airflow_client.client.DAGRunApi

All URIs are relative to /api/v1

Method	HTTP request	Description
clear_dag_run	POST /dags/{dag_id}/dagRuns/{dag_run_id}/clear	Clear a DAG run
delete_dag_run	DELETE /dags/{dag_id}/dagRuns/{dag_run_id}	Delete a DAG run
get_dag_run	GET /dags/{dag_id}/dagRuns/{dag_run_id}	Get a DAG run
get_dag_runs	GET /dags/{dag_id}/dagRuns	List DAG runs
get_dag_runs_batch	POST /dags/~/dagRuns/list	List DAG runs (batch)
get_upstream_dataset_events	GET /dags/{dag_id}/dagRuns/{dag_run_id}/upstreamDatasetEvents	Get dataset events for a DAG run
post_dag_run	POST /dags/{dag_id}/dagRuns	Trigger a new DAG run.
set_dag_run_note	PATCH /dags/{dag_id}/dagRuns/{dag_run_id}/setNote	Update the DagRun note.
update_dag_run_state	PATCH /dags/{dag_id}/dagRuns/{dag_run_id}	Modify a DAG run

clear_dag_run

bool, date, datetime, dict, float, int, list, str, none_type clear_dag_run(dag_id, dag_run_id, clear_dag_run)

Clear a DAG run

Clear a DAG run. New in version 2.4.0

Example

Basic Authentication (Basic):

import time
import airflow_client.client
from airflow_client.client.api import dag_run_api
from airflow_client.client.model.error import Error
from airflow_client.client.model.clear_dag_run import ClearDagRun
from pprint import pprint
# Defining the host is optional and defaults to /api/v1
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "/api/v1"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure HTTP basic authorization: Basic
configuration = airflow_client.client.Configuration(
    username = 'YOUR_USERNAME',
    password = 'YOUR_PASSWORD'
)

# Enter a context with an instance of the API client
with airflow_client.client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = dag_run_api.DAGRunApi(api_client)
    dag_id = "dag_id_example" # str | The DAG ID.
    dag_run_id = "dag_run_id_example" # str | The DAG run ID.
    clear_dag_run = ClearDagRun(
        dry_run=True,
    ) # ClearDagRun | 

    # example passing only required values which don't have defaults set
    try:
        # Clear a DAG run
        api_response = api_instance.clear_dag_run(dag_id, dag_run_id, clear_dag_run)
        pprint(api_response)
    except airflow_client.client.ApiException as e:
        print("Exception when calling DAGRunApi->clear_dag_run: %s\n" % e)

Parameters

Name	Type	Description
dag_id	str	The DAG ID.
dag_run_id	str	The DAG run ID.
clear_dag_run	ClearDagRun

Return type

bool, date, datetime, dict, float, int, list, str, none_type

Authorization

Basic, Kerberos

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Success.	-
400	Client specified an invalid argument.	-
401	Request not authenticated due to missing, invalid, authentication info.	-
403	Client does not have sufficient permission.	-
404	A specified resource is not found.	-

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delete_dag_run

delete_dag_run(dag_id, dag_run_id)

Delete a DAG run

Example

Basic Authentication (Basic):

import time
import airflow_client.client
from airflow_client.client.api import dag_run_api
from airflow_client.client.model.error import Error
from pprint import pprint
# Defining the host is optional and defaults to /api/v1
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "/api/v1"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure HTTP basic authorization: Basic
configuration = airflow_client.client.Configuration(
    username = 'YOUR_USERNAME',
    password = 'YOUR_PASSWORD'
)

# Enter a context with an instance of the API client
with airflow_client.client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = dag_run_api.DAGRunApi(api_client)
    dag_id = "dag_id_example" # str | The DAG ID.
    dag_run_id = "dag_run_id_example" # str | The DAG run ID.

    # example passing only required values which don't have defaults set
    try:
        # Delete a DAG run
        api_instance.delete_dag_run(dag_id, dag_run_id)
    except airflow_client.client.ApiException as e:
        print("Exception when calling DAGRunApi->delete_dag_run: %s\n" % e)

Parameters

Name	Type	Description	Notes
dag_id	str	The DAG ID.
dag_run_id	str	The DAG run ID.

Return type

void (empty response body)

Authorization

Basic, Kerberos

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
204	Success.	-
400	Client specified an invalid argument.	-
401	Request not authenticated due to missing, invalid, authentication info.	-
403	Client does not have sufficient permission.	-
404	A specified resource is not found.	-

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get_dag_run

DAGRun get_dag_run(dag_id, dag_run_id)

Get a DAG run

Example

Basic Authentication (Basic):

import time
import airflow_client.client
from airflow_client.client.api import dag_run_api
from airflow_client.client.model.error import Error
from airflow_client.client.model.dag_run import DAGRun
from pprint import pprint
# Defining the host is optional and defaults to /api/v1
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "/api/v1"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure HTTP basic authorization: Basic
configuration = airflow_client.client.Configuration(
    username = 'YOUR_USERNAME',
    password = 'YOUR_PASSWORD'
)

# Enter a context with an instance of the API client
with airflow_client.client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = dag_run_api.DAGRunApi(api_client)
    dag_id = "dag_id_example" # str | The DAG ID.
    dag_run_id = "dag_run_id_example" # str | The DAG run ID.
    fields = [
        "fields_example",
    ] # [str] | List of field for return.  (optional)

    # example passing only required values which don't have defaults set
    try:
        # Get a DAG run
        api_response = api_instance.get_dag_run(dag_id, dag_run_id)
        pprint(api_response)
    except airflow_client.client.ApiException as e:
        print("Exception when calling DAGRunApi->get_dag_run: %s\n" % e)

    # example passing only required values which don't have defaults set
    # and optional values
    try:
        # Get a DAG run
        api_response = api_instance.get_dag_run(dag_id, dag_run_id, fields=fields)
        pprint(api_response)
    except airflow_client.client.ApiException as e:
        print("Exception when calling DAGRunApi->get_dag_run: %s\n" % e)

Parameters

Name	Type	Description	Notes
dag_id	str	The DAG ID.
dag_run_id	str	The DAG run ID.
fields	[str]	List of field for return.	[optional]

Return type

DAGRun

Authorization

Basic, Kerberos

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Success.	-
401	Request not authenticated due to missing, invalid, authentication info.	-
403	Client does not have sufficient permission.	-
404	A specified resource is not found.	-

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get_dag_runs

DAGRunCollection get_dag_runs(dag_id)

List DAG runs

This endpoint allows specifying ~ as the dag_id to retrieve DAG runs for all DAGs.

Example

Basic Authentication (Basic):

import time
import airflow_client.client
from airflow_client.client.api import dag_run_api
from airflow_client.client.model.error import Error
from airflow_client.client.model.dag_run_collection import DAGRunCollection
from pprint import pprint
# Defining the host is optional and defaults to /api/v1
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "/api/v1"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure HTTP basic authorization: Basic
configuration = airflow_client.client.Configuration(
    username = 'YOUR_USERNAME',
    password = 'YOUR_PASSWORD'
)

# Enter a context with an instance of the API client
with airflow_client.client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = dag_run_api.DAGRunApi(api_client)
    dag_id = "dag_id_example" # str | The DAG ID.
    limit = 100 # int | The numbers of items to return. (optional) if omitted the server will use the default value of 100
    offset = 0 # int | The number of items to skip before starting to collect the result set. (optional)
    execution_date_gte = dateutil_parser('1970-01-01T00:00:00.00Z') # datetime | Returns objects greater or equal to the specified date.  This can be combined with execution_date_lte parameter to receive only the selected period.  (optional)
    execution_date_lte = dateutil_parser('1970-01-01T00:00:00.00Z') # datetime | Returns objects less than or equal to the specified date.  This can be combined with execution_date_gte parameter to receive only the selected period.  (optional)
    start_date_gte = dateutil_parser('1970-01-01T00:00:00.00Z') # datetime | Returns objects greater or equal the specified date.  This can be combined with start_date_lte parameter to receive only the selected period.  (optional)
    start_date_lte = dateutil_parser('1970-01-01T00:00:00.00Z') # datetime | Returns objects less or equal the specified date.  This can be combined with start_date_gte parameter to receive only the selected period.  (optional)
    end_date_gte = dateutil_parser('1970-01-01T00:00:00.00Z') # datetime | Returns objects greater or equal the specified date.  This can be combined with start_date_lte parameter to receive only the selected period.  (optional)
    end_date_lte = dateutil_parser('1970-01-01T00:00:00.00Z') # datetime | Returns objects less than or equal to the specified date.  This can be combined with start_date_gte parameter to receive only the selected period.  (optional)
    updated_at_gte = dateutil_parser('1970-01-01T00:00:00.00Z') # datetime | Returns objects greater or equal the specified date.  This can be combined with updated_at_lte parameter to receive only the selected period.  *New in version 2.6.0*  (optional)
    updated_at_lte = dateutil_parser('1970-01-01T00:00:00.00Z') # datetime | Returns objects less or equal the specified date.  This can be combined with updated_at_gte parameter to receive only the selected period.  *New in version 2.6.0*  (optional)
    state = [
        "state_example",
    ] # [str] | The value can be repeated to retrieve multiple matching values (OR condition). (optional)
    order_by = "order_by_example" # str | The name of the field to order the results by. Prefix a field name with `-` to reverse the sort order.  *New in version 2.1.0*  (optional)
    fields = [
        "fields_example",
    ] # [str] | List of field for return.  (optional)

    # example passing only required values which don't have defaults set
    try:
        # List DAG runs
        api_response = api_instance.get_dag_runs(dag_id)
        pprint(api_response)
    except airflow_client.client.ApiException as e:
        print("Exception when calling DAGRunApi->get_dag_runs: %s\n" % e)

    # example passing only required values which don't have defaults set
    # and optional values
    try:
        # List DAG runs
        api_response = api_instance.get_dag_runs(dag_id, limit=limit, offset=offset, execution_date_gte=execution_date_gte, execution_date_lte=execution_date_lte, start_date_gte=start_date_gte, start_date_lte=start_date_lte, end_date_gte=end_date_gte, end_date_lte=end_date_lte, updated_at_gte=updated_at_gte, updated_at_lte=updated_at_lte, state=state, order_by=order_by, fields=fields)
        pprint(api_response)
    except airflow_client.client.ApiException as e:
        print("Exception when calling DAGRunApi->get_dag_runs: %s\n" % e)

Parameters

Name	Type	Description	Notes
dag_id	str	The DAG ID.
limit	int	The numbers of items to return.	[optional] if omitted the server will use the default value of 100
offset	int	The number of items to skip before starting to collect the result set.	[optional]
execution_date_gte	datetime	Returns objects greater or equal to the specified date. This can be combined with execution_date_lte parameter to receive only the selected period.	[optional]
execution_date_lte	datetime	Returns objects less than or equal to the specified date. This can be combined with execution_date_gte parameter to receive only the selected period.	[optional]
start_date_gte	datetime	Returns objects greater or equal the specified date. This can be combined with start_date_lte parameter to receive only the selected period.	[optional]
start_date_lte	datetime	Returns objects less or equal the specified date. This can be combined with start_date_gte parameter to receive only the selected period.	[optional]
end_date_gte	datetime	Returns objects greater or equal the specified date. This can be combined with start_date_lte parameter to receive only the selected period.	[optional]
end_date_lte	datetime	Returns objects less than or equal to the specified date. This can be combined with start_date_gte parameter to receive only the selected period.	[optional]
updated_at_gte	datetime	Returns objects greater or equal the specified date. This can be combined with updated_at_lte parameter to receive only the selected period. New in version 2.6.0	[optional]
updated_at_lte	datetime	Returns objects less or equal the specified date. This can be combined with updated_at_gte parameter to receive only the selected period. New in version 2.6.0	[optional]
state	[str]	The value can be repeated to retrieve multiple matching values (OR condition).	[optional]
order_by	str	The name of the field to order the results by. Prefix a field name with `-` to reverse the sort order. New in version 2.1.0	[optional]
fields	[str]	List of field for return.	[optional]

Return type

DAGRunCollection

Authorization

Basic, Kerberos

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	List of DAG runs.	-
401	Request not authenticated due to missing, invalid, authentication info.	-

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get_dag_runs_batch

DAGRunCollection get_dag_runs_batch(list_dag_runs_form)

List DAG runs (batch)

This endpoint is a POST to allow filtering across a large number of DAG IDs, where as a GET it would run in to maximum HTTP request URL length limit.

Example

Basic Authentication (Basic):

import time
import airflow_client.client
from airflow_client.client.api import dag_run_api
from airflow_client.client.model.error import Error
from airflow_client.client.model.list_dag_runs_form import ListDagRunsForm
from airflow_client.client.model.dag_run_collection import DAGRunCollection
from pprint import pprint
# Defining the host is optional and defaults to /api/v1
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "/api/v1"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure HTTP basic authorization: Basic
configuration = airflow_client.client.Configuration(
    username = 'YOUR_USERNAME',
    password = 'YOUR_PASSWORD'
)

# Enter a context with an instance of the API client
with airflow_client.client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = dag_run_api.DAGRunApi(api_client)
    list_dag_runs_form = ListDagRunsForm(
        dag_ids=[
            "dag_ids_example",
        ],
        end_date_gte=dateutil_parser('1970-01-01T00:00:00.00Z'),
        end_date_lte=dateutil_parser('1970-01-01T00:00:00.00Z'),
        execution_date_gte=dateutil_parser('1970-01-01T00:00:00.00Z'),
        execution_date_lte=dateutil_parser('1970-01-01T00:00:00.00Z'),
        order_by="order_by_example",
        page_limit=100,
        page_offset=0,
        start_date_gte=dateutil_parser('1970-01-01T00:00:00.00Z'),
        start_date_lte=dateutil_parser('1970-01-01T00:00:00.00Z'),
        states=[
            "states_example",
        ],
    ) # ListDagRunsForm | 

    # example passing only required values which don't have defaults set
    try:
        # List DAG runs (batch)
        api_response = api_instance.get_dag_runs_batch(list_dag_runs_form)
        pprint(api_response)
    except airflow_client.client.ApiException as e:
        print("Exception when calling DAGRunApi->get_dag_runs_batch: %s\n" % e)

Parameters

Name	Type	Description	Notes
list_dag_runs_form	ListDagRunsForm

Return type

DAGRunCollection

Authorization

Basic, Kerberos

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Success.	-
400	Client specified an invalid argument.	-
401	Request not authenticated due to missing, invalid, authentication info.	-
403	Client does not have sufficient permission.	-

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get_upstream_dataset_events

DatasetEventCollection get_upstream_dataset_events(dag_id, dag_run_id)

Get dataset events for a DAG run

Get datasets for a dag run. New in version 2.4.0

Example

Basic Authentication (Basic):

import time
import airflow_client.client
from airflow_client.client.api import dag_run_api
from airflow_client.client.model.dataset_event_collection import DatasetEventCollection
from airflow_client.client.model.error import Error
from pprint import pprint
# Defining the host is optional and defaults to /api/v1
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "/api/v1"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure HTTP basic authorization: Basic
configuration = airflow_client.client.Configuration(
    username = 'YOUR_USERNAME',
    password = 'YOUR_PASSWORD'
)

# Enter a context with an instance of the API client
with airflow_client.client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = dag_run_api.DAGRunApi(api_client)
    dag_id = "dag_id_example" # str | The DAG ID.
    dag_run_id = "dag_run_id_example" # str | The DAG run ID.

    # example passing only required values which don't have defaults set
    try:
        # Get dataset events for a DAG run
        api_response = api_instance.get_upstream_dataset_events(dag_id, dag_run_id)
        pprint(api_response)
    except airflow_client.client.ApiException as e:
        print("Exception when calling DAGRunApi->get_upstream_dataset_events: %s\n" % e)

Parameters

Name	Type	Description	Notes
dag_id	str	The DAG ID.
dag_run_id	str	The DAG run ID.

Return type

DatasetEventCollection

Authorization

Basic, Kerberos

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Success.	-
401	Request not authenticated due to missing, invalid, authentication info.	-
403	Client does not have sufficient permission.	-
404	A specified resource is not found.	-

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post_dag_run

DAGRun post_dag_run(dag_id, dag_run)

Trigger a new DAG run.

This will initiate a dagrun. If DAG is paused then dagrun state will remain queued, and the task won't run.

Example

Basic Authentication (Basic):

import time
import airflow_client.client
from airflow_client.client.api import dag_run_api
from airflow_client.client.model.error import Error
from airflow_client.client.model.dag_run import DAGRun
from pprint import pprint
# Defining the host is optional and defaults to /api/v1
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "/api/v1"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure HTTP basic authorization: Basic
configuration = airflow_client.client.Configuration(
    username = 'YOUR_USERNAME',
    password = 'YOUR_PASSWORD'
)

# Enter a context with an instance of the API client
with airflow_client.client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = dag_run_api.DAGRunApi(api_client)
    dag_id = "dag_id_example" # str | The DAG ID.
    dag_run = DAGRun(
        conf={},
        dag_run_id="dag_run_id_example",
        data_interval_end=dateutil_parser('1970-01-01T00:00:00.00Z'),
        data_interval_start=dateutil_parser('1970-01-01T00:00:00.00Z'),
        execution_date=dateutil_parser('1970-01-01T00:00:00.00Z'),
        logical_date=dateutil_parser('1970-01-01T00:00:00.00Z'),
        note="note_example",
    ) # DAGRun | 

    # example passing only required values which don't have defaults set
    try:
        # Trigger a new DAG run.
        api_response = api_instance.post_dag_run(dag_id, dag_run)
        pprint(api_response)
    except airflow_client.client.ApiException as e:
        print("Exception when calling DAGRunApi->post_dag_run: %s\n" % e)

Parameters

Name	Type	Description	Notes
dag_id	str	The DAG ID.
dag_run	DAGRun

Return type

DAGRun

Authorization

Basic, Kerberos

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Success.	-
400	Client specified an invalid argument.	-
401	Request not authenticated due to missing, invalid, authentication info.	-
403	Client does not have sufficient permission.	-
404	A specified resource is not found.	-
409	An existing resource conflicts with the request.	-

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set_dag_run_note

DAGRun set_dag_run_note(dag_id, dag_run_id, set_dag_run_note)

Update the DagRun note.

Update the manual user note of a DagRun. New in version 2.5.0

Example

Basic Authentication (Basic):

import time
import airflow_client.client
from airflow_client.client.api import dag_run_api
from airflow_client.client.model.set_dag_run_note import SetDagRunNote
from airflow_client.client.model.error import Error
from airflow_client.client.model.dag_run import DAGRun
from pprint import pprint
# Defining the host is optional and defaults to /api/v1
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "/api/v1"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure HTTP basic authorization: Basic
configuration = airflow_client.client.Configuration(
    username = 'YOUR_USERNAME',
    password = 'YOUR_PASSWORD'
)

# Enter a context with an instance of the API client
with airflow_client.client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = dag_run_api.DAGRunApi(api_client)
    dag_id = "dag_id_example" # str | The DAG ID.
    dag_run_id = "dag_run_id_example" # str | The DAG run ID.
    set_dag_run_note = SetDagRunNote(
        note="note_example",
    ) # SetDagRunNote | Parameters of set DagRun note.

    # example passing only required values which don't have defaults set
    try:
        # Update the DagRun note.
        api_response = api_instance.set_dag_run_note(dag_id, dag_run_id, set_dag_run_note)
        pprint(api_response)
    except airflow_client.client.ApiException as e:
        print("Exception when calling DAGRunApi->set_dag_run_note: %s\n" % e)

Parameters

Name	Type	Description
dag_id	str	The DAG ID.
dag_run_id	str	The DAG run ID.
set_dag_run_note	SetDagRunNote	Parameters of set DagRun note.

Return type

DAGRun

Authorization

Basic, Kerberos

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Success.	-
400	Client specified an invalid argument.	-
401	Request not authenticated due to missing, invalid, authentication info.	-
403	Client does not have sufficient permission.	-
404	A specified resource is not found.	-

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update_dag_run_state

DAGRun update_dag_run_state(dag_id, dag_run_id, update_dag_run_state)

Modify a DAG run

Modify a DAG run. New in version 2.2.0

Example

Basic Authentication (Basic):

import time
import airflow_client.client
from airflow_client.client.api import dag_run_api
from airflow_client.client.model.error import Error
from airflow_client.client.model.update_dag_run_state import UpdateDagRunState
from airflow_client.client.model.dag_run import DAGRun
from pprint import pprint
# Defining the host is optional and defaults to /api/v1
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "/api/v1"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure HTTP basic authorization: Basic
configuration = airflow_client.client.Configuration(
    username = 'YOUR_USERNAME',
    password = 'YOUR_PASSWORD'
)

# Enter a context with an instance of the API client
with airflow_client.client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = dag_run_api.DAGRunApi(api_client)
    dag_id = "dag_id_example" # str | The DAG ID.
    dag_run_id = "dag_run_id_example" # str | The DAG run ID.
    update_dag_run_state = UpdateDagRunState(
        state="success",
    ) # UpdateDagRunState | 

    # example passing only required values which don't have defaults set
    try:
        # Modify a DAG run
        api_response = api_instance.update_dag_run_state(dag_id, dag_run_id, update_dag_run_state)
        pprint(api_response)
    except airflow_client.client.ApiException as e:
        print("Exception when calling DAGRunApi->update_dag_run_state: %s\n" % e)

Parameters

Name	Type	Description
dag_id	str	The DAG ID.
dag_run_id	str	The DAG run ID.
update_dag_run_state	UpdateDagRunState

Return type

DAGRun

Authorization

Basic, Kerberos

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Success.	-
400	Client specified an invalid argument.	-
401	Request not authenticated due to missing, invalid, authentication info.	-
403	Client does not have sufficient permission.	-
404	A specified resource is not found.	-

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Files

DAGRunApi.md

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DAGRunApi.md

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airflow_client.client.DAGRunApi

clear_dag_run

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

delete_dag_run

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

get_dag_run

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

get_dag_runs

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

get_dag_runs_batch

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

get_upstream_dataset_events

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

post_dag_run

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

set_dag_run_note

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

update_dag_run_state

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details