> ## Documentation Index
> Fetch the complete documentation index at: https://docs.domino.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Write to a local file

## Parquet

Because Domino uses [PyArrow](https://arrow.apache.org/docs/python/) to serialize and transport data, the query result is easily written to a local parquet file. You can also use pandas as shown in the CSV example.

```python theme={null}
redshift = DataSourceClient().get_datasource("redshift-test")

res = redshift.query("SELECT * FROM wines LIMIT 1000")

# to_parquet() accepts a path or file-like object
# the whole result is loaded and written once
res.to_parquet("./wines_1000.parquet")
```

```r theme={null}
client <- DominoDataR::datasource_client()
table <- DominoDataR::query(client, "redshift-test", "SELECT* FROM wines LIMIT 1000")

# We can use https://arrow.apache.org/docs/r/reference/write_parquet.html since we leverage the arrow library
arrow::write_parquet(table, "./wines_1000.parquet")
```

## CSV

Because serializing to a CSV is lossy, Domino recommends using the [Pandas.to\_csv](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_csv.html#pandas-dataframe-to-csv) API so you can leverage the multiple options that it provides.

```python theme={null}
redshift = DataSourceClient().get_datasource("redshift-test")

res = redshift.query("SELECT * FROM wines LIMIT 1000")

# See Pandas.to_csv documentation for all options
csv_options = {header: True, quotechar: "'"}

res.to_pandas().to_csv("./wines_1000.csv", **csv_options)
```

```r theme={null}
client <- DominoDataR::datasource_client()
table <- DominoDataR::query(client, "redshift-test", "SELECT* FROM wines LIMIT 1000")

# We can use https://arrow.apache.org/docs/r/reference/write_csv_arrow.html since we leverage the arrow library
arrow::write_csv_arrow(table, "./wines_1000.csv")
```