Developer guide for creating and modifying data rows via the Python SDK.
Dataset
class. For complete details and additional examples of approaches for creating data rows, please see Dataset.
We recommend using created_data_rows()
and upsert_data_rows()
methods for large data row upload operations.
#
,<
, >
and |
| are not supported in URLs and should be avoided in your file names to prevent loading issues.Please refer to https://datatracker.ietf.org/doc/html/rfc2396#section-2.4.3 on URI standards.A good test for the handling of special characters is to test URLs in your browser address bar — if the URL doesn’t load properly in your browser, it won’t load in Labelbox.row_data
. However, Labelbox strongly recommends supplying each data row with a global key upon creation.
upsert_data_rows()
method to update data rows.
When using this method to update data rows, you need to pass a key
, which can reference either a global key or data row ID.
Include any fields you wish to update along with their new values.
update
method is also available; however, for a large number of data row updates, we recommend using upsert_data_rows()
The update
method only supports updates on global_key
, row_data
or external_id
values.
lb.DataRow.bulk_delete()
method can delete a maximum of 4,000 data rows per call.