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CHANGELOG.md

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under the License.
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-->
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# v2.7.0
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Apache Airflow API version: 2.7.0
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### Major changes:
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- Enable pools to consider deferred tasks ([#32709](https://github.com/apache/airflow/pull/32709))
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- add dag_run_ids and task_ids filter for the batch task instance API endpoint ([#32705](https://github.com/apache/airflow/pull/32705))
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- Add xcom map_index as a filter to xcom endpoint ([#32453](https://github.com/apache/airflow/pull/32453))
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- Updates health check endpoint to include dag_processor status. ([#32382](https://github.com/apache/airflow/pull/32382))
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- Add TriggererStatus to OpenAPI spec ([#31579](https://github.com/apache/airflow/pull/31579))
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### Major Fixes
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- OpenAPI Spec fix nullable alongside $ref ([#32887](https://github.com/apache/airflow/pull/32887))
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- Fix incorrect default on readonly property in our API ([#32510](https://github.com/apache/airflow/pull/32510))
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- Fix broken links in openapi/v1.yaml ([#31619](https://github.com/apache/airflow/pull/31619))
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- Update Dag trigger API and command docs ([#32696](https://github.com/apache/airflow/pull/32696))
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### NEW API supported
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- NA
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# v2.6.2
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Apache Airflow API version: 2.6.2

airflow_client/.openapi-generator/FILES

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@@ -50,6 +50,7 @@ client/model/dag_collection.py
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client/model/dag_collection_all_of.py
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client/model/dag_detail.py
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client/model/dag_detail_all_of.py
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client/model/dag_processor_status.py
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client/model/dag_run.py
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client/model/dag_run_collection.py
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client/model/dag_run_collection_all_of.py
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docs/DAGRunApi.md
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docs/DAGRunCollection.md
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docs/DAGRunCollectionAllOf.md
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docs/DagProcessorStatus.md
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docs/DagScheduleDatasetReference.md
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docs/DagState.md
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docs/DagWarning.md
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test/test_dag_collection_all_of.py
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test/test_dag_detail.py
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test/test_dag_detail_all_of.py
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test/test_dag_processor_status.py
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test/test_dag_run.py
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test/test_dag_run_api.py
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test/test_dag_run_collection.py

airflow_client/README.md

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This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
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- API version: 2.6.2
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- Package version: 2.6.2
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- API version: 2.7.0
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- Package version: 2.7.0
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- Build package: org.openapitools.codegen.languages.PythonClientCodegen
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For more information, please visit [https://airflow.apache.org](https://airflow.apache.org)
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Then import the package:
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```python
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import airflow_client.client
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import client
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```
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### Setuptools
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Then import the package:
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```python
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import airflow_client.client
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import client
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```
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## Getting Started
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```python
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import time
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import airflow_client.client
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import client
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from pprint import pprint
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from airflow_client.client.api import config_api
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from airflow_client.client.model.config import Config
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from airflow_client.client.model.error import Error
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from client.api import config_api
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from client.model.config import Config
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from client.model.error import Error
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# Defining the host is optional and defaults to /api/v1
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# See configuration.py for a list of all supported configuration parameters.
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configuration = client.Configuration(
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with client.ApiClient(configuration) as api_client:
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# Create an instance of the API class
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api_instance = config_api.ConfigApi(api_client)
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section = "section_example" # str | If given, only return config of this section. (optional)
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try:
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# Get current configuration
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api_response = api_instance.get_config()
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api_response = api_instance.get_config(section=section)
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pprint(api_response)
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except client.ApiException as e:
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print("Exception when calling ConfigApi->get_config: %s\n" % e)
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Class | Method | HTTP request | Description
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------------ | ------------- | ------------- | -------------
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*ConfigApi* | [**get_config**](docs/ConfigApi.md#get_config) | **GET** /config | Get current configuration
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*ConfigApi* | [**get_value**](docs/ConfigApi.md#get_value) | **GET** /config/section/{section}/option/{option} | Get a option from configuration
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*ConnectionApi* | [**delete_connection**](docs/ConnectionApi.md#delete_connection) | **DELETE** /connections/{connection_id} | Delete a connection
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*ConnectionApi* | [**get_connection**](docs/ConnectionApi.md#get_connection) | **GET** /connections/{connection_id} | Get a connection
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*ConnectionApi* | [**get_connections**](docs/ConnectionApi.md#get_connections) | **GET** /connections | List connections
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*DAGRunApi* | [**get_dag_runs**](docs/DAGRunApi.md#get_dag_runs) | **GET** /dags/{dag_id}/dagRuns | List DAG runs
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*DAGRunApi* | [**get_dag_runs_batch**](docs/DAGRunApi.md#get_dag_runs_batch) | **POST** /dags/~/dagRuns/list | List DAG runs (batch)
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*DAGRunApi* | [**get_upstream_dataset_events**](docs/DAGRunApi.md#get_upstream_dataset_events) | **GET** /dags/{dag_id}/dagRuns/{dag_run_id}/upstreamDatasetEvents | Get dataset events for a DAG run
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*DAGRunApi* | [**post_dag_run**](docs/DAGRunApi.md#post_dag_run) | **POST** /dags/{dag_id}/dagRuns | Trigger a new DAG run
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*DAGRunApi* | [**post_dag_run**](docs/DAGRunApi.md#post_dag_run) | **POST** /dags/{dag_id}/dagRuns | Trigger a new DAG run.
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*DAGRunApi* | [**set_dag_run_note**](docs/DAGRunApi.md#set_dag_run_note) | **PATCH** /dags/{dag_id}/dagRuns/{dag_run_id}/setNote | Update the DagRun note.
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*DAGRunApi* | [**update_dag_run_state**](docs/DAGRunApi.md#update_dag_run_state) | **PATCH** /dags/{dag_id}/dagRuns/{dag_run_id} | Modify a DAG run
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*DagWarningApi* | [**get_dag_warnings**](docs/DagWarningApi.md#get_dag_warnings) | **GET** /dagWarnings | List dag warnings
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- [DAGRun](docs/DAGRun.md)
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- [DAGRunCollection](docs/DAGRunCollection.md)
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- [DAGRunCollectionAllOf](docs/DAGRunCollectionAllOf.md)
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- [DagProcessorStatus](docs/DagProcessorStatus.md)
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- [DagScheduleDatasetReference](docs/DagScheduleDatasetReference.md)
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- [DagState](docs/DagState.md)
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- [DagWarning](docs/DagWarning.md)
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Solution 1:
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Use specific imports for apis and models like:
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- `from airflow_client.client.api.default_api import DefaultApi`
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- `from airflow_client.client.model.pet import Pet`
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- `from client.api.default_api import DefaultApi`
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- `from client.model.pet import Pet`
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Solution 2:
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Before importing the package, adjust the maximum recursion limit as shown below:
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```
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import sys
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sys.setrecursionlimit(1500)
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import airflow_client.client
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from airflow_client.client.apis import *
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from airflow_client.client.models import *
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import client
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from client.apis import *
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from client.models import *
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```
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airflow_client/client/__init__.py

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# Overview To facilitate management, Apache Airflow supports a range of REST API endpoints across its objects. This section provides an overview of the API design, methods, and supported use cases. Most of the endpoints accept `JSON` as input and return `JSON` responses. This means that you must usually add the following headers to your request: ``` Content-type: application/json Accept: application/json ``` ## Resources The term `resource` refers to a single type of object in the Airflow metadata. An API is broken up by its endpoint's corresponding resource. The name of a resource is typically plural and expressed in camelCase. Example: `dagRuns`. Resource names are used as part of endpoint URLs, as well as in API parameters and responses. ## CRUD Operations The platform supports **C**reate, **R**ead, **U**pdate, and **D**elete operations on most resources. You can review the standards for these operations and their standard parameters below. Some endpoints have special behavior as exceptions. ### Create To create a resource, you typically submit an HTTP `POST` request with the resource's required metadata in the request body. The response returns a `201 Created` response code upon success with the resource's metadata, including its internal `id`, in the response body. ### Read The HTTP `GET` request can be used to read a resource or to list a number of resources. A resource's `id` can be submitted in the request parameters to read a specific resource. The response usually returns a `200 OK` response code upon success, with the resource's metadata in the response body. If a `GET` request does not include a specific resource `id`, it is treated as a list request. The response usually returns a `200 OK` response code upon success, with an object containing a list of resources' metadata in the response body. When reading resources, some common query parameters are usually available. e.g.: ``` v1/connections?limit=25&offset=25 ``` |Query Parameter|Type|Description| |---------------|----|-----------| |limit|integer|Maximum number of objects to fetch. Usually 25 by default| |offset|integer|Offset after which to start returning objects. For use with limit query parameter.| ### Update Updating a resource requires the resource `id`, and is typically done using an HTTP `PATCH` request, with the fields to modify in the request body. The response usually returns a `200 OK` response code upon success, with information about the modified resource in the response body. ### Delete Deleting a resource requires the resource `id` and is typically executed via an HTTP `DELETE` request. The response usually returns a `204 No Content` response code upon success. ## Conventions - Resource names are plural and expressed in camelCase. - Names are consistent between URL parameter name and field name. - Field names are in snake_case. ```json { \"description\": \"string\", \"name\": \"string\", \"occupied_slots\": 0, \"open_slots\": 0 \"queued_slots\": 0, \"running_slots\": 0, \"scheduled_slots\": 0, \"slots\": 0, } ``` ### Update Mask Update mask is available as a query parameter in patch endpoints. It is used to notify the API which fields you want to update. Using `update_mask` makes it easier to update objects by helping the server know which fields to update in an object instead of updating all fields. The update request ignores any fields that aren't specified in the field mask, leaving them with their current values. Example: ``` resource = request.get('/resource/my-id').json() resource['my_field'] = 'new-value' request.patch('/resource/my-id?update_mask=my_field', data=json.dumps(resource)) ``` ## Versioning and Endpoint Lifecycle - API versioning is not synchronized to specific releases of the Apache Airflow. - APIs are designed to be backward compatible. - Any changes to the API will first go through a deprecation phase. # Trying the API You can use a third party client, such as [curl](https://curl.haxx.se/), [HTTPie](https://httpie.org/), [Postman](https://www.postman.com/) or [the Insomnia rest client](https://insomnia.rest/) to test the Apache Airflow API. Note that you will need to pass credentials data. For e.g., here is how to pause a DAG with [curl](https://curl.haxx.se/), when basic authorization is used: ```bash curl -X PATCH 'https://example.com/api/v1/dags/{dag_id}?update_mask=is_paused' \\ -H 'Content-Type: application/json' \\ --user \"username:password\" \\ -d '{ \"is_paused\": true }' ``` Using a graphical tool such as [Postman](https://www.postman.com/) or [Insomnia](https://insomnia.rest/), it is possible to import the API specifications directly: 1. Download the API specification by clicking the **Download** button at the top of this document 2. Import the JSON specification in the graphical tool of your choice. - In *Postman*, you can click the **import** button at the top - With *Insomnia*, you can just drag-and-drop the file on the UI Note that with *Postman*, you can also generate code snippets by selecting a request and clicking on the **Code** button. ## Enabling CORS [Cross-origin resource sharing (CORS)](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS) is a browser security feature that restricts HTTP requests that are initiated from scripts running in the browser. For details on enabling/configuring CORS, see [Enabling CORS](https://airflow.apache.org/docs/apache-airflow/stable/security/api.html). # Authentication To be able to meet the requirements of many organizations, Airflow supports many authentication methods, and it is even possible to add your own method. If you want to check which auth backend is currently set, you can use `airflow config get-value api auth_backends` command as in the example below. ```bash $ airflow config get-value api auth_backends airflow.api.auth.backend.basic_auth ``` The default is to deny all requests. For details on configuring the authentication, see [API Authorization](https://airflow.apache.org/docs/apache-airflow/stable/security/api.html). # Errors We follow the error response format proposed in [RFC 7807](https://tools.ietf.org/html/rfc7807) also known as Problem Details for HTTP APIs. As with our normal API responses, your client must be prepared to gracefully handle additional members of the response. ## Unauthenticated This indicates that the request has not been applied because it lacks valid authentication credentials for the target resource. Please check that you have valid credentials. ## PermissionDenied This response means that the server understood the request but refuses to authorize it because it lacks sufficient rights to the resource. It happens when you do not have the necessary permission to execute the action you performed. You need to get the appropriate permissions in other to resolve this error. ## BadRequest This response means that the server cannot or will not process the request due to something that is perceived to be a client error (e.g., malformed request syntax, invalid request message framing, or deceptive request routing). To resolve this, please ensure that your syntax is correct. ## NotFound This client error response indicates that the server cannot find the requested resource. ## MethodNotAllowed Indicates that the request method is known by the server but is not supported by the target resource. ## NotAcceptable The target resource does not have a current representation that would be acceptable to the user agent, according to the proactive negotiation header fields received in the request, and the server is unwilling to supply a default representation. ## AlreadyExists The request could not be completed due to a conflict with the current state of the target resource, e.g. the resource it tries to create already exists. ## Unknown This means that the server encountered an unexpected condition that prevented it from fulfilling the request. # noqa: E501
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The version of the OpenAPI document: 2.6.2
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The version of the OpenAPI document: 2.7.0
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Contact: dev@airflow.apache.org
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Generated by: https://openapi-generator.tech
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"""
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__version__ = "2.6.2"
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__version__ = "2.7.0"
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# import ApiClient
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from airflow_client.client.api_client import ApiClient
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from client.api_client import ApiClient
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# import Configuration
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from airflow_client.client.configuration import Configuration
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from client.configuration import Configuration
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# import exceptions
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from airflow_client.client.exceptions import OpenApiException
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from airflow_client.client.exceptions import ApiAttributeError
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from airflow_client.client.exceptions import ApiTypeError
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from airflow_client.client.exceptions import ApiValueError
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from airflow_client.client.exceptions import ApiKeyError
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from airflow_client.client.exceptions import ApiException
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from client.exceptions import OpenApiException
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from client.exceptions import ApiAttributeError
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from client.exceptions import ApiTypeError
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from client.exceptions import ApiValueError
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from client.exceptions import ApiKeyError
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from client.exceptions import ApiException

airflow_client/client/api/__init__.py

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# do not import all apis into this module because that uses a lot of memory and stack frames
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# if you need the ability to import all apis from one package, import them with
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# from airflow_client.client.apis import ConfigApi
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# from client.apis import ConfigApi

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