Release notes#
PyStarburst 0.13.0 - June 19, 2026#
Features#
Add methods DataFrame.to_arrow_batches() and DataFrame.to_arrow_table()
Fixes#
Fix
DataFrame.to_local_iterator()truncating results at the first protocol response page. The iterator now correctly paginates through all rows and runs on its own cursor, isolated from subsequent actions on the same DataFrame.
PyStarburst 0.12.1 - May 29, 2026#
Dependencies#
Restrict pydantic to >=2.12.5,<2.13, as 2.13.4 causes pystarburst to crash on import
PyStarburst 0.12.0 - April 29, 2026#
Features#
Add Python 3.14 support
Add Arrow spooling support for DataFrame.to_pandas()
Under the Hood#
Migrate to Pydantic V2
PyStarburst 0.11.0 - February 05, 2026#
Under the Hood#
Drop support for end-of-life Python 3.9
Dependencies#
Bump dependencies to address CVEs
PyStarburst 0.10.0 - August 06, 2025#
Features#
Add support for Python 3.13
Dependencies#
Bump trino-python-client to 0.335.0
PyStarburst 0.9.0 - July 08, 2024#
Features#
Add session.cache_results method that allows caching dataframes
Add df.write.copy_into_location method that allows export dataframe to external location
Dependencies#
Bump pydantic to v2 and adjust code to still use pydantic v1
Bump dependencies and trino-python-client to 0.329.0
PyStarburst 0.8.0 - April 30, 2024#
Breaking Changes#
- Use JodaTime’s DateTimeFormat. Previously we used Teradata functions underneath,which for date and time year-month-day hour:minute:second use format:
yyyy-mm-dd hh24:mi:ssNow we use JodaTime’s DateTimeFormat, which use format:yyyy-MM-dd HH:mm:sswhich is far more common. Going forward please use JodaTime’s DateTimeFormat in to_date and to_timestamp functions.
Features#
Add explode, posexplode, inline dataframe methods
Add struct function
Support schema discovery for Iceberg and Delta
Add if_exists clause to Table.drop_table
Fixes#
Do not accept a boolean value for ‘on’ parameter in ‘join’ method
Under the Hood#
Compress logical plan if server supports it
Dependencies#
Update trino-python-client to 0.328.0
Update dependencies
PyStarburst 0.7.0 - February 21, 2024#
Features#
Add DataFrame.is_empty() method
Adds melt alias to unpivot
Add DataFrame.to() method
Add DataFrame.with_columns_renamed() and modified with_column_renamed accordingly
Add LambdaFunctionExpression
Add transform function
Add zip_with function
Added filter function
Added any_match function
Added all_match function
Added array_sort function
Added reduce function
Added transform_keys, transform_values functions
Added map_filter function
Added map_zip_with function
Support type coercion
Add json_array_length function
Add is_not_null function
Add to_json function
Support type coercion
Add from_json function
Add programmatic access to Starburst schema discovery feature, using discover method
Add get_json_object function
Add json_tuple function
Under the Hood#
Use EXECUTE IMMEDIATE for prepared statements by default
Allow up to 3 arguments for LambdaFunctionExpression
Give random names for lambda parameters
Add tests against Python 3.12
Lambda functions retain context
Remove source_plan from TrinoPlan
Dependencies#
Remove typing-extensions dependency
Remove backports-zoneinfo dependency
Remove testcontainers dependency
Update dependencies
Update trino to 0.327.0
PyStarburst 0.6.3 - November 09, 2023#
Under the Hood#
Conda release
PyStarburst 0.6.2 - October 18, 2023#
Features#
Add support for stack function
Implement to_pandas() method
Add map functions: create_map, map_from_arrays, map_keys, map_values, map_entries, map_from_entries, map_concat
Add array functions: reverse, flatten, sort_array, shuffle, sequence, array_prepend, array_compact, get
Add support for unpivot function
Fixes#
Fix to_timestamp to accept not only VARCHAR as an argument
Under the Hood#
PyPi release
PyStarburst 0.5.0 - August 17, 2023#
Features#
Add support for regexp_split
Add collect_list and collect_set
Add support for TIME WITH TIME ZONE
Implement array functions: array_distinct, array_min, array_max, array_union, array_except, array_slice, size, array_repeat, array_insert, array_join, array_remove, element_at, arrays_zip
Support for aggregate functions: max_by, min_by, product
Support tuple as struct
Support ilike column function
Support math functions