airflow.models.taskinstance

Module Contents

airflow.models.taskinstance.clear_task_instances(tis, session, activate_dag_runs=True, dag=None)[source]
Clears a set of task instances, but makes sure the running ones
get killed.
Parameters
  • tis – a list of task instances

  • session – current session

  • activate_dag_runs – flag to check for active dag run

  • dag – DAG object

class airflow.models.taskinstance.TaskInstance(task, execution_date, state=None)[source]

Bases: airflow.models.base.Base, airflow.utils.log.logging_mixin.LoggingMixin

Task instances store the state of a task instance. This table is the authority and single source of truth around what tasks have run and the state they are in.

The SqlAlchemy model doesn’t have a SqlAlchemy foreign key to the task or dag model deliberately to have more control over transactions.

Database transactions on this table should insure double triggers and any confusion around what task instances are or aren’t ready to run even while multiple schedulers may be firing task instances.

__tablename__ = task_instance[source]
task_id[source]
dag_id[source]
execution_date[source]
start_date[source]
end_date[source]
duration[source]
state[source]
_try_number[source]
max_tries[source]
hostname[source]
unixname[source]
job_id[source]
pool[source]
queue[source]
priority_weight[source]
operator[source]
queued_dttm[source]
pid[source]
executor_config[source]
__table_args__[source]
try_number[source]

Return the try number that this task number will be when it is actually run.

If the TI is currently running, this will match the column in the databse, in all othercases this will be incremenetd

next_try_number[source]
log_filepath[source]
log_url[source]
mark_success_url[source]
key[source]

Returns a tuple that identifies the task instance uniquely

is_premature[source]

Returns whether a task is in UP_FOR_RETRY state and its retry interval has elapsed.

previous_ti[source]

The task instance for the task that ran before this task instance.

previous_ti_success[source]

The ti from prior succesful dag run for this task, by execution date.

previous_execution_date_success[source]

The execution date from property previous_ti_success.

previous_start_date_success[source]

The start date from property previous_ti_success.

init_on_load(self)[source]

Initialize the attributes that aren’t stored in the DB.

command(self, mark_success=False, ignore_all_deps=False, ignore_depends_on_past=False, ignore_task_deps=False, ignore_ti_state=False, local=False, pickle_id=None, raw=False, job_id=None, pool=None, cfg_path=None)[source]

Returns a command that can be executed anywhere where airflow is installed. This command is part of the message sent to executors by the orchestrator.

command_as_list(self, mark_success=False, ignore_all_deps=False, ignore_task_deps=False, ignore_depends_on_past=False, ignore_ti_state=False, local=False, pickle_id=None, raw=False, job_id=None, pool=None, cfg_path=None)[source]

Returns a command that can be executed anywhere where airflow is installed. This command is part of the message sent to executors by the orchestrator.

static generate_command(dag_id, task_id, execution_date, mark_success=False, ignore_all_deps=False, ignore_depends_on_past=False, ignore_task_deps=False, ignore_ti_state=False, local=False, pickle_id=None, file_path=None, raw=False, job_id=None, pool=None, cfg_path=None)[source]

Generates the shell command required to execute this task instance.

Parameters
  • dag_id (unicode) – DAG ID

  • task_id (unicode) – Task ID

  • execution_date (datetime.datetime) – Execution date for the task

  • mark_success (bool) – Whether to mark the task as successful

  • ignore_all_deps (bool) – Ignore all ignorable dependencies. Overrides the other ignore_* parameters.

  • ignore_depends_on_past (bool) – Ignore depends_on_past parameter of DAGs (e.g. for Backfills)

  • ignore_task_deps (bool) – Ignore task-specific dependencies such as depends_on_past and trigger rule

  • ignore_ti_state (bool) – Ignore the task instance’s previous failure/success

  • local (bool) – Whether to run the task locally

  • pickle_id (unicode) – If the DAG was serialized to the DB, the ID associated with the pickled DAG

  • file_path – path to the file containing the DAG definition

  • raw – raw mode (needs more details)

  • job_id – job ID (needs more details)

  • pool (unicode) – the Airflow pool that the task should run in

  • cfg_path (basestring) – the Path to the configuration file

Returns

shell command that can be used to run the task instance

current_state(self, session=None)[source]

Get the very latest state from the database, if a session is passed, we use and looking up the state becomes part of the session, otherwise a new session is used.

error(self, session=None)[source]

Forces the task instance’s state to FAILED in the database.

refresh_from_db(self, session=None, lock_for_update=False, refresh_executor_config=False)[source]

Refreshes the task instance from the database based on the primary key

Parameters
  • refresh_executor_config – if True, revert executor config to result from DB. Often, however, we will want to keep the newest version

  • lock_for_update – if True, indicates that the database should lock the TaskInstance (issuing a FOR UPDATE clause) until the session is committed.

clear_xcom_data(self, session=None)[source]

Clears all XCom data from the database for the task instance

set_state(self, state, session=None, commit=True)[source]
are_dependents_done(self, session=None)[source]

Checks whether the dependents of this task instance have all succeeded. This is meant to be used by wait_for_downstream.

This is useful when you do not want to start processing the next schedule of a task until the dependents are done. For instance, if the task DROPs and recreates a table.

_get_previous_ti(self, state=None, session=None)[source]
are_dependencies_met(self, dep_context=None, session=None, verbose=False)[source]

Returns whether or not all the conditions are met for this task instance to be run given the context for the dependencies (e.g. a task instance being force run from the UI will ignore some dependencies).

Parameters
  • dep_context (DepContext) – The execution context that determines the dependencies that should be evaluated.

  • session (sqlalchemy.orm.session.Session) – database session

  • verbose (bool) – whether log details on failed dependencies on info or debug log level

get_failed_dep_statuses(self, dep_context=None, session=None)[source]
__repr__(self)[source]
next_retry_datetime(self)[source]

Get datetime of the next retry if the task instance fails. For exponential backoff, retry_delay is used as base and will be converted to seconds.

ready_for_retry(self)[source]

Checks on whether the task instance is in the right state and timeframe to be retried.

pool_full(self, session)[source]

Returns a boolean as to whether the slot pool has room for this task to run

get_dagrun(self, session)[source]

Returns the DagRun for this TaskInstance

Parameters

session

Returns

DagRun

_check_and_change_state_before_execution(self, verbose=True, ignore_all_deps=False, ignore_depends_on_past=False, ignore_task_deps=False, ignore_ti_state=False, mark_success=False, test_mode=False, job_id=None, pool=None, session=None)[source]

Checks dependencies and then sets state to RUNNING if they are met. Returns True if and only if state is set to RUNNING, which implies that task should be executed, in preparation for _run_raw_task

Parameters
  • verbose (bool) – whether to turn on more verbose logging

  • ignore_all_deps (bool) – Ignore all of the non-critical dependencies, just runs

  • ignore_depends_on_past (bool) – Ignore depends_on_past DAG attribute

  • ignore_task_deps (bool) – Don’t check the dependencies of this TI’s task

  • ignore_ti_state (bool) – Disregards previous task instance state

  • mark_success (bool) – Don’t run the task, mark its state as success

  • test_mode (bool) – Doesn’t record success or failure in the DB

  • pool (str) – specifies the pool to use to run the task instance

Returns

whether the state was changed to running or not

Return type

bool

_run_raw_task(self, mark_success=False, test_mode=False, job_id=None, pool=None, session=None)[source]

Immediately runs the task (without checking or changing db state before execution) and then sets the appropriate final state after completion and runs any post-execute callbacks. Meant to be called only after another function changes the state to running.

Parameters
  • mark_success (bool) – Don’t run the task, mark its state as success

  • test_mode (bool) – Doesn’t record success or failure in the DB

  • pool (str) – specifies the pool to use to run the task instance

run(self, verbose=True, ignore_all_deps=False, ignore_depends_on_past=False, ignore_task_deps=False, ignore_ti_state=False, mark_success=False, test_mode=False, job_id=None, pool=None, session=None)[source]
dry_run(self)[source]
_handle_reschedule(self, actual_start_date, reschedule_exception, test_mode=False, context=None, session=None)[source]
handle_failure(self, error, test_mode=False, context=None, session=None)[source]
is_eligible_to_retry(self)[source]

Is task instance is eligible for retry

get_template_context(self, session=None)[source]
overwrite_params_with_dag_run_conf(self, params, dag_run)[source]
render_templates(self, context=None)[source]

Render templates in the operator fields.

email_alert(self, exception)[source]
set_duration(self)[source]
xcom_push(self, key, value, execution_date=None)[source]

Make an XCom available for tasks to pull.

Parameters
  • key (str) – A key for the XCom

  • value (any pickleable object) – A value for the XCom. The value is pickled and stored in the database.

  • execution_date (datetime) – if provided, the XCom will not be visible until this date. This can be used, for example, to send a message to a task on a future date without it being immediately visible.

xcom_pull(self, task_ids=None, dag_id=None, key=XCOM_RETURN_KEY, include_prior_dates=False)[source]

Pull XComs that optionally meet certain criteria.

The default value for key limits the search to XComs that were returned by other tasks (as opposed to those that were pushed manually). To remove this filter, pass key=None (or any desired value).

If a single task_id string is provided, the result is the value of the most recent matching XCom from that task_id. If multiple task_ids are provided, a tuple of matching values is returned. None is returned whenever no matches are found.

Parameters
  • key (str) – A key for the XCom. If provided, only XComs with matching keys will be returned. The default key is ‘return_value’, also available as a constant XCOM_RETURN_KEY. This key is automatically given to XComs returned by tasks (as opposed to being pushed manually). To remove the filter, pass key=None.

  • task_ids (str or iterable of strings (representing task_ids)) – Only XComs from tasks with matching ids will be pulled. Can pass None to remove the filter.

  • dag_id (str) – If provided, only pulls XComs from this DAG. If None (default), the DAG of the calling task is used.

  • include_prior_dates (bool) – If False, only XComs from the current execution_date are returned. If True, XComs from previous dates are returned as well.

get_num_running_task_instances(self, session)[source]
init_run_context(self, raw=False)[source]

Sets the log context.