docs/DagRunApi.md

# airflow_client.client.DagRunApi

All URIs are relative to *http://localhost*

Method | HTTP request | Description
------------- | ------------- | -------------
[**bulk_dag_runs**](DagRunApi.md#bulk_dag_runs) | **PATCH** /api/v2/dags/{dag_id}/dagRuns | Bulk Dag Runs
[**clear_dag_run**](DagRunApi.md#clear_dag_run) | **POST** /api/v2/dags/{dag_id}/dagRuns/{dag_run_id}/clear | Clear Dag Run
[**clear_dag_run_partitions**](DagRunApi.md#clear_dag_run_partitions) | **POST** /api/v2/dags/{dag_id}/clearPartitions | Clear Dag Run Partitions
[**clear_dag_runs**](DagRunApi.md#clear_dag_runs) | **POST** /api/v2/dags/{dag_id}/clearDagRuns | Clear Dag Runs
[**delete_dag_run**](DagRunApi.md#delete_dag_run) | **DELETE** /api/v2/dags/{dag_id}/dagRuns/{dag_run_id} | Delete Dag Run
[**get_dag_run**](DagRunApi.md#get_dag_run) | **GET** /api/v2/dags/{dag_id}/dagRuns/{dag_run_id} | Get Dag Run
[**get_dag_runs**](DagRunApi.md#get_dag_runs) | **GET** /api/v2/dags/{dag_id}/dagRuns | Get Dag Runs
[**get_list_dag_runs_batch**](DagRunApi.md#get_list_dag_runs_batch) | **POST** /api/v2/dags/{dag_id}/dagRuns/list | Get List Dag Runs Batch
[**get_upstream_asset_events**](DagRunApi.md#get_upstream_asset_events) | **GET** /api/v2/dags/{dag_id}/dagRuns/{dag_run_id}/upstreamAssetEvents | Get Upstream Asset Events
[**patch_dag_run**](DagRunApi.md#patch_dag_run) | **PATCH** /api/v2/dags/{dag_id}/dagRuns/{dag_run_id} | Patch Dag Run
[**trigger_dag_run**](DagRunApi.md#trigger_dag_run) | **POST** /api/v2/dags/{dag_id}/dagRuns | Trigger Dag Run
[**wait_dag_run_until_finished**](DagRunApi.md#wait_dag_run_until_finished) | **GET** /api/v2/dags/{dag_id}/dagRuns/{dag_run_id}/wait | Experimental: 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):

```python
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


Name | Type | Description  | Notes
------------- | ------------- | ------------- | -------------
 **dag_id** | **str**|  | 
 **bulk_body_bulk_dag_run_body** | [**BulkBodyBulkDAGRunBody**](BulkBodyBulkDAGRunBody.md)|  | 

### Return type

[**BulkResponse**](BulkResponse.md)

### Authorization

[OAuth2PasswordBearer](../README.md#OAuth2PasswordBearer), [HTTPBearer](../README.md#HTTPBearer)

### HTTP request headers

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

### HTTP response details

| Status code | Description | Response headers |
|-------------|-------------|------------------|
**200** | Successful Response |  -  |
**401** | Unauthorized |  -  |
**403** | Forbidden |  -  |
**422** | Validation Error |  -  |

[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md)

# **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):

```python
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


Name | Type | Description  | Notes
------------- | ------------- | ------------- | -------------
 **dag_id** | **str**|  | 
 **dag_run_id** | **str**|  | 
 **dag_run_clear_body** | [**DAGRunClearBody**](DAGRunClearBody.md)|  | 

### Return type

[**ResponseClearDagRun**](ResponseClearDagRun.md)

### Authorization

[OAuth2PasswordBearer](../README.md#OAuth2PasswordBearer), [HTTPBearer](../README.md#HTTPBearer)

### HTTP request headers

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

### HTTP response details

| Status code | Description | Response headers |
|-------------|-------------|------------------|
**200** | Successful Response |  -  |
**401** | Unauthorized |  -  |
**403** | Forbidden |  -  |
**404** | Not Found |  -  |
**422** | Validation Error |  -  |

[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md)

# **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):

```python
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


Name | Type | Description  | Notes
------------- | ------------- | ------------- | -------------
 **dag_id** | **str**|  | 
 **clear_partitions_body** | [**ClearPartitionsBody**](ClearPartitionsBody.md)|  | 

### Return type

[**ClearPartitionsResponse**](ClearPartitionsResponse.md)

### Authorization

[OAuth2PasswordBearer](../README.md#OAuth2PasswordBearer), [HTTPBearer](../README.md#HTTPBearer)

### HTTP request headers

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

### HTTP response details

| Status code | Description | Response headers |
|-------------|-------------|------------------|
**200** | Successful Response |  -  |
**400** | Bad Request |  -  |
**401** | Unauthorized |  -  |
**403** | Forbidden |  -  |
**404** | Not Found |  -  |
**422** | Validation Error |  -  |

[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md)

# **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):

```python
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


Name | Type | Description  | Notes
------------- | ------------- | ------------- | -------------
 **dag_id** | **str**|  | 
 **bulk_dag_run_clear_body** | [**BulkDAGRunClearBody**](BulkDAGRunClearBody.md)|  | 

### Return type

[**ResponseClearDagRuns**](ResponseClearDagRuns.md)

### Authorization

[OAuth2PasswordBearer](../README.md#OAuth2PasswordBearer), [HTTPBearer](../README.md#HTTPBearer)

### HTTP request headers

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

### HTTP response details

| Status code | Description | Response headers |
|-------------|-------------|------------------|
**200** | Successful Response |  -  |
**400** | Bad Request |  -  |
**401** | Unauthorized |  -  |
**403** | Forbidden |  -  |
**404** | Not Found |  -  |
**422** | Validation Error |  -  |

[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md)

# **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):

```python
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


Name | Type | Description  | Notes
------------- | ------------- | ------------- | -------------
 **dag_id** | **str**|  | 
 **dag_run_id** | **str**|  | 

### Return type

void (empty response body)

### Authorization

[OAuth2PasswordBearer](../README.md#OAuth2PasswordBearer), [HTTPBearer](../README.md#HTTPBearer)

### HTTP request headers

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

### HTTP response details

| Status code | Description | Response headers |
|-------------|-------------|------------------|
**204** | Successful Response |  -  |
**400** | Bad Request |  -  |
**401** | Unauthorized |  -  |
**403** | Forbidden |  -  |
**404** | Not Found |  -  |
**422** | Validation Error |  -  |

[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md)

# **get_dag_run**
> DAGRunResponse get_dag_run(dag_id, dag_run_id)

Get Dag Run

### Example

* OAuth Authentication (OAuth2PasswordBearer):
* Bearer Authentication (HTTPBearer):

```python
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


Name | Type | Description  | Notes
------------- | ------------- | ------------- | -------------
 **dag_id** | **str**|  | 
 **dag_run_id** | **str**|  | 

### Return type

[**DAGRunResponse**](DAGRunResponse.md)

### Authorization

[OAuth2PasswordBearer](../README.md#OAuth2PasswordBearer), [HTTPBearer](../README.md#HTTPBearer)

### HTTP request headers

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

### HTTP response details

| Status code | Description | Response headers |
|-------------|-------------|------------------|
**200** | Successful Response |  -  |
**401** | Unauthorized |  -  |
**403** | Forbidden |  -  |
**404** | Not Found |  -  |
**422** | Validation Error |  -  |

[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md)

# **get_dag_runs**
> DAGRunCollectionResponse get_dag_runs(dag_id, 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):

```python
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 | 
    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, 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 | SQL LIKE expression — use `%` / `_` wildcards (e.g. `%customer_%`). Use the pipe `|` operator for OR logic (e.g. `dag1 | dag2`). Regular expressions are **not** supported.   **Performance note:** this full-match pattern is evaluated as ``ILIKE '%term%'`` and most of the time prevents the database from using B-tree indexes, which can be very slow on large tables. Prefer the equivalent ``run_id_prefix_pattern`` parameter when possible. (optional)
    run_id_prefix_pattern = 'run_id_prefix_pattern_example' # str | Prefix match — returns items whose value starts with the given string (case-sensitive, index-friendly). Use the pipe `|` operator for OR logic (e.g. `dag1|dag2`). Use `~` to match all. Wildcard characters (`%`, `_`) are treated as literal characters. Trailing non-alphanumeric characters in the prefix are stripped before matching so the range scan stays index-compatible under locale-aware collations — e.g. `test_` effectively matches items starting with `test`, and `s3://` matches items starting with `s3`. (optional)
    triggering_user_name_pattern = 'triggering_user_name_pattern_example' # str | SQL LIKE expression — use `%` / `_` wildcards (e.g. `%customer_%`). Use the pipe `|` operator for OR logic (e.g. `dag1 | dag2`). Regular expressions are **not** supported.   **Performance note:** this full-match pattern is evaluated as ``ILIKE '%term%'`` and most of the time prevents the database from using B-tree indexes, which can be very slow on large tables. Prefer the equivalent ``triggering_user_name_prefix_pattern`` parameter when possible. (optional)
    triggering_user_name_prefix_pattern = 'triggering_user_name_prefix_pattern_example' # str | Prefix match — returns items whose value starts with the given string (case-sensitive, index-friendly). Use the pipe `|` operator for OR logic (e.g. `dag1|dag2`). Use `~` to match all. Wildcard characters (`%`, `_`) are treated as literal characters. Trailing non-alphanumeric characters in the prefix are stripped before matching so the range scan stays index-compatible under locale-aware collations — e.g. `test_` effectively matches items starting with `test`, and `s3://` matches items starting with `s3`. (optional)
    dag_id_pattern = 'dag_id_pattern_example' # str | SQL LIKE expression — use `%` / `_` wildcards (e.g. `%customer_%`). Use the pipe `|` operator for OR logic (e.g. `dag1 | dag2`). Regular expressions are **not** supported.   **Performance note:** this full-match pattern is evaluated as ``ILIKE '%term%'`` and most of the time prevents the database from using B-tree indexes, which can be very slow on large tables. Prefer the equivalent ``dag_id_prefix_pattern`` parameter when possible. (optional)
    dag_id_prefix_pattern = 'dag_id_prefix_pattern_example' # str | Prefix match — returns items whose value starts with the given string (case-sensitive, index-friendly). Use the pipe `|` operator for OR logic (e.g. `dag1|dag2`). Use `~` to match all. Wildcard characters (`%`, `_`) are treated as literal characters. Trailing non-alphanumeric characters in the prefix are stripped before matching so the range scan stays index-compatible under locale-aware collations — e.g. `test_` effectively matches items starting with `test`, and `s3://` matches items starting with `s3`. (optional)
    partition_key_pattern = 'partition_key_pattern_example' # str | SQL LIKE expression — use `%` / `_` wildcards (e.g. `%customer_%`). The pipe `|` is matched literally, not as an OR separator. Regular expressions are **not** supported.   **Performance note:** this full-match pattern is evaluated as ``ILIKE '%term%'`` and most of the time prevents the database from using B-tree indexes, which can be very slow on large tables. Prefer the equivalent ``partition_key_prefix_pattern`` parameter when possible. (optional)
    partition_key_prefix_pattern = 'partition_key_prefix_pattern_example' # str | Prefix match — returns items whose value starts with the given string (case-sensitive, index-friendly). The pipe `|` is part of the prefix, not an OR separator. Use `~` to match all. Wildcard characters (`%`, `_`) are treated as literal characters. Trailing non-alphanumeric characters in the prefix are stripped before matching so the range scan stays index-compatible under locale-aware collations — e.g. `test_` effectively matches items starting with `test`, and `s3://` matches items starting with `s3`. (optional)
    consuming_asset_pattern = 'consuming_asset_pattern_example' # str | Filter by consuming asset name or URI using pattern matching (optional)

    try:
        # Get Dag Runs
        api_response = api_instance.get_dag_runs(dag_id, 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


Name | Type | Description  | Notes
------------- | ------------- | ------------- | -------------
 **dag_id** | **str**|  | 
 **cursor** | **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** | **int**|  | [optional] [default to 50]
 **offset** | **int**|  | [optional] [default to 0]
 **run_after_gte** | **datetime**|  | [optional] 
 **run_after_gt** | **datetime**|  | [optional] 
 **run_after_lte** | **datetime**|  | [optional] 
 **run_after_lt** | **datetime**|  | [optional] 
 **logical_date_gte** | **datetime**|  | [optional] 
 **logical_date_gt** | **datetime**|  | [optional] 
 **logical_date_lte** | **datetime**|  | [optional] 
 **logical_date_lt** | **datetime**|  | [optional] 
 **start_date_gte** | **datetime**|  | [optional] 
 **start_date_gt** | **datetime**|  | [optional] 
 **start_date_lte** | **datetime**|  | [optional] 
 **start_date_lt** | **datetime**|  | [optional] 
 **end_date_gte** | **datetime**|  | [optional] 
 **end_date_gt** | **datetime**|  | [optional] 
 **end_date_lte** | **datetime**|  | [optional] 
 **end_date_lt** | **datetime**|  | [optional] 
 **duration_gte** | **float**|  | [optional] 
 **duration_gt** | **float**|  | [optional] 
 **duration_lte** | **float**|  | [optional] 
 **duration_lt** | **float**|  | [optional] 
 **updated_at_gte** | **datetime**|  | [optional] 
 **updated_at_gt** | **datetime**|  | [optional] 
 **updated_at_lte** | **datetime**|  | [optional] 
 **updated_at_lt** | **datetime**|  | [optional] 
 **conf_contains** | **str**|  | [optional] 
 **run_type** | [**List[str]**](str.md)|  | [optional] 
 **state** | [**List[str]**](str.md)|  | [optional] 
 **dag_version** | [**List[int]**](int.md)|  | [optional] 
 **bundle_version** | **str**|  | [optional] 
 **order_by** | [**List[str]**](str.md)| Attributes to order by, multi criteria sort is supported. Prefix with `-` for descending order. Supported attributes: `id, state, dag_id, run_id, logical_date, run_after, start_date, end_date, updated_at, conf, duration, dag_run_id` | [optional] [default to ["id"]]
 **run_id_pattern** | **str**| SQL LIKE expression — use `%` / `_` wildcards (e.g. `%customer_%`). Use the pipe `|` operator for OR logic (e.g. `dag1 | dag2`). Regular expressions are **not** supported.   **Performance note:** this full-match pattern is evaluated as ``ILIKE '%term%'`` and most of the time prevents the database from using B-tree indexes, which can be very slow on large tables. Prefer the equivalent ``run_id_prefix_pattern`` parameter when possible. | [optional] 
 **run_id_prefix_pattern** | **str**| Prefix match — returns items whose value starts with the given string (case-sensitive, index-friendly). Use the pipe `|` operator for OR logic (e.g. `dag1|dag2`). Use `~` to match all. Wildcard characters (`%`, `_`) are treated as literal characters. Trailing non-alphanumeric characters in the prefix are stripped before matching so the range scan stays index-compatible under locale-aware collations — e.g. `test_` effectively matches items starting with `test`, and `s3://` matches items starting with `s3`. | [optional] 
 **triggering_user_name_pattern** | **str**| SQL LIKE expression — use `%` / `_` wildcards (e.g. `%customer_%`). Use the pipe `|` operator for OR logic (e.g. `dag1 | dag2`). Regular expressions are **not** supported.   **Performance note:** this full-match pattern is evaluated as ``ILIKE '%term%'`` and most of the time prevents the database from using B-tree indexes, which can be very slow on large tables. Prefer the equivalent ``triggering_user_name_prefix_pattern`` parameter when possible. | [optional] 
 **triggering_user_name_prefix_pattern** | **str**| Prefix match — returns items whose value starts with the given string (case-sensitive, index-friendly). Use the pipe `|` operator for OR logic (e.g. `dag1|dag2`). Use `~` to match all. Wildcard characters (`%`, `_`) are treated as literal characters. Trailing non-alphanumeric characters in the prefix are stripped before matching so the range scan stays index-compatible under locale-aware collations — e.g. `test_` effectively matches items starting with `test`, and `s3://` matches items starting with `s3`. | [optional] 
 **dag_id_pattern** | **str**| SQL LIKE expression — use `%` / `_` wildcards (e.g. `%customer_%`). Use the pipe `|` operator for OR logic (e.g. `dag1 | dag2`). Regular expressions are **not** supported.   **Performance note:** this full-match pattern is evaluated as ``ILIKE '%term%'`` and most of the time prevents the database from using B-tree indexes, which can be very slow on large tables. Prefer the equivalent ``dag_id_prefix_pattern`` parameter when possible. | [optional] 
 **dag_id_prefix_pattern** | **str**| Prefix match — returns items whose value starts with the given string (case-sensitive, index-friendly). Use the pipe `|` operator for OR logic (e.g. `dag1|dag2`). Use `~` to match all. Wildcard characters (`%`, `_`) are treated as literal characters. Trailing non-alphanumeric characters in the prefix are stripped before matching so the range scan stays index-compatible under locale-aware collations — e.g. `test_` effectively matches items starting with `test`, and `s3://` matches items starting with `s3`. | [optional] 
 **partition_key_pattern** | **str**| SQL LIKE expression — use `%` / `_` wildcards (e.g. `%customer_%`). The pipe `|` is matched literally, not as an OR separator. Regular expressions are **not** supported.   **Performance note:** this full-match pattern is evaluated as ``ILIKE '%term%'`` and most of the time prevents the database from using B-tree indexes, which can be very slow on large tables. Prefer the equivalent ``partition_key_prefix_pattern`` parameter when possible. | [optional] 
 **partition_key_prefix_pattern** | **str**| Prefix match — returns items whose value starts with the given string (case-sensitive, index-friendly). The pipe `|` is part of the prefix, not an OR separator. Use `~` to match all. Wildcard characters (`%`, `_`) are treated as literal characters. Trailing non-alphanumeric characters in the prefix are stripped before matching so the range scan stays index-compatible under locale-aware collations — e.g. `test_` effectively matches items starting with `test`, and `s3://` matches items starting with `s3`. | [optional] 
 **consuming_asset_pattern** | **str**| Filter by consuming asset name or URI using pattern matching | [optional] 

### Return type

[**DAGRunCollectionResponse**](DAGRunCollectionResponse.md)

### Authorization

[OAuth2PasswordBearer](../README.md#OAuth2PasswordBearer), [HTTPBearer](../README.md#HTTPBearer)

### HTTP request headers

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

### HTTP response details

| Status code | Description | Response headers |
|-------------|-------------|------------------|
**200** | Successful Response |  -  |
**401** | Unauthorized |  -  |
**403** | Forbidden |  -  |
**404** | Not Found |  -  |
**422** | Validation Error |  -  |

[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md)

# **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):

```python
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


Name | Type | Description  | Notes
------------- | ------------- | ------------- | -------------
 **dag_id** | **str**|  | 
 **dag_runs_batch_body** | [**DAGRunsBatchBody**](DAGRunsBatchBody.md)|  | 

### Return type

[**DAGRunCollectionResponse**](DAGRunCollectionResponse.md)

### Authorization

[OAuth2PasswordBearer](../README.md#OAuth2PasswordBearer), [HTTPBearer](../README.md#HTTPBearer)

### HTTP request headers

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

### HTTP response details

| Status code | Description | Response headers |
|-------------|-------------|------------------|
**200** | Successful Response |  -  |
**401** | Unauthorized |  -  |
**403** | Forbidden |  -  |
**404** | Not Found |  -  |
**422** | Validation Error |  -  |

[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md)

# **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):

```python
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


Name | Type | Description  | Notes
------------- | ------------- | ------------- | -------------
 **dag_id** | **str**|  | 
 **dag_run_id** | **str**|  | 

### Return type

[**AssetEventCollectionResponse**](AssetEventCollectionResponse.md)

### Authorization

[OAuth2PasswordBearer](../README.md#OAuth2PasswordBearer), [HTTPBearer](../README.md#HTTPBearer)

### HTTP request headers

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

### HTTP response details

| Status code | Description | Response headers |
|-------------|-------------|------------------|
**200** | Successful Response |  -  |
**401** | Unauthorized |  -  |
**403** | Forbidden |  -  |
**404** | Not Found |  -  |
**422** | Validation Error |  -  |

[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md)

# **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):

```python
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


Name | Type | Description  | Notes
------------- | ------------- | ------------- | -------------
 **dag_id** | **str**|  | 
 **dag_run_id** | **str**|  | 
 **dag_run_patch_body** | [**DAGRunPatchBody**](DAGRunPatchBody.md)|  | 
 **update_mask** | [**List[str]**](str.md)|  | [optional] 

### Return type

[**DAGRunResponse**](DAGRunResponse.md)

### Authorization

[OAuth2PasswordBearer](../README.md#OAuth2PasswordBearer), [HTTPBearer](../README.md#HTTPBearer)

### HTTP request headers

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

### HTTP response details

| Status code | Description | Response headers |
|-------------|-------------|------------------|
**200** | Successful Response |  -  |
**400** | Bad Request |  -  |
**401** | Unauthorized |  -  |
**403** | Forbidden |  -  |
**404** | Not Found |  -  |
**422** | Validation Error |  -  |

[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md)

# **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):

```python
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


Name | Type | Description  | Notes
------------- | ------------- | ------------- | -------------
 **dag_id** | [**object**](.md)|  | 
 **trigger_dag_run_post_body** | [**TriggerDAGRunPostBody**](TriggerDAGRunPostBody.md)|  | 

### Return type

[**DAGRunResponse**](DAGRunResponse.md)

### Authorization

[OAuth2PasswordBearer](../README.md#OAuth2PasswordBearer), [HTTPBearer](../README.md#HTTPBearer)

### HTTP request headers

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

### HTTP response details

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

[[Back to top]](#) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to Model list]](../README.md#documentation-for-models) [[Back to README]](../README.md)

# **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):

```python
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


Name | Type | Description  | Notes
------------- | ------------- | ------------- | -------------
 **dag_id** | **str**|  | 
 **dag_run_id** | **str**|  | 
 **interval** | **float**| Seconds to wait between dag run state checks | 
 **result** | [**List[str]**](str.md)| 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](../README.md#OAuth2PasswordBearer), [HTTPBearer](../README.md#HTTPBearer)

### HTTP request headers

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

### HTTP response details

| Status code | Description | Response headers |
|-------------|-------------|------------------|
**200** | Successful Response |  -  |
**401** | Unauthorized |  -  |
**403** | Forbidden |  -  |
**404** | Not Found |  -  |
**422** | Validation Error |  -  |

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