buid: add pins for Snowflake + small refactoring (#1860)

Author: anakin87

.github/workflows/snowflake.yml

@@ -60,9 +60,16 @@ jobs:
       - name: Run tests
         run: hatch run cov-retry
 
+      - name: Run unit tests with lowest direct dependencies
+        run: |
+          hatch run uv pip compile pyproject.toml --resolution lowest-direct --output-file requirements_lowest_direct.txt
+          hatch run uv pip install -r requirements_lowest_direct.txt
+          hatch run test -m "not integration"
+
       - name: Nightly - run unit tests with Haystack main branch
         if: github.event_name == 'schedule'
         run: |
+          hatch env prune
           hatch run uv pip install git+https://github.com/deepset-ai/haystack.git@main
           hatch run cov-retry -m "not integration"
 

integrations/snowflake/pyproject.toml

@@ -24,7 +24,7 @@ classifiers = [
   "Programming Language :: Python :: Implementation :: CPython",
   "Programming Language :: Python :: Implementation :: PyPy",
 ]
-dependencies = ["haystack-ai", "adbc_driver_snowflake>=1.4.0", "polars>=1.23.0", "pyarrow>=19.0.1", "pandas"]
+dependencies = ["haystack-ai", "adbc_driver_snowflake>=1.4.0", "polars[pandas,pyarrow]>=1.23.0"]
 
 [project.urls]
 Documentation = "https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/snowflake#readme"

integrations/snowflake/src/haystack_integrations/components/retrievers/snowflake/snowflake_table_retriever.py

@@ -3,13 +3,10 @@
 # SPDX-License-Identifier: Apache-2.0
 from typing import Any, Dict, Optional
 
-import pandas as pd
+import polars as pl
 from haystack import component, default_from_dict, default_to_dict, logging
-from haystack.lazy_imports import LazyImport
 from haystack.utils import Secret, deserialize_secrets_inplace
-
-with LazyImport("Run 'pip install polars>=1.23.0'") as polars_import:
-    import polars as pl
+from pandas import DataFrame
 
 logger = logging.getLogger(__name__)
 
@@ -151,15 +148,14 @@ def _snowflake_uri_constructor(self) -> str:
         return uri
 
     @staticmethod
-    def _polars_to_md(data: "pl.DataFrame") -> str:
+    def _polars_to_md(data: pl.DataFrame) -> str:
         """
         Converts a Polars DataFrame to a Markdown-formatted string.
         Uses Polars' built-in table formatting for efficient conversion.
 
         :param data: The Polars DataFrame to convert.
         :returns: A Markdown-formatted string if `data` is not empty; otherwise, an empty string.
         """
-        polars_import.check()  # Ensure polars is imported
         if data.is_empty():
             return ""  # No markdown for empty DataFrame.
 
@@ -184,9 +180,9 @@ def _empty_response() -> Dict[str, Any]:
             - `dataframe`: An empty Pandas DataFrame.
             - `table`: An empty Markdown string.
         """
-        return {"dataframe": pd.DataFrame(), "table": ""}
+        return {"dataframe": DataFrame(), "table": ""}
 
-    @component.output_types(dataframe=pd.DataFrame, table=str)
+    @component.output_types(dataframe=DataFrame, table=str)
     def run(self, query: str, return_markdown: Optional[bool] = None) -> Dict[str, Any]:
         """
         Executes a SQL query against a Snowflake database using ADBC and Polars.