airflow_client.client.DagRunApi

August 13, 2026 · View on GitHub

All URIs are relative to http://localhost

MethodHTTP requestDescription
bulk_dag_runsPATCH /api/v2/dags/{dag_id}/dagRunsBulk Dag Runs
clear_dag_runPOST /api/v2/dags/{dag_id}/dagRuns/{dag_run_id}/clearClear Dag Run
clear_dag_run_partitionsPOST /api/v2/dags/{dag_id}/clearPartitionsClear Dag Run Partitions
clear_dag_runsPOST /api/v2/dags/{dag_id}/clearDagRunsClear Dag Runs
delete_dag_runDELETE /api/v2/dags/{dag_id}/dagRuns/{dag_run_id}Delete Dag Run
get_dag_runGET /api/v2/dags/{dag_id}/dagRuns/{dag_run_id}Get Dag Run
get_dag_runsGET /api/v2/dags/{dag_id}/dagRunsGet Dag Runs
get_list_dag_runs_batchPOST /api/v2/dags/{dag_id}/dagRuns/listGet List Dag Runs Batch
get_upstream_asset_eventsGET /api/v2/dags/{dag_id}/dagRuns/{dag_run_id}/upstreamAssetEventsGet Upstream Asset Events
patch_dag_runPATCH /api/v2/dags/{dag_id}/dagRuns/{dag_run_id}Patch Dag Run
trigger_dag_runPOST /api/v2/dags/{dag_id}/dagRunsTrigger Dag Run
wait_dag_run_until_finishedGET /api/v2/dags/{dag_id}/dagRuns/{dag_run_id}/waitExperimental: Wait for a dag run to complete, and return task results if requested.

bulk_dag_runs

BulkResponse bulk_dag_runs(dag_id, bulk_body_bulk_dag_run_body)

Bulk Dag Runs

Bulk update or delete Dag Runs.

Example

  • OAuth Authentication (OAuth2PasswordBearer):
  • Bearer Authentication (HTTPBearer):
import airflow_client.client
from airflow_client.client.models.bulk_body_bulk_dag_run_body import BulkBodyBulkDAGRunBody
from airflow_client.client.models.bulk_response import BulkResponse
from airflow_client.client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "http://localhost"
)

# 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.

configuration.access_token = os.environ["ACCESS_TOKEN"]

# Configure Bearer authorization: HTTPBearer
configuration = airflow_client.client.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# 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 = airflow_client.client.DagRunApi(api_client)
    dag_id = 'dag_id_example' # str | 
    bulk_body_bulk_dag_run_body = airflow_client.client.BulkBodyBulkDAGRunBody() # BulkBodyBulkDAGRunBody | 

    try:
        # Bulk Dag Runs
        api_response = api_instance.bulk_dag_runs(dag_id, bulk_body_bulk_dag_run_body)
        print("The response of DagRunApi->bulk_dag_runs:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling DagRunApi->bulk_dag_runs: %s\n" % e)

Parameters

NameTypeDescriptionNotes
dag_idstr
bulk_body_bulk_dag_run_bodyBulkBodyBulkDAGRunBody

Return type

BulkResponse

Authorization

OAuth2PasswordBearer, HTTPBearer

HTTP request headers

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

HTTP response details

Status codeDescriptionResponse headers
200Successful Response-
401Unauthorized-
403Forbidden-
422Validation Error-

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clear_dag_run

ResponseClearDagRun clear_dag_run(dag_id, dag_run_id, dag_run_clear_body)

Clear Dag Run

Example

  • OAuth Authentication (OAuth2PasswordBearer):
  • Bearer Authentication (HTTPBearer):
import airflow_client.client
from airflow_client.client.models.dag_run_clear_body import DAGRunClearBody
from airflow_client.client.models.response_clear_dag_run import ResponseClearDagRun
from airflow_client.client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "http://localhost"
)

# 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.

configuration.access_token = os.environ["ACCESS_TOKEN"]

# Configure Bearer authorization: HTTPBearer
configuration = airflow_client.client.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# 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 = airflow_client.client.DagRunApi(api_client)
    dag_id = 'dag_id_example' # str | 
    dag_run_id = 'dag_run_id_example' # str | 
    dag_run_clear_body = airflow_client.client.DAGRunClearBody() # DAGRunClearBody | 

    try:
        # Clear Dag Run
        api_response = api_instance.clear_dag_run(dag_id, dag_run_id, dag_run_clear_body)
        print("The response of DagRunApi->clear_dag_run:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling DagRunApi->clear_dag_run: %s\n" % e)

Parameters

NameTypeDescriptionNotes
dag_idstr
dag_run_idstr
dag_run_clear_bodyDAGRunClearBody

Return type

ResponseClearDagRun

Authorization

OAuth2PasswordBearer, HTTPBearer

HTTP request headers

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

HTTP response details

Status codeDescriptionResponse headers
200Successful Response-
401Unauthorized-
403Forbidden-
404Not Found-
422Validation Error-

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clear_dag_run_partitions

ClearPartitionsResponse clear_dag_run_partitions(dag_id, clear_partitions_body)

Clear Dag Run Partitions

Reset partition_key and partition_date fields on matching Dag Runs.

Example

  • OAuth Authentication (OAuth2PasswordBearer):
  • Bearer Authentication (HTTPBearer):
import airflow_client.client
from airflow_client.client.models.clear_partitions_body import ClearPartitionsBody
from airflow_client.client.models.clear_partitions_response import ClearPartitionsResponse
from airflow_client.client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "http://localhost"
)

# 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.

configuration.access_token = os.environ["ACCESS_TOKEN"]

# Configure Bearer authorization: HTTPBearer
configuration = airflow_client.client.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# 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 = airflow_client.client.DagRunApi(api_client)
    dag_id = 'dag_id_example' # str | 
    clear_partitions_body = airflow_client.client.ClearPartitionsBody() # ClearPartitionsBody | 

    try:
        # Clear Dag Run Partitions
        api_response = api_instance.clear_dag_run_partitions(dag_id, clear_partitions_body)
        print("The response of DagRunApi->clear_dag_run_partitions:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling DagRunApi->clear_dag_run_partitions: %s\n" % e)

Parameters

NameTypeDescriptionNotes
dag_idstr
clear_partitions_bodyClearPartitionsBody

Return type

ClearPartitionsResponse

Authorization

OAuth2PasswordBearer, HTTPBearer

HTTP request headers

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

HTTP response details

Status codeDescriptionResponse headers
200Successful Response-
400Bad Request-
401Unauthorized-
403Forbidden-
404Not Found-
422Validation Error-

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clear_dag_runs

ResponseClearDagRuns clear_dag_runs(dag_id, bulk_dag_run_clear_body)

Clear Dag Runs

Clear multiple Dag Runs in a single request.

Example

  • OAuth Authentication (OAuth2PasswordBearer):
  • Bearer Authentication (HTTPBearer):
import airflow_client.client
from airflow_client.client.models.bulk_dag_run_clear_body import BulkDAGRunClearBody
from airflow_client.client.models.response_clear_dag_runs import ResponseClearDagRuns
from airflow_client.client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "http://localhost"
)

# 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.

configuration.access_token = os.environ["ACCESS_TOKEN"]

# Configure Bearer authorization: HTTPBearer
configuration = airflow_client.client.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# 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 = airflow_client.client.DagRunApi(api_client)
    dag_id = 'dag_id_example' # str | 
    bulk_dag_run_clear_body = airflow_client.client.BulkDAGRunClearBody() # BulkDAGRunClearBody | 

    try:
        # Clear Dag Runs
        api_response = api_instance.clear_dag_runs(dag_id, bulk_dag_run_clear_body)
        print("The response of DagRunApi->clear_dag_runs:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling DagRunApi->clear_dag_runs: %s\n" % e)

Parameters

NameTypeDescriptionNotes
dag_idstr
bulk_dag_run_clear_bodyBulkDAGRunClearBody

Return type

ResponseClearDagRuns

Authorization

OAuth2PasswordBearer, HTTPBearer

HTTP request headers

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

HTTP response details

Status codeDescriptionResponse headers
200Successful Response-
400Bad Request-
401Unauthorized-
403Forbidden-
404Not Found-
422Validation Error-

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delete_dag_run

delete_dag_run(dag_id, dag_run_id)

Delete Dag Run

Delete a Dag Run entry.

Example

  • OAuth Authentication (OAuth2PasswordBearer):
  • Bearer Authentication (HTTPBearer):
import airflow_client.client
from airflow_client.client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "http://localhost"
)

# 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.

configuration.access_token = os.environ["ACCESS_TOKEN"]

# Configure Bearer authorization: HTTPBearer
configuration = airflow_client.client.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# 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 = airflow_client.client.DagRunApi(api_client)
    dag_id = 'dag_id_example' # str | 
    dag_run_id = 'dag_run_id_example' # str | 

    try:
        # Delete Dag Run
        api_instance.delete_dag_run(dag_id, dag_run_id)
    except Exception as e:
        print("Exception when calling DagRunApi->delete_dag_run: %s\n" % e)

Parameters

NameTypeDescriptionNotes
dag_idstr
dag_run_idstr

Return type

void (empty response body)

Authorization

OAuth2PasswordBearer, HTTPBearer

HTTP request headers

  • Content-Type: Not defined
  • Accept: application/json

HTTP response details

Status codeDescriptionResponse headers
204Successful Response-
400Bad Request-
401Unauthorized-
403Forbidden-
404Not Found-
422Validation Error-

[Back to top] [Back to API list] [Back to Model list] [Back to README]

get_dag_run

DAGRunResponse get_dag_run(dag_id, dag_run_id)

Get Dag Run

Example

  • OAuth Authentication (OAuth2PasswordBearer):
  • Bearer Authentication (HTTPBearer):
import airflow_client.client
from airflow_client.client.models.dag_run_response import DAGRunResponse
from airflow_client.client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "http://localhost"
)

# 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.

configuration.access_token = os.environ["ACCESS_TOKEN"]

# Configure Bearer authorization: HTTPBearer
configuration = airflow_client.client.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# 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 = airflow_client.client.DagRunApi(api_client)
    dag_id = 'dag_id_example' # str | 
    dag_run_id = 'dag_run_id_example' # str | 

    try:
        # Get Dag Run
        api_response = api_instance.get_dag_run(dag_id, dag_run_id)
        print("The response of DagRunApi->get_dag_run:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling DagRunApi->get_dag_run: %s\n" % e)

Parameters

NameTypeDescriptionNotes
dag_idstr
dag_run_idstr

Return type

DAGRunResponse

Authorization

OAuth2PasswordBearer, HTTPBearer

HTTP request headers

  • Content-Type: Not defined
  • Accept: application/json

HTTP response details

Status codeDescriptionResponse headers
200Successful Response-
401Unauthorized-
403Forbidden-
404Not Found-
422Validation Error-

[Back to top] [Back to API list] [Back to Model list] [Back to README]

get_dag_runs

DAGRunCollectionResponse get_dag_runs(dag_id, partition_date_gte=partition_date_gte, partition_date_lte=partition_date_lte, cursor=cursor, limit=limit, offset=offset, run_after_gte=run_after_gte, run_after_gt=run_after_gt, run_after_lte=run_after_lte, run_after_lt=run_after_lt, logical_date_gte=logical_date_gte, logical_date_gt=logical_date_gt, logical_date_lte=logical_date_lte, logical_date_lt=logical_date_lt, start_date_gte=start_date_gte, start_date_gt=start_date_gt, start_date_lte=start_date_lte, start_date_lt=start_date_lt, end_date_gte=end_date_gte, end_date_gt=end_date_gt, end_date_lte=end_date_lte, end_date_lt=end_date_lt, duration_gte=duration_gte, duration_gt=duration_gt, duration_lte=duration_lte, duration_lt=duration_lt, updated_at_gte=updated_at_gte, updated_at_gt=updated_at_gt, updated_at_lte=updated_at_lte, updated_at_lt=updated_at_lt, conf_contains=conf_contains, run_type=run_type, state=state, dag_version=dag_version, bundle_version=bundle_version, order_by=order_by, run_id_pattern=run_id_pattern, run_id_prefix_pattern=run_id_prefix_pattern, triggering_user_name_pattern=triggering_user_name_pattern, triggering_user_name_prefix_pattern=triggering_user_name_prefix_pattern, dag_id_pattern=dag_id_pattern, dag_id_prefix_pattern=dag_id_prefix_pattern, partition_key_pattern=partition_key_pattern, partition_key_prefix_pattern=partition_key_prefix_pattern, consuming_asset_pattern=consuming_asset_pattern)

Get Dag Runs

Get all Dag Runs.

This endpoint allows specifying ~ as the dag_id to retrieve Dag Runs for all Dags.

Supports two pagination modes:

Offset (default): use limit and offset query parameters. Returns total_entries.

Cursor: pass cursor (empty string for the first page, then next_cursor from the response). When cursor is provided, offset is ignored and total_entries is not returned. next_cursor is null when there are no more pages; previous_cursor is null on the first page.

Example

  • OAuth Authentication (OAuth2PasswordBearer):
  • Bearer Authentication (HTTPBearer):
import airflow_client.client
from airflow_client.client.models.dag_run_collection_response import DAGRunCollectionResponse
from airflow_client.client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "http://localhost"
)

# 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.

configuration.access_token = os.environ["ACCESS_TOKEN"]

# Configure Bearer authorization: HTTPBearer
configuration = airflow_client.client.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# 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 = airflow_client.client.DagRunApi(api_client)
    dag_id = 'dag_id_example' # str | 
    partition_date_gte = '2013-10-20' # date | Inclusive lower bound of the partition_date window, interpreted as a local calendar day in the Dag's timetable timezone. Runs from the start of this day onwards match. (optional)
    partition_date_lte = '2013-10-20' # date | Inclusive upper bound of the partition_date window, interpreted as a local calendar day in the Dag's timetable timezone. The whole day is included: runs up to the end of this day match. (optional)
    cursor = 'cursor_example' # str | Cursor for keyset-based pagination. Pass an empty string for the first page, then use ``next_cursor`` from the response. When ``cursor`` is provided, ``offset`` is ignored. (optional)
    limit = 50 # int |  (optional) (default to 50)
    offset = 0 # int |  (optional) (default to 0)
    run_after_gte = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    run_after_gt = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    run_after_lte = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    run_after_lt = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    logical_date_gte = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    logical_date_gt = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    logical_date_lte = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    logical_date_lt = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    start_date_gte = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    start_date_gt = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    start_date_lte = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    start_date_lt = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    end_date_gte = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    end_date_gt = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    end_date_lte = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    end_date_lt = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    duration_gte = 3.4 # float |  (optional)
    duration_gt = 3.4 # float |  (optional)
    duration_lte = 3.4 # float |  (optional)
    duration_lt = 3.4 # float |  (optional)
    updated_at_gte = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    updated_at_gt = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    updated_at_lte = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    updated_at_lt = '2013-10-20T19:20:30+01:00' # datetime |  (optional)
    conf_contains = 'conf_contains_example' # str |  (optional)
    run_type = ['run_type_example'] # List[str] |  (optional)
    state = ['state_example'] # List[str] |  (optional)
    dag_version = [56] # List[int] |  (optional)
    bundle_version = 'bundle_version_example' # str |  (optional)
    order_by = ["id"] # List[str] | Attributes to order by, multi criteria sort is supported. Prefix with `-` for descending order. Supported attributes: `id, state, dag_id, run_id, logical_date, partition_date, run_after, start_date, end_date, updated_at, conf, duration, dag_run_id` (optional) (default to ["id"])
    run_id_pattern = 'run_id_pattern_example' # str | Case-insensitive substring match (SQL `ILIKE`). Slower than `run_id_prefix_pattern` on large tables — see \"Filtering with pattern parameters\". (optional)
    run_id_prefix_pattern = 'run_id_prefix_pattern_example' # str | Case-sensitive, index-friendly prefix match. See \"Filtering with pattern parameters\". (optional)
    triggering_user_name_pattern = 'triggering_user_name_pattern_example' # str | Case-insensitive substring match (SQL `ILIKE`). Slower than `triggering_user_name_prefix_pattern` on large tables — see \"Filtering with pattern parameters\". (optional)
    triggering_user_name_prefix_pattern = 'triggering_user_name_prefix_pattern_example' # str | Case-sensitive, index-friendly prefix match. See \"Filtering with pattern parameters\". (optional)
    dag_id_pattern = 'dag_id_pattern_example' # str | Case-insensitive substring match (SQL `ILIKE`). Slower than `dag_id_prefix_pattern` on large tables — see \"Filtering with pattern parameters\". (optional)
    dag_id_prefix_pattern = 'dag_id_prefix_pattern_example' # str | Case-sensitive, index-friendly prefix match. See \"Filtering with pattern parameters\". (optional)
    partition_key_pattern = 'partition_key_pattern_example' # str | Case-insensitive substring match (SQL `ILIKE`). Here `|` is matched literally, not as OR. Slower than `partition_key_prefix_pattern` on large tables — see \"Filtering with pattern parameters\". (optional)
    partition_key_prefix_pattern = 'partition_key_prefix_pattern_example' # str | Case-sensitive, index-friendly prefix match. Here `|` is matched literally, not as OR. See \"Filtering with pattern parameters\". (optional)
    consuming_asset_pattern = 'consuming_asset_pattern_example' # str | Case-insensitive substring match against the consuming asset name or URI. Unlike the wildcard `*_pattern` parameters, `%` and `_` are matched literally, `|` is not an OR separator, and `~` does not match everything. (optional)

    try:
        # Get Dag Runs
        api_response = api_instance.get_dag_runs(dag_id, partition_date_gte=partition_date_gte, partition_date_lte=partition_date_lte, cursor=cursor, limit=limit, offset=offset, run_after_gte=run_after_gte, run_after_gt=run_after_gt, run_after_lte=run_after_lte, run_after_lt=run_after_lt, logical_date_gte=logical_date_gte, logical_date_gt=logical_date_gt, logical_date_lte=logical_date_lte, logical_date_lt=logical_date_lt, start_date_gte=start_date_gte, start_date_gt=start_date_gt, start_date_lte=start_date_lte, start_date_lt=start_date_lt, end_date_gte=end_date_gte, end_date_gt=end_date_gt, end_date_lte=end_date_lte, end_date_lt=end_date_lt, duration_gte=duration_gte, duration_gt=duration_gt, duration_lte=duration_lte, duration_lt=duration_lt, updated_at_gte=updated_at_gte, updated_at_gt=updated_at_gt, updated_at_lte=updated_at_lte, updated_at_lt=updated_at_lt, conf_contains=conf_contains, run_type=run_type, state=state, dag_version=dag_version, bundle_version=bundle_version, order_by=order_by, run_id_pattern=run_id_pattern, run_id_prefix_pattern=run_id_prefix_pattern, triggering_user_name_pattern=triggering_user_name_pattern, triggering_user_name_prefix_pattern=triggering_user_name_prefix_pattern, dag_id_pattern=dag_id_pattern, dag_id_prefix_pattern=dag_id_prefix_pattern, partition_key_pattern=partition_key_pattern, partition_key_prefix_pattern=partition_key_prefix_pattern, consuming_asset_pattern=consuming_asset_pattern)
        print("The response of DagRunApi->get_dag_runs:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling DagRunApi->get_dag_runs: %s\n" % e)

Parameters

NameTypeDescriptionNotes
dag_idstr
partition_date_gtedateInclusive lower bound of the partition_date window, interpreted as a local calendar day in the Dag's timetable timezone. Runs from the start of this day onwards match.[optional]
partition_date_ltedateInclusive upper bound of the partition_date window, interpreted as a local calendar day in the Dag's timetable timezone. The whole day is included: runs up to the end of this day match.[optional]
cursorstrCursor for keyset-based pagination. Pass an empty string for the first page, then use ``next_cursor`` from the response. When ``cursor`` is provided, ``offset`` is ignored.[optional]
limitint[optional] [default to 50]
offsetint[optional] [default to 0]
run_after_gtedatetime[optional]
run_after_gtdatetime[optional]
run_after_ltedatetime[optional]
run_after_ltdatetime[optional]
logical_date_gtedatetime[optional]
logical_date_gtdatetime[optional]
logical_date_ltedatetime[optional]
logical_date_ltdatetime[optional]
start_date_gtedatetime[optional]
start_date_gtdatetime[optional]
start_date_ltedatetime[optional]
start_date_ltdatetime[optional]
end_date_gtedatetime[optional]
end_date_gtdatetime[optional]
end_date_ltedatetime[optional]
end_date_ltdatetime[optional]
duration_gtefloat[optional]
duration_gtfloat[optional]
duration_ltefloat[optional]
duration_ltfloat[optional]
updated_at_gtedatetime[optional]
updated_at_gtdatetime[optional]
updated_at_ltedatetime[optional]
updated_at_ltdatetime[optional]
conf_containsstr[optional]
run_typeList[str][optional]
stateList[str][optional]
dag_versionList[int][optional]
bundle_versionstr[optional]
order_byList[str]Attributes to order by, multi criteria sort is supported. Prefix with `-` for descending order. Supported attributes: `id, state, dag_id, run_id, logical_date, partition_date, run_after, start_date, end_date, updated_at, conf, duration, dag_run_id`[optional] [default to ["id"]]
run_id_patternstrCase-insensitive substring match (SQL `ILIKE`). Slower than `run_id_prefix_pattern` on large tables — see "Filtering with pattern parameters".[optional]
run_id_prefix_patternstrCase-sensitive, index-friendly prefix match. See "Filtering with pattern parameters".[optional]
triggering_user_name_patternstrCase-insensitive substring match (SQL `ILIKE`). Slower than `triggering_user_name_prefix_pattern` on large tables — see "Filtering with pattern parameters".[optional]
triggering_user_name_prefix_patternstrCase-sensitive, index-friendly prefix match. See "Filtering with pattern parameters".[optional]
dag_id_patternstrCase-insensitive substring match (SQL `ILIKE`). Slower than `dag_id_prefix_pattern` on large tables — see "Filtering with pattern parameters".[optional]
dag_id_prefix_patternstrCase-sensitive, index-friendly prefix match. See "Filtering with pattern parameters".[optional]
partition_key_patternstrCase-insensitive substring match (SQL `ILIKE`). Here `` is matched literally, not as OR. Slower than `partition_key_prefix_pattern` on large tables — see "Filtering with pattern parameters".
partition_key_prefix_patternstrCase-sensitive, index-friendly prefix match. Here `` is matched literally, not as OR. See "Filtering with pattern parameters".
consuming_asset_patternstrCase-insensitive substring match against the consuming asset name or URI. Unlike the wildcard `*pattern` parameters, `%` and `` are matched literally, `` is not an OR separator, and `~` does not match everything.

Return type

DAGRunCollectionResponse

Authorization

OAuth2PasswordBearer, HTTPBearer

HTTP request headers

  • Content-Type: Not defined
  • Accept: application/json

HTTP response details

Status codeDescriptionResponse headers
200Successful Response-
401Unauthorized-
403Forbidden-
404Not Found-
422Validation Error-

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get_list_dag_runs_batch

DAGRunCollectionResponse get_list_dag_runs_batch(dag_id, dag_runs_batch_body)

Get List Dag Runs Batch

Get a list of Dag Runs.

Example

  • OAuth Authentication (OAuth2PasswordBearer):
  • Bearer Authentication (HTTPBearer):
import airflow_client.client
from airflow_client.client.models.dag_run_collection_response import DAGRunCollectionResponse
from airflow_client.client.models.dag_runs_batch_body import DAGRunsBatchBody
from airflow_client.client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "http://localhost"
)

# 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.

configuration.access_token = os.environ["ACCESS_TOKEN"]

# Configure Bearer authorization: HTTPBearer
configuration = airflow_client.client.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# 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 = airflow_client.client.DagRunApi(api_client)
    dag_id = 'dag_id_example' # str | 
    dag_runs_batch_body = airflow_client.client.DAGRunsBatchBody() # DAGRunsBatchBody | 

    try:
        # Get List Dag Runs Batch
        api_response = api_instance.get_list_dag_runs_batch(dag_id, dag_runs_batch_body)
        print("The response of DagRunApi->get_list_dag_runs_batch:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling DagRunApi->get_list_dag_runs_batch: %s\n" % e)

Parameters

NameTypeDescriptionNotes
dag_idstr
dag_runs_batch_bodyDAGRunsBatchBody

Return type

DAGRunCollectionResponse

Authorization

OAuth2PasswordBearer, HTTPBearer

HTTP request headers

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

HTTP response details

Status codeDescriptionResponse headers
200Successful Response-
401Unauthorized-
403Forbidden-
404Not Found-
422Validation Error-

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get_upstream_asset_events

AssetEventCollectionResponse get_upstream_asset_events(dag_id, dag_run_id)

Get Upstream Asset Events

If dag run is asset-triggered, return the asset events that triggered it.

Example

  • OAuth Authentication (OAuth2PasswordBearer):
  • Bearer Authentication (HTTPBearer):
import airflow_client.client
from airflow_client.client.models.asset_event_collection_response import AssetEventCollectionResponse
from airflow_client.client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "http://localhost"
)

# 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.

configuration.access_token = os.environ["ACCESS_TOKEN"]

# Configure Bearer authorization: HTTPBearer
configuration = airflow_client.client.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# 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 = airflow_client.client.DagRunApi(api_client)
    dag_id = 'dag_id_example' # str | 
    dag_run_id = 'dag_run_id_example' # str | 

    try:
        # Get Upstream Asset Events
        api_response = api_instance.get_upstream_asset_events(dag_id, dag_run_id)
        print("The response of DagRunApi->get_upstream_asset_events:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling DagRunApi->get_upstream_asset_events: %s\n" % e)

Parameters

NameTypeDescriptionNotes
dag_idstr
dag_run_idstr

Return type

AssetEventCollectionResponse

Authorization

OAuth2PasswordBearer, HTTPBearer

HTTP request headers

  • Content-Type: Not defined
  • Accept: application/json

HTTP response details

Status codeDescriptionResponse headers
200Successful Response-
401Unauthorized-
403Forbidden-
404Not Found-
422Validation Error-

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patch_dag_run

DAGRunResponse patch_dag_run(dag_id, dag_run_id, dag_run_patch_body, update_mask=update_mask)

Patch Dag Run

Modify a Dag Run.

Example

  • OAuth Authentication (OAuth2PasswordBearer):
  • Bearer Authentication (HTTPBearer):
import airflow_client.client
from airflow_client.client.models.dag_run_patch_body import DAGRunPatchBody
from airflow_client.client.models.dag_run_response import DAGRunResponse
from airflow_client.client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "http://localhost"
)

# 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.

configuration.access_token = os.environ["ACCESS_TOKEN"]

# Configure Bearer authorization: HTTPBearer
configuration = airflow_client.client.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# 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 = airflow_client.client.DagRunApi(api_client)
    dag_id = 'dag_id_example' # str | 
    dag_run_id = 'dag_run_id_example' # str | 
    dag_run_patch_body = airflow_client.client.DAGRunPatchBody() # DAGRunPatchBody | 
    update_mask = ['update_mask_example'] # List[str] |  (optional)

    try:
        # Patch Dag Run
        api_response = api_instance.patch_dag_run(dag_id, dag_run_id, dag_run_patch_body, update_mask=update_mask)
        print("The response of DagRunApi->patch_dag_run:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling DagRunApi->patch_dag_run: %s\n" % e)

Parameters

NameTypeDescriptionNotes
dag_idstr
dag_run_idstr
dag_run_patch_bodyDAGRunPatchBody
update_maskList[str][optional]

Return type

DAGRunResponse

Authorization

OAuth2PasswordBearer, HTTPBearer

HTTP request headers

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

HTTP response details

Status codeDescriptionResponse headers
200Successful Response-
400Bad Request-
401Unauthorized-
403Forbidden-
404Not Found-
422Validation Error-

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trigger_dag_run

DAGRunResponse trigger_dag_run(dag_id, trigger_dag_run_post_body)

Trigger Dag Run

Trigger a Dag.

Example

  • OAuth Authentication (OAuth2PasswordBearer):
  • Bearer Authentication (HTTPBearer):
import airflow_client.client
from airflow_client.client.models.dag_run_response import DAGRunResponse
from airflow_client.client.models.trigger_dag_run_post_body import TriggerDAGRunPostBody
from airflow_client.client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "http://localhost"
)

# 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.

configuration.access_token = os.environ["ACCESS_TOKEN"]

# Configure Bearer authorization: HTTPBearer
configuration = airflow_client.client.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# 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 = airflow_client.client.DagRunApi(api_client)
    dag_id = None # object | 
    trigger_dag_run_post_body = airflow_client.client.TriggerDAGRunPostBody() # TriggerDAGRunPostBody | 

    try:
        # Trigger Dag Run
        api_response = api_instance.trigger_dag_run(dag_id, trigger_dag_run_post_body)
        print("The response of DagRunApi->trigger_dag_run:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling DagRunApi->trigger_dag_run: %s\n" % e)

Parameters

NameTypeDescriptionNotes
dag_idobject
trigger_dag_run_post_bodyTriggerDAGRunPostBody

Return type

DAGRunResponse

Authorization

OAuth2PasswordBearer, HTTPBearer

HTTP request headers

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

HTTP response details

Status codeDescriptionResponse headers
200Successful Response-
400Bad Request-
401Unauthorized-
403Forbidden-
404Not Found-
409Conflict-
422Validation Error-

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wait_dag_run_until_finished

object wait_dag_run_until_finished(dag_id, dag_run_id, interval, result=result)

Experimental: Wait for a dag run to complete, and return task results if requested.

🚧 This is an experimental endpoint and may change or be removed without notice.Successful response are streamed as newline-delimited JSON (NDJSON). Each line is a JSON object representing the Dag run state.

Example

  • OAuth Authentication (OAuth2PasswordBearer):
  • Bearer Authentication (HTTPBearer):
import airflow_client.client
from airflow_client.client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost
# See configuration.py for a list of all supported configuration parameters.
configuration = airflow_client.client.Configuration(
    host = "http://localhost"
)

# 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.

configuration.access_token = os.environ["ACCESS_TOKEN"]

# Configure Bearer authorization: HTTPBearer
configuration = airflow_client.client.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# 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 = airflow_client.client.DagRunApi(api_client)
    dag_id = 'dag_id_example' # str | 
    dag_run_id = 'dag_run_id_example' # str | 
    interval = 3.4 # float | Seconds to wait between dag run state checks
    result = ['result_example'] # List[str] | Collect result XCom from task. Can be set multiple times. If unset, return value of the return task as specified in the dag (in present) is returned by default. (optional)

    try:
        # Experimental: Wait for a dag run to complete, and return task results if requested.
        api_response = api_instance.wait_dag_run_until_finished(dag_id, dag_run_id, interval, result=result)
        print("The response of DagRunApi->wait_dag_run_until_finished:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling DagRunApi->wait_dag_run_until_finished: %s\n" % e)

Parameters

NameTypeDescriptionNotes
dag_idstr
dag_run_idstr
intervalfloatSeconds to wait between dag run state checks
resultList[str]Collect result XCom from task. Can be set multiple times. If unset, return value of the return task as specified in the dag (in present) is returned by default.[optional]

Return type

object

Authorization

OAuth2PasswordBearer, HTTPBearer

HTTP request headers

  • Content-Type: Not defined
  • Accept: application/json, application/x-ndjson

HTTP response details

Status codeDescriptionResponse headers
200Successful Response-
401Unauthorized-
403Forbidden-
404Not Found-
422Validation Error-

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