%global _empty_manifest_terminate_build 0 Name: python-airflow-provider-fivetran Version: 1.1.4 Release: 1 Summary: A Fivetran provider for Apache Airflow License: Apache License 2.0 URL: https://github.com/fivetran/airflow-provider-fivetran Source0: https://mirrors.nju.edu.cn/pypi/web/packages/00/f4/187ef2c73cb5778e3db716750557db5b5fd7c4d1d7153d38ecaa65609796/airflow-provider-fivetran-1.1.4.tar.gz BuildArch: noarch Requires: python3-requests Requires: python3-apache-airflow %description # Fivetran Provider for Apache Airflow This package provides an operator, sensor, and hook that integrates [Fivetran](https://fivetran.com) into Apache Airflow. `FivetranOperator` allows you to start Fivetran jobs from Airflow and `FivetranSensor` allows you to monitor a Fivetran sync job for completion before running downstream processes. [Fivetran automates your data pipeline, and Airflow automates your data processing.](https://www.youtube.com/watch?v=siSx6L2ckSw&ab_channel=Fivetran) ## Installation Prerequisites: An environment running `apache-airflow`. ``` pip install airflow-provider-fivetran ``` ## Configuration In the Airflow user interface, configure a Connection for Fivetran. Most of the Connection config fields will be left blank. Configure the following fields: * `Conn Id`: `fivetran_default` * `Conn Type`: `Fivetran` * `Fivetran API Key`: Your Fivetran API Key * `Fivetran API Secret`: Your Fivetran API Secret Find the Fivetran API Key and Secret in the [Fivetran Account Settings](https://fivetran.com/account/settings), under the **API Config** section. See our documentation for more information on [Fivetran API Authentication](https://fivetran.com/docs/rest-api/getting-started#authentication). The sensor and operator assume the `Conn Id` is set to `fivetran_default`, however if you are managing multipe Fivetran accounts, you can set this to anything you like. See the DAG in examples to see how to specify a custom `Conn Id`. ## Modules ### [Fivetran Operator](https://github.com/fivetran/airflow-provider-fivetran/blob/main/fivetran_provider/operators/fivetran.py) `FivetranOperator` starts a Fivetran sync job. Note that when a Fivetran sync job is controlled via an Operator, it is no longer run on the schedule as managed by Fivetran. In other words, it is now scheduled only from Airflow. `FivetranOperator` requires that you specify the `connector_id` of the sync job to start. You can find `connector_id` in the Settings page of the connector you configured in the [Fivetran dashboard](https://fivetran.com/dashboard/connectors). Import into your DAG via: ``` from fivetran_provider.operators.fivetran import FivetranOperator ``` ### [Fivetran Sensor](https://github.com/fivetran/airflow-provider-fivetran/blob/main/fivetran_provider/sensors/fivetran.py) `FivetranSensor` monitors a Fivetran sync job for completion. Monitoring with `FivetranSensor` allows you to trigger downstream processes only when the Fivetran sync jobs have completed, ensuring data consistency. You can use multiple instances of `FivetranSensor` to monitor multiple Fivetran connectors. Note, it is possible to monitor a sync that is scheduled and managed from Fivetran; in other words, you can use `FivetranSensor` without using `FivetranOperator`. If used in this way, your DAG will wait until the sync job starts on its Fivetran-controlled schedule and then completes. `FivetranSensor` requires that you specify the `connector_id` of the sync job to start. You can find `connector_id` in the Settings page of the connector you configured in the [Fivetran dashboard](https://fivetran.com/dashboard/connectors). Import into your DAG via: ``` from fivetran_provider.sensors.fivetran import FivetranSensor ``` ## Examples See the [**examples**](https://github.com/fivetran/airflow-provider-fivetran/tree/main/fivetran_provider/example_dags) directory for an example DAG. ## Issues Please submit [issues](https://github.com/fivetran/airflow-provider-fivetran/issues) and [pull requests](https://github.com/fivetran/airflow-provider-fivetran/pulls) in our official repo: [https://github.com/fivetran/airflow-provider-fivetran](https://github.com/fivetran/airflow-provider-fivetran) We are happy to hear from you. Please email any feedback to the authors at [devrel@fivetran.com](mailto:devrel@fivetran.com). ## Acknowledgements Special thanks to [Pete DeJoy](https://github.com/petedejoy), [Plinio Guzman](https://github.com/pgzmnk), and [David Koenitzer](https://github.com/sunkickr) of [Astronomer.io](https://www.astronomer.io/) for their contributions and support in getting this provider off the ground. %package -n python3-airflow-provider-fivetran Summary: A Fivetran provider for Apache Airflow Provides: python-airflow-provider-fivetran BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-airflow-provider-fivetran # Fivetran Provider for Apache Airflow This package provides an operator, sensor, and hook that integrates [Fivetran](https://fivetran.com) into Apache Airflow. `FivetranOperator` allows you to start Fivetran jobs from Airflow and `FivetranSensor` allows you to monitor a Fivetran sync job for completion before running downstream processes. [Fivetran automates your data pipeline, and Airflow automates your data processing.](https://www.youtube.com/watch?v=siSx6L2ckSw&ab_channel=Fivetran) ## Installation Prerequisites: An environment running `apache-airflow`. ``` pip install airflow-provider-fivetran ``` ## Configuration In the Airflow user interface, configure a Connection for Fivetran. Most of the Connection config fields will be left blank. Configure the following fields: * `Conn Id`: `fivetran_default` * `Conn Type`: `Fivetran` * `Fivetran API Key`: Your Fivetran API Key * `Fivetran API Secret`: Your Fivetran API Secret Find the Fivetran API Key and Secret in the [Fivetran Account Settings](https://fivetran.com/account/settings), under the **API Config** section. See our documentation for more information on [Fivetran API Authentication](https://fivetran.com/docs/rest-api/getting-started#authentication). The sensor and operator assume the `Conn Id` is set to `fivetran_default`, however if you are managing multipe Fivetran accounts, you can set this to anything you like. See the DAG in examples to see how to specify a custom `Conn Id`. ## Modules ### [Fivetran Operator](https://github.com/fivetran/airflow-provider-fivetran/blob/main/fivetran_provider/operators/fivetran.py) `FivetranOperator` starts a Fivetran sync job. Note that when a Fivetran sync job is controlled via an Operator, it is no longer run on the schedule as managed by Fivetran. In other words, it is now scheduled only from Airflow. `FivetranOperator` requires that you specify the `connector_id` of the sync job to start. You can find `connector_id` in the Settings page of the connector you configured in the [Fivetran dashboard](https://fivetran.com/dashboard/connectors). Import into your DAG via: ``` from fivetran_provider.operators.fivetran import FivetranOperator ``` ### [Fivetran Sensor](https://github.com/fivetran/airflow-provider-fivetran/blob/main/fivetran_provider/sensors/fivetran.py) `FivetranSensor` monitors a Fivetran sync job for completion. Monitoring with `FivetranSensor` allows you to trigger downstream processes only when the Fivetran sync jobs have completed, ensuring data consistency. You can use multiple instances of `FivetranSensor` to monitor multiple Fivetran connectors. Note, it is possible to monitor a sync that is scheduled and managed from Fivetran; in other words, you can use `FivetranSensor` without using `FivetranOperator`. If used in this way, your DAG will wait until the sync job starts on its Fivetran-controlled schedule and then completes. `FivetranSensor` requires that you specify the `connector_id` of the sync job to start. You can find `connector_id` in the Settings page of the connector you configured in the [Fivetran dashboard](https://fivetran.com/dashboard/connectors). Import into your DAG via: ``` from fivetran_provider.sensors.fivetran import FivetranSensor ``` ## Examples See the [**examples**](https://github.com/fivetran/airflow-provider-fivetran/tree/main/fivetran_provider/example_dags) directory for an example DAG. ## Issues Please submit [issues](https://github.com/fivetran/airflow-provider-fivetran/issues) and [pull requests](https://github.com/fivetran/airflow-provider-fivetran/pulls) in our official repo: [https://github.com/fivetran/airflow-provider-fivetran](https://github.com/fivetran/airflow-provider-fivetran) We are happy to hear from you. Please email any feedback to the authors at [devrel@fivetran.com](mailto:devrel@fivetran.com). ## Acknowledgements Special thanks to [Pete DeJoy](https://github.com/petedejoy), [Plinio Guzman](https://github.com/pgzmnk), and [David Koenitzer](https://github.com/sunkickr) of [Astronomer.io](https://www.astronomer.io/) for their contributions and support in getting this provider off the ground. %package help Summary: Development documents and examples for airflow-provider-fivetran Provides: python3-airflow-provider-fivetran-doc %description help # Fivetran Provider for Apache Airflow This package provides an operator, sensor, and hook that integrates [Fivetran](https://fivetran.com) into Apache Airflow. `FivetranOperator` allows you to start Fivetran jobs from Airflow and `FivetranSensor` allows you to monitor a Fivetran sync job for completion before running downstream processes. [Fivetran automates your data pipeline, and Airflow automates your data processing.](https://www.youtube.com/watch?v=siSx6L2ckSw&ab_channel=Fivetran) ## Installation Prerequisites: An environment running `apache-airflow`. ``` pip install airflow-provider-fivetran ``` ## Configuration In the Airflow user interface, configure a Connection for Fivetran. Most of the Connection config fields will be left blank. Configure the following fields: * `Conn Id`: `fivetran_default` * `Conn Type`: `Fivetran` * `Fivetran API Key`: Your Fivetran API Key * `Fivetran API Secret`: Your Fivetran API Secret Find the Fivetran API Key and Secret in the [Fivetran Account Settings](https://fivetran.com/account/settings), under the **API Config** section. See our documentation for more information on [Fivetran API Authentication](https://fivetran.com/docs/rest-api/getting-started#authentication). The sensor and operator assume the `Conn Id` is set to `fivetran_default`, however if you are managing multipe Fivetran accounts, you can set this to anything you like. See the DAG in examples to see how to specify a custom `Conn Id`. ## Modules ### [Fivetran Operator](https://github.com/fivetran/airflow-provider-fivetran/blob/main/fivetran_provider/operators/fivetran.py) `FivetranOperator` starts a Fivetran sync job. Note that when a Fivetran sync job is controlled via an Operator, it is no longer run on the schedule as managed by Fivetran. In other words, it is now scheduled only from Airflow. `FivetranOperator` requires that you specify the `connector_id` of the sync job to start. You can find `connector_id` in the Settings page of the connector you configured in the [Fivetran dashboard](https://fivetran.com/dashboard/connectors). Import into your DAG via: ``` from fivetran_provider.operators.fivetran import FivetranOperator ``` ### [Fivetran Sensor](https://github.com/fivetran/airflow-provider-fivetran/blob/main/fivetran_provider/sensors/fivetran.py) `FivetranSensor` monitors a Fivetran sync job for completion. Monitoring with `FivetranSensor` allows you to trigger downstream processes only when the Fivetran sync jobs have completed, ensuring data consistency. You can use multiple instances of `FivetranSensor` to monitor multiple Fivetran connectors. Note, it is possible to monitor a sync that is scheduled and managed from Fivetran; in other words, you can use `FivetranSensor` without using `FivetranOperator`. If used in this way, your DAG will wait until the sync job starts on its Fivetran-controlled schedule and then completes. `FivetranSensor` requires that you specify the `connector_id` of the sync job to start. You can find `connector_id` in the Settings page of the connector you configured in the [Fivetran dashboard](https://fivetran.com/dashboard/connectors). Import into your DAG via: ``` from fivetran_provider.sensors.fivetran import FivetranSensor ``` ## Examples See the [**examples**](https://github.com/fivetran/airflow-provider-fivetran/tree/main/fivetran_provider/example_dags) directory for an example DAG. ## Issues Please submit [issues](https://github.com/fivetran/airflow-provider-fivetran/issues) and [pull requests](https://github.com/fivetran/airflow-provider-fivetran/pulls) in our official repo: [https://github.com/fivetran/airflow-provider-fivetran](https://github.com/fivetran/airflow-provider-fivetran) We are happy to hear from you. Please email any feedback to the authors at [devrel@fivetran.com](mailto:devrel@fivetran.com). ## Acknowledgements Special thanks to [Pete DeJoy](https://github.com/petedejoy), [Plinio Guzman](https://github.com/pgzmnk), and [David Koenitzer](https://github.com/sunkickr) of [Astronomer.io](https://www.astronomer.io/) for their contributions and support in getting this provider off the ground. %prep %autosetup -n airflow-provider-fivetran-1.1.4 %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-airflow-provider-fivetran -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Wed Apr 12 2023 Python_Bot - 1.1.4-1 - Package Spec generated