Merge remote-tracking branch 'origin/main' into yixie-SNOW-2203826-flatten-filter-sort

Author: sfc-gh-aling

.github/workflows/create-test-branch-from-release.yml

@@ -1,22 +1,11 @@
 # This workflow automatically creates a test branch from a release tag
 # For example, when release v1.40.0 is published, it creates test-v1.40.0 branch
-# Can also be triggered manually to create a test branch from any existing tag
 
 name: Create Test Branch from Release
 
 on:
   release:
     types: [published]
-  workflow_dispatch:
-    inputs:
-      tag_name:
-        description: 'Tag name to create test branch from (e.g., v1.40.0)'
-        required: true
-        type: string
-      test_branch_name:
-        description: 'Test branch name (optional, defaults to test-<tag_name>)'
-        required: false
-        type: string
 
 permissions:
   contents: write
@@ -29,18 +18,8 @@ jobs:
     - name: Extract tag name
       id: extract_tag
       run: |
-        # Determine tag name based on trigger type
-        if [ "${{ github.event_name }}" = "workflow_dispatch" ]; then
-          TAG_NAME=${{ inputs.tag_name }}
-          if [ -n "${{ inputs.test_branch_name }}" ]; then
-            TEST_BRANCH_NAME=${{ inputs.test_branch_name }}
-          else
-            TEST_BRANCH_NAME="test-${TAG_NAME}"
-          fi
-        else
-          TAG_NAME=${{ github.event.release.tag_name }}
-          TEST_BRANCH_NAME="test-${TAG_NAME}"
-        fi
+        TAG_NAME=${{ github.event.release.tag_name }}
+        TEST_BRANCH_NAME="test-${TAG_NAME}"
 
         echo "tag_name=${TAG_NAME}" >> $GITHUB_OUTPUT
         echo "test_branch_name=${TEST_BRANCH_NAME}" >> $GITHUB_OUTPUT

CHANGELOG.md

@@ -1,6 +1,6 @@
 # Release History
 
-## 1.42.0 (YYYY-MM-DD)
+## 1.43.0 (YYYY-MM-DD)
 
 ### Snowpark Python API Updates
 
@@ -26,13 +26,27 @@
 - 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`.
 
+#### 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`
+
 #### 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`.
 
 #### Improvements
 
 - Add support for the following in faster pandas:
+  - `groupby.apply`
   - `groupby.nunique`
   - `groupby.size`
   - `concat`
@@ -44,9 +58,50 @@
   - `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`  
+  - `rolling.min`
+  - `rolling.max`
+  - `rolling.count`
+  - `rolling.sum`
+  - `rolling.mean`
+  - `rolling.std`
+  - `rolling.var`
+  - `rolling.sem`
+  - `rolling.corr`
 - Make faster pandas disabled by default (opt-in instead of opt-out).
 
+## 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.
+
 ## 1.41.0 (2025-10-23)
 
 ### Snowpark Python API Updates
@@ -143,6 +198,11 @@
   - `skew()` with `axis=1` or `numeric_only=False` parameters
   - `round()` with `decimals` parameter as a Series
   - `corr()` with `method!=pearson` parameter
+  - `df.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`
+  - `shift()` with `freq` parameter
 - Set `cte_optimization_enabled` to True for all Snowpark pandas sessions.
 - Add support for the following in faster pandas:
   - `isin`

recipe/meta.yaml

@@ -1,5 +1,5 @@
 {% set name = "snowflake-snowpark-python" %}
-{% set version = "1.41.0" %}
+{% set version = "1.42.0" %}
 {% set noarch_build = (os.environ.get('SNOWFLAKE_SNOWPARK_PYTHON_NOARCH_BUILD', 'false')) == 'true' %}
 {% set build_number = os.environ.get('SNOWFLAKE_SNOWPARK_PYTHON_BUILD_NUMBER', 0) %}
 

src/snowflake/snowpark/modin/plugin/_internal/indexing_utils.py

@@ -962,7 +962,7 @@ def get_valid_col_pos_list_from_columns(
 
         # convert float like keys to integers
         elif not is_integer_dtype(pos_array.dtype):
-            assert is_float_dtype(
+            assert pos_array.size == 0 or is_float_dtype(
                 pos_array.dtype
             ), "list-like key must be list of int or float"
             pos_list = pos_array.astype(int)

src/snowflake/snowpark/modin/plugin/_internal/pivot_utils.py

@@ -1866,3 +1866,58 @@ def generate_column_prefix_groupings(
         )
 
     return list(zip(margin_data_column_prefixes, margin_data_column_groupings))
+
+
+def check_pivot_table_unsupported_args(args: dict) -> Optional[str]:
+    """
+    Validate pivot_table arguments for unsupported conditions.
+
+    This helper function checks various argument combinations that are not yet
+    supported by Snowpark pandas pivot_table implementation.
+
+    Args:
+        args : dictionary of arguments passed to pivot_table
+
+    Returns:
+        Error message if an unsupported condition is found, None otherwise
+    """
+    # Check if index argument is a string or list of strings
+    index = args.get("index")
+    if (
+        index is not None
+        and not isinstance(index, str)
+        and not all(isinstance(v, str) for v in index)
+        and None not in index
+    ):
+        return "index argument should be a string or a list of strings"
+
+    # Check if columns argument is a string or list of strings
+    columns = args.get("columns")
+    if (
+        columns is not None
+        and not isinstance(columns, str)
+        and not all(isinstance(v, str) for v in columns)
+        and None not in columns
+    ):
+        return "columns argument should be a string or a list of strings"
+
+    # Check if values argument is a string or list of strings
+    values = args.get("values")
+    if (
+        values is not None
+        and not isinstance(values, str)
+        and not all(isinstance(v, str) for v in values)
+        and None not in values
+    ):
+        return "values argument should be a string or a list of strings"
+
+    # Check for dictionary aggfunc with non-string functions when index is None
+    aggfunc = args.get("aggfunc")
+    if (
+        isinstance(aggfunc, dict)
+        and any(not isinstance(af, str) for af in aggfunc.values())
+        and args.get("index") is None
+    ):
+        return "dictionary aggfunc with non-string aggregation functions is not yet supported for pivot_table when index is None"
+
+    return None