path: root/python-apache-airflow-client.spec

%global _empty_manifest_terminate_build 0
Name:		python-apache-airflow-client
Version:	2.6.1
Release:	1
Summary:	Apache Airflow API (Stable)
License:	Apache License 2.0
URL:		https://airflow.apache.org/
Source0:	https://mirrors.aliyun.com/pypi/web/packages/30/b5/5344a76fc495940ba568daa670d95ab7c6cb9dfbd80c28bff5f7e96e44f7/apache-airflow-client-2.6.1.tar.gz
BuildArch:	noarch

Requires:	python3-urllib3
Requires:	python3-dateutil

%description
<!--
 Licensed to the Apache Software Foundation (ASF) under one
 or more contributor license agreements.  See the NOTICE file
 distributed with this work for additional information
 regarding copyright ownership.  The ASF licenses this file
 to you under the Apache License, Version 2.0 (the
 "License"); you may not use this file except in compliance
 with the License.  You may obtain a copy of the License at

   http://www.apache.org/licenses/LICENSE-2.0

 Unless required by applicable law or agreed to in writing,
 software distributed under the License is distributed on an
 "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
 KIND, either express or implied.  See the License for the
 specific language governing permissions and limitations
 under the License.
 -->

# Apache Airflow Python Client

## Requirements.

Python >= 3.7

## Installation & Usage

### pip install

You can install directly using pip:

```sh
pip install apache-airflow-client
````

### Setuptools

Or install via [Setuptools](http://pypi.python.org/pypi/setuptools).

```shell
git clone git@github.com:apache/airflow-client-python.git
cd airflow-client-python
python setup.py install --user
```
(or `sudo python setup.py install` to install the package for all users)

Then import the package:
```python
import airflow_client.client
```

## Changelog

See [CHANGELOG.md](https://github.com/apache/airflow-client-python/blob/main/CHANGELOG.md) for keeping
track on what has changed in the client.


## Getting Started

Please follow the [installation procedure](#installation--usage) and then run the following
example python script:

```python
import uuid

import airflow_client.client
try:
    # If you have rich installed, you will have nice colored output of the API responses
    from rich import print
except ImportError:
    print("Output will not be colored. Please install rich to get colored output: `pip install rich`")
    pass
from airflow_client.client.api import config_api, dag_api, dag_run_api
from airflow_client.client.model.dag_run import DAGRun

# The client must use 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.
#
# In case of the basic authentication below, make sure that Airflow is
# configured also with the basic_auth as backend additionally to regular session backend needed
# by the UI. In the `[api]` section of your `airflow.cfg` set:
#
# auth_backend = airflow.api.auth.backend.session,airflow.api.auth.backend.basic_auth
#
# Make sure that your user/name are configured properly - using the user/password that has admin
# privileges in Airflow

# Configure HTTP basic authorization: Basic
configuration = airflow_client.client.Configuration(
    host="http://localhost:8080/api/v1",
    username='admin',
    password='admin'
)

# Make sure in the [core] section, the  `load_examples` config is set to True in your airflow.cfg
# or AIRFLOW__CORE__LOAD_EXAMPLES environment variable set to True
DAG_ID = "example_bash_operator"

# Enter a context with an instance of the API client
with airflow_client.client.ApiClient(configuration) as api_client:

    errors = False

    print('[blue]Getting DAG list')
    dag_api_instance = dag_api.DAGApi(api_client)
    try:
        api_response = dag_api_instance.get_dags()
        print(api_response)
    except airflow_client.client.OpenApiException as e:
        print("[red]Exception when calling DagAPI->get_dags: %s\n" % e)
        errors = True
    else:
        print('[green]Getting DAG list successful')


    print('[blue]Getting Tasks for a DAG')
    try:
        api_response = dag_api_instance.get_tasks(DAG_ID)
        print(api_response)
    except airflow_client.client.exceptions.OpenApiException as e:
        print("[red]Exception when calling DagAPI->get_tasks: %s\n" % e)
        errors = True
    else:
        print('[green]Getting Tasks successful')


    print('[blue]Triggering a DAG run')
    dag_run_api_instance = dag_run_api.DAGRunApi(api_client)
    try:
        # Create a DAGRun object (no dag_id should be specified because it is read-only property of DAGRun)
        # dag_run id is generated randomly to allow multiple executions of the script
        dag_run = DAGRun(
            dag_run_id='some_test_run_' + uuid.uuid4().hex,
        )
        api_response = dag_run_api_instance.post_dag_run(DAG_ID, dag_run)
        print(api_response)
    except airflow_client.client.exceptions.OpenApiException as e:
        print("[red]Exception when calling DAGRunAPI->post_dag_run: %s\n" % e)
        errors = True
    else:
        print('[green]Posting DAG Run successful')

    # Get current configuration. Note, this is disabled by default with most installation.
    # You need to set `expose_config = True` in Airflow configuration in order to retrieve configuration.
    conf_api_instance = config_api.ConfigApi(api_client)
    try:
        api_response = conf_api_instance.get_config()
        print(api_response)
    except airflow_client.client.OpenApiException as e:
        print("[red]Exception when calling ConfigApi->get_config: %s\n" % e)
        errors = True
    else:
        print('[green]Config retrieved successfully')

    if errors:
        print ('\n[red]There were errors while running the script - see above for details')
    else:
        print ('\n[green]Everything went well')
```

See [README](https://github.com/apache/airflow-client-python/blob/main/README.md#documentation-for-api-endpoints) 
for full client API documentation.



%package -n python3-apache-airflow-client
Summary:	Apache Airflow API (Stable)
Provides:	python-apache-airflow-client
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-apache-airflow-client
<!--
 Licensed to the Apache Software Foundation (ASF) under one
 or more contributor license agreements.  See the NOTICE file
 distributed with this work for additional information
 regarding copyright ownership.  The ASF licenses this file
 to you under the Apache License, Version 2.0 (the
 "License"); you may not use this file except in compliance
 with the License.  You may obtain a copy of the License at

   http://www.apache.org/licenses/LICENSE-2.0

 Unless required by applicable law or agreed to in writing,
 software distributed under the License is distributed on an
 "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
 KIND, either express or implied.  See the License for the
 specific language governing permissions and limitations
 under the License.
 -->

# Apache Airflow Python Client

## Requirements.

Python >= 3.7

## Installation & Usage

### pip install

You can install directly using pip:

```sh
pip install apache-airflow-client
````

### Setuptools

Or install via [Setuptools](http://pypi.python.org/pypi/setuptools).

```shell
git clone git@github.com:apache/airflow-client-python.git
cd airflow-client-python
python setup.py install --user
```
(or `sudo python setup.py install` to install the package for all users)

Then import the package:
```python
import airflow_client.client
```

## Changelog

See [CHANGELOG.md](https://github.com/apache/airflow-client-python/blob/main/CHANGELOG.md) for keeping
track on what has changed in the client.


## Getting Started

Please follow the [installation procedure](#installation--usage) and then run the following
example python script:

```python
import uuid

import airflow_client.client
try:
    # If you have rich installed, you will have nice colored output of the API responses
    from rich import print
except ImportError:
    print("Output will not be colored. Please install rich to get colored output: `pip install rich`")
    pass
from airflow_client.client.api import config_api, dag_api, dag_run_api
from airflow_client.client.model.dag_run import DAGRun

# The client must use 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.
#
# In case of the basic authentication below, make sure that Airflow is
# configured also with the basic_auth as backend additionally to regular session backend needed
# by the UI. In the `[api]` section of your `airflow.cfg` set:
#
# auth_backend = airflow.api.auth.backend.session,airflow.api.auth.backend.basic_auth
#
# Make sure that your user/name are configured properly - using the user/password that has admin
# privileges in Airflow

# Configure HTTP basic authorization: Basic
configuration = airflow_client.client.Configuration(
    host="http://localhost:8080/api/v1",
    username='admin',
    password='admin'
)

# Make sure in the [core] section, the  `load_examples` config is set to True in your airflow.cfg
# or AIRFLOW__CORE__LOAD_EXAMPLES environment variable set to True
DAG_ID = "example_bash_operator"

# Enter a context with an instance of the API client
with airflow_client.client.ApiClient(configuration) as api_client:

    errors = False

    print('[blue]Getting DAG list')
    dag_api_instance = dag_api.DAGApi(api_client)
    try:
        api_response = dag_api_instance.get_dags()
        print(api_response)
    except airflow_client.client.OpenApiException as e:
        print("[red]Exception when calling DagAPI->get_dags: %s\n" % e)
        errors = True
    else:
        print('[green]Getting DAG list successful')


    print('[blue]Getting Tasks for a DAG')
    try:
        api_response = dag_api_instance.get_tasks(DAG_ID)
        print(api_response)
    except airflow_client.client.exceptions.OpenApiException as e:
        print("[red]Exception when calling DagAPI->get_tasks: %s\n" % e)
        errors = True
    else:
        print('[green]Getting Tasks successful')


    print('[blue]Triggering a DAG run')
    dag_run_api_instance = dag_run_api.DAGRunApi(api_client)
    try:
        # Create a DAGRun object (no dag_id should be specified because it is read-only property of DAGRun)
        # dag_run id is generated randomly to allow multiple executions of the script
        dag_run = DAGRun(
            dag_run_id='some_test_run_' + uuid.uuid4().hex,
        )
        api_response = dag_run_api_instance.post_dag_run(DAG_ID, dag_run)
        print(api_response)
    except airflow_client.client.exceptions.OpenApiException as e:
        print("[red]Exception when calling DAGRunAPI->post_dag_run: %s\n" % e)
        errors = True
    else:
        print('[green]Posting DAG Run successful')

    # Get current configuration. Note, this is disabled by default with most installation.
    # You need to set `expose_config = True` in Airflow configuration in order to retrieve configuration.
    conf_api_instance = config_api.ConfigApi(api_client)
    try:
        api_response = conf_api_instance.get_config()
        print(api_response)
    except airflow_client.client.OpenApiException as e:
        print("[red]Exception when calling ConfigApi->get_config: %s\n" % e)
        errors = True
    else:
        print('[green]Config retrieved successfully')

    if errors:
        print ('\n[red]There were errors while running the script - see above for details')
    else:
        print ('\n[green]Everything went well')
```

See [README](https://github.com/apache/airflow-client-python/blob/main/README.md#documentation-for-api-endpoints) 
for full client API documentation.



%package help
Summary:	Development documents and examples for apache-airflow-client
Provides:	python3-apache-airflow-client-doc
%description help
<!--
 Licensed to the Apache Software Foundation (ASF) under one
 or more contributor license agreements.  See the NOTICE file
 distributed with this work for additional information
 regarding copyright ownership.  The ASF licenses this file
 to you under the Apache License, Version 2.0 (the
 "License"); you may not use this file except in compliance
 with the License.  You may obtain a copy of the License at

   http://www.apache.org/licenses/LICENSE-2.0

 Unless required by applicable law or agreed to in writing,
 software distributed under the License is distributed on an
 "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
 KIND, either express or implied.  See the License for the
 specific language governing permissions and limitations
 under the License.
 -->

# Apache Airflow Python Client

## Requirements.

Python >= 3.7

## Installation & Usage

### pip install

You can install directly using pip:

```sh
pip install apache-airflow-client
````

### Setuptools

Or install via [Setuptools](http://pypi.python.org/pypi/setuptools).

```shell
git clone git@github.com:apache/airflow-client-python.git
cd airflow-client-python
python setup.py install --user
```
(or `sudo python setup.py install` to install the package for all users)

Then import the package:
```python
import airflow_client.client
```

## Changelog

See [CHANGELOG.md](https://github.com/apache/airflow-client-python/blob/main/CHANGELOG.md) for keeping
track on what has changed in the client.


## Getting Started

Please follow the [installation procedure](#installation--usage) and then run the following
example python script:

```python
import uuid

import airflow_client.client
try:
    # If you have rich installed, you will have nice colored output of the API responses
    from rich import print
except ImportError:
    print("Output will not be colored. Please install rich to get colored output: `pip install rich`")
    pass
from airflow_client.client.api import config_api, dag_api, dag_run_api
from airflow_client.client.model.dag_run import DAGRun

# The client must use 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.
#
# In case of the basic authentication below, make sure that Airflow is
# configured also with the basic_auth as backend additionally to regular session backend needed
# by the UI. In the `[api]` section of your `airflow.cfg` set:
#
# auth_backend = airflow.api.auth.backend.session,airflow.api.auth.backend.basic_auth
#
# Make sure that your user/name are configured properly - using the user/password that has admin
# privileges in Airflow

# Configure HTTP basic authorization: Basic
configuration = airflow_client.client.Configuration(
    host="http://localhost:8080/api/v1",
    username='admin',
    password='admin'
)

# Make sure in the [core] section, the  `load_examples` config is set to True in your airflow.cfg
# or AIRFLOW__CORE__LOAD_EXAMPLES environment variable set to True
DAG_ID = "example_bash_operator"

# Enter a context with an instance of the API client
with airflow_client.client.ApiClient(configuration) as api_client:

    errors = False

    print('[blue]Getting DAG list')
    dag_api_instance = dag_api.DAGApi(api_client)
    try:
        api_response = dag_api_instance.get_dags()
        print(api_response)
    except airflow_client.client.OpenApiException as e:
        print("[red]Exception when calling DagAPI->get_dags: %s\n" % e)
        errors = True
    else:
        print('[green]Getting DAG list successful')


    print('[blue]Getting Tasks for a DAG')
    try:
        api_response = dag_api_instance.get_tasks(DAG_ID)
        print(api_response)
    except airflow_client.client.exceptions.OpenApiException as e:
        print("[red]Exception when calling DagAPI->get_tasks: %s\n" % e)
        errors = True
    else:
        print('[green]Getting Tasks successful')


    print('[blue]Triggering a DAG run')
    dag_run_api_instance = dag_run_api.DAGRunApi(api_client)
    try:
        # Create a DAGRun object (no dag_id should be specified because it is read-only property of DAGRun)
        # dag_run id is generated randomly to allow multiple executions of the script
        dag_run = DAGRun(
            dag_run_id='some_test_run_' + uuid.uuid4().hex,
        )
        api_response = dag_run_api_instance.post_dag_run(DAG_ID, dag_run)
        print(api_response)
    except airflow_client.client.exceptions.OpenApiException as e:
        print("[red]Exception when calling DAGRunAPI->post_dag_run: %s\n" % e)
        errors = True
    else:
        print('[green]Posting DAG Run successful')

    # Get current configuration. Note, this is disabled by default with most installation.
    # You need to set `expose_config = True` in Airflow configuration in order to retrieve configuration.
    conf_api_instance = config_api.ConfigApi(api_client)
    try:
        api_response = conf_api_instance.get_config()
        print(api_response)
    except airflow_client.client.OpenApiException as e:
        print("[red]Exception when calling ConfigApi->get_config: %s\n" % e)
        errors = True
    else:
        print('[green]Config retrieved successfully')

    if errors:
        print ('\n[red]There were errors while running the script - see above for details')
    else:
        print ('\n[green]Everything went well')
```

See [README](https://github.com/apache/airflow-client-python/blob/main/README.md#documentation-for-api-endpoints) 
for full client API documentation.



%prep
%autosetup -n apache-airflow-client-2.6.1

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-apache-airflow-client -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Thu Jun 08 2023 Python_Bot <Python_Bot@openeuler.org> - 2.6.1-1
- Package Spec generated