Exporting data - Lasso

Once your table is complete, you can export the data in several formats.

Available formats

Format	Description	Use case
JSON	Array of row objects	Programmatic processing, API integrations
CSV	Semicolon-delimited file	Spreadsheet import, data analysis
XLSX	Excel spreadsheet	Business users, reporting
Images	ZIP archive of all images	Asset management, media libraries

Exporting via SDK

// JSON -- returns data directly
const data = await client.export.json("tbl_abc123");

// CSV -- returns raw CSV string
const csv = await client.export.csv("tbl_abc123");

// XLSX -- returns binary buffer
const xlsx = await client.export.xlsx("tbl_abc123");

// Images -- returns ZIP buffer
const images = await client.export.images("tbl_abc123");

# JSON -- returns list of dicts
data = client.export.json("tbl_abc123")

# CSV -- returns raw CSV string
csv = client.export.csv("tbl_abc123")

# XLSX -- save directly to file
client.export.xlsx("tbl_abc123", path="export.xlsx")

# Images -- save ZIP to file
client.export.images("tbl_abc123", path="images.zip")

Selecting columns

By default, all columns are exported. To export only specific columns, pass a comma-separated list of column keys:

const data = await client.export.json("tbl_abc123", {
  columns: "product_name,price,image_url",
});

data = client.export.json("tbl_abc123", columns="product_name,price,image_url")

Pandas integration (Python)

The Python SDK includes a helper to load all rows as a pandas DataFrame:

df = client.tables.results_as_dataframe("tbl_abc123")

# Filter, analyze, or export further
expensive = df[df["price"] > 100]
df.to_csv("products.csv", index=False)

This fetches all pages automatically and returns a ready-to-use DataFrame.