate() method is called on a given View to make it active. Once this has been done, the magic commands can be used.

  `apply`(f, *args, **kwargs)

    calls f(*args, **kwargs) on remote engines, returning the result.

    This method sets all apply flags via this View’s attributes.

    if self.block is False:
      returns AsyncResult
    else:
      returns actual result of f(*args, **kwargs)
  `apply_async`(f, *args, **kwargs)

    calls f(*args, **kwargs) on remote engines in a nonblocking manner.

    returns AsyncResult

  `apply_sync`(f, *args, **kwargs)
    calls f(*args, **kwargs) on remote engines in a blocking manner,
      returning the result.

    returns: actual result of f(*args, **kwargs)

  `block`

    A boolean (True, False) trait.

  classmethod `class_trait_names`(**metadata)

    Get a list of all the names of this classes traits.

    This method is just like the `trait_names()` method, but is unbound.

  classmethod `class_traits`(**metadata)

    Get a list of all the traits of this class.

    This method is just like the `traits()` method, but is unbound.

    The TraitTypes returned don’t know anything about the values that the various HasTrait’s instances are holding.

    This follows the same algorithm as traits does and does not allow for any simple way of specifying merely that a metadata name exists, but has any value. This is because get_metadata returns None if a metadata key doesn’t exist.

  `clear`(targets=None, block=False)

    Clear the remote namespaces on my engines.

  `client`

    A trait whose value must be an instance of a specified class.

    The value can also be an instance of a subclass of the specified class.

  `execute`(code, targets=None, block=None)

    Executes code on targets in blocking or nonblocking manner.

    `execute` is always bound (affects engine namespace)

    Parameters : | code : str the code string to be executed block : bool whether or not to wait until done to return default: self.block

  `gather`(key, dist='b', targets=None, block=None)

    Gather a partitioned sequence on a set of engines as a single local seq.

  `get`(key_s)

    get object(s) by key_s from remote namespace

    see pull for details.

  `get_result`(indices_or_msg_ids=None)

    return one or more results, specified by history index or msg_id.

    See client.get_result for details.

  `history`

    An instance of a Python list.

  `imap`(f, *sequences, **kwargs)

    Parallel version of itertools.imap.

    See self.map for details.

  `importer`

    sync_imports(local=True) as a property.

    See sync_imports for details.

  `kill`(targets=None, block=True)

    Kill my engines.

  `map`(f, *sequences, **kwargs)

    view.map(f, *sequences, block=self.block) => list|AsyncMapResult

    Parallel version of builtin map, using this View’s targets.

    There will be one task per target, so work will be chunked if the sequences are longer than targets.

    Results can be iterated as they are ready, but will become available in chunks.

    Parameters : | f : callable function to be mapped *sequences: one or more sequences of matching length : the sequences to be distributed and passed to f block : bool whether to wait for the result or not [default self.block]
    Returns : | if block=False: : AsyncMapResult An object like AsyncResult, but which reassembles the sequence of results into a single list. AsyncMapResults can be iterated through before all results are complete. else: : list the result of map(f,*sequences)

  `map_async`(f, *sequences, **kwargs)

    Parallel version of builtin map, using this view’s engines.

    This is equivalent to map(...block=False)

    See self.map for details.

  `map_sync`(f, *sequences, **kwargs)

    Parallel version of builtin map, using this view’s engines.

    This is equivalent to map(...block=True)

    See self.map for details.

  `on_trait_change`(handler, name=None, remove=False)

    Setup a handler to be called when a trait changes.

    This is used to setup dynamic notifications of trait changes.

    Static handlers can be created by creating methods on a HasTraits subclass with the naming convention ‘_[traitname]_changed’. Thus, to create static handler for the trait ‘a’, create the method _a_changed(self, name, old, new) (fewer arguments can be used, see below).

    Parameters : | handler : callable A callable that is called when a trait changes. Its signature can be handler(), handler(name), handler(name, new) or handler(name, old, new). name : list, str, None If None, the handler will apply to all traits. If a list of str, handler will apply to all names in the list. If a str, the handler will apply just to that name. remove : bool If False (the default), then install the handler. If True then unintall it.

  `outstanding`

    An instance of a Python set.

  `parallel`(dist='b', block=None, **flags)

    Decorator for making a ParallelFunction

  `pull`(names, targets=None, block=None)

    get object(s) by name from remote namespace

    will return one object if it is a key. can also take a list of keys, in which case it will return a list of objects.

  `purge_results`(jobs=[], targets=[])

    Instruct the controller to forget specific results.

  `push`(ns, targets=None, block=None, track=None)

    update remote namespace with dict ns

    Parameters : | ns : dict dict of keys with which to update engine namespace(s) block : bool [default whether to wait to be notified of engine receipt

  `queue_status`(targets=None, verbose=False)

    Fetch the Queue status of my engines

  `remote`(block=True, **flags)

    Decorator for making a RemoteFunction

  `results`

    An instance of a Python dict.

  `run`(filename, targets=None, block=None)

    Execute contents of filename on my engine(s).

    This simply reads the contents of the file and calls execute.

    Parameters : | filename : str The path to the file targets : int/str/list of ints/strs the engines on which to execute default : all block : bool whether or not to wait until done default: self.block

  `scatter`(key, seq, dist='b', flatten=False, targets=None, block=None, track=None)

    Partition a Python sequence and send the partitions to a set of engines.

  `set_flags`(**kwargs)

    set my attribute flags by keyword.

    Views determine behavior with a few attributes (block, track, etc.). These attributes can be set all at once by name with this method.

    Parameters : | block : bool whether to wait for results track : bool whether to create a MessageTracker to allow the user to safely edit after arrays and buffers during non-copying sends.

  `shutdown`(targets=None, restart=False, hub=False, block=None)

    Terminates one or more engine processes, optionally including the hub.

  `spin`()

    spin the client, and sync

  `sync_imports`(*args, **kwds)

    Context Manager for performing simultaneous local and remote imports.

    ‘import x as y’ will not work. The ‘as y’ part will simply be ignored.

        >>> with view.sync_imports():
        ...    from numpy import recarray
        importing recarray from numpy on engine(s)

  `targets`
  `temp_flags`(*args, **kwds)

    temporarily set flags, for use in with statements.

    See set_flags for permanent setting of flags

    Examples

        >>> view.track=False
        ...
        >>> with view.temp_flags(track=True):
        ...    ar = view.apply(dostuff, my_big_array)
        ...    ar.tracker.wait() # wait for send to finish
        >>> view.track
        False

  `track`

    A boolean (True, False) trait.

  `trait_metadata`(traitname, key)

    Get metadata values for trait by key.

  `trait_names`(**metadata)

    Get a list of all the names of this classes traits.

  `traits`(**metadata)

    Get a list of all the traits of this class.

    The TraitTypes returned don’t know anything about the values that the various HasTrait’s instances are holding.

    This follows the same algorithm as traits does and does not allow for any simple way of specifying merely that a metadata name exists, but has any value. This is because get_metadata returns None if a metadata key doesn’t exist.

  `update`(ns)

    update remote namespace with dict ns

    See push for details.

  `wait`(jobs=None, timeout=-1)

    waits on one or more jobs, for up to timeout seconds.

    Parameters : | jobs : int, str, or list of ints and/or strs, or one or more AsyncResult objects ints are indices to self.history strs are msg_ids default: wait on all outstanding messages timeout : float a time in seconds, after which to give up. default is -1, which means no timeout
    Returns : | True : when all msg_ids are done False : timeout reached, some msg_ids still outstanding

### `LoadBalancedView`

class `IPython.parallel.client.view.``LoadBalancedView`(client=None, socket=None, **flags)

  Bases: `IPython.parallel.client.view.View`

  An load-balancing View that only executes via the Task scheduler.

  Load-balanced views can be created with the client’s view method:

      >>> v = client.load_balanced_view()

  or targets can be specified, to restrict the potential destinations:

      >>> v = client.client.load_balanced_view([1,3])

  which would restrict loadbalancing to between engines 1 and 3.

  `__init__`(client=None, socket=None, **flags)
  `abort`(jobs=None, targets=None, block=None)

    Abort jobs on my engines.

    Parameters : | jobs : None, str, list of strs, optional if None: abort all jobs. else: abort specific msg_id(s).

  `after`
  `apply`(f, *args, **kwargs)

    calls f(*args, **kwargs) on remote engines, returning the result.

    This method sets all apply flags via this View’s attributes.

    if self.block is False:
      returns AsyncResult
    else:
      returns actual result of f(*args, **kwargs)
  `apply_async`(f, *args, **kwargs)

    calls f(*args, **kwargs) on remote engines in a nonblocking manner.

    returns AsyncResult

  `apply_sync`(f, *args, **kwargs)
    calls f(*args, **kwargs) on remote engines in a blocking manner,
      returning the result.

    returns: actual result of f(*args, **kwargs)

  `block`

    A boolean (True, False) trait.

  classmethod `class_trait_names`(**metadata)

    Get a list of all the names of this classes traits.

    This method is just like the `trait_names()` method, but is unbound.

  classmethod `class_traits`(**metadata)

    Get a list of all the traits of this class.

    This method is just like the `traits()` method, but is unbound.

    The TraitTypes returned don’t know anything about the values that the various HasTrait’s instances are holding.

    This follows the same algorithm as traits does and does not allow for any simple way of specifying merely that a metadata name exists, but has any value. This is because get_metadata returns None if a metadata key doesn’t exist.

  `client`

    A trait whose value must be an instance of a specified class.

    The value can also be an instance of a subclass of the specified class.

  `follow`
  `get_result`(indices_or_msg_ids=None)

    return one or more results, specified by history index or msg_id.

    See client.get_result for details.

  `history`

    An instance of a Python list.

  `imap`(f, *sequences, **kwargs)

    Parallel version of itertools.imap.

    See self.map for details.

  `map`(f, *sequences, **kwargs)

    view.map(f, *sequences, block=self.block, chunksize=1, ordered=True) => list|AsyncMapResult

    Parallel version of builtin map, load-balanced by this View.

    block, and chunksize can be specified by keyword only.

    Each chunksize elements will be a separate task, and will be load-balanced. This lets individual elements be available for iteration as soon as they arrive.

    Parameters : | f : callable function to be mapped *sequences: one or more sequences of matching length : the sequences to be distributed and passed to f block : bool [default self.block] whether to wait for the result or not track : bool whether to create a MessageTracker to allow the user to safely edit after arrays and buffers during non-copying sends. chunksize : int [default 1] how many elements should be in each task. ordered : bool [default True] Whether the results should be gathered as they arrive, or enforce the order of submission. Only applies when iterating through AsyncMapResult as results arrive. Has no effect when block=True.
    Returns : | if block=False: : AsyncMapResult An object like AsyncResult, but which reassembles the sequence of results into a single list. AsyncMapResults can be iterated through before all results are complete. else: the result of map(f,*sequences)

  `map_async`(f, *sequences, **kwargs)

    Parallel version of builtin map, using this view’s engines.

    This is equivalent to map(...block=False)

    See self.map for details.

  `map_sync`(f, *sequences, **kwargs)

    Parallel version of builtin map, using this view’s engines.

    This is equivalent to map(...block=True)

    See self.map for details.

  `on_trait_change`(handler, name=None, remove=False)

    Setup a handler to be called when a trait changes.

    This is used to setup dynamic notifications of trait changes.

    Static handlers can be created by creating methods on a HasTraits subclass with the naming convention ‘_[traitname]_changed’. Thus, to create static handler for the trait ‘a’, create the method _a_changed(self, name, old, new) (fewer arguments can be used, see below).

    Parameters : | handler : callable A callable that is called when a trait changes. Its signature can be handler(), handler(name), handler(name, new) or handler(name, old, new). name : list, str, None If None, the handler will apply to all traits. If a list of str, handler will apply to all names in the list. If a str, the handler will apply just to that name. remove : bool If False (the default), then install the handler. If True then unintall it.

  `outstanding`

    An instance of a Python set.

  `parallel`(dist='b', block=None, **flags)

    Decorator for making a ParallelFunction

  `purge_results`(jobs=[], targets=[])

    Instruct the controller to forget specific results.

  `queue_status`(targets=None, verbose=False)

    Fetch the Queue status of my engines

  `remote`(block=True, **flags)

    Decorator for making a RemoteFunction

  `results`

    An instance of a Python dict.

  `retries`

    An integer trait.

    Longs that are unnecessary (<= sys.maxint) are cast to ints.

  `set_flags`(**kwargs)

    set my attribute flags by keyword.

    A View is a wrapper for the Client’s apply method, but with attributes that specify keyword arguments, those attributes can be set by keyword argument with this method.

    Parameters : | block : bool whether to wait for results track : bool whether to create a MessageTracker to allow the user to safely edit after arrays and buffers during non-copying sends. after : Dependency or collection of msg_ids Only for load-balanced execution (targets=None) Specify a list of msg_ids as a time-based dependency. This job will only be run after the dependencies have been met. follow : Dependency or collection of msg_ids Only for load-balanced execution (targets=None) Specify a list of msg_ids as a location-based dependency. This job will only be run on an engine where this dependency is met. timeout : float/int or None Only for load-balanced execution (targets=None) Specify an amount of time (in seconds) for the scheduler to wait for dependencies to be met before failing with a DependencyTimeout. retries : int Number of times a task will be retried on failure.

  `shutdown`(targets=None, restart=False, hub=False, block=None)

    Terminates one or more engine processes, optionally including the hub.

  `spin`()

    spin the client, and sync

  `targets`
  `temp_flags`(*args, **kwds)

    temporarily set flags, for use in with statements.

    See set_flags for permanent setting of flags

    Examples

        >>> view.track=False
        ...
        >>> with view.temp_flags(track=True):
        ...    ar = view.apply(dostuff, my_big_array)
        ...    ar.tracker.wait() # wait for send to finish
        >>> view.track
        False

  `timeout`

    A casting version of the float trait.

  `track`

    A boolean (True, False) trait.

  `trait_metadata`(traitname, key)

    Get metadata values for trait by key.

  `trait_names`(**metadata)

    Get a list of all the names of this classes traits.

  `traits`(**metadata)

    Get a list of all the traits of this class.

    The TraitTypes returned don’t know anything about the values that the various HasTrait’s instances are holding.

    This follows the same algorithm as traits does and does not allow for any simple way of specifying merely that a metadata name exists, but has any value. This is because get_metadata returns None if a metadata key doesn’t exist.

  `wait`(jobs=None, timeout=-1)

    waits on one or more jobs, for up to timeout seconds.

    Parameters : | jobs : int, str, or list of ints and/or strs, or one or more AsyncResult objects ints are indices to self.history strs are msg_ids default: wait on all outstanding messages timeout : float a time in seconds, after which to give up. default is -1, which means no timeout
    Returns : | True : when all msg_ids are done False : timeout reached, some msg_ids still outstanding

### `View`

class `IPython.parallel.client.view.``View`(client=None, socket=None, **flags)

  Bases: `IPython.utils.traitlets.HasTraits`

  Base View class for more convenint apply(f,*args,**kwargs) syntax via attributes.

  Don’t use this class, use subclasses.

  Methods : | spin : flushes incoming results and registration state changes control methods spin, and requesting ids also ensures up to date wait : wait on one or more msg_ids execution methods : apply legacy: execute, run data movement : push, pull, scatter, gather query methods : get_result, queue_status, purge_results, result_status control methods : abort, shutdown

  `__init__`(client=None, socket=None, **flags)
  `abort`(jobs=None, targets=None, block=None)

    Abort jobs on my engines.

    Parameters : | jobs : None, str, list of strs, optional if None: abort all jobs. else: abort specific msg_id(s).

  `apply`(f, *args, **kwargs)

    calls f(*args, **kwargs) on remote engines, returning the result.

    This method sets all apply flags via this View’s attributes.

    if self.block is False:
      returns AsyncResult
    else:
      returns actual result of f(*args, **kwargs)
  `apply_async`(f, *args, **kwargs)

    calls f(*args, **kwargs) on remote engines in a nonblocking manner.

    returns AsyncResult

  `apply_sync`(f, *args, **kwargs)
    calls f(*args, **kwargs) on remote engines in a blocking manner,
      returning the result.

    returns: actual result of f(*args, **kwargs)

  `block`

    A boolean (True, False) trait.

  classmethod `class_trait_names`(**metadata)

    Get a list of all the names of this classes traits.

    This method is just like the `trait_names()` method, but is unbound.

  classmethod `class_traits`(**metadata)

    Get a list of all the traits of this class.

    This method is just like the `traits()` method, but is unbound.

    The TraitTypes returned don’t know anything about the values that the various HasTrait’s instances are holding.

    This follows the same algorithm as traits does and does not allow for any simple way of specifying merely that a metadata name exists, but has any value. This is because get_metadata returns None if a metadata key doesn’t exist.

  `client`

    A trait whose value must be an instance of a specified class.

    The value can also be an instance of a subclass of the specified class.

  `get_result`(indices_or_msg_ids=None)

    return one or more results, specified by history index or msg_id.

    See client.get_result for details.

  `history`

    An instance of a Python list.

  `imap`(f, *sequences, **kwargs)

    Parallel version of itertools.imap.

    See self.map for details.

  `map`(f, *sequences, **kwargs)

    override in subclasses

  `map_async`(f, *sequences, **kwargs)

    Parallel version of builtin map, using this view’s engines.

    This is equivalent to map(...block=False)

    See self.map for details.

  `map_sync`(f, *sequences, **kwargs)

    Parallel version of builtin map, using this view’s engines.

    This is equivalent to map(...block=True)

    See self.map for details.

  `on_trait_change`(handler, name=None, remove=False)

    Setup a handler to be called when a trait changes.

    This is used to setup dynamic notifications of trait changes.

    Static handlers can be created by creating methods on a HasTraits subclass with the naming convention ‘_[traitname]_changed’. Thus, to create static handler for the trait ‘a’, create the method _a_changed(self, name, old, new) (fewer arguments can be used, see below).

    Parameters : | handler : callable A callable that is called when a trait changes. Its signature can be handler(), handler(name), handler(name, new) or handler(name, old, new). name : list, str, None If None, the handler will apply to all traits. If a list of str, handler will apply to all names in the list. If a str, the handler will apply just to that name. remove : bool If False (the default), then install the handler. If True then unintall it.

  `outstanding`

    An instance of a Python set.

  `parallel`(dist='b', block=None, **flags)

    Decorator for making a ParallelFunction

  `purge_results`(jobs=[], targets=[])

    Instruct the controller to forget specific results.

  `queue_status`(targets=None, verbose=False)

    Fetch the Queue status of my engines

  `remote`(block=True, **flags)

    Decorator for making a RemoteFunction

  `results`

    An instance of a Python dict.

  `set_flags`(**kwargs)

    set my attribute flags by keyword.

    Views determine behavior with a few attributes (block, track, etc.). These attributes can be set all at once by name with this method.

    Parameters : | block : bool whether to wait for results track : bool whether to create a MessageTracker to allow the user to safely edit after arrays and buffers during non-copying sends.

  `shutdown`(targets=None, restart=False, hub=False, block=None)

    Terminates one or more engine processes, optionally including the hub.

  `spin`()

    spin the client, and sync

  `targets`
  `temp_flags`(*args, **kwds)

    temporarily set flags, for use in with statements.

    See set_flags for permanent setting of flags

    Examples

        >>> view.track=False
        ...
        >>> with view.temp_flags(track=True):
        ...    ar = view.apply(dostuff, my_big_array)
        ...    ar.tracker.wait() # wait for send to finish
        >>> view.track
        False

  `track`

    A boolean (True, False) trait.

  `trait_metadata`(traitname, key)

    Get metadata values for trait by key.

  `trait_names`(**metadata)

    Get a list of all the names of this classes traits.

  `traits`(**metadata)

    Get a list of all the traits of this class.

    The TraitTypes returned don’t know anything about the values that the various HasTrait’s instances are holding.

    This follows the same algorithm as traits does and does not allow for any simple way of specifying merely that a metadata name exists, but has any value. This is because get_metadata returns None if a metadata key doesn’t exist.

  `wait`(jobs=None, timeout=-1)

    waits on one or more jobs, for up to timeout seconds.

    Parameters : | jobs : int, str, or list of ints and/or strs, or one or more AsyncResult objects ints are indices to self.history strs are msg_ids default: wait on all outstanding messages timeout : float a time in seconds, after which to give up. default is -1, which means no timeout
    Returns : | True : when all msg_ids are done False : timeout reached, some msg_ids still outstanding

## Functions

`IPython.parallel.client.view.``save_ids`(f)

  Keep our history and outstanding attributes up to date after a method call.

`IPython.parallel.client.view.``spin_after`(f)

  call spin after the method.

`IPython.parallel.client.view.``sync_results`(f)

  sync relevant results from self.client to our results attribute.

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