Release

1.47.0 (2026-03-05)

Snowpark Python API Updates

New Features

• Added support for the array_union_agg function in the snowflake.snowpark.functions module.

Bug Fixes

• Fixed a bug where Session.udf.register_from_file did not properly process the strict and secure parameters.
• Fixed a bug when create dataframe with small data(< array binding threshold), and error is raised when have string value in a DecimalType column.

Release

1.46.0 (2026-02-23)

Snowpark Python API Updates

New Features

• Added support for the DECFLOAT data type that allows users to represent decimal numbers exactly with 38 digits of precision and a dynamic base-10 exponent.
• Added support for the DEFAULT_PYTHON_ARTIFACT_REPOSITORY parameter that allows users to configure the default artifact repository at the account, database, and schema level.

Bug Fixes

• Fixed a bug where cloudpickle was not automatically added to the package list when using artifact_repository with custom packages, causing ModuleNotFoundError at runtime.
• Fixed a bug when reading xml with custom schema, result include element attributes when column is not StructType type.
• Fixed a bug where Session.udf.register_from_file did not properly process the strict and secure parameters.

Improvements

• Reduced the size of queries generated by certain DataFrame.join operations.
• Removed redundant aliases in generated queries (for example, SELECT "A" AS "A" is now always simplified to SELECT "A").

Snowpark pandas API Updates

New Features

Bug Fixes

Improvements

Release

1.45.0 (2026-02-02)

Snowpark Python API Updates

New Features

• Allow user input schema when reading XML file on stage.
• Added support for the following functions in functions.py:
  • String and Binary functions:
    • hex_decode_string
    • jarowinkler_similarity
    • parse_url
    • regexp_instr
    • regexp_like
    • regexp_substr
    • regexp_substr_all
    • rtrimmed_length
    • space
    • split_part
• Added preserve_parameter_names flag to sproc, UDF, UDTF, and UDAF creation

Bug Fixes

• Fixed a bug that opentelemetry is not correctly import when using Session.client_telemetry.enable_event_table_telemetry_collection.

Improvements

• snowflake.snowpark.context.configure_development_features is effective for multiple sessions including newly created sessions after the configuration. No duplicate experimental warning any more.
• Removed experimental warning from DataFrame.to_arrow and DataFrame.to_arrow_batches.
• When both Session.reduce_describe_query_enabled and Session.cte_optimization_enabled are enabled, fewer DESCRIBE queries are issued when resolving table attributes.

Release

1.44.0 (2025-12-15)

Snowpark Python API Updates

New Features

• Added support for targeted delete-insert via the overwrite_condition parameter in DataFrameWriter.save_as_table

Improvements

• Improved DataFrameReader to return columns in deterministic order when using INFER_SCHEMA.

Dependency Updates

• Added a dependency on protobuf<6.34 (was <6.32).

Release

1.43.0 (2025-12-03)

Snowpark Python API Updates

New Features

• Added support for DataFrame.lateral_join
• Added support for PrPr feature Session.client_telemetry.
• Added support for Session.udf_profiler.
• Added support for functions.ai_translate.
• Added support for the following iceberg_config options in DataFrameWriter.save_as_table and DataFrame.copy_into_table:
  • target_file_size
  • partition_by
• Added support for the following functions in functions.py:

  • String and Binary functions:

    • base64_decode_binary
    • bucket
    • compress
    • day
    • decompress_binary
    • decompress_string
    • md5_binary
    • md5_number_lower64
    • md5_number_upper64
    • sha1_binary
    • sha2_binary
    • soundex_p123
    • strtok
    • truncate
    • try_base64_decode_binary
    • try_base64_decode_string
    • try_hex_decode_binary
    • try_hex_decode_string
    • unicode
    • uuid_string

  • Conditional expressions:

    • booland_agg
    • boolxor_agg
    • regr_valy
    • zeroifnull

  • Numeric expressions:

    • cot
    • mod
    • pi
    • square
    • width_bucket

Bug Fixes

• Fixed a bug where automatically-generated temporary objects were not properly cleaned up.
• Fixed with a bug when sql generation when joining two DataFrames created using DataFrame.alias and CTE optimization is enabled.
• Fixed a bug in XMLReader where finding the start position of a row tag could return an incorrect file position.

Improvements

• Enhanced DataFrame.sort() to support ORDER BY ALL when no columns are specified.
• Removed experimental warning from Session.cte_optimization_enabled.

Snowpark pandas API Updates

New Features

• Added support for Dataframe.groupby.rolling().
• Added support for mapping np.percentile with DataFrame and Series inputs to Series.quantile.
• Added support for setting the random_state parameter to an integer when calling DataFrame.sample or Series.sample.
• Added support for the following iceberg_config options in to_iceberg:
  • target_file_size
  • partition_by

Improvements

• Enhanced autoswitching functionality from Snowflake to native pandas for methods with unsupported argument combinations:
  • shift() with suffix or non-integer periods parameters
  • sort_index() with axis=1 or key parameters
  • sort_values() with axis=1
  • melt() with col_level parameter
  • apply() with result_type parameter for DataFrame
  • pivot_table() with sort=True, non-string index list, non-string columns list, non-string values list, or aggfunc dict with non-string values
  • fillna() with downcast parameter or using limit together with value
  • dropna() with axis=1
  • asfreq() with how parameter, fill_value parameter, normalize=True, or freq parameter being week, month, quarter, or year
  • groupby() with axis=1, by!=None and level!=None, or by containing any non-pandas hashable labels.
  • groupby_fillna() with downcast parameter
  • groupby_first() with min_count>1
  • groupby_last() with min_count>1
  • groupby_shift() with freq parameter
• Slightly improved the performance of agg, nunique, describe, and related methods on 1-column DataFrame and Series objects.

Bug Fixes

• Fixed a bug in DataFrameGroupBy.agg where func is a list of tuples used to set the names of the output columns.
• Fixed a bug where converting a modin datetime index with a timezone to a numpy array with np.asarray would cause a TypeError.
• Fixed a bug where Series.isin with a Series argument matched index labels instead of the row position.

Improvements

• Add support for the following in faster pandas:
  • groupby.apply
  • groupby.nunique
  • groupby.size
  • concat
  • copy
  • str.isdigit
  • str.islower
  • str.isupper
  • str.istitle
  • str.lower
  • str.upper
  • str.title
  • str.match
  • str.capitalize
  • str.__getitem__
  • str.center
  • str.count
  • str.get
  • str.pad
  • str.len
  • str.ljust
  • str.rjust
  • str.split
  • str.replace
  • str.strip
  • str.lstrip
  • str.rstrip
  • str.translate
  • dt.tz_localize
  • dt.tz_convert
  • dt.ceil
  • dt.round
  • dt.floor
  • dt.normalize
  • dt.month_name
  • dt.day_name
  • dt.strftime
  • dt.dayofweek
  • dt.weekday
  • dt.dayofyear
  • dt.isocalendar
  • rolling.min
  • rolling.max
  • rolling.count
  • rolling.sum
  • rolling.mean
  • rolling.std
  • rolling.var
  • rolling.sem
  • rolling.corr
  • expanding.min
  • expanding.max
  • expanding.count
  • expanding.sum
  • expanding.mean
  • expanding.std
  • expanding.var
  • expanding.sem
  • cumsum
  • cummin
  • cummax
  • groupby.groups
  • groupby.indices
  • groupby.first
  • groupby.last
  • groupby.rank
  • groupby.shift
  • groupby.cumcount
  • groupby.cumsum
  • groupby.cummin
  • groupby.cummax
  • groupby.any
  • groupby.all
  • groupby.unique
  • groupby.get_group
  • groupby.rolling
  • groupby.resample
  • to_snowflake
  • to_snowpark
  • resample.min
  • resample.max
  • resample.count
  • resample.sum
  • resample.mean
  • resample.median
  • resample.std
  • resample.var
  • resample.size
  • resample.first
  • resample.last
  • resample.quantile
  • resample.nunique
• Make faster pandas disabled by default (opt-in instead of opt-out).
• Improve performance of drop_duplicates by avoiding joins when keep!=False in faster pandas.

Release

1.42.0 (2025-10-28)

Snowpark Python API Updates

New Features

• Snowpark python DB-api is now generally available. Access this feature with DataFrameReader.dbapi() to read data from a database table or query into a DataFrame using a DBAPI connection.

Release

1.41.0 (2025-10-23)

Snowpark Python API Updates

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 connection_parameters parameter to DataFrameReader.dbapi() (PuPr) 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 (PuPr) 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 16MB to 128MB 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 support for the dtypes parameter of pd.get_dummies
• Added support for nunique in df.pivot_table, df.agg and other places where aggregate functions can be used.
• Added support for DataFrame.interpolate and Series.interpolate with the "linear", "ffill"/"pad", and "backfill"/bfill" methods. These use the SQL INTERPOLATE_LINEAR, INTERPOLATE_FFILL, and INTERPOLATE_BFILL functions (PuPr).

Improvements

• Improved performance of Series.to_snowflake and pd.to_snowflake(series) for large data by uploading data via a parquet file. You can control the dataset size at which Snowpark pandas switches to parquet with the variable modin.config.PandasToSnowflakeParquetThresholdBytes.
• Enhanced autoswitching functionality from Snowflake to native Pandas for methods with unsupported argument combinations:
  • get_dummies() with dummy_na=True, drop_first=True, or custom dtype parameters
  • cumsum(), cummin(), cummax() with axis=1 (column-wise operations)
  • skew() with axis=1 or numeric_only=False parameters
  • round() with decimals parameter as a Series
  • corr() with method!=pearson parameter
• Set cte_optimization_enabled to True for all Snowpark pandas sessions.
• Add support for the following in faster pandas:
  • isin
  • isna
  • isnull
  • notna
  • notnull
  • str.contains
  • str.startswith
  • str.endswith
  • str.slice
  • dt.date
  • dt.time
  • dt.hour
  • dt.minute
  • dt.second
  • dt.microsecond
  • dt.nanosecond
  • dt.year
  • dt.month
  • dt.day
  • dt.quarter
  • dt.is_month_start
  • dt.is_month_end
  • dt.is_quarter_start
  • dt.is_quarter_end
  • dt.is_year_start
  • dt.is_year_end
  • dt.is_leap_year
  • dt.days_in_month
  • dt.daysinmonth
  • sort_values
  • loc (setting columns)
  • to_datetime
  • rename
  • drop
  • invert
  • duplicated
  • iloc
  • head
  • columns (e.g., df.columns = ["A", "B"])
  • agg
  • min
  • max
  • count
  • sum
  • mean
  • median
  • std
  • var
  • groupby.agg
  • groupby.min
  • groupby.max
  • groupby.count
  • groupby.sum
  • groupby.mean
  • groupby.median
  • groupby.std
  • groupby.var
  • drop_duplicates
• Reuse row count from the relaxed query compiler in get_axis_len.

Bug Fixes

• Fixed a bug where the row count was not getting cached in the ordered dataframe each time count_rows() is called.

Release

1.40.0 (2025-10-02)

Snowpark Python 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 DataFrame.limit() fail if there is parameter binding in the executed SQL when used in non-stored-procedure/udxf environment.
• 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 (PuPr):
  • 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(PuPr) that dbapi will not retry on non-retryable error 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 (PuPr) 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

Dependency Updates

• Updated the supported modin versions to >=0.36.0 and <0.38.0 (was previously >= 0.35.0 and <0.37.0).

New Features

• Added support for DataFrame.query for dataframes with single-level indexes.
• Added support for DataFrameGroupby.__len__ and SeriesGroupBy.__len__.

Improvements

• Hybrid execution mode is now enabled by default. Certain operations on smaller data will now automatically execute in native pandas in-memory. Use from modin.config import AutoSwitchBackend; AutoSwitchBackend.disable() to turn this off and force all execution to occur in Snowflake.
• Added a session parameter pandas_hybrid_execution_enabled to enable/disable hybrid execution as an alternative to using AutoSwitchBackend.
• Removed an unnecessary SHOW OBJECTS query issued from read_snowflake under certain conditions.
• When hybrid execution is enabled, pd.merge, pd.concat, DataFrame.merge, and DataFrame.join may now move arguments to backends other than those among the function arguments.
• Improved performance of DataFrame.to_snowflake and pd.to_snowflake(dataframe) for large data by uploading data via a parquet file. You can control the dataset size at which Snowpark pandas switches to parquet with the variable modin.config.PandasToSnowflakeParquetThresholdBytes.

Release

1.39.1 (2024-09-25)

Snowpark Python 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.

Release

1.39.0 (2025-09-17)

Snowpark Python API Updates

New Features

• Added support for unstructured data engineering in Snowpark, powered by Snowflake AISQL and Cortex functions:
  • DataFrame.ai.complete: Generate per-row LLM completions from prompts built over columns and files.
  • DataFrame.ai.filter: Keep rows where an AI classifier returns TRUE for the given predicate.
  • DataFrame.ai.agg: Reduce a text column into one result using a natural-language task description.
  • RelationalGroupedDataFrame.ai_agg: Perform the same natural-language aggregation per group.
  • DataFrame.ai.classify: Assign single or multiple labels from given categories to text or images.
  • DataFrame.ai.similarity: Compute cosine-based similarity scores between two columns via embeddings.
  • DataFrame.ai.sentiment: Extract overall and aspect-level sentiment from text into JSON.
  • DataFrame.ai.embed: Generate VECTOR embeddings for text or images using configurable models.
  • DataFrame.ai.summarize_agg: Aggregate and produce a single comprehensive summary over many rows.
  • DataFrame.ai.transcribe: Transcribe audio files to text with optional timestamps and speaker labels.
  • DataFrame.ai.parse_document: OCR/layout-parse documents or images into structured JSON.
  • DataFrame.ai.extract: Pull structured fields from text or files using a response schema.
  • DataFrame.ai.count_tokens: Estimate token usage for a given model and input text per row.
  • DataFrame.ai.split_text_markdown_header: Split Markdown into hierarchical header-aware chunks.
  • DataFrame.ai.split_text_recursive_character: Split text into size-bounded chunks using recursive separators.
  • DataFrameReader.file: Create a DataFrame containing all files from a stage as FILE data type for downstream unstructured data processing.
• Added a new datatype YearMonthIntervalType that allows users to create intervals for datetime operations.
• Added a new function interval_year_month_from_parts that allows users to easily create YearMonthIntervalType without using SQL.
• Added a new datatype DayTimeIntervalType that allows users to create intervals for datetime operations.
• Added a new function interval_day_time_from_parts that allows users to easily create DayTimeIntervalType without using SQL.
• Added support for FileOperation.list to list files in a stage with metadata.
• Added support for FileOperation.remove to remove files in a stage.
• Added an option to specify copy_grants for the following DataFrame APIs:
  • create_or_replace_view
  • create_or_replace_temp_view
  • create_or_replace_dynamic_table
• Added a new function snowflake.snowpark.functions.vectorized that allows users to mark a function as vectorized UDF.
• Added support for parameter use_vectorized_scanner in function Session.write_pandas().
• Added support for the following scalar functions in functions.py:
  • getdate
  • getvariable
  • invoker_role
  • invoker_share
  • is_application_role_in_session
  • is_database_role_in_session
  • is_granted_to_invoker_role
  • is_role_in_session
  • localtime
  • systimestamp

Bug Fixes

Deprecations

• Deprecated warnings will be triggered when using snowpark-python with Python 3.9. For more details, please refer to https://docs.snowflake.com/en/developer-guide/python-runtime-support-policy.

Dependency Updates

Improvements

• Unsupported types in DataFrameReader.dbapi(PuPr) are ingested as StringType now.
• Improved error message to list available columns when dataframe cannot resolve given column name.
• Added a new option cacheResult to DataFrameReader.xml that allows users to cache the result of the XML reader to a temporary table after calling xml. It helps improve performance when subsequent operations are performed on the same DataFrame.

Snowpark pandas API Updates

New Features

Improvements

• 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 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 to allow patching functions.ai_complete.