fireworks.core package

Submodules

fireworks.core.firework module

class fireworks.core.firework.FWAction(stored_data=None, exit=False, update_spec=None, mod_spec=None, additions=None, detours=None, defuse_children=False, defuse_workflow=False)

Bases: fireworks.utilities.fw_serializers.FWSerializable

A FWAction encapsulates the output of a Firetask (it is returned by a Firetask after the Firetask completes). The FWAction allows a user to store rudimentary output data as well as return commands that alter the workflow.

classmethod from_dict(*args, **kwargs)
skip_remaining_tasks

If the FWAction gives any dynamic action, we skip the subsequent Firetasks

Returns:bool
to_dict(*args, **kwargs)
class fireworks.core.firework.FireTaskBase(*args, **kwargs)

Bases: fireworks.core.firework.FiretaskBase

class fireworks.core.firework.FiretaskBase(*args, **kwargs)

Bases: collections.defaultdict, fireworks.utilities.fw_serializers.FWSerializable

FiretaskBase is used like an abstract class that defines a computing task (Firetask). All Firetasks should inherit from FiretaskBase.

You can set parameters of a Firetask like you’d use a dict.

classmethod from_dict(*args, **kwargs)
required_params = []
run_task(fw_spec)

This method gets called when the Firetask is run. It can take in a Firework spec, perform some task using that data, and then return an output in the form of a FWAction.

Parameters:fw_spec (dict) – A Firework spec. This comes from the master spec. In addition, this spec contains a special “_fw_env” key that contains the env settings of the FWorker calling this method. This provides for abstracting out certain commands or settings. For example, “foo” may be named “foo1” in resource 1 and “foo2” in resource 2. The FWorker env can specify { “foo”: “foo1”}, which maps an abstract variable “foo” to the relevant “foo1” or “foo2”. You can then write a task that uses fw_spec[“_fw_env”][“foo”] that will work across all these multiple resources.
Returns:(FWAction)
to_dict(*args, **kwargs)
class fireworks.core.firework.FiretaskMeta

Bases: abc.ABCMeta

class fireworks.core.firework.Firework(tasks, spec=None, name=None, launches=None, archived_launches=None, state=u'WAITING', created_on=None, fw_id=None, parents=None, updated_on=None)

Bases: fireworks.utilities.fw_serializers.FWSerializable

A Firework is a workflow step and might be contain several Firetasks.

STATE_RANKS = {u'PAUSED': 0, u'RUNNING': 4, u'ARCHIVED': -2, u'WAITING': 1, u'FIZZLED': -1, u'READY': 2, u'RESERVED': 3, u'COMPLETED': 5, u'DEFUSED': 0}
classmethod from_dict(*args, **kwargs)
state

**Returns* – str* – The current state of the Firework

to_db_dict()

Return firework dict with updated launches and state.

to_dict(*args, **kwargs)
class fireworks.core.firework.Launch(state, launch_dir, fworker=None, host=None, ip=None, trackers=None, action=None, state_history=None, launch_id=None, fw_id=None)

Bases: fireworks.utilities.fw_serializers.FWSerializable, object

A Launch encapsulates data about a specific run of a Firework on a computing resource.

classmethod from_dict(*args, **kwargs)
last_pinged

**Returns* – datetime* – the time the Launch last pinged a heartbeat that it was still running

reservedtime_secs

**Returns* – int* – number of seconds the Launch was stuck as RESERVED in a queue.

runtime_secs

**Returns* – int* – the number of seconds that the Launch ran for.

set_reservation_id(reservation_id)

Adds the job_id to the reservation.

Parameters:reservation_id (int or str) – the id of the reservation (e.g., queue reservation)
state

**Returns* – str* – The current state of the Launch.

time_end

**Returns* – datetime* – the time the Launch was COMPLETED or FIZZLED

time_reserved

**Returns* – datetime* – the time the Launch was RESERVED in the queue

time_start

**Returns* – datetime* – the time the Launch started RUNNING

to_db_dict(*args, **kwargs)
to_dict(*args, **kwargs)
touch_history(update_time=None, checkpoint=None)

Updates the update_on field of the state history of a Launch. Used to ping that a Launch is still alive.

Parameters:update_time (datetime) –
class fireworks.core.firework.Tracker(filename, nlines=25, content=u'', allow_zipped=False)

Bases: fireworks.utilities.fw_serializers.FWSerializable, object

A Tracker monitors a file and returns the last N lines for updating the Launch object.

MAX_TRACKER_LINES = 1000
classmethod from_dict(m_dict)
to_dict()
track_file(launch_dir=None)

Reads the monitored file and returns back the last N lines

Parameters:launch_dir (str) – directory where job was launched in case of relative filename
Returns:the content(last N lines)
Return type:str
class fireworks.core.firework.Workflow(fireworks, links_dict=None, name=None, metadata=None, created_on=None, updated_on=None, fw_states=None)

Bases: fireworks.utilities.fw_serializers.FWSerializable

A Workflow connects a group of FireWorks in an execution order.

Bases: dict, fireworks.utilities.fw_serializers.FWSerializable

An inner class for storing the DAG links between FireWorks

classmethod from_dict(m_dict)
nodes

Return list of all nodes

Return a dict of child and its parents.

Note: if performance of parent_links becomes an issue, override delitem/setitem to update parent_links

to_db_dict()

Convert to str form for Mongo, which cannot have int keys .

Returns:dict
to_dict()

Convert to str form for Mongo, which cannot have int keys.

Returns:dict
Workflow.append_wf(new_wf, fw_ids, detour=False, pull_spec_mods=False)

Method to add a workflow as a child to a Firework Note: detours must have children that have STATE_RANK that is WAITING or below

Parameters:
  • new_wf (Workflow) – New Workflow to add.
  • fw_ids ([int]) – ids of the parent Fireworks on which to add the Workflow.
  • detour (bool) – add children of the current Firework to the Workflow’s leaves.
  • pull_spec_mods (bool) – pull spec mods of COMPLETED parents, refreshes the WF states.
Returns:

list of Firework ids that were updated or new

Return type:

[int]

Workflow.apply_action(action, fw_id)

Apply a FWAction on a Firework in the Workflow.

Parameters:
  • action (FWAction) – action to apply
  • fw_id (int) – id of Firework on which to apply the action
Returns:

list of Firework ids that were updated or new

Return type:

[int]

classmethod Workflow.from_Firework(fw, name=None, metadata=None)

Return Workflow from the given Firework.

Parameters:
  • fw (Firework) –
  • name (str) – New workflow’s name. if not provided, the firework name is used
  • metadata (dict) – New workflow’s metadata.
Returns:

Workflow

classmethod Workflow.from_dict(m_dict)

Return Workflow from its dict representation.

Parameters:m_dict (dict) – either a Workflow dict or a Firework dict
Returns:Workflow
classmethod Workflow.from_wflow(wflow)

Create a fresh Workflow from an existing one.

Parameters:wflow (Workflow) –
Returns:Workflow
Workflow.fws

Return list of all fireworks

Workflow.leaf_fw_ids

Gets leaf FireWorks of this workflow (those with no children).

Returns:Firework ids of leaf FWs
Return type:[int]
Workflow.refresh(fw_id, updated_ids=None)

Refreshes the state of a Firework and any affected children.

Parameters:
  • fw_id (int) – id of the Firework on which to perform the refresh
  • updated_ids ([int]) –
Returns:

list of Firework ids that were updated

Return type:

set(int)

Workflow.remove_fws(fw_ids)

Remove the fireworks corresponding to the input firework ids and update the workflow i.e the parents of the removed fireworks become the parents of the children fireworks (only if the children dont have any other parents).

Parameters:fw_ids (list) – list of fw ids to remove.
Workflow.rerun_fw(fw_id, updated_ids=None)

Archives the launches of a Firework so that it can be re-run.

Parameters:
  • fw_id (int) – id of firework to tbe rerun
  • updated_ids (set(int)) – set of fireworks id to rerun
Returns:

list of Firework ids that were updated

Return type:

[int]

Workflow.reset(reset_ids=True)

Reset the states of all Fireworks in this workflow to ‘WAITING’.

Parameters:reset_ids (bool) – if True, give each Firework a new id.
Workflow.root_fw_ids

Gets root FireWorks of this workflow (those with no parents).

Returns:Firework ids of root FWs
Return type:[int]
Workflow.state

**Returns* – state (str)* – state of workflow

Workflow.to_db_dict()
Workflow.to_dict()
Workflow.to_display_dict()

fireworks.core.fworker module

class fireworks.core.fworker.FWorker(name=u'Automatically generated Worker', category=u'', query=None, env=None)

Bases: fireworks.utilities.fw_serializers.FWSerializable

classmethod auto_load()

Returns FWorker object from settings file(my_fworker.yaml).

classmethod from_dict(*args, **kwargs)
query

Returns updated query dict.

to_dict(*args, **kwargs)

fireworks.core.launchpad module

class fireworks.core.launchpad.LaunchPad(host=u'localhost', port=27017, name=u'fireworks', username=None, password=None, logdir=None, strm_lvl=None, user_indices=None, wf_user_indices=None, ssl_ca_file=None)

Bases: fireworks.utilities.fw_serializers.FWSerializable

The LaunchPad manages the FireWorks database.

add_offline_run(launch_id, fw_id, name)

Add the launch and firework to the offline_run collection.

Parameters:
  • launch_id (int) – launch id
  • fw_id (id) – firework id
  • name (str) –
add_wf(wf, reassign_all=True)

Add workflow(or firework) to the launchpad. The firework ids will be reassigned.

Parameters:wf (Workflow/Firework) –
Returns:mapping between old and new Firework ids
Return type:dict
append_wf(new_wf, fw_ids, detour=False, pull_spec_mods=True)

Append a new workflow on top of an existing workflow.

Parameters:
  • new_wf (Workflow) – The new workflow to append
  • fw_ids ([int]) – The parent fw_ids at which to append the workflow
  • detour (bool) – Whether to connect the new Workflow in a “detour” style, i.e., move
  • children of the parent fw_ids to the new_wf (original) –
  • pull_spec_mods (bool) – Whether the new Workflow should pull the FWActions of the parent fw_ids
archive_wf(fw_id)

Archive the workflow containing the given firework id.

Parameters:fw_id (int) – firework id
classmethod auto_load()
cancel_reservation(launch_id)

given the launch id, cancel the reservation and rerun the fireworks

cancel_reservation_by_reservation_id(reservation_id)

Given the reservation id, cancel the reservation and rerun the corresponding fireworks.

change_launch_dir(launch_id, launch_dir)

Change the launch directory corresponding to the given launch id.

Parameters:
  • launch_id (int) –
  • launch_dir (str) – path to the new launch directory.
checkout_fw(fworker, launch_dir, fw_id=None, host=None, ip=None, state=u'RUNNING')

Checkout the next ready firework, mark it with the given state(RESERVED or RUNNING) and return it to the caller. The caller is responsible for running the Firework.

Parameters:
  • fworker (FWorker) – A FWorker instance
  • launch_dir (str) – the dir the FW will be run in (for creating a Launch object)
  • fw_id (int) – Firework id
  • host (str) – the host making the request (for creating a Launch object)
  • ip (str) – the ip making the request (for creating a Launch object)
  • state (str) – RESERVED or RUNNING, the fetched firework’s state will be set to this value.
Returns:

firework and the new launch id

Return type:

(Firework, int)

complete_launch(launch_id, action=None, state=u'COMPLETED')

Internal method used to mark a Firework’s Launch as completed.

Parameters:
  • launch_id (int) –
  • action (FWAction) – the FWAction of what to do next
  • state (str) – COMPLETED or FIZZLED
Returns:

updated launch

Return type:

dict

defuse_fw(fw_id, rerun_duplicates=True)

Given the firework id, defuse the firework and refresh the workflow.

Parameters:
  • fw_id (int) – firework id
  • rerun_duplicates (bool) – if True, duplicate fireworks(ones with the same launch) are marked for rerun and then defused.
defuse_wf(fw_id, defuse_all_states=True)

Defuse the workflow containing the given firework id.

Parameters:
  • fw_id (int) – firework id
  • defuse_all_states (bool) –
delete_wf(fw_id)

Delete the workflow containing firework with the given id.

Parameters:fw_id (int) – Firework id
detect_lostruns(expiration_secs=14400, fizzle=False, rerun=False, max_runtime=None, min_runtime=None, refresh=False)

Detect lost runs i.e running fireworks that haven’t been updated within the specified time limit or running firework whose launch has been marked fizzed or completed.

Parameters:
  • expiration_secs (seconds) – expiration time in seconds
  • fizzle (bool) – if True, mark the lost runs fizzed
  • rerun (bool) – if True, mark the lost runs fizzed and rerun
  • max_runtime (seconds) – maximum run time
  • min_runtime (seconds) – minimum run time
  • refresh (bool) – if True, refresh the workflow with inconsistent fireworks.
Returns:

tuple of list of lost launch ids, lost firework ids and

inconsistent firework ids.

Return type:

([int], [int], [int])

detect_unreserved(expiration_secs=1209600, rerun=False)

Return the reserved launch ids that have not been updated for a while.

Parameters:
  • expiration_secs (seconds) – time limit
  • rerun (bool) – if True, the expired reservations are cancelled and the fireworks rerun.
Returns:

list of expired lacunh ids

Return type:

[int]

forget_offline(launchid_or_fwid, launch_mode=True)

Unmark the offline run for the given launch or firework id.

Parameters:
  • launchid_or_fwid (int) – launch od or firework id
  • launch_mode (bool) – if True then launch id is given.
classmethod from_dict(d)
get_fw_by_id(fw_id)

Given a Firework id, give back a Firework object.

Parameters:fw_id (int) – Firework id.
Returns:Firework object
get_fw_dict_by_id(fw_id)

Given firework id, return firework dict.

Parameters:fw_id (int) – firework id
Returns:dict
get_fw_ids(query=None, sort=None, limit=0, count_only=False, launches_mode=False)

Return all the fw ids that match a query.

Parameters:
  • query (dict) – representing a Mongo query
  • [ (sort) – sort argument in Pymongo format
  • limit (int) – limit the results
  • count_only (bool) – only return the count rather than explicit ids
  • launches_mode (bool) – query the launches collection instead of fireworks
Returns:

list of firework ids matching the query

Return type:

list

get_fw_ids_from_reservation_id(reservation_id)

Given the reservation id, return the list of firework ids.

Parameters:reservation_id (int) –
Returns:list of firework ids.
Return type:[int]
get_launch_by_id(launch_id)

Given a Launch id, return details of the Launch.

Parameters:launch_id (int) – launch id
Returns:Launch object
get_logdir()

Return the log directory.

AJ: This is needed for job packing due to Proxy objects not being fully featured...

get_new_fw_id()

Checkout the next Firework id

get_new_launch_id()

Checkout the next Launch id

get_recovery(fw_id, launch_id=u'last')

function to get recovery data for a given fw and launch :param fw_id: fw id to get recovery data for :type fw_id: int :param launch_id: launch_id to get recovery data for, if ‘last’

recovery data is generated from last launch
get_reservation_id_from_fw_id(fw_id)

Given the firework id, return the reservation id

get_tracker_data(fw_id)
Parameters:fw_id (id) – firework id
Returns:list tracker dicts
Return type:[dict]
get_wf_by_fw_id(fw_id)

Given a Firework id, give back the Workflow containing that Firework.

Parameters:fw_id (int) –
Returns:A Workflow object
get_wf_by_fw_id_lzyfw(fw_id)

Given a FireWork id, give back the Workflow containing that FireWork.

Parameters:fw_id (int) –
Returns:A Workflow object
get_wf_ids(query=None, sort=None, limit=0, count_only=False)

Return one fw id for all workflows that match a query.

Parameters:
  • query (dict) – representing a Mongo query
  • [ (sort) – sort argument in Pymongo format
  • limit (int) – limit the results
  • count_only (bool) – only return the count rather than explicit ids
Returns:

list of firework ids

Return type:

list

get_wf_summary_dict(fw_id, mode=u'more')

A much faster way to get summary information about a Workflow by querying only for needed information.

Parameters:
  • fw_id (int) – A Firework id.
  • mode (str) – Choose between “more”, “less” and “all” in terms of quantity of information.
Returns:

information about Workflow.

Return type:

dict

log_message(level, message)

Support for job packing

Parameters:
  • level (str) –
  • message (str) –
maintain(infinite=True, maintain_interval=None)

Perform launchpad maintenance: detect lost runs and unreserved RESERVE launches.

Parameters:
  • infinite (bool) –
  • maintain_interval (seconds) – sleep time
mark_fizzled(launch_id)

Mark the launch corresponding to the given id as FIZZLED.

Parameters:launch_id (int) – launch id
Returns:updated launch
Return type:dict
pause_fw(fw_id)

Given the firework id, pauses the firework and refresh the workflow

Parameters:fw_id (int) – firework id
pause_wf(fw_id)

Pause the workflow containing the given firework id.

Parameters:
  • fw_id (int) – firework id
  • defuse_all_states (bool) –
ping_launch(launch_id, ptime=None, checkpoint=None)

Ping that a Launch is still alive: updates the ‘update_on ‘field of the state history of a Launch.

Parameters:
recover_offline(launch_id, ignore_errors=False, print_errors=False)

Update the launch state using the offline data in FW_offline.json file.

Parameters:
  • launch_id (int) – launch id
  • ignore_errors (bool) –
  • print_errors (bool) –
Returns:

firework id if the recovering fails otherwise None

reignite_fw(fw_id)

Given the firework id, re-ignite(set state=WAITING) the defused firework.

Parameters:fw_id (int) – firework id
reignite_wf(fw_id)

Reignite the workflow containing the given firework id.

Parameters:fw_id (int) – firework id
rerun_fw(fw_id, rerun_duplicates=True, recover_launch=None, recover_mode=None)

Rerun the firework corresponding to the given id.

Parameters:
  • fw_id (int) – firework id
  • rerun_duplicates (bool) – flag for whether duplicates should be rerun
  • recover_launch ('last' or int) – launch_id for last recovery, if set to ‘last’ (default), recovery will find the last available launch. If it is an int, will recover that specific launch
  • recover_mode ('prev_dir' or 'copy') – flag to indicate whether to copy or run recovery fw in previous directory
Returns:

list of firework ids that were rerun

Return type:

[int]

reserve_fw(fworker, launch_dir, host=None, ip=None, fw_id=None)

Checkout the next ready firework and mark the launch reserved.

Parameters:
  • fworker (FWorker) –
  • launch_dir (str) – path to the launch directory.
  • host (str) – hostname
  • ip (str) – ip address
  • fw_id (int) – fw_id to be reserved, if desired
Returns:

the checked out firework and the new launch id

Return type:

(Firework, int)

reset(password, require_password=True, max_reset_wo_password=25)

Create a new FireWorks database. This will overwrite the existing FireWorks database! To safeguard against accidentally erasing an existing database, a password must be entered.

Parameters:
  • password (str) – A String representing today’s date, e.g. ‘2012-12-31’
  • require_password (bool) – Whether a password is required to reset the DB. Setting to false is dangerous because running code unintentionally could clear your DB - use max_reset_wo_password to minimize risk.
  • max_reset_wo_password (int) – A failsafe; when require_password is set to False, FWS will not clear DBs that contain more workflows than this parameter
restore_backup_data(launch_id, fw_id)

For the given launch id and firework id, restore the back up data.

resume_fw(fw_id)

Given the firework id, resume (set state=WAITING) the paused firework.

Parameters:fw_id (int) – firework id
run_exists(fworker=None)

Checks to see if the database contains any FireWorks that are ready to run.

Returns:True if the database contains any FireWorks that are ready to run.
Return type:bool
set_priority(fw_id, priority)

Set priority to the firework with the given id.

Parameters:
  • fw_id (int) – firework id
  • priority
set_reservation_id(launch_id, reservation_id)

Set reservation id to the launch corresponding to the given launch id.

Parameters:
  • launch_id (int) –
  • reservation_id (int) –
to_dict()

Note: usernames/passwords are exported as unencrypted Strings!

tuneup(bkground=True)

Database tuneup: build indexes

update_spec(fw_ids, spec_document, mongo=False)

Update fireworks with a spec. Sometimes you need to modify a firework in progress.

Parameters:
  • [int] (fw_ids) – All fw_ids to modify.
  • spec_document (dict) – The spec document. Note that only modifications to the spec key are allowed. So if you supply {“_tasks.1.parameter”: “hello”}, you are effectively modifying spec._tasks.1.parameter in the actual fireworks collection.
  • mongo (bool) – spec_document uses mongo syntax to directly update the spec
class fireworks.core.launchpad.LazyFirework(fw_id, fw_coll, launch_coll)

Bases: object

A LazyFirework only has the fw_id, and grabs other data just-in-time. This representation can speed up Workflow loading as only “important” FWs need to be fully loaded.

archived_launches
created_on
db_fields = (u'name', u'fw_id', u'spec', u'created_on', u'state')
db_launch_fields = (u'launches', u'archived_launches')
full_fw
launches
name
parents
partial_fw
spec
state
tasks
to_db_dict()
to_dict()
updated_on
exception fireworks.core.launchpad.LockedWorkflowError

Bases: exceptions.ValueError

Error raised if the context manager WFLock can’t acquire the lock on the WF within the selected time interval (WFLOCK_EXPIRATION_SECS), if the killing of the lock is disabled (WFLOCK_EXPIRATION_KILL)

class fireworks.core.launchpad.WFLock(lp, fw_id, expire_secs=300, kill=False)

Bases: object

Lock a Workflow, i.e. for performing update operations Raises a LockedWorkflowError if the lock couldn’t be acquired withing expire_secs and kill==False. Calling functions are responsible for handling the error in order to avoid database inconsistencies.

fireworks.core.rocket module

class fireworks.core.rocket.Rocket(launchpad, fworker, fw_id)

The Rocket fetches a workflow step from the FireWorks database and executes it.

decorate_fwaction(fwaction, my_spec, m_fw, launch_dir)
run()

Run the rocket (check out a job from the database and execute it)

update_checkpoint(launchpad, launch_id, checkpoint)

Helper function to update checkpoint

Parameters:
  • launchpad (LaunchPad) – LaunchPad to ping with checkpoint data
  • launch_id (int) – launch id to update
  • checkpoint (dict) – checkpoint data
fireworks.core.rocket.background_task(btask, spec, stop_event, master_thread)
fireworks.core.rocket.do_ping(launchpad, launch_id)
fireworks.core.rocket.ping_launch(launchpad, launch_id, stop_event, master_thread)
fireworks.core.rocket.start_background_task(btask, spec)
fireworks.core.rocket.start_ping_launch(launchpad, launch_id)
fireworks.core.rocket.stop_backgrounds(ping_stop, btask_stops)

fireworks.core.rocket_launcher module

fireworks.core.rocket_launcher.get_fworker(fworker)
fireworks.core.rocket_launcher.launch_rocket(launchpad, fworker=None, fw_id=None, strm_lvl=u'INFO')

Run a single rocket in the current directory.

Parameters:
  • launchpad (LaunchPad) –
  • fworker (FWorker) –
  • fw_id (int) – if set, a particular Firework to run
  • strm_lvl (str) – level at which to output logs to stdout
Returns:

bool

fireworks.core.rocket_launcher.rapidfire(launchpad, fworker=None, m_dir=None, nlaunches=0, max_loops=-1, sleep_time=None, strm_lvl=u'INFO', timeout=None, local_redirect=False)

Keeps running Rockets in m_dir until we reach an error. Automatically creates subdirectories for each Rocket. Usually stops when we run out of FireWorks from the LaunchPad.

Parameters:
  • launchpad (LaunchPad) –
  • fworker (FWorker object) –
  • m_dir (str) – the directory in which to loop Rocket running
  • nlaunches (int) – 0 means ‘until completion’, -1 or “infinite” means to loop until max_loops
  • max_loops (int) – maximum number of loops (default -1 is infinite)
  • sleep_time (int) – secs to sleep between rapidfire loop iterations
  • strm_lvl (str) – level at which to output logs to stdout
  • timeout (int) – of seconds after which to stop the rapidfire process
  • local_redirect (bool) – redirect standard input and output to local file

Module contents