learning/prompts/code-generation/10_io_parquet.md

Prompt:
Write the Python code to read data from Apache Parquet files using Apache Beam.

Response:
Your Apache Beam pipeline can read data from [Apache Parquet](https://parquet.apache.org/) files using the [ParquetIO connector](https://beam.apache.org/releases/pydoc/current/apache_beam.io.parquetio.html).

```python
import logging

import apache_beam as beam
from apache_beam import Map
from apache_beam.io.parquetio import ReadFromParquet
from apache_beam.options.pipeline_options import PipelineOptions


def run(argv=None):

  class ReadParquetOptions(PipelineOptions):

    @classmethod
    def _add_argparse_args(cls, parser):
      parser.add_argument(
          "--path",
          help="GCS path to Parquet file")

  options = ReadParquetOptions()

  with beam.Pipeline(options=options) as p:

    (p | "Read Parquet" >> ReadFromParquet(options.path)
       | Map(logging.info))


if __name__ == "__main__":
  logging.getLogger().setLevel(logging.INFO)
  run()
```

The `ReadParquetOptions` class is used to define the command-line argument `--path`, which specifies the path to the Parquet file. This code uses [pipeline options](https://beam.apache.org/documentation/patterns/pipeline-options/) for the required `path` argument.

The code creates an Apache Beam pipeline using the `ReadParquetOptions` class to set the Parquet file path and the [`ReadFromParquet` transform](https://beam.apache.org/releases/pydoc/current/apache_beam.io.parquetio.html#apache_beam.io.parquetio.ReadFromParquet) to read data from the file.