### Hooks

Source: https://airflow.apache.org/docs/apache-airflow/2.2.2/python-api-ref.html

Hooks serve as interfaces to external platforms and databases, providing a common implementation for interoperability. They are the building blocks for operators and all derive from `BaseHook`.

```APIDOC
## Hooks

Hooks are interfaces to external platforms and databases, implementing a common interface when possible and acting as building blocks for operators. All hooks are derived from `BaseHook`.

### Hooks packages

All hooks are in the following packages:
  * `airflow.hooks`
```

--------------------------------

### Timetables

Source: https://airflow.apache.org/docs/apache-airflow/2.2.2/python-api-ref.html

Custom timetable implementations provide advanced scheduling logic for DAG runs, extending beyond built-in schedule expressions.

```APIDOC
## Timetables

Custom timetable implementations provide Airflow’s scheduler additional logic to schedule DAG runs in ways not possible with built-in schedule expressions.
  * `airflow.timetables`
```

--------------------------------

### Exceptions

Source: https://airflow.apache.org/docs/apache-airflow/2.2.2/python-api-ref.html

This section details the exceptions raised within the Airflow system.

```APIDOC
## Exceptions

  * `airflow.exceptions`
```

--------------------------------

### Models

Source: https://airflow.apache.org/docs/apache-airflow/2.2.2/python-api-ref.html

Models in Airflow are built upon the SQLAlchemy ORM's base class, enabling the persistence of instances within the database.

```APIDOC
## Models

Models are built on top of the SQLAlchemy ORM Base class, and instances are persisted in the database.
  * `airflow.models`
```

--------------------------------

### Secrets Backends

Source: https://airflow.apache.org/docs/apache-airflow/2.2.2/python-api-ref.html

Secrets backends are utilized by Airflow to retrieve Connection objects. All secrets backends inherit from `BaseSecretsBackend`.

```APIDOC
## Secrets Backends

Airflow relies on secrets backends to retrieve `Connection` objects. All secrets backends derive from `BaseSecretsBackend`.
  * `airflow.secrets`
```

--------------------------------

### Operators

Source: https://airflow.apache.org/docs/apache-airflow/2.2.2/python-api-ref.html

Operators define the tasks that form nodes in a Directed Acyclic Graph (DAG). They are categorized into action operators, transfer operators, and sensors. All operators inherit from BaseOperator.

```APIDOC
## Operators

Operators allow for generation of certain types of tasks that become nodes in the DAG when instantiated. All operators derive from `BaseOperator` and inherit many attributes and methods that way.
There are 3 main types of operators:
  * Operators that performs an **action** , or tell another system to perform an action
  * **Transfer** operators move data from one system to another
  * **Sensors** are a certain type of operator that will keep running until a certain criterion is met. Examples include a specific file landing in HDFS or S3, a partition appearing in Hive, or a specific time of the day. Sensors are derived from `BaseSensorOperator` and run a poke method at a specified `poke_interval` until it returns `True`.

### BaseOperator

All operators are derived from `BaseOperator` and acquire much functionality through inheritance. Since this is the core of the engine, it’s worth taking the time to understand the parameters of `BaseOperator` to understand the primitive features that can be leveraged in your DAGs.

### BaseSensorOperator

All sensors are derived from `BaseSensorOperator`. All sensors inherit the `timeout` and `poke_interval` on top of the `BaseOperator` attributes.

### Operators packages

All operators are in the following packages:
  * `airflow.operators`
  * `airflow.sensors`
```

--------------------------------

### Executors

Source: https://airflow.apache.org/docs/apache-airflow/2.2.2/python-api-ref.html

Executors manage the execution of task instances within Airflow. They are responsible for running tasks and all executors are derived from `BaseExecutor`.

```APIDOC
## Executors

Executors are the mechanism by which task instances get run. All executors are derived from `BaseExecutor`.

### Executors packages

All executors are in the following packages:
  * `airflow.executors`
```

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