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 |
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
import time import airflow_client.client from airflow_client.client.api import dag_run_api from airflow_client.client.model.clear_dag_run import ClearDagRun 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 = 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 = client.Configuration( username = 'YOUR_USERNAME', password = 'YOUR_PASSWORD' ) # Enter a context with an instance of the API client with 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 client.ApiException as e: print("Exception when calling DAGRunApi->clear_dag_run: %s\n" % e)
Name | Type | Description | Notes |
---|---|---|---|
dag_id | str | The DAG ID. | |
dag_run_id | str | The DAG run ID. | |
clear_dag_run | ClearDagRun |
bool, date, datetime, dict, float, int, list, str, none_type
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(dag_id, dag_run_id)
Delete a DAG run
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 = 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 = client.Configuration( username = 'YOUR_USERNAME', password = 'YOUR_PASSWORD' ) # Enter a context with an instance of the API client with 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 client.ApiException as e: print("Exception when calling DAGRunApi->delete_dag_run: %s\n" % e)
Name | Type | Description | Notes |
---|---|---|---|
dag_id | str | The DAG ID. | |
dag_run_id | str | The DAG run ID. |
void (empty response body)
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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DAGRun get_dag_run(dag_id, dag_run_id)
Get a DAG run
import time import airflow_client.client from airflow_client.client.api import dag_run_api from airflow_client.client.model.dag_run import DAGRun 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 = 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 = client.Configuration( username = 'YOUR_USERNAME', password = 'YOUR_PASSWORD' ) # Enter a context with an instance of the API client with 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 a DAG run api_response = api_instance.get_dag_run(dag_id, dag_run_id) pprint(api_response) except client.ApiException as e: print("Exception when calling DAGRunApi->get_dag_run: %s\n" % e)
Name | Type | Description | Notes |
---|---|---|---|
dag_id | str | The DAG ID. | |
dag_run_id | str | The DAG run ID. |
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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DAGRunCollection get_dag_runs(dag_id)
List DAG runs
This endpoint allows specifying ~
as the dag_id to retrieve DAG runs for all DAGs.
import time import airflow_client.client from airflow_client.client.api import dag_run_api from airflow_client.client.model.dag_run_collection import DAGRunCollection 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 = 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 = client.Configuration( username = 'YOUR_USERNAME', password = 'YOUR_PASSWORD' ) # Enter a context with an instance of the API client with 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) # 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 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) pprint(api_response) except client.ApiException as e: print("Exception when calling DAGRunApi->get_dag_runs: %s\n" % e)
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] |
Status code | Description | Response headers |
---|---|---|
200 | List of DAG runs. | - |
401 | Request not authenticated due to missing, invalid, authentication info. | - |
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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.
import time import airflow_client.client from airflow_client.client.api import dag_run_api from airflow_client.client.model.list_dag_runs_form import ListDagRunsForm from airflow_client.client.model.dag_run_collection import DAGRunCollection 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 = 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 = client.Configuration( username = 'YOUR_USERNAME', password = 'YOUR_PASSWORD' ) # Enter a context with an instance of the API client with 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( order_by="order_by_example", page_offset=0, page_limit=100, dag_ids=[ "dag_ids_example", ], states=[ "states_example", ], execution_date_gte=dateutil_parser('1970-01-01T00:00:00.00Z'), execution_date_lte=dateutil_parser('1970-01-01T00:00:00.00Z'), start_date_gte=dateutil_parser('1970-01-01T00:00:00.00Z'), start_date_lte=dateutil_parser('1970-01-01T00:00:00.00Z'), end_date_gte=dateutil_parser('1970-01-01T00:00:00.00Z'), end_date_lte=dateutil_parser('1970-01-01T00:00:00.00Z'), ) # 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 client.ApiException as e: print("Exception when calling DAGRunApi->get_dag_runs_batch: %s\n" % e)
Name | Type | Description | Notes |
---|---|---|---|
list_dag_runs_form | ListDagRunsForm |
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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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
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 = 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 = client.Configuration( username = 'YOUR_USERNAME', password = 'YOUR_PASSWORD' ) # Enter a context with an instance of the API client with 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 client.ApiException as e: print("Exception when calling DAGRunApi->get_upstream_dataset_events: %s\n" % e)
Name | Type | Description | Notes |
---|---|---|---|
dag_id | str | The DAG ID. | |
dag_run_id | str | The DAG run ID. |
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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DAGRun post_dag_run(dag_id, dag_run)
Trigger a new DAG run
import time import airflow_client.client from airflow_client.client.api import dag_run_api from airflow_client.client.model.dag_run import DAGRun 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 = 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 = client.Configuration( username = 'YOUR_USERNAME', password = 'YOUR_PASSWORD' ) # Enter a context with an instance of the API client with 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( dag_run_id="dag_run_id_example", logical_date=dateutil_parser('1970-01-01T00:00:00.00Z'), execution_date=dateutil_parser('1970-01-01T00:00:00.00Z'), conf={}, 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 client.ApiException as e: print("Exception when calling DAGRunApi->post_dag_run: %s\n" % e)
Name | Type | Description | Notes |
---|---|---|---|
dag_id | str | The DAG ID. | |
dag_run | DAGRun |
Status code | Description | Response headers |
---|---|---|
200 | Success. | - |
400 | Client specified an invalid argument. | - |
401 | Request not authenticated due to missing, invalid, authentication info. | - |
409 | An existing resource conflicts with the request. | - |
403 | Client does not have sufficient permission. | - |
404 | A specified resource is not found. | - |
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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
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.dag_run import DAGRun 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 = 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 = client.Configuration( username = 'YOUR_USERNAME', password = 'YOUR_PASSWORD' ) # Enter a context with an instance of the API client with 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 client.ApiException as e: print("Exception when calling DAGRunApi->set_dag_run_note: %s\n" % e)
Name | Type | Description | Notes |
---|---|---|---|
dag_id | str | The DAG ID. | |
dag_run_id | str | The DAG run ID. | |
set_dag_run_note | SetDagRunNote | Parameters of set DagRun note. |
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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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
import time import airflow_client.client from airflow_client.client.api import dag_run_api from airflow_client.client.model.dag_run import DAGRun from airflow_client.client.model.update_dag_run_state import UpdateDagRunState 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 = 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 = client.Configuration( username = 'YOUR_USERNAME', password = 'YOUR_PASSWORD' ) # Enter a context with an instance of the API client with 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 client.ApiException as e: print("Exception when calling DAGRunApi->update_dag_run_state: %s\n" % e)
Name | Type | Description | Notes |
---|---|---|---|
dag_id | str | The DAG ID. | |
dag_run_id | str | The DAG run ID. | |
update_dag_run_state | UpdateDagRunState |
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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