Snowpark Library for Python release notes for 2025¶

New features¶

• Added a new function service in snowflake.snowpark.functions that allows users to create a callable representing a Snowpark Container Services (SPCS) service.

• Added a new function group_by_all() to the DataFrame class.

• Added connection_parameters parameter to DataFrameReader.dbapi() (Public Preview) method to allow passing keyword arguments to the create_connection callable.

• Added support for Session.begin_transaction, Session.commit, and Session.rollback.

• Added support for the following functions in functions.py:

  • Geospatial functions:

    • st_interpolate

    • st_intersection

    • st_intersection_agg

    • st_intersects

    • st_isvalid

    • st_length

    • st_makegeompoint

    • st_makeline

    • st_makepolygon

    • st_makepolygonoriented

    • st_disjoint

    • st_distance

    • st_dwithin

    • st_endpoint

    • st_envelope

    • st_geohash

    • st_geomfromgeohash

    • st_geompointfromgeohash

    • st_hausdorffdistance

    • st_makepoint

    • st_npoints

    • st_perimeter

    • st_pointn

    • st_setsrid

    • st_simplify

    • st_srid

    • st_startpoint

    • st_symdifference

    • st_transform

    • st_union

    • st_union_agg

    • st_within

    • st_x

    • st_xmax

    • st_xmin

    • st_y

    • st_ymax

    • st_ymin

    • st_geogfromgeohash

    • st_geogpointfromgeohash

    • st_geographyfromwkb

    • st_geographyfromwkt

    • st_geometryfromwkb

    • st_geometryfromwkt

    • try_to_geography

    • try_to_geometry

• Added a parameter to enable and disable automatic column name aliasing for interval_day_time_from_parts and interval_year_month_from_parts functions.

Bug fixes¶

• Fixed a bug that DataFrameReader.xml fails to parse XML files with undeclared namespaces when ignoreNamespace is True.

• Added a fix for floating point precision discrepancies in interval_day_time_from_parts.

• Fixed a bug where writing Snowpark pandas DataFrames on the pandas backend with a column multiindex to Snowflake with to_snowflake would raise KeyError.

• Fixed a bug that DataFrameReader.dbapi (Public Preview) is not compatible with oracledb 3.4.0.

• Fixed a bug where modin would unintentionally be imported during session initialization in some scenarios.

• Fixed a bug where session.udf|udtf|udaf|sproc.register failed when an extra session argument was passed. These methods do not expect a session argument; please remove it if provided.

Improvements¶

• The default maximum length for inferred StringType columns during schema inference in DataFrameReader.dbapi is now increased from 16 MB to 128 MB in parquet file–based ingestion.

Dependency updates¶

• Updated dependency of snowflake-connector-python>=3.17,<5.0.0.

Snowpark pandas API updates¶

New features¶

• Added a new module snowflake.snowpark.secrets that provides Python wrappers for accessing Snowflake Secrets within Python UDFs and stored procedures that execute inside Snowflake.

  • get_generic_secret_string

  • get_oauth_access_token

  • get_secret_type

  • get_username_password

  • get_cloud_provider_token

• Added support for the following scalar functions in functions.py:

  • Conditional expression functions:

    • booland

    • boolnot

    • boolor

    • boolxor

    • boolor_agg

    • decode

    • greatest_ignore_nulls

    • least_ignore_nulls

    • nullif

    • nvl2

    • regr_valx

  • Semi-structured and structured date functions:

    • array_remove_at

    • as_boolean

    • map_delete

    • map_insert

    • map_pick

    • map_size

  • String & binary functions:

    • chr

    • hex_decode_binary

  • Numeric functions:

    • div0null

  • Differential privacy functions:

    • dp_interval_high

    • dp_interval_low

  • Context functions:

    • last_query_id

    • last_transaction

  • Geospatial functions:

    • h3_cell_to_boundary

    • h3_cell_to_children

    • h3_cell_to_children_string

    • h3_cell_to_parent

    • h3_cell_to_point

    • h3_compact_cells

    • h3_compact_cells_strings

    • h3_coverage

    • h3_coverage_strings

    • h3_get_resolution

    • h3_grid_disk

    • h3_grid_distance

    • h3_int_to_string

    • h3_polygon_to_cells

    • h3_polygon_to_cells_strings

    • h3_string_to_int

    • h3_try_grid_path

    • h3_try_polygon_to_cells

    • h3_try_polygon_to_cells_strings

    • h3_uncompact_cells

    • h3_uncompact_cells_strings

    • haversine

    • h3_grid_path

    • h3_is_pentagon

    • h3_is_valid_cell

    • h3_latlng_to_cell

    • h3_latlng_to_cell_string

    • h3_point_to_cell

    • h3_point_to_cell_string

    • h3_try_coverage

    • h3_try_coverage_strings

    • h3_try_grid_distance

    • st_area

    • st_asewkb

    • st_asewkt

    • st_asgeojson

    • st_aswkb

    • st_aswkt

    • st_azimuth

    • st_buffer

    • st_centroid

    • st_collect

    • st_contains

    • st_coveredby

    • st_covers

    • st_difference

    • st_dimension

Bug fixes¶

• Fixed a bug that caused DataFrame.limit() to fail if the executed SQL contained parameter binding when used in non-stored-procedure/udxf environments.

• Added an experimental fix for a bug in schema query generation that could cause invalid sql to be generated when using nested structured types.

• Fixed multiple bugs in DataFrameReader.dbapi (Public Preview):

  • Fixed UDTF ingestion failure with pyodbc driver caused by unprocessed row data.

  • Fixed SQL Server query input failure due to incorrect select query generation.

  • Fixed UDTF ingestion not preserving column nullability in the output schema.

  • Fixed an issue that caused the program to hang during multithreaded Parquet based ingestion when a data fetching error occurred.

  • Fixed a bug in schema parsing when custom schema strings used upper-cased data type names (NUMERIC, NUMBER, DECIMAL, VARCHAR, STRING, TEXT).

• Fixed a bug in Session.create_dataframe where schema string parsing failed when using upper-cased data type names (e.g., NUMERIC, NUMBER, DECIMAL, VARCHAR, STRING, TEXT).

Improvements¶

• Improved DataFrameReader.dbapi (Public Preview) so it doesn’t retry on non-retryable errors, such as SQL syntax error on external data source query.

• Removed unnecessary warnings about local package version mismatch when using session.read.option('rowTag', <tag_name>).xml(<stage_file_path>) or xpath functions.

• Improved DataFrameReader.dbapi (Public Preview) reading performance by setting the default fetch_size parameter value to 100000.

• Improved error message for XSD validation failure when reading XML files using session.read.option('rowValidationXSDPath', <xsd_path>).xml(<stage_file_path>).

Snowpark pandas API updates¶

Bug fixes¶

• Added an experimental fix for a bug in schema query generation that could cause invalid SQL to be genrated when using nested structured types.

New features¶

• Downgraded to level logging.DEBUG - 1 the log message saying that the Snowpark DataFrame reference of an internal DataFrameReference object has changed.

• Eliminate duplicate parameter check queries for casing status when retrieving the session.

• Retrieve DataFrame row counts through object metadata to avoid a COUNT(*) query (performance)

• Added support for applying the Snowflake Cortex function Complete.

• Introduce faster pandas: Improved performance by deferring row position computation.

  • The following operations are currently supported and can benefit from the optimization: read_snowflake, repr, loc, reset_index, merge, and binary operations.

  • If a lazy object (e.g., DataFrame or Series) depends on a mix of supported and unsupported operations, the optimization will not be used.

• Updated the error message for when Snowpark pandas is referenced within apply.

• Added a session parameter dummy_row_pos_optimization_enabled to enable/disable dummy row position optimization in faster pandas.

Dependency updates¶

• Updated the supported modin versions to >=0.35.0 and <0.37.0 (was previously >= 0.34.0 and <0.36.0).

Bug fixes¶

• Fixed an issue with drop_duplicates where the same data source could be read multiple times in the same query but in a different order each time, resulting in missing rows in the final result. The fix ensures that the data source is read only once.

• Fixed a bug with hybrid execution mode where an AssertionError was unexpectedly raised by certain indexing operations.

Snowpark local testing updates¶

New features¶

• Added support for the following AI-powered functions in functions.py:

  • ai_extract

  • ai_parse_document

  • ai_transcribe

• Added time travel support for querying historical data:

  • Session.table() now supports time travel parameters:

    • time_travel_mode

    • statement

    • offset

    • timestamp

    • timestamp_type

    • stream

  • DataFrameReader.table() supports the same time travel parameters as direct arguments.

  • DataFrameReader supports time travel via option chaining (e.g., session.read.option("time_travel_mode", "at").option("offset", -60).table("my_table")).

• Added support for specifying the following parameters to DataFrameWriter.copy_into_location for validation and writing data to external locations:

  • validation_mode

  • storage_integration

  • credentials

  • encryption

• Added support for Session.directory and Session.read.directory to retrieve the list of all files on a stage with metadata.

• Added support for DataFrameReader.jdbc(Private Preview) that allows the JDBC driver to ingest external data sources.

• Added support for FileOperation.copy_files to copy files from a source location to an output stage.

• Added support for the following scalar functions in functions.py:

  • all_user_names

  • bitand

  • bitand_agg

  • bitor

  • bitor_agg

  • bitxor

  • bitxor_agg

  • current_account_name

  • current_client

  • current_ip_address

  • current_role_type

  • current_organization_name

  • current_organization_user

  • current_secondary_roles

  • current_transaction

  • getbit

Bug fixes¶

• Fixed the _repr_ of TimestampType to match the actual subtype it represents.

• Fixed a bug in DataFrameReader.dbapi that UDTF ingestion does not work in stored procedures.

• Fixed a bug in schema inference that caused incorrect stage prefixes to be used.

Improvements¶

• Enhanced error handling in DataFrameReader.dbapi thread-based ingestion to prevent unnecessary operations, which improves resource efficiency.

• Bumped cloudpickle dependency to also support cloudpickle==3.1.1 in addition to previous versions.

• Improved DataFrameReader.dbapi (Public Preview) ingestion performance for PostgreSQL and MySQL by using a server-side cursor to fetch data.

Snowpark pandas API Updates¶

New features¶

• Completed support for the following functions on the “Pandas” and “Ray” backends:

  • pd.read_snowflake()

  • pd.to_iceberg()

  • pd.to_pandas()

  • pd.to_snowpark()

  • pd.to_snowflake()

  • DataFrame.to_iceberg()

  • DataFrame.to_pandas()

  • DataFrame.to_snowpark()

  • DataFrame.to_snowflake()

  • Series.to_iceberg()

  • Series.to_pandas()

  • Series.to_snowpark()

  • Series.to_snowflake()

    on the “Pandas” and “Ray” backends. Previously, only some of these functions and methods were supported on the Pandas backend.

• Added support for Index.get_level_values().

Improvements¶

• Set the default transfer limit in hybrid execution for data leaving Snowflake to 100k, which can be overridden with the SnowflakePandasTransferThreshold environment variable. This configuration is appropriate for scenarios with two available engines, “pandas” and “Snowflake,” on relational workloads.

• Improved the import error message by adding --upgrade to pip install "snowflake-snowpark-python[modin]" in the message.

• Reduced the telemetry messages from the modin client by pre-aggregating into five-second windows and only keeping a narrow band of metrics that are useful for tracking hybrid execution and native pandas performance.

• Set the initial row count only when hybrid execution is enabled, which reduces the number of queries issued for many workloads.

• Added a new test parameter for integration tests to enable hybrid execution.

Bug fixes¶

• Raised NotImplementedError instead of AttributeError on attempting to call Snowflake extension functions/methods to_dynamic_table(), cache_result(), to_view(), create_or_replace_dynamic_table(), and create_or_replace_view() on DataFrames or series using the pandas or ray backends.

New features¶

• Added support for the following xpath functions in functions.py:

  • xpath

  • xpath_string

  • xpath_boolean

  • xpath_int

  • xpath_float

  • xpath_double

  • xpath_long

  • xpath_short

• Added support for the use_vectorized_scanner parameter in the Session.write_arrow() function.

• DataFrame profiler adds the following information about each query: describe query time, execution time, and sql query text. To view this information, call session.dataframe_profiler.enable() and call get_execution_profile on a DataFrame.

• Added support for DataFrame.col_ilike.

• Added support for non-blocking stored procedure calls that return AsyncJob objects.

  • Added the block: bool = True parameter to Session.call(). When block=False, returns an AsyncJob instead of blocking until completion.

  • Added the block: bool = True parameter to StoredProcedure.__call__() for async support across both named and anonymous stored procedures.

  • Added Session.call_nowait() that is equivalent to Session.call(block=False).

Bug fixes¶

• Fixed a bug in CTE optimization stage where deepcopy of internal plans would cause a memory spike when a DataFrame is created locally using session.create_dataframe() using large input data.

• Fixed a bug in DataFrameReader.parquet where the ignore_case option in the infer_schema_options was not respected.

• Fixed a bug where to_pandas() had a different format of column name when the query result format is set to JSON and ARROW.

Deprecations¶

• Deprecated pkg_resources.

Dependency updates¶

• Added a dependency on protobuf<6.32

Snowpark pandas API Updates¶

New features¶

• Added support for efficient transfer of data between Snowflake and <Ray with the DataFrame.set_backend method. The installed version of modin must be at least 0.35.0, and ray must be installed.

Dependency updates¶

• Updated the supported modin versions to >=0.34.0 and <0.36.0 (was previously >= 0.33.0 and <0.35.0).

• Added support for pandas 2.3 when the installed modin version is 0.35.0 or greater.

Bug fixes¶

• Fixed an issue in hybrid execution mode (Private Preview) where pd.to_datetime and pd.to_timedelta would unexpectedly raise IndexError.

• Fixed a bug where pd.explain_switch would raise IndexError or return None if called before any potential switch operations were performed.

New features¶

• Session.create_dataframe now accepts keyword arguments that are forwarded in the internal call to Session.write_pandas or Session.write_arrow when creating a DataFrame from a pandas DataFrame or a pyarrow table.

• Added new APIs for AsyncJob:

  • AsyncJob.is_failed() returns a bool indicating whether a job has failed. Can be used in combination with AsyncJob.is_done() to determine if a job is finished and erred.

  • AsyncJob.status() returns a string representing the current query status (such as, “RUNNING”, “SUCCESS”, “FAILED_WITH_ERROR”) for detailed monitoring without calling result().

• Added a DataFrame profiler. To use, you can call get_execution_profile() on your desired DataFrame. This profiler reports the queries executed to evaluate a DataFrame and statistics about each of the query operators. Currently an experimental feature.

• Added support for the following functions in functions.py:

  • ai_sentiment

• Updated the interface for the context.configure_development_features experimental feature. All development features are disabled by default unless explicitly enabled by the user.

Improvements¶

• Hybrid execution row estimate improvements and a reduction of eager calls.

• Added a new configuration variable to control transfer costs out of Snowflake when using hybrid execution.

• Added support for creating permanent and immutable UDFs/UDTFs with DataFrame/Series/GroupBy.apply, map, and transform by passing the snowflake_udf_params keyword argument.

• Added support for mapping np.unique to DataFrame and Series inputs using pd.unique.

Bug fixes¶

• Fixed an issue where the Snowpark pandas plugin would unconditionally disable AutoSwitchBackend even when users have explicitly configured it programmatically or with environment variables.

New features¶

• Added support for the following functions in functions.py:

  • ai_embed

  • try_parse_json

Improvements¶

• Improved query parameter in DataFrameReader.dbapi (Private Preview) so that parentheses aren’t needed around the query.

• Improved error experience in DataFrameReader.dbapi (Private Preview) for exceptions raised when inferring the schema of the target data source.

Bug fixes¶

• Fixed a bug in DataFrameReader.dbapi (Private Preview) that fails dbapi with process exit code 1 in a Python stored procedure.

• Fixed a bug in DataFrameReader.dbapi (Private Preview) where custom_schema accepts an illegal schema.

• Fixed a bug in DataFrameReader.dbapi (Private Preview) where custom_schema doesn’t work when connecting to Postgres and MySQL.

• Fixed a bug in schema inference that causes it to fail for external stages.

Snowpark local testing updates¶

New features¶

• Added a new option TRY_CAST to DataFrameReader. When TRY_CAST is True, columns are wrapped in a TRY_CAST statement instead of a hard cast when loading data.

• Added a new option USE_RELAXED_TYPES to the INFER_SCHEMA_OPTIONS of DataFrameReader. When set to True, this option casts all strings to max length strings and all numeric types to DoubleType.

• Added debuggability improvements to eagerly validate dataframe schema metadata. Enable it using snowflake.snowpark.context.configure_development_features().

• Added a new function snowflake.snowpark.dataframe.map_in_pandas that allows users to map a function across a dataframe. The mapping function takes an iterator of pandas DataFrames as input and provides one as output.

• Added a ttl cache to describe queries. Repeated queries in a 15-second interval use the cached value rather than requery Snowflake.

• Added a parameter fetch_with_process to DataFrameReader.dbapi (PrPr) to enable multiprocessing for parallel data fetching in local ingestion. By default, local ingestion uses multithreading. Multiprocessing can improve performance for CPU-bound tasks like Parquet file generation.

• Added a new function snowflake.snowpark.functions.model that allows users to call methods of a model.

Improvements¶

• Added support for row validation using XSD schema using rowValidationXSDPath option when reading XML files with a row tag using rowTag option.

• Improved SQL generation for session.table().sample() to generate a flat SQL statement.

• Added support for complex column expression as input for functions.explode.

• Added debuggability improvements to show which Python lines a SQL compilation error corresponds to. Enable it using snowflake.snowpark.context.configure_development_features(). This feature also depends on AST collections to be enabled in the session, which can be done using session.ast_enabled = True.

• Set enforce_ordering=True when calling to_snowpark_pandas():code: from a Snowpark DataFrame containing DML/DDL queries instead of throwing a NotImplementedError.

Bug fixes¶

• Fixed a bug caused by redundant validation when creating an iceberg table.

• Fixed a bug in DataFrameReader.dbapi (Private Preview) where closing the cursor or connection could unexpectedly raise an error and terminate the program.

• Fixed ambiguous column errors when using table functions in DataFrame.select() that have output columns matching the input DataFrame’s columns. This improvement works when DataFrame columns are provided as Column objects.

• Fixed a bug where having a NULL in a column with DecimalTypes would cast the column to FloatTypes instead and lead to precision loss.

Snowpark Local testing Updates¶

• Fixed a bug when processing windowed functions that lead to incorrect indexing in results.

• When a scalar numeric is passed to fillna, Snowflake will ignore non-numeric columns instead of producing an error.

Snowpark pandas API Updates¶

New features¶

• Added support for MySQL in DataFrameWriter.dbapi (Private Preview) for both Parquet and UDTF-based ingestion.

• Added support for PostgreSQL in DataFrameReader.dbapi (Private Preview) for both Parquet and UDTF-based ingestion.

• Added support for Databricks in DataFrameWriter.dbapi (Private Preview) for UDTF-based ingestion, consolidating with other mentions of Databricks support.

• Added support to DataFrameReader to enable use of PATTERN when reading files with INFER_SCHEMA enabled.

• Added support for the following AI-powered functions in functions.py:

  • ai_complete

  • ai_similarity

  • ai_summarize_agg (originally summarize_agg)

  • different config options for ai_classify

• Added support for more options when reading XML files with a row tag using rowTag option:

  • Added support for removing namespace prefixes from column names using ignoreNamespace option.

  • Added support for specifying the prefix for the attribute column in the result table using attributePrefix option.

  • Added support for excluding attributes from the XML element using excludeAttributes option.

  • Added support for specifying the column name for the value when there are attributes in an element that has no child elements using valueTag option.

  • Added support for specifying the value to treat as a null value using nullValue option.

  • Added support for specifying the character encoding of the XML file using charset option.

  • Added support for ignoring surrounding whitespace in the XML element using ignoreSurroundingWhitespace option.

• Added support for parameter return_dataframe in Session.call, which can be used to set the return type of the functions to a DataFrame object.

• Added a new argument to Dataframe.describe called strings_include_math_stats that triggers stddev and mean to be calculated for String columns.

• Added support for retrieving Edge.properties when retrieving lineage from DGQL in DataFrame.lineage.trace.

• Added a parameter table_exists to DataFrameWriter.save_as_table that allows specifying if a table already exists. This allows skipping a table lookup that can be expensive.

Bug fixes¶

• Fixed a bug in DataFrameReader.dbapi (Private Preview) where the create_connection defined as local function was incompatible with multiprocessing.

• Fixed a bug in DataFrameReader.dbapi (Private Preview) where Databricks TIMESTAMP type was converted to Snowflake TIMESTAMP_NTZ type which should be TIMESTAMP_LTZ type.

• Fixed a bug in DataFrameReader.json where repeated reads with the same reader object would create incorrectly quoted columns.

• Fixed a bug in DataFrame.to_pandas() that would drop column names when converting a DataFrame that did not originate from a select statement.

• Fixed a bug where DataFrame.create_or_replace_dynamic_table raises an error when the DataFrame contains a UDTF and SELECT * in the UDTF is not parsed correctly.

• Fixed a bug where casted columns could not be used in the values clause of functions.

Improvements¶

• Improved the error message for Session.write_pandas() and Session.create_dataframe() when the input pandas DataFrame does not have a column.

• Improved DataFrame.select when the arguments contain a table function with output columns that collide with columns of current DataFrame. With the improvement, if user provides non-colliding columns in df.select("col1", "col2", table_func(...)) as string arguments, then the query generated by Snowpark client will not raise ambiguous column error.

• Improved DataFrameReader.dbapi (Private Preview) to use in-memory Parquet-based ingestion for better performance and security.

• Improved DataFrameReader.dbapi (Private Preview) to use MATCH_BY_COLUMN_NAME=CASE_SENSITIVE in copy into table operation.

Snowpark Local testing Updates¶

Snowpark pandas API Updates¶

Improvements¶

• Invoking Snowflake system procedures does not invoke an additional describe procedure call to check the return type of the procedure.

• Added support for Session.create_dataframe() with the stage URL and FILE data type.

• Added support for different modes for dealing with corrupt XML records when reading an XML file using session.read.option('mode', <mode>), option('rowTag', <tag_name>).xml(<stage_file_path>). Currently PERMISSIVE, DROPMALFORMED and FAILFAST are supported.

• Improved the error message of the XML reader when the specified ROWTAG is not found in the file.

• Improved query generation for Dataframe.drop to use SELECT * EXCLUDE () to exclude the dropped columns. To enable this feature, set session.conf.set("use_simplified_query_generation", True).

• Added support for VariantType to StructType.from_json.

Bug fixes¶

• Fixed a bug in DataFrameWriter.dbapi (Private preview) where unicode or double-quoted column names in external databases cause errors because they are not quoted correctly.

• Fixed a bug where named fields in nested OBJECT data could cause errors when containing spaces.

Snowpark local testing updates¶

Snowpark pandas API Updates¶

New features¶

• Added support for the restricted caller permission of execute_as argument in StoredProcedure.register():code:.

• Added support for non-select statements in DataFrame.to_pandas().

• Added support for the artifact_repository parameter to Session.add_packages, Session.add_requirements, Session.get_packages, Session.remove_package, and Session.clear_packages.

• Added support for reading an XML file using a row tag by session.read.option('rowTag', <tag_name>).xml(<stage_file_path>) (experimental).

  • Each XML record is extracted as a separate row.

  • Each field within that record becomes a separate column of type VARIANT, which can be further queried using the dot notation, such as col(a.b.c).

• Added updates to DataFrameReader.dbapi (PrPr):

  • Added the fetch_merge_count parameter for optimizing performance by merging multiple fetched data into a single Parquet file.

  • Added support for Databricks.

  • Added support for ingestion with Snowflake UDTF.

• Added support for the following AI-powered functions in functions.py (Private Preview):

  • prompt

  • ai_filter (added support for prompt() function and image files, and changed the second argument name from expr to file)

  • ai_classify

Snowpark local testing updates¶

Snowpark pandas API updates¶

New features¶

• Added Support for relaxed consistency and ordering guarantees in Dataframe.to_snowpark_pandas by introducing the relaxed_ordering parameter.

• DataFrameReader.dbapi (preview) now accepts a list of strings for the session_init_statement parameter, allowing multiple SQL statements to be executed during session initialization.

Improvements¶

• Improved query generation for Dataframe.stat.sample_by to generate a single flat query that scales well with large fractions dictionary compared to older method of creating a UNION ALL subquery for each key in fractions. To enable this feature, set session.conf.set("use_simplified_query_generation", True).

• Improved the performance of DataFrameReader.dbapi by enabling the vectorized option when copying a parquet file into a table.

• Improved query generation for DataFrame.random_split in the following ways. They can be enabled by setting session.conf.set("use_simplified_query_generation", True):

  • Removed the need to cache_result in the internal implementation of the input dataframe resulting in a pure lazy dataframe operation.

  • The seed argument now behaves as expected with repeatable results across multiple calls and sessions.

• DataFrame.fillna and DataFrame.replace now both support fitting int and float into Decimal columns if include_decimal is set to True.

• Added documentation for the following UDF and stored procedure functions in files.py as a result of their General Availability.

  • SnowflakeFile.write

  • SnowflakeFile.writelines

  • SnowflakeFile.writeable

• Minor documentation changes for SnowflakeFile and SnowflakeFile.open().

Bug fixes¶

• Fixed a bug for the following functions that raised errors. .cast() is applied to their output:

  • from_json

  • size

Snowpark local testing updates¶

Snowpark pandas API updates¶

Snowpark local testing updates¶

Bug fixes¶

• Fixed a bug in DataFrameReader.dbapi (private preview) that prevents usage in stored procedures and Snowbooks.

New features¶

• Added support for the following AI-powered functions in functions.py (Private Preview):

  • ai_filter

  • ai_agg

  • summarize_agg

• Added support for the new FILE SQL type, with the following related functions in functions.py (Private Preview):

  • fl_get_content_type

  • fl_get_etag

  • fl_get_file_type

  • fl_get_last_modified

  • fl_get_relative_path

  • fl_get_scoped_file_url

  • fl_get_size

  • fl_get_stage

  • fl_get_stage_file_url

  • fl_is_audio

  • fl_is_compressed

  • fl_is_document

  • fl_is_image

  • fl_is_video

• Added support for importing third-party packages from PyPi using Artifact Repository (Private Preview):

  • Use keyword arguments artifact_repository and packages to specify your artifact repository and packages respectively when registering stored procedures or user defined functions.

  • Supported APIs are:

    • Session.sproc.register

    • Session.udf.register

    • Session.udaf.register

    • Session.udtf.register

    • functions.sproc

    • functions.udf

    • functions.udaf

    • functions.udtf

    • functions.pandas_udf

    • functions.pandas_udtf

Improvements¶

• Improved version validation warnings for snowflake-snowpark-python package compatibility when registering stored procedures. Now, warnings are only triggered if the major or minor version does not match, while bugfix version differences no longer generate warnings.

• Bumped cloudpickle dependency to also support cloudpickle==3.0.0 in addition to previous versions.

Bug fixes¶

• Fixed a bug where creating a Dataframe with large number of values raised Unsupported feature 'SCOPED_TEMPORARY'. error if thread-safe session was disabled.

• Fixed a bug where df.describe raised internal SQL execution error when the DataFrame is created from reading a stage file and CTE optimization is enabled.

• Fixed a bug where df.order_by(A).select(B).distinct() would generate invalid SQL when simplified query generation was enabled using session.conf.set("use_simplified_query_generation", True).

  • Disabled simplified query generation by default.

Snowpark pandas API updates¶

Snowpark local testing updates¶

New features¶

• Added support for the following functions in functions.py

  • normal

  • randn

• Added support for allow_missing_columns parameter to Dataframe.union_by_name and Dataframe.union_all_by_name.

Improvements¶

• Improved random object name generation to avoid collisions.

• Improved query generation for Dataframe.distinct to generate SELECT DISTINCT instead of SELECT with GROUP BY all columns. To disable this feature, set session.conf.set("use_simplified_query_generation", False).

Deprecations¶

• Deprecated Snowpark Python function snowflake_cortex_summarize. Users can install snowflake-ml-python and use the snowflake.cortex.summarize function instead.

• Deprecated Snowpark Python function snowflake_cortex_sentiment. Users can install snowflake-ml-python and use the snowflake.cortex.sentiment function instead.

Bug fixes¶

• Fixed a bug where session-level query tag was overwritten by a stack trace for DataFrames that generate multiple queries. Now, the query tag will only be set to the stacktrace if session.conf.set("collect_stacktrace_in_query_tag", True).

• Fixed a bug in Session._write_pandas where it was erroneously passing use_logical_type parameter to Session._write_modin_pandas_helper when writing a Snowpark pandas object.

• Fixed a bug in options SQL generation that could cause multiple values to be formatted incorrectly.

• Fixed a bug in Session.catalog where empty strings for database or schema were not handled correctly and were generating erroneous SQL statements.

Experimental Features¶

• Added support for writing pyarrow Tables to Snowflake tables.

Snowpark pandas API updates¶

Bug fixes¶

• Fixed a bug in apply where kwargs were not being correctly passed into the applied function.

Snowpark local testing updates¶

Bug fixes¶

• Fixed a bug in DataFrame.join that caused columns to have incorrect typing.

• Fixed a bug in when statements that caused incorrect results in the otherwise clause.

New features¶

Added support for the following functions in functions.py:

• array_reverse

• divnull

• map_cat

• map_contains_key

• map_keys

• nullifzero

• snowflake_cortex_sentiment

• acosh

• asinh

• atanh

• bit_length

• bitmap_bit_position

• bitmap_bucket_number

• bitmap_construct_agg

• cbrt

• equal_null

• from_json

• ifnull

• localtimestamp

• max_by

• min_by

• nth_value

• nvl

• octet_length

• position

• regr_avgx

• regr_avgy

• regr_count

• regr_intercept

• regr_r2

• regr_slope

• regr_sxx

• regr_sxy

• regr_syy

• try_to_binary

• base64

• base64_decode_string

• base64_encode

• editdistance

• hex

• hex_encode

• instr

• log1p

• log2

• log10

• percentile_approx

• unbase64

• Added support for specifying a schema string (including implicit struct syntax) when calling DataFrame.create_dataframe.

• Added support for DataFrameWriter.insert_into/insertInto. This method also supports local testing mode.

• Added support for DataFrame.create_temp_view to create a temporary view. It will fail if the view already exists.

• Added support for multiple columns in the functions map_cat and map_concat.

• Added an option keep_column_order for keeping original column order in DataFrame.with_column and DataFrame.with_columns.

• Added options to column casts that allow renaming or adding fields in StructType columns.

• Added support for contains_null parameter to ArrayType.

• Added support for creating a temporary view via DataFrame.create_or_replace_temp_view from a DataFrame created by reading a file from a stage.

• Added support for value_contains_null parameter to MapType.

• Added interactive to telemetry that indicates whether the current environment is an interactive one.

• Allow session.file.get in a Native App to read file paths starting with / from the current version

• Added support for multiple aggregation functions after DataFrame.pivot.

Experimental features¶

• Added Session.catalog class to manage Snowflake objects. It can be accessed via Session.catalog.

  • snowflake.core is a dependency required for this feature.

• Allow user input schema or user input schemas when reading JSON file on stage.

• Added support for specifying a schema string (including implicit struct syntax) when calling DataFrame.create_dataframe.

Improvements¶

• Updated README.md to include instructions on how to verify package signatures using cosign.

Bug fixes¶

• Fixed a bug in local testing mode that caused a column to contain None when it should contain 0.

• Fixed a bug in StructField.from_json that prevented TimestampTypes with tzinfo from being parsed correctly.

• Fixed a bug in function date_format that caused an error when the input column was date type or timestamp type.

• Fixed a bug in DataFrame that allowed null values to be inserted in a non-nullable column.

• Fixed a bug in functions replace and lit which raised type hint assertion error when passing Column expression objects.

• Fixed a bug in pandas_udf and pandas_udtf where session parameters were erroneously ignored.

• Fixed a bug that raised an incorrect type conversion error for system function called through session.call.

Snowpark pandas API updates¶