Prompt:
What is a pipeline in Apache Beam?

Response:
In Apache Beam, a pipeline encapsulates the entirety of a data processing task, including all the data and each step of the process. Essentially, it's a Directed Acyclic Graph of transformations (known as `PTransform`) applied to data collections (`PCollection`).

The simplest pipelines in Apache Beam follow a linear flow of operations, typically adhering to a read-process-write pattern. However, pipelines can also be significantly more complex, featuring multiple input sources, output sinks, and operations (known as a `PTransform`) that can both read from and output to multiple `PCollection` objects. For more information about pipeline design and best practices, see the 'Common Pipeline Patterns' section in the Apache Beam documentation.

To use Apache Beam, your driver program must first create an instance of the Beam SDK class `Pipeline` (typically in the `main()` function).

```python
import apache_beam as beam

with beam.Pipeline() as pipeline:
  pass  # Build your pipeline here.
```

When you create your pipeline, you need to set configuration options. You can set your pipeline’s configuration options programmatically. You can also set the options ahead of time, or read them from the command line, and then pass them to the `Pipeline` object when you create the object. This option is often easier than setting the pipeline configuration options programmatically.
