Source code for luigi.task

# -*- coding: utf-8 -*-
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The abstract :py:class:`Task` class.
It is a central concept of Luigi and represents the state of the workflow.
See :doc:`/tasks` for an overview.

    from itertools import imap as map
except ImportError:
from contextlib import contextmanager
import logging
import traceback
import warnings
import json
import hashlib
import re
import copy
import functools

import luigi
from luigi import six

from luigi import parameter
from luigi.task_register import Register
from luigi.parameter import ParameterVisibility

Parameter = parameter.Parameter
logger = logging.getLogger('luigi-interface')

TASK_ID_INVALID_CHAR_REGEX = re.compile(r'[^A-Za-z0-9_]')
_SAME_AS_PYTHON_MODULE = '_same_as_python_module'

[docs]def namespace(namespace=None, scope=''): """ Call to set namespace of tasks declared after the call. It is often desired to call this function with the keyword argument ``scope=__name__``. The ``scope`` keyword makes it so that this call is only effective for task classes with a matching [*]_ ``__module__``. The default value for ``scope`` is the empty string, which means all classes. Multiple calls with the same scope simply replace each other. The namespace of a :py:class:`Task` can also be changed by specifying the property ``task_namespace``. .. code-block:: python class Task2(luigi.Task): task_namespace = 'namespace2' This explicit setting takes priority over whatever is set in the ``namespace()`` method, and it's also inherited through normal python inheritence. There's no equivalent way to set the ``task_family``. *New since Luigi 2.6.0:* ``scope`` keyword argument. .. [*] When there are multiple levels of matching module scopes like ``a.b`` vs ``a.b.c``, the more specific one (``a.b.c``) wins. .. seealso:: The new and better scaling :py:func:`auto_namespace` """ Register._default_namespace_dict[scope] = namespace or ''
[docs]def auto_namespace(scope=''): """ Same as :py:func:`namespace`, but instead of a constant namespace, it will be set to the ``__module__`` of the task class. This is desirable for these reasons: * Two tasks with the same name will not have conflicting task families * It's more pythonic, as modules are Python's recommended way to do namespacing. * It's traceable. When you see the full name of a task, you can immediately identify where it is defined. We recommend calling this function from your package's outermost ```` file. The file contents could look like this: .. code-block:: python import luigi luigi.auto_namespace(scope=__name__) To reset an ``auto_namespace()`` call, you can use ``namespace(scope='my_scope')``. But this will not be needed (and is also discouraged) if you use the ``scope`` kwarg. *New since Luigi 2.6.0.* """ namespace(namespace=_SAME_AS_PYTHON_MODULE, scope=scope)
[docs]def task_id_str(task_family, params): """ Returns a canonical string used to identify a particular task :param task_family: The task family (class name) of the task :param params: a dict mapping parameter names to their serialized values :return: A unique, shortened identifier corresponding to the family and params """ # task_id is a concatenation of task family, the first values of the first 3 parameters # sorted by parameter name and a md5hash of the family/parameters as a cananocalised json. param_str = json.dumps(params, separators=(',', ':'), sort_keys=True) param_hash = hashlib.md5(param_str.encode('utf-8')).hexdigest() param_summary = '_'.join(p[:TASK_ID_TRUNCATE_PARAMS] for p in (params[p] for p in sorted(params)[:TASK_ID_INCLUDE_PARAMS])) param_summary = TASK_ID_INVALID_CHAR_REGEX.sub('_', param_summary) return '{}_{}_{}'.format(task_family, param_summary, param_hash[:TASK_ID_TRUNCATE_HASH])
[docs]class BulkCompleteNotImplementedError(NotImplementedError): """This is here to trick pylint. pylint thinks anything raising NotImplementedError needs to be implemented in any subclass. bulk_complete isn't like that. This tricks pylint into thinking that the default implementation is a valid implementation and not an abstract method.""" pass
[docs]@six.add_metaclass(Register) class Task(object): """ This is the base class of all Luigi Tasks, the base unit of work in Luigi. A Luigi Task describes a unit or work. The key methods of a Task, which must be implemented in a subclass are: * :py:meth:`run` - the computation done by this task. * :py:meth:`requires` - the list of Tasks that this Task depends on. * :py:meth:`output` - the output :py:class:`Target` that this Task creates. Each :py:class:`~luigi.Parameter` of the Task should be declared as members: .. code:: python class MyTask(luigi.Task): count = luigi.IntParameter() second_param = luigi.Parameter() In addition to any declared properties and methods, there are a few non-declared properties, which are created by the :py:class:`Register` metaclass: """ _event_callbacks = {} #: Priority of the task: the scheduler should favor available #: tasks with higher priority values first. #: See :ref:`Task.priority` priority = 0 disabled = False #: Resources used by the task. Should be formatted like {"scp": 1} to indicate that the #: task requires 1 unit of the scp resource. resources = {} #: Number of seconds after which to time out the run function. #: No timeout if set to 0. #: Defaults to 0 or worker-timeout value in config worker_timeout = None #: Maximum number of tasks to run together as a batch. Infinite by default max_batch_size = float('inf') @property def batchable(self): """ True if this instance can be run as part of a batch. By default, True if it has any batched parameters """ return bool(self.batch_param_names()) @property def retry_count(self): """ Override this positive integer to have different ``retry_count`` at task level Check :ref:`scheduler-config` """ return None @property def disable_hard_timeout(self): """ Override this positive integer to have different ``disable_hard_timeout`` at task level. Check :ref:`scheduler-config` """ return None @property def disable_window_seconds(self): """ Override this positive integer to have different ``disable_window_seconds`` at task level. Check :ref:`scheduler-config` """ return None @property def owner_email(self): ''' Override this to send out additional error emails to task owner, in addition to the one defined in the global configuration. This should return a string or a list of strings. e.g. '' or ['', ''] ''' return None def _owner_list(self): """ Turns the owner_email property into a list. This should not be overridden. """ owner_email = self.owner_email if owner_email is None: return [] elif isinstance(owner_email, six.string_types): return owner_email.split(',') else: return owner_email @property def use_cmdline_section(self): ''' Property used by core config such as `--workers` etc. These will be exposed without the class as prefix.''' return True
[docs] @classmethod def event_handler(cls, event): """ Decorator for adding event handlers. """ def wrapped(callback): cls._event_callbacks.setdefault(cls, {}).setdefault(event, set()).add(callback) return callback return wrapped
[docs] def trigger_event(self, event, *args, **kwargs): """ Trigger that calls all of the specified events associated with this class. """ for event_class, event_callbacks in six.iteritems(self._event_callbacks): if not isinstance(self, event_class): continue for callback in event_callbacks.get(event, []): try: # callbacks are protected callback(*args, **kwargs) except KeyboardInterrupt: return except BaseException: logger.exception("Error in event callback for %r", event)
@property def accepts_messages(self): """ For configuring which scheduler messages can be received. When falsy, this tasks does not accept any message. When True, all messages are accepted. """ return False @property def task_module(self): ''' Returns what Python module to import to get access to this class. ''' # TODO(erikbern): we should think about a language-agnostic mechanism return self.__class__.__module__ _visible_in_registry = True # TODO: Consider using in luigi.util as well __not_user_specified = '__not_user_specified' # This is here just to help pylint, the Register metaclass will always set # this value anyway. _namespace_at_class_time = None task_namespace = __not_user_specified """ This value can be overriden to set the namespace that will be used. (See :ref:`Task.namespaces_famlies_and_ids`) If it's not specified and you try to read this value anyway, it will return garbage. Please use :py:meth:`get_task_namespace` to read the namespace. Note that setting this value with ``@property`` will not work, because this is a class level value. """
[docs] @classmethod def get_task_namespace(cls): """ The task family for the given class. Note: You normally don't want to override this. """ if cls.task_namespace != cls.__not_user_specified: return cls.task_namespace elif cls._namespace_at_class_time == _SAME_AS_PYTHON_MODULE: return cls.__module__ return cls._namespace_at_class_time
@property def task_family(self): """ DEPRECATED since after 2.4.0. See :py:meth:`get_task_family` instead. Hopefully there will be less meta magic in Luigi. Convenience method since a property on the metaclass isn't directly accessible through the class instances. """ return self.__class__.task_family
[docs] @classmethod def get_task_family(cls): """ The task family for the given class. If ``task_namespace`` is not set, then it's simply the name of the class. Otherwise, ``<task_namespace>.`` is prefixed to the class name. Note: You normally don't want to override this. """ if not cls.get_task_namespace(): return cls.__name__ else: return "{}.{}".format(cls.get_task_namespace(), cls.__name__)
[docs] @classmethod def get_params(cls): """ Returns all of the Parameters for this Task. """ # We want to do this here and not at class instantiation, or else there is no room to extend classes dynamically params = [] for param_name in dir(cls): param_obj = getattr(cls, param_name) if not isinstance(param_obj, Parameter): continue params.append((param_name, param_obj)) # The order the parameters are created matters. See Parameter class params.sort(key=lambda t: t[1]._counter) return params
[docs] @classmethod def batch_param_names(cls): return [name for name, p in cls.get_params() if p._is_batchable()]
[docs] @classmethod def get_param_names(cls, include_significant=False): return [name for name, p in cls.get_params() if include_significant or p.significant]
[docs] @classmethod def get_param_values(cls, params, args, kwargs): """ Get the values of the parameters from the args and kwargs. :param params: list of (param_name, Parameter). :param args: positional arguments :param kwargs: keyword arguments. :returns: list of `(name, value)` tuples, one for each parameter. """ result = {} params_dict = dict(params) task_family = cls.get_task_family() # In case any exceptions are thrown, create a helpful description of how the Task was invoked # TODO: should we detect non-reprable arguments? These will lead to mysterious errors exc_desc = '%s[args=%s, kwargs=%s]' % (task_family, args, kwargs) # Fill in the positional arguments positional_params = [(n, p) for n, p in params if p.positional] for i, arg in enumerate(args): if i >= len(positional_params): raise parameter.UnknownParameterException('%s: takes at most %d parameters (%d given)' % (exc_desc, len(positional_params), len(args))) param_name, param_obj = positional_params[i] result[param_name] = param_obj.normalize(arg) # Then the keyword arguments for param_name, arg in six.iteritems(kwargs): if param_name in result: raise parameter.DuplicateParameterException('%s: parameter %s was already set as a positional parameter' % (exc_desc, param_name)) if param_name not in params_dict: raise parameter.UnknownParameterException('%s: unknown parameter %s' % (exc_desc, param_name)) result[param_name] = params_dict[param_name].normalize(arg) # Then use the defaults for anything not filled in for param_name, param_obj in params: if param_name not in result: if not param_obj.has_task_value(task_family, param_name): raise parameter.MissingParameterException("%s: requires the '%s' parameter to be set" % (exc_desc, param_name)) result[param_name] = param_obj.task_value(task_family, param_name) def list_to_tuple(x): """ Make tuples out of lists and sets to allow hashing """ if isinstance(x, list) or isinstance(x, set): return tuple(x) else: return x # Sort it by the correct order and make a list return [(param_name, list_to_tuple(result[param_name])) for param_name, param_obj in params]
def __init__(self, *args, **kwargs): params = self.get_params() param_values = self.get_param_values(params, args, kwargs) # Set all values on class instance for key, value in param_values: setattr(self, key, value) # Register kwargs as an attribute on the class. Might be useful self.param_kwargs = dict(param_values) self._warn_on_wrong_param_types() self.task_id = task_id_str(self.get_task_family(), self.to_str_params(only_significant=True, only_public=True)) self.__hash = hash(self.task_id) self.set_tracking_url = None self.set_status_message = None self.set_progress_percentage = None @property def param_args(self): warnings.warn("Use of param_args has been deprecated.", DeprecationWarning) return tuple(self.param_kwargs[k] for k, v in self.get_params())
[docs] def initialized(self): """ Returns ``True`` if the Task is initialized and ``False`` otherwise. """ return hasattr(self, 'task_id')
def _warn_on_wrong_param_types(self): params = dict(self.get_params()) for param_name, param_value in six.iteritems(self.param_kwargs): params[param_name]._warn_on_wrong_param_type(param_name, param_value)
[docs] @classmethod def from_str_params(cls, params_str): """ Creates an instance from a str->str hash. :param params_str: dict of param name -> value as string. """ kwargs = {} for param_name, param in cls.get_params(): if param_name in params_str: param_str = params_str[param_name] if isinstance(param_str, list): kwargs[param_name] = param._parse_list(param_str) else: kwargs[param_name] = param.parse(param_str) return cls(**kwargs)
[docs] def to_str_params(self, only_significant=False, only_public=False): """ Convert all parameters to a str->str hash. """ params_str = {} params = dict(self.get_params()) for param_name, param_value in six.iteritems(self.param_kwargs): if (((not only_significant) or params[param_name].significant) and ((not only_public) or params[param_name].visibility == ParameterVisibility.PUBLIC) and params[param_name].visibility != ParameterVisibility.PRIVATE): params_str[param_name] = params[param_name].serialize(param_value) return params_str
def _get_param_visibilities(self): param_visibilities = {} params = dict(self.get_params()) for param_name, param_value in six.iteritems(self.param_kwargs): if params[param_name].visibility != ParameterVisibility.PRIVATE: param_visibilities[param_name] = params[param_name].visibility.serialize() return param_visibilities
[docs] def clone(self, cls=None, **kwargs): """ Creates a new instance from an existing instance where some of the args have changed. There's at least two scenarios where this is useful (see test/ * remove a lot of boiler plate when you have recursive dependencies and lots of args * there's task inheritance and some logic is on the base class :param cls: :param kwargs: :return: """ if cls is None: cls = self.__class__ new_k = {} for param_name, param_class in cls.get_params(): if param_name in kwargs: new_k[param_name] = kwargs[param_name] elif hasattr(self, param_name): new_k[param_name] = getattr(self, param_name) return cls(**new_k)
def __hash__(self): return self.__hash def __repr__(self): """ Build a task representation like `MyTask(param1=1.5, param2='5')` """ params = self.get_params() param_values = self.get_param_values(params, [], self.param_kwargs) # Build up task id repr_parts = [] param_objs = dict(params) for param_name, param_value in param_values: if param_objs[param_name].significant: repr_parts.append('%s=%s' % (param_name, param_objs[param_name].serialize(param_value))) task_str = '{}({})'.format(self.get_task_family(), ', '.join(repr_parts)) return task_str def __eq__(self, other): return self.__class__ == other.__class__ and self.task_id == other.task_id
[docs] def complete(self): """ If the task has any outputs, return ``True`` if all outputs exist. Otherwise, return ``False``. However, you may freely override this method with custom logic. """ outputs = flatten(self.output()) if len(outputs) == 0: warnings.warn( "Task %r without outputs has no custom complete() method" % self, stacklevel=2 ) return False return all(map(lambda output: output.exists(), outputs))
[docs] @classmethod def bulk_complete(cls, parameter_tuples): """ Returns those of parameter_tuples for which this Task is complete. Override (with an efficient implementation) for efficient scheduling with range tools. Keep the logic consistent with that of complete(). """ raise BulkCompleteNotImplementedError()
[docs] def output(self): """ The output that this Task produces. The output of the Task determines if the Task needs to be run--the task is considered finished iff the outputs all exist. Subclasses should override this method to return a single :py:class:`Target` or a list of :py:class:`Target` instances. Implementation note If running multiple workers, the output must be a resource that is accessible by all workers, such as a DFS or database. Otherwise, workers might compute the same output since they don't see the work done by other workers. See :ref:`Task.output` """ return [] # default impl
[docs] def requires(self): """ The Tasks that this Task depends on. A Task will only run if all of the Tasks that it requires are completed. If your Task does not require any other Tasks, then you don't need to override this method. Otherwise, a subclass can override this method to return a single Task, a list of Task instances, or a dict whose values are Task instances. See :ref:`Task.requires` """ return [] # default impl
def _requires(self): """ Override in "template" tasks which themselves are supposed to be subclassed and thus have their requires() overridden (name preserved to provide consistent end-user experience), yet need to introduce (non-input) dependencies. Must return an iterable which among others contains the _requires() of the superclass. """ return flatten(self.requires()) # base impl
[docs] def process_resources(self): """ Override in "template" tasks which provide common resource functionality but allow subclasses to specify additional resources while preserving the name for consistent end-user experience. """ return self.resources # default impl
[docs] def input(self): """ Returns the outputs of the Tasks returned by :py:meth:`requires` See :ref:`Task.input` :return: a list of :py:class:`Target` objects which are specified as outputs of all required Tasks. """ return getpaths(self.requires())
[docs] def deps(self): """ Internal method used by the scheduler. Returns the flattened list of requires. """ # used by scheduler return flatten(self._requires())
[docs] def run(self): """ The task run method, to be overridden in a subclass. See :ref:`` """ pass # default impl
[docs] def on_failure(self, exception): """ Override for custom error handling. This method gets called if an exception is raised in :py:meth:`run`. The returned value of this method is json encoded and sent to the scheduler as the `expl` argument. Its string representation will be used as the body of the error email sent out if any. Default behavior is to return a string representation of the stack trace. """ traceback_string = traceback.format_exc() return "Runtime error:\n%s" % traceback_string
[docs] def on_success(self): """ Override for doing custom completion handling for a larger class of tasks This method gets called when :py:meth:`run` completes without raising any exceptions. The returned value is json encoded and sent to the scheduler as the `expl` argument. Default behavior is to send an None value""" pass
[docs] @contextmanager def no_unpicklable_properties(self): """ Remove unpicklable properties before dump task and resume them after. This method could be called in subtask's dump method, to ensure unpicklable properties won't break dump. This method is a context-manager which can be called as below: .. code-block: python class DummyTask(luigi): def _dump(self): with self.no_unpicklable_properties(): pickle.dumps(self) """ unpicklable_properties = tuple(luigi.worker.TaskProcess.forward_reporter_attributes.values()) reserved_properties = {} for property_name in unpicklable_properties: if hasattr(self, property_name): reserved_properties[property_name] = getattr(self, property_name) setattr(self, property_name, 'placeholder_during_pickling') yield for property_name, value in six.iteritems(reserved_properties): setattr(self, property_name, value)
[docs]class MixinNaiveBulkComplete(object): """ Enables a Task to be efficiently scheduled with e.g. range tools, by providing a bulk_complete implementation which checks completeness in a loop. Applicable to tasks whose completeness checking is cheap. This doesn't exploit output location specific APIs for speed advantage, nevertheless removes redundant scheduler roundtrips. """
[docs] @classmethod def bulk_complete(cls, parameter_tuples): generated_tuples = [] for parameter_tuple in parameter_tuples: if isinstance(parameter_tuple, (list, tuple)): if cls(*parameter_tuple).complete(): generated_tuples.append(parameter_tuple) elif isinstance(parameter_tuple, dict): if cls(**parameter_tuple).complete(): generated_tuples.append(parameter_tuple) else: if cls(parameter_tuple).complete(): generated_tuples.append(parameter_tuple) return generated_tuples
[docs]class ExternalTask(Task): """ Subclass for references to external dependencies. An ExternalTask's does not have a `run` implementation, which signifies to the framework that this Task's :py:meth:`output` is generated outside of Luigi. """ run = None
[docs]def externalize(taskclass_or_taskobject): """ Returns an externalized version of a Task. You may both pass an instantiated task object or a task class. Some examples: .. code-block:: python class RequiringTask(luigi.Task): def requires(self): task_object = self.clone(MyTask) return externalize(task_object) ... Here's mostly equivalent code, but ``externalize`` is applied to a task class instead. .. code-block:: python @luigi.util.requires(externalize(MyTask)) class RequiringTask(luigi.Task): pass ... Of course, it may also be used directly on classes and objects (for example for reexporting or other usage). .. code-block:: python MyTask = externalize(MyTask) my_task_2 = externalize(MyTask2(param='foo')) If you however want a task class to be external from the beginning, you're better off inheriting :py:class:`ExternalTask` rather than :py:class:`Task`. This function tries to be side-effect free by creating a copy of the class or the object passed in and then modify that object. In particular this code shouldn't do anything. .. code-block:: python externalize(MyTask) # BAD: This does nothing (as after luigi 2.4.0) """ # Seems like with python < 3.3 copy.copy can't copy classes # and objects with specified metaclass compatible_copy = copy.copy if six.PY3 else copy.deepcopy copied_value = compatible_copy(taskclass_or_taskobject) if copied_value is taskclass_or_taskobject: # Assume it's a class clazz = taskclass_or_taskobject @_task_wraps(clazz) class _CopyOfClass(clazz): # How to copy a class: _visible_in_registry = False = None return _CopyOfClass else: # We assume it's an object = None return copied_value
[docs]class WrapperTask(Task): """ Use for tasks that only wrap other tasks and that by definition are done if all their requirements exist. """
[docs] def complete(self): return all(r.complete() for r in flatten(self.requires()))
[docs]class Config(Task): """ Class for configuration. See :ref:`ConfigClasses`. """ # TODO: let's refactor Task & Config so that it inherits from a common # ParamContainer base class pass
[docs]def getpaths(struct): """ Maps all Tasks in a structured data object to their .output(). """ if isinstance(struct, Task): return struct.output() elif isinstance(struct, dict): return struct.__class__((k, getpaths(v)) for k, v in six.iteritems(struct)) elif isinstance(struct, (list, tuple)): return struct.__class__(getpaths(r) for r in struct) else: # Remaining case: assume struct is iterable... try: return [getpaths(r) for r in struct] except TypeError: raise Exception('Cannot map %s to Task/dict/list' % str(struct))
[docs]def flatten(struct): """ Creates a flat list of all all items in structured output (dicts, lists, items): .. code-block:: python >>> sorted(flatten({'a': 'foo', 'b': 'bar'})) ['bar', 'foo'] >>> sorted(flatten(['foo', ['bar', 'troll']])) ['bar', 'foo', 'troll'] >>> flatten('foo') ['foo'] >>> flatten(42) [42] """ if struct is None: return [] flat = [] if isinstance(struct, dict): for _, result in six.iteritems(struct): flat += flatten(result) return flat if isinstance(struct, six.string_types): return [struct] try: # if iterable iterator = iter(struct) except TypeError: return [struct] for result in iterator: flat += flatten(result) return flat
[docs]def flatten_output(task): """ Lists all output targets by recursively walking output-less (wrapper) tasks. FIXME order consistently. """ r = flatten(task.output()) if not r: for dep in flatten(task.requires()): r += flatten_output(dep) return r
def _task_wraps(task_class): # In order to make the behavior of a wrapper class nicer, we set the name of the # new class to the wrapped class, and copy over the docstring and module as well. # This makes it possible to pickle the wrapped class etc. # Btw, this is a slight abuse of functools.wraps. It's meant to be used only for # functions, but it works for classes too, if you pass updated=[] assigned = functools.WRAPPER_ASSIGNMENTS + ('_namespace_at_class_time',) return functools.wraps(task_class, assigned=assigned, updated=[])