Bump snowflake-snowpark-python from 1.26.0 to 1.34.0 in /python-wrapper

[dependabot]

Bumps snowflake-snowpark-python from 1.26.0 to 1.34.0.

Release notes

Sourced from snowflake-snowpark-python's releases.

Release

1.34.0 (2025-07-15)

Snowpark Python API Updates

New Features

• Added a new option TRY_CAST to DataFrameReader. When TRY_CAST is True columns are wrapped in a TRY_CAST statement rather than 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 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 will 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 may 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 an SQL compilation error corresponds to. Enable it using snowflake.snowpark.context.configure_development_features(). This feature also depends on AST collection to be enabled in the session which can be done using session.ast_enabled = True.
• Set enforce_ordering=True when calling to_snowpark_pandas() 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 (PrPr) 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

Bug Fixes

• Fixed a bug when processing windowed functions that lead to incorrect indexing in results.
• When a scalar numeric is passed to fillna we will ignore non-numeric columns instead of producing an error.

Snowpark pandas API Updates

New Features

• Added support for DataFrame.to_excel and Series.to_excel.
• Added support for pd.read_feather, pd.read_orc, and pd.read_stata.
• Added support for pd.explain_switch() to return debugging information on hybrid execution decisions.
• Support pd.read_snowflake when the global modin backend is Pandas.
• Added support for pd.to_dynamic_table, pd.to_iceberg, and pd.to_view.

Improvements

... (truncated)

Changelog

Sourced from snowflake-snowpark-python's changelog.

1.34.0 (2025-07-15)

Snowpark Python API Updates

New Features

• Added a new option TRY_CAST to DataFrameReader. When TRY_CAST is True columns are wrapped in a TRY_CAST statement rather than 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 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 will 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 may 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 an SQL compilation error corresponds to. Enable it using snowflake.snowpark.context.configure_development_features(). This feature also depends on AST collection to be enabled in the session which can be done using session.ast_enabled = True.
• Set enforce_ordering=True when calling to_snowpark_pandas() 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 (PrPr) 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

Bug Fixes

• Fixed a bug when processing windowed functions that lead to incorrect indexing in results.
• When a scalar numeric is passed to fillna we will ignore non-numeric columns instead of producing an error.

Snowpark pandas API Updates

New Features

• Added support for DataFrame.to_excel and Series.to_excel.
• Added support for pd.read_feather, pd.read_orc, and pd.read_stata.
• Added support for pd.explain_switch() to return debugging information on hybrid execution decisions.
• Support pd.read_snowflake when the global modin backend is Pandas.
• Added support for pd.to_dynamic_table, pd.to_iceberg, and pd.to_view.

Improvements

• Added modin telemetry on API calls and hybrid engine switches.

... (truncated)

Commits

• 9c8fc52 Update date in CHANGELOG.md
• 5a0a625 Revert "Merge branch 'main' into release-v1.34.0"
• 4b41b45 Revert "Update date in CHANGELOG.md"
• 9f1cd19 Update date in CHANGELOG.md
• 61c49de Merge branch 'main' into release-v1.34.0
• ea884e6 SNOW-2192236: Add schema inference for extern stages (#3542)
• 6b77dfc NO-SNOW: Fix file cleanup in test_read_json_empty_file (#3549)
• d57f40c SNOW-2002725: Add support for DataFrame.boxplot (#3532)
• d91b13b SNOW-2202094: Remove references to pandas versions in docstrings (#3545)
• 9e3d399 Using regex for join tests to fix flakiness (#3546)
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

• @dependabot rebase will rebase this PR
• @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
• @dependabot merge will merge this PR after your CI passes on it
• @dependabot squash and merge will squash and merge this PR after your CI passes on it
• @dependabot cancel merge will cancel a previously requested merge and block automerging
• @dependabot reopen will reopen this PR if it is closed
• @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
• @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
• @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)

[dependabot]

Superseded by #203.