diff --git a/.semversioner/next-release/patch-20250417174516646520.json b/.semversioner/next-release/patch-20250417174516646520.json
new file mode 100644
index 0000000000..bdc2dfa7ed
--- /dev/null
+++ b/.semversioner/next-release/patch-20250417174516646520.json
@@ -0,0 +1,4 @@
+{
+  "type": "patch",
+  "description": "SQL server storage support for indexing"
+}
diff --git a/graphrag/config/defaults.py b/graphrag/config/defaults.py
index 3977ed5820..e643fd9d4f 100644
--- a/graphrag/config/defaults.py
+++ b/graphrag/config/defaults.py
@@ -324,6 +324,10 @@ class OutputDefaults:
     container_name: None = None
     storage_account_blob_url: None = None
     cosmosdb_account_url: None = None
+    database_name: None = None
+    database_server_name: None = None
+    autogenerate_tables: None = None
+    client_id: None = None
 
 
 @dataclass
diff --git a/graphrag/config/enums.py b/graphrag/config/enums.py
index e382bf1a44..1c8e1705a4 100644
--- a/graphrag/config/enums.py
+++ b/graphrag/config/enums.py
@@ -66,6 +66,8 @@ class OutputType(str, Enum):
     """The blob output type."""
     cosmosdb = "cosmosdb"
     """The cosmosdb output type"""
+    sqlserver = "sqlserver"
+    """The sqlserver output type"""
 
     def __repr__(self):
         """Get a string representation."""
diff --git a/graphrag/config/models/output_config.py b/graphrag/config/models/output_config.py
index e38b137d0f..9bbf6bda4b 100644
--- a/graphrag/config/models/output_config.py
+++ b/graphrag/config/models/output_config.py
@@ -36,3 +36,19 @@ class OutputConfig(BaseModel):
         description="The cosmosdb account url to use.",
         default=graphrag_config_defaults.output.cosmosdb_account_url,
     )
+    database_name: str | None = Field(
+        description="The database name to use for SQL Server.",
+        default=graphrag_config_defaults.output.database_name,
+    )
+    database_server_name: str | None = Field(
+        description="The database server name to use for SQL Server.",
+        default=graphrag_config_defaults.output.database_server_name,
+    )
+    autogenerate_tables: bool | None = Field(
+        description="Whether to automatically generate tables in SQL Server.",
+        default=graphrag_config_defaults.output.autogenerate_tables,
+    )
+    client_id: str | None = Field(
+        description="The client ID for a User-Assigned Managed Identity (SQL Server).",
+        default=graphrag_config_defaults.output.client_id,
+    )
diff --git a/graphrag/index/operations/summarize_communities/graph_context/context_builder.py b/graphrag/index/operations/summarize_communities/graph_context/context_builder.py
index e171ce40b6..6eb52ea788 100644
--- a/graphrag/index/operations/summarize_communities/graph_context/context_builder.py
+++ b/graphrag/index/operations/summarize_communities/graph_context/context_builder.py
@@ -44,7 +44,6 @@ def build_local_context(
 ):
     """Prep communities for report generation."""
     levels = get_levels(nodes, schemas.COMMUNITY_LEVEL)
-
     dfs = []
 
     for level in progress_iterable(levels, callbacks.progress, len(levels)):
diff --git a/graphrag/storage/factory.py b/graphrag/storage/factory.py
index 8a6e0df4d6..5282b3ee27 100644
--- a/graphrag/storage/factory.py
+++ b/graphrag/storage/factory.py
@@ -12,6 +12,7 @@
 from graphrag.storage.cosmosdb_pipeline_storage import create_cosmosdb_storage
 from graphrag.storage.file_pipeline_storage import create_file_storage
 from graphrag.storage.memory_pipeline_storage import MemoryPipelineStorage
+from graphrag.storage.sql_server_pipeline_storage import create_sql_server_storage
 
 if TYPE_CHECKING:
     from graphrag.storage.pipeline_storage import PipelineStorage
@@ -45,6 +46,8 @@ def create_storage(
                 return create_cosmosdb_storage(**kwargs)
             case OutputType.file:
                 return create_file_storage(**kwargs)
+            case OutputType.sqlserver:
+                return create_sql_server_storage(**kwargs)
             case OutputType.memory:
                 return MemoryPipelineStorage()
             case _:
diff --git a/graphrag/storage/sql_server_pipeline_storage.py b/graphrag/storage/sql_server_pipeline_storage.py
new file mode 100644
index 0000000000..5426ab95c5
--- /dev/null
+++ b/graphrag/storage/sql_server_pipeline_storage.py
@@ -0,0 +1,519 @@
+# Copyright (c) 2024 Microsoft Corporation.
+# Licensed under the MIT License
+
+"""Azure SQL Server implementation of PipelineStorage."""
+
+import json
+import logging
+import re
+import struct
+from collections.abc import Iterator
+from io import BytesIO
+from typing import Any
+
+import numpy as np
+import pandas as pd
+import pyodbc
+from azure.identity import DefaultAzureCredential
+from pyodbc import Connection
+
+from graphrag.logger.base import ProgressLogger
+from graphrag.logger.progress import Progress
+from graphrag.storage.pipeline_storage import (
+    PipelineStorage,
+    get_timestamp_formatted_with_local_tz,
+)
+
+log = logging.getLogger(__name__)
+
+
+class SQLServerPipelineStorage(PipelineStorage):
+    """Azure SQL Server implementation of PipelineStorage."""
+
+    _database_name: str
+    _database_server_name: str
+    _local_connection_string: str
+    _autogenerate_tables: bool
+    _connection: Connection
+
+    def __init__(
+        self,
+        database_name: str,
+        database_server_name: str,
+        autogenerate_tables: bool = True,
+        client_id: str | None = None,
+    ):
+        """Initialize connection to Azure SQL Server."""
+        # Currently, the SQL Server storage requires that the database and tables are created before indexing
+        # This initialization establishes a connection using the pyodbc SQL driver
+        self._database_name = database_name
+        self._database_server_name = database_server_name
+        self._autogenerate_tables = autogenerate_tables
+
+        # Use password-less authentication for the db server
+        self._local_connection_string = f"Driver={{ODBC Driver 18 for SQL Server}};Server=tcp:{database_server_name}.database.windows.net,1433;Database={database_name};Encrypt=yes;TrustServerCertificate=no;Connection Timeout=30;LongAsMax=yes"
+        credential = DefaultAzureCredential()
+
+        # These connection options are recommended by Microsoft
+        token_bytes = credential.get_token(
+            "https://database.windows.net/.default"
+        ).token.encode("UTF-16-LE")
+        token_struct = struct.pack(
+            f"<I{len(token_bytes)}s", len(token_bytes), token_bytes
+        )
+        sql_copt_ss_access_token = 1256
+
+        # Create initial connection to database
+        connection = pyodbc.connect(
+            self._local_connection_string,
+            attrs_before={sql_copt_ss_access_token: token_struct},
+        )
+        self._connection = connection
+        log.info(
+            "Creating connection to SQL Server database e%s on server %s",
+            database_name,
+            database_server_name,
+        )
+
+        if not self._autogenerate_tables:
+            self.create_tables()
+
+    def create_tables(self) -> None:
+        """Create tables in SQL Server.
+
+        If autogenerate_tables is not enabled, this method will manually create tables for all parquet outputs using a predefined schema.
+        """
+        # TODO: Currently, most parquet outputs are written to storage and updated multiple times throughout the indexing pipeline, making it difficult to start with a predefined schema.
+        # In a future PR, figure out how to use the SQL Server storage with a predefined table schema.
+        msg = "SQL Server storage does not yet support manually predefined table creation."
+        raise NotImplementedError(msg)
+
+    def find(
+        self,
+        file_pattern: re.Pattern[str],
+        base_dir: str | None = None,
+        progress: ProgressLogger | None = None,
+        file_filter: dict[str, Any] | None = None,
+        max_count=-1,
+    ) -> Iterator[tuple[str, dict[str, Any]]]:
+        """Find tables in SQL Server matching a file pattern.
+
+        This method lists available tables that match the pattern (table names in SQL Server).
+
+        Args:
+            file_pattern: The regex pattern to match against table names
+            base_dir: Not used for SQL Server
+            progress: Optional progress logger
+            file_filter: Optional filter dictionary
+            max_count: Maximum number of results to return
+
+        Returns
+        -------
+            Iterator of tuples with table name and match groups
+        """
+        log.info(
+            "Searching SQL Server database %s for tables matching %s",
+            self._database_name,
+            file_pattern.pattern,
+        )
+
+        def item_filter(item: dict[str, Any]) -> bool:
+            if file_filter is None:
+                return True
+            return all(
+                re.search(value, item.get(key, ""))
+                for key, value in file_filter.items()
+            )
+
+        try:
+            cursor = self._connection.cursor()
+            cursor.execute(
+                "SELECT TABLE_NAME FROM INFORMATION_SCHEMA.TABLES WHERE TABLE_TYPE = 'BASE TABLE'"
+            )
+
+            tables = [row[0] for row in cursor.fetchall()]
+            num_total = len(tables)
+            num_loaded = 0
+            num_filtered = 0
+
+            if num_total == 0:
+                return
+
+            for table_name in tables:
+                match = file_pattern.search(table_name)
+                if match:
+                    group = match.groupdict()
+                    if item_filter(group):
+                        yield (table_name, group)
+                        num_loaded += 1
+                        if max_count > 0 and num_loaded >= max_count:
+                            break
+                    else:
+                        num_filtered += 1
+                else:
+                    num_filtered += 1
+
+                if progress is not None:
+                    progress(
+                        _create_progress_status(num_loaded, num_filtered, num_total)
+                    )
+
+        except Exception:
+            log.exception("An error occurred while searching for tables in SQL Server")
+
+    async def get(
+        self, key: str, as_bytes: bool | None = None, encoding: str | None = None
+    ) -> Any:
+        """Get data from SQL Server.
+
+        For parquet files, this will query all rows from the table corresponding to the key.
+
+        Args:
+            key: The name of the table/file to retrieve
+            as_bytes: If True, returns parquet bytes for DataFrame data
+            encoding: Not used for SQL Server
+
+        Returns
+        -------
+            Parquet bytes or JSON string representation of the data
+        """
+        # Only retrieve table contents for parquet files
+        if key.endswith(".parquet") and as_bytes:
+            try:
+                table_name = key.split(".")[0]
+                query = f"SELECT * FROM [{table_name}]"  # noqa: S608
+
+                cursor = self._connection.cursor()
+                cursor.execute(query)
+
+                columns = [column[0] for column in cursor.description]
+                rows = cursor.fetchall()
+
+                # Construct a dataframe from the query results
+                data = []
+                for row in rows:
+                    processed_row = []
+                    for val in row:
+                        if val is None:
+                            processed_row.append(val)
+                        elif isinstance(val, bytearray):
+                            processed_row.append(bytes(val))
+                        elif (
+                            isinstance(val, str)
+                            and val.startswith("[")
+                            and val.endswith("]")
+                        ):
+                            # Parse strings that are fetched as serialized lists
+                            import ast
+
+                            try:
+                                parsed_val = ast.literal_eval(val)
+                                if isinstance(parsed_val, list):
+                                    processed_row.append(parsed_val)
+                                else:
+                                    processed_row.append(val)
+                            except (SyntaxError, ValueError):
+                                processed_row.append(val)
+                        else:
+                            processed_row.append(val)
+                    data.append(processed_row)
+
+                # Create DataFrame from processed data
+                data_frame = pd.DataFrame(data, columns=np.array(columns))
+                buffer = BytesIO()
+                data_frame.to_parquet(buffer)
+                buffer.seek(0)
+
+                log.info(
+                    "Successfully fetched table contents for %s from SQL Server", key
+                )
+                return buffer.read()
+            except Exception:
+                log.exception("Error reading data %s", key)
+                return None
+        else:
+            log.warning(
+                "Attempted to call get() on SQL Server storage with non-parquet key %s. Skipping...",
+                key,
+            )
+            return None
+        
+    def _get_embeddings_dimension(self, df: pd.DataFrame) -> int:
+        """Get the dimension of the embeddings column in the DataFrame.
+
+        Args:
+            df: The DataFrame containing the embeddings column
+
+        Returns
+        -------
+            The dimension of the embeddings column
+        """
+        if "embedding" in df.columns:
+            embedding_column = df["embedding"].iloc[0]
+            if isinstance(embedding_column, list):
+                return len(embedding_column)
+            if isinstance(embedding_column, np.ndarray):
+                return embedding_column.shape[0]
+        return 0
+
+    async def set(self, key: str, value: Any, encoding: str | None = None) -> None:
+        """Set data in SQL Server.
+
+        For parquet files, this creates or replaces a table with the DataFrame data.
+
+        Args:
+            key: The table/file name
+            value: Either bytes (parquet) or string (JSON) (only parquet files are written to SQL Server)
+            encoding: Not used for SQL Server
+        """
+        try:
+            # Only store parquet file data
+            if isinstance(value, bytes) and key.endswith(".parquet"):
+                table_name = key.split(".")[0]
+                data_frame = pd.read_parquet(BytesIO(value))
+
+                # Automatically build CREATE TABLE statement based on DataFrame columns
+                if self._autogenerate_tables:
+                    cursor = self._connection.cursor()
+                    columns = []
+                    for col_name, dtype in zip(
+                        data_frame.columns, data_frame.dtypes, strict=False
+                    ):
+                        sql_type = "NVARCHAR(MAX)"  # Default type
+
+                        # Map pandas dtypes to SQL Server types
+                        if col_name == "embedding":
+                            # If we are writing the vector embeddings dataframe, set the embedding column to VECTOR
+                            dim = self._get_embeddings_dimension(data_frame)
+                            sql_type = f"VECTOR({dim})" if dim != 0 else "VECTOR(1536)"  # GraphRAG default embedding dimension
+                        elif pd.api.types.is_integer_dtype(dtype):
+                            sql_type = "BIGINT"
+                        elif pd.api.types.is_float_dtype(dtype):
+                            sql_type = "FLOAT"
+                        elif pd.api.types.is_bool_dtype(dtype):
+                            sql_type = "BIT"
+                        elif pd.api.types.is_datetime64_dtype(dtype):
+                            sql_type = "DATETIME2"
+
+                        columns.append(f"[{col_name}] {sql_type}")
+
+                    cursor.execute(
+                        f"IF OBJECT_ID('{table_name}', 'U') IS NOT NULL DROP TABLE [{table_name}]"
+                    )
+                    create_table_sql = (
+                        f"CREATE TABLE [{table_name}] ({', '.join(columns)})"
+                    )
+                    log.info(
+                        "Automatically generated table: %s with columns: %s",
+                        table_name,
+                        columns,
+                    )
+                    cursor.execute(create_table_sql)
+                    self._connection.commit()
+
+                # Insert parquet data into SQL server
+                num_rows = len(data_frame)
+                placeholders = ", ".join([
+                    "?" for _ in range(len(data_frame.columns))
+                ])
+                column_names = ", ".join([
+                    f"[{col}]" for col in data_frame.columns
+                ])
+                insert_sql = f"INSERT INTO [{table_name}] ({column_names}) VALUES ({placeholders})"  # noqa: S608
+                log.info(
+                    "Inserting %s rows into table %s", num_rows, table_name
+                )
+
+                # Use a row-wise cursor loop for small tables
+                if num_rows < 1000:
+                    cursor = self._connection.cursor()
+                    for _, row in data_frame.iterrows():
+                        try:
+                            # Handle various value types, converting complex types to strings
+                            values = []
+                            for val in row:
+                                if isinstance(val, np.ndarray):
+                                    values.append(json.dumps(val.tolist()))
+                                elif isinstance(val, list):
+                                    values.append(json.dumps(val))
+                                elif pd.isna(val):
+                                    values.append(None)
+                                else:
+                                    values.append(val)
+                            cursor.execute(insert_sql, values)
+                        except Exception:  # noqa: BLE001
+                            log.info(
+                                "Error inserting row %s into table: %s, skipping...",
+                                row.to_dict(),
+                                table_name,
+                            )
+                            continue
+                # For large tables, use a bulk insert strategy
+                else:
+                    cursor = self._connection.cursor()
+                    cursor.fast_executemany = True
+                    bulk_values = []
+                    for row in data_frame.itertuples(index=False):
+                        # Handle various value types, converting complex types to strings
+                        values = []
+                        for val in row:
+                            if isinstance(val, np.ndarray):
+                                values.append(json.dumps(val.tolist()))
+                            elif isinstance(val, list):
+                                values.append(json.dumps(val))
+                            elif pd.isna(val):
+                                values.append(None)
+                            else:
+                                values.append(val)
+                        bulk_values.append(values)
+                    cursor.executemany(insert_sql, bulk_values)
+                self._connection.commit()
+                log.info("Successfully stored %s in SQL Server", key)
+            else:
+                log.warning(
+                    "Attempted to call set() on SQL Server storage with non-parquet key %s. Skipping...",
+                    key,
+                )
+        except Exception:
+            self._connection.commit()
+            log.exception("Error writing data %s: %s.", key)
+
+    async def has(self, key: str) -> bool:
+        """Check if a table/file exists in SQL Server.
+
+        Args:
+            key: The table/file name to check
+
+        Returns
+        -------
+            True if the table or metadata entry exists
+        """
+        try:
+            # Only check existence for parquet files, otherwise return False
+            if key.endswith(".parquet"):
+                cursor = self._connection.cursor()
+                table_name = key.split(".")[0]
+                cursor.execute(
+                    "SELECT 1 FROM INFORMATION_SCHEMA.TABLES WHERE TABLE_NAME = ?",
+                    table_name,
+                )
+                return cursor.fetchone() is not None
+        except Exception:
+            log.exception("Error checking existence of %s: %s", key)
+            return False
+        else:
+            log.warning(
+                "Attempted to call has() on SQL Server storage with non-parquet key %s",
+                key,
+            )
+            return False
+
+    async def delete(self, key: str) -> None:
+        """Delete a table/file from SQL Server.
+
+        Args:
+            key: The table/file name to delete
+        """
+        # Only delete parquet files
+        if key.endswith(".parquet"):
+            try:
+                table_name = key.split(".")[0]
+                cursor = self._connection.cursor()
+                cursor.execute(
+                    f"IF OBJECT_ID('{table_name}', 'U') IS NOT NULL DROP TABLE [{table_name}]"
+                )
+                self._connection.commit()
+                log.info("Successfully deleted %s from SQL Server", key)
+            except Exception:
+                self._connection.rollback()
+                log.exception("Error deleting %s: %s", key)
+        else:
+            log.warning(
+                "Attempted to call delete() on SQL Server storage with non-parquet key %s. Skipping...",
+                key,
+            )
+
+    async def clear(self) -> None:
+        """Clear the pipeline storage."""
+        msg = "SQL Server storage does not yet support the clear operation."
+        raise NotImplementedError(msg)
+
+    def child(self, name: str | None) -> "PipelineStorage":
+        """Create a child pipeline storage."""
+        return self
+
+    def keys(self) -> list[str]:
+        """List all keys in the storage."""
+        msg = "SQL Server storage does not yet support listing keys."
+        raise NotImplementedError(msg)
+
+    async def get_creation_date(self, key: str) -> str:
+        """Get the creation date for a table or metadata entry.
+
+        Args:
+            key: The table/file name
+
+        Returns
+        -------
+            Formatted timestamp of creation date or empty string
+        """
+        try:
+            # Only get creation date for parquet files
+            if key.endswith(".parquet"):
+                cursor = self._connection.cursor()
+                table_name = key.split(".")[0]
+                cursor.execute(
+                    """
+                    SELECT create_date
+                    FROM sys.tables t
+                    JOIN sys.objects o ON t.object_id = o.object_id
+                    WHERE t.name = ?
+                """,
+                    table_name,
+                )
+                row = cursor.fetchone()
+                if row:
+                    log.info("Successfully retrieved creation date for %s", key)
+                    return get_timestamp_formatted_with_local_tz(row[0])
+                return ""
+        except Exception:
+            log.exception("Error getting creation date for %s: %s", key)
+            return ""
+        else:
+            log.warning(
+                "Attempted to call get_creation_date() on SQL Server storage with non-parquet key %s",
+                key,
+            )
+            return ""
+
+
+def create_sql_server_storage(**kwargs: Any) -> PipelineStorage:
+    """Create a SQLServer storage instance."""
+    log.info("Creating SQL Server storage")
+    database_name = kwargs.get("database_name")
+    database_server_name = kwargs.get("database_server_name")
+    autogenerate_tables = kwargs.get("autogenerate_tables", True)
+    connection_string = kwargs.get("connection_string")
+    client_id = kwargs.get("client_id")
+    if connection_string:
+        msg = "SQL Server storage does not support connection string authentication. Use managed-identities instead."
+        raise ValueError(msg)
+    if not database_name or not database_server_name:
+        msg = "Both 'database_name' and 'database_server_name' must be provided."
+        raise ValueError(msg)
+    return SQLServerPipelineStorage(
+        database_name=database_name,
+        database_server_name=database_server_name,
+        autogenerate_tables=autogenerate_tables,
+        client_id=client_id,
+    )
+
+
+def _create_progress_status(
+    num_loaded: int, num_filtered: int, num_total: int
+) -> Progress:
+    return Progress(
+        total_items=num_total,
+        completed_items=num_loaded + num_filtered,
+        description=f"{num_loaded} files loaded ({num_filtered} filtered)",
+    )
diff --git a/poetry.lock b/poetry.lock
index 397330cb52..fb0a1e8bb2 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
 [[package]]
 name = "aiofiles"
@@ -57,18 +57,15 @@ trio = ["trio (>=0.26.1)"]
 
 [[package]]
 name = "anytree"
-version = "2.12.1"
+version = "2.13.0"
 description = "Powerful and Lightweight Python Tree Data Structure with various plugins"
 optional = false
-python-versions = ">=3.7.2,<4"
+python-versions = "<4.0,>=3.9.2"
 files = [
-    {file = "anytree-2.12.1-py3-none-any.whl", hash = "sha256:5ea9e61caf96db1e5b3d0a914378d2cd83c269dfce1fb8242ce96589fa3382f0"},
-    {file = "anytree-2.12.1.tar.gz", hash = "sha256:244def434ccf31b668ed282954e5d315b4e066c4940b94aff4a7962d85947830"},
+    {file = "anytree-2.13.0-py3-none-any.whl", hash = "sha256:4cbcf10df36b1f1cba131b7e487ff3edafc9d6e932a3c70071b5b768bab901ff"},
+    {file = "anytree-2.13.0.tar.gz", hash = "sha256:c9d3aa6825fdd06af7ebb05b4ef291d2db63e62bb1f9b7d9b71354be9d362714"},
 ]
 
-[package.dependencies]
-six = "*"
-
 [[package]]
 name = "appnope"
 version = "0.1.4"
@@ -237,13 +234,13 @@ files = [
 
 [[package]]
 name = "azure-core"
-version = "1.32.0"
+version = "1.33.0"
 description = "Microsoft Azure Core Library for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "azure_core-1.32.0-py3-none-any.whl", hash = "sha256:eac191a0efb23bfa83fddf321b27b122b4ec847befa3091fa736a5c32c50d7b4"},
-    {file = "azure_core-1.32.0.tar.gz", hash = "sha256:22b3c35d6b2dae14990f6c1be2912bf23ffe50b220e708a28ab1bb92b1c730e5"},
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 ]
 
 [package.dependencies]
@@ -253,6 +250,7 @@ typing-extensions = ">=4.6.0"
 
 [package.extras]
 aio = ["aiohttp (>=3.0)"]
+tracing = ["opentelemetry-api (>=1.26,<2.0)"]
 
 [[package]]
 name = "azure-cosmos"
@@ -306,13 +304,13 @@ typing-extensions = ">=4.6.0"
 
 [[package]]
 name = "azure-storage-blob"
-version = "12.25.0"
+version = "12.25.1"
 description = "Microsoft Azure Blob Storage Client Library for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "azure_storage_blob-12.25.0-py3-none-any.whl", hash = "sha256:a38e18bf10258fb19028f343db0d3d373280c6427a619c98c06d76485805b755"},
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 ]
 
 [package.dependencies]
@@ -338,6 +336,62 @@ files = [
 [package.extras]
 dev = ["backports.zoneinfo", "freezegun (>=1.0,<2.0)", "jinja2 (>=3.0)", "pytest (>=6.0)", "pytest-cov", "pytz", "setuptools", "tzdata"]
 
+[[package]]
+name = "backports-datetime-fromisoformat"
+version = "2.0.3"
+description = "Backport of Python 3.11's datetime.fromisoformat"
+optional = false
+python-versions = ">3"
+files = [
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+]
+
 [[package]]
 name = "backrefs"
 version = "5.8"
@@ -376,13 +430,13 @@ test-tox-coverage = ["coverage (>=5.5)"]
 
 [[package]]
 name = "beautifulsoup4"
-version = "4.13.3"
+version = "4.13.4"
 description = "Screen-scraping library"
 optional = false
 python-versions = ">=3.7.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -416,40 +470,39 @@ css = ["tinycss2 (>=1.1.0,<1.5)"]
 
 [[package]]
 name = "blis"
-version = "1.2.0"
+version = "1.2.1"
 description = "The Blis BLAS-like linear algebra library, as a self-contained C-extension."
 optional = false
 python-versions = "<3.13,>=3.6"
 files = [
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 [package.dependencies]
@@ -803,80 +859,80 @@ numpy = ">=1.23"
 [package.extras]
 bokeh = ["bokeh", "selenium"]
 docs = ["furo", "sphinx (>=7.2)", "sphinx-copybutton"]
-mypy = ["contourpy[bokeh,docs]", "docutils-stubs", "mypy (==1.11.1)", "types-Pillow"]
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 test = ["Pillow", "contourpy[test-no-images]", "matplotlib"]
 test-no-images = ["pytest", "pytest-cov", "pytest-rerunfailures", "pytest-xdist", "wurlitzer"]
 
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 [[package]]
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 ]
 
 [package.extras]
@@ -1407,15 +1463,16 @@ umap-learn = ">=0.5.6,<0.6.0"
 
 [[package]]
 name = "graspologic-native"
-version = "1.2.3"
+version = "1.2.5"
 description = "Python native companion module to the graspologic library"
 optional = false
 python-versions = "<3.14,>=3.8"
 files = [
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 ]
 
 [[package]]
@@ -1431,13 +1488,13 @@ files = [
 
 [[package]]
 name = "httpcore"
-version = "1.0.7"
+version = "1.0.8"
 description = "A minimal low-level HTTP client."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -1551,13 +1608,13 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio
 
 [[package]]
 name = "ipython"
-version = "8.34.0"
+version = "8.35.0"
 description = "IPython: Productive Interactive Computing"
 optional = false
 python-versions = ">=3.10"
 files = [
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 ]
 
 [package.dependencies]
@@ -1585,25 +1642,25 @@ notebook = ["ipywidgets", "notebook"]
 parallel = ["ipyparallel"]
 qtconsole = ["qtconsole"]
 test = ["packaging", "pickleshare", "pytest", "pytest-asyncio (<0.22)", "testpath"]
-test-extra = ["curio", "ipython[test]", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.23)", "pandas", "trio"]
+test-extra = ["curio", "ipython[test]", "jupyter_ai", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.23)", "pandas", "trio"]
 
 [[package]]
 name = "ipywidgets"
-version = "8.1.5"
+version = "8.1.6"
 description = "Jupyter interactive widgets"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
 comm = ">=0.1.3"
 ipython = ">=6.1.0"
-jupyterlab-widgets = ">=3.0.12,<3.1.0"
+jupyterlab_widgets = ">=3.0.14,<3.1.0"
 traitlets = ">=4.3.1"
-widgetsnbextension = ">=4.0.12,<4.1.0"
+widgetsnbextension = ">=4.0.14,<4.1.0"
 
 [package.extras]
 test = ["ipykernel", "jsonschema", "pytest (>=3.6.0)", "pytest-cov", "pytz"]
@@ -1778,17 +1835,17 @@ files = [
 
 [[package]]
 name = "json5"
-version = "0.10.0"
+version = "0.12.0"
 description = "A Python implementation of the JSON5 data format."
 optional = false
 python-versions = ">=3.8.0"
 files = [
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 ]
 
 [package.extras]
-dev = ["build (==1.2.2.post1)", "coverage (==7.5.3)", "mypy (==1.13.0)", "pip (==24.3.1)", "pylint (==3.2.3)", "ruff (==0.7.3)", "twine (==5.1.1)", "uv (==0.5.1)"]
+dev = ["build (==1.2.2.post1)", "coverage (==7.5.4)", "coverage (==7.8.0)", "mypy (==1.14.1)", "mypy (==1.15.0)", "pip (==25.0.1)", "pylint (==3.2.7)", "pylint (==3.3.6)", "ruff (==0.11.2)", "twine (==6.1.0)", "uv (==0.6.11)"]
 
 [[package]]
 name = "jsonpointer"
@@ -2026,13 +2083,13 @@ test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (>
 
 [[package]]
 name = "jupyterlab"
-version = "4.3.6"
+version = "4.4.0"
 description = "JupyterLab computational environment"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "jupyterlab-4.3.6-py3-none-any.whl", hash = "sha256:fc9eb0455562a56a9bd6d2977cf090842f321fa1a298fcee9bf8c19de353d5fd"},
-    {file = "jupyterlab-4.3.6.tar.gz", hash = "sha256:2900ffdbfca9ed37c4ad7fdda3eb76582fd945d46962af3ac64741ae2d6b2ff4"},
+    {file = "jupyterlab-4.4.0-py3-none-any.whl", hash = "sha256:61d33991fbb352cc7caac08bd0c34577fea86d8d5d9772600d9d5a6bcbc882c0"},
+    {file = "jupyterlab-4.4.0.tar.gz", hash = "sha256:f1767d5f0104e40f3b4a63bf6892bbef8e4704dcabf0c78408a3bdc411792f04"},
 ]
 
 [package.dependencies]
@@ -2046,15 +2103,15 @@ jupyter-server = ">=2.4.0,<3"
 jupyterlab-server = ">=2.27.1,<3"
 notebook-shim = ">=0.2"
 packaging = "*"
-setuptools = ">=40.8.0"
+setuptools = ">=41.1.0"
 tomli = {version = ">=1.2.2", markers = "python_version < \"3.11\""}
 tornado = ">=6.2.0"
 traitlets = "*"
 
 [package.extras]
-dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.6.9)"]
-docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-jupyter", "sphinx (>=1.8,<8.1.0)", "sphinx-copybutton"]
-docs-screenshots = ["altair (==5.4.1)", "ipython (==8.16.1)", "ipywidgets (==8.1.5)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.2.post3)", "matplotlib (==3.9.2)", "nbconvert (>=7.0.0)", "pandas (==2.2.3)", "scipy (==1.14.1)", "vega-datasets (==0.9.0)"]
+dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.9.9)"]
+docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-jupyter", "sphinx (>=1.8,<8.2.0)", "sphinx-copybutton"]
+docs-screenshots = ["altair (==5.5.0)", "ipython (==8.16.1)", "ipywidgets (==8.1.5)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.3.post1)", "matplotlib (==3.10.0)", "nbconvert (>=7.0.0)", "pandas (==2.2.3)", "scipy (==1.15.1)", "vega-datasets (==0.9.0)"]
 test = ["coverage", "pytest (>=7.0)", "pytest-check-links (>=0.7)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter (>=0.5.3)", "pytest-timeout", "pytest-tornasync", "requests", "requests-cache", "virtualenv"]
 upgrade-extension = ["copier (>=9,<10)", "jinja2-time (<0.3)", "pydantic (<3.0)", "pyyaml-include (<3.0)", "tomli-w (<2.0)"]
 
@@ -2096,24 +2153,24 @@ test = ["hatch", "ipykernel", "openapi-core (>=0.18.0,<0.19.0)", "openapi-spec-v
 
 [[package]]
 name = "jupyterlab-widgets"
-version = "3.0.13"
+version = "3.0.14"
 description = "Jupyter interactive widgets for JupyterLab"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "jupyterlab_widgets-3.0.13-py3-none-any.whl", hash = "sha256:e3cda2c233ce144192f1e29914ad522b2f4c40e77214b0cc97377ca3d323db54"},
-    {file = "jupyterlab_widgets-3.0.13.tar.gz", hash = "sha256:a2966d385328c1942b683a8cd96b89b8dd82c8b8f81dda902bb2bc06d46f5bed"},
+    {file = "jupyterlab_widgets-3.0.14-py3-none-any.whl", hash = "sha256:54c33e3306b7fca139d165d6190dc6c0627aafa5d14adfc974a4e9a3d26cb703"},
+    {file = "jupyterlab_widgets-3.0.14.tar.gz", hash = "sha256:bad03e59546869f026e537e0d170e454259e6dc7048e14041707ca31e523c8a1"},
 ]
 
 [[package]]
 name = "jupytext"
-version = "1.16.7"
+version = "1.17.0"
 description = "Jupyter notebooks as Markdown documents, Julia, Python or R scripts"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupytext-1.16.7-py3-none-any.whl", hash = "sha256:912f9d9af7bd3f15470105e5c5dddf1669b2d8c17f0c55772687fc5a4a73fe69"},
-    {file = "jupytext-1.16.7.tar.gz", hash = "sha256:fc4e97f0890e22062c4ef10313c7ca960b07b3767246a1fef7585888cc2afe5d"},
+    {file = "jupytext-1.17.0-py3-none-any.whl", hash = "sha256:d75b7cd198b3640a12f9cdf4d610bb80c9f27a8c3318b00372f90d21466d40e1"},
+    {file = "jupytext-1.17.0.tar.gz", hash = "sha256:c74adf6d205a778f481189e986b6066af79bdeb69099f4138d933cc15c398fb6"},
 ]
 
 [package.dependencies]
@@ -2125,14 +2182,14 @@ pyyaml = "*"
 tomli = {version = "*", markers = "python_version < \"3.11\""}
 
 [package.extras]
-dev = ["autopep8", "black", "flake8", "gitpython", "ipykernel", "isort", "jupyter-fs (>=1.0)", "jupyter-server (!=2.11)", "nbconvert", "pre-commit", "pytest", "pytest-cov (>=2.6.1)", "pytest-randomly", "pytest-xdist", "sphinx (<8)", "sphinx-gallery (<0.8)"]
+dev = ["autopep8", "black", "flake8", "gitpython", "ipykernel", "isort", "jupyter-fs (>=1.0)", "jupyter-server (!=2.11)", "nbconvert", "pre-commit", "pytest", "pytest-asyncio", "pytest-cov (>=2.6.1)", "pytest-randomly", "pytest-xdist", "sphinx", "sphinx-gallery (>=0.8)"]
 docs = ["myst-parser", "sphinx", "sphinx-copybutton", "sphinx-rtd-theme"]
-test = ["pytest", "pytest-randomly", "pytest-xdist"]
-test-cov = ["ipykernel", "jupyter-server (!=2.11)", "nbconvert", "pytest", "pytest-cov (>=2.6.1)", "pytest-randomly", "pytest-xdist"]
-test-external = ["autopep8", "black", "flake8", "gitpython", "ipykernel", "isort", "jupyter-fs (>=1.0)", "jupyter-server (!=2.11)", "nbconvert", "pre-commit", "pytest", "pytest-randomly", "pytest-xdist", "sphinx (<8)", "sphinx-gallery (<0.8)"]
-test-functional = ["pytest", "pytest-randomly", "pytest-xdist"]
-test-integration = ["ipykernel", "jupyter-server (!=2.11)", "nbconvert", "pytest", "pytest-randomly", "pytest-xdist"]
-test-ui = ["calysto-bash"]
+test = ["pytest", "pytest-asyncio", "pytest-randomly", "pytest-xdist"]
+test-cov = ["black", "ipykernel", "jupyter-server (!=2.11)", "nbconvert", "pytest", "pytest-asyncio", "pytest-cov (>=2.6.1)", "pytest-randomly", "pytest-xdist"]
+test-external = ["autopep8", "black", "flake8", "gitpython", "ipykernel", "isort", "jupyter-fs (>=1.0)", "jupyter-server (!=2.11)", "nbconvert", "pre-commit", "pytest", "pytest-asyncio", "pytest-randomly", "pytest-xdist", "sphinx", "sphinx-gallery (>=0.8)"]
+test-functional = ["black", "pytest", "pytest-asyncio", "pytest-randomly", "pytest-xdist"]
+test-integration = ["black", "ipykernel", "jupyter-server (!=2.11)", "nbconvert", "pytest", "pytest-asyncio", "pytest-randomly", "pytest-xdist"]
+test-ui = ["bash-kernel"]
 
 [[package]]
 name = "kiwisolver"
@@ -2413,17 +2470,17 @@ test = ["hypothesis", "pytest", "readme-renderer"]
 
 [[package]]
 name = "markdown"
-version = "3.7"
+version = "3.8"
 description = "Python implementation of John Gruber's Markdown."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
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-    {file = "markdown-3.7.tar.gz", hash = "sha256:2ae2471477cfd02dbbf038d5d9bc226d40def84b4fe2986e49b59b6b472bbed2"},
+    {file = "markdown-3.8-py3-none-any.whl", hash = "sha256:794a929b79c5af141ef5ab0f2f642d0f7b1872981250230e72682346f7cc90dc"},
+    {file = "markdown-3.8.tar.gz", hash = "sha256:7df81e63f0df5c4b24b7d156eb81e4690595239b7d70937d0409f1b0de319c6f"},
 ]
 
 [package.extras]
-docs = ["mdx-gh-links (>=0.2)", "mkdocs (>=1.5)", "mkdocs-gen-files", "mkdocs-literate-nav", "mkdocs-nature (>=0.6)", "mkdocs-section-index", "mkdocstrings[python]"]
+docs = ["mdx_gh_links (>=0.2)", "mkdocs (>=1.6)", "mkdocs-gen-files", "mkdocs-literate-nav", "mkdocs-nature (>=0.6)", "mkdocs-section-index", "mkdocstrings[python]"]
 testing = ["coverage", "pyyaml"]
 
 [[package]]
@@ -2522,21 +2579,22 @@ files = [
 
 [[package]]
 name = "marshmallow"
-version = "3.26.1"
+version = "4.0.0"
 description = "A lightweight library for converting complex datatypes to and from native Python datatypes."
 optional = false
 python-versions = ">=3.9"
 files = [
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+    {file = "marshmallow-4.0.0-py3-none-any.whl", hash = "sha256:e7b0528337e9990fd64950f8a6b3a1baabed09ad17a0dfb844d701151f92d203"},
+    {file = "marshmallow-4.0.0.tar.gz", hash = "sha256:3b6e80aac299a7935cfb97ed01d1854fb90b5079430969af92118ea1b12a8d55"},
 ]
 
 [package.dependencies]
-packaging = ">=17.0"
+backports-datetime-fromisoformat = {version = "*", markers = "python_version < \"3.11\""}
+typing-extensions = {version = "*", markers = "python_version < \"3.11\""}
 
 [package.extras]
 dev = ["marshmallow[tests]", "pre-commit (>=3.5,<5.0)", "tox"]
-docs = ["autodocsumm (==0.2.14)", "furo (==2024.8.6)", "sphinx (==8.1.3)", "sphinx-copybutton (==0.5.2)", "sphinx-issues (==5.0.0)", "sphinxext-opengraph (==0.9.1)"]
+docs = ["autodocsumm (==0.2.14)", "furo (==2024.8.6)", "sphinx (==8.2.3)", "sphinx-copybutton (==0.5.2)", "sphinx-issues (==5.0.1)", "sphinxext-opengraph (==0.10.0)"]
 tests = ["pytest", "simplejson"]
 
 [[package]]
@@ -2746,20 +2804,20 @@ pygments = ">2.12.0"
 
 [[package]]
 name = "mkdocs-material"
-version = "9.6.9"
+version = "9.6.12"
 description = "Documentation that simply works"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "mkdocs_material-9.6.9-py3-none-any.whl", hash = "sha256:6e61b7fb623ce2aa4622056592b155a9eea56ff3487d0835075360be45a4c8d1"},
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+    {file = "mkdocs_material-9.6.12-py3-none-any.whl", hash = "sha256:92b4fbdc329e4febc267ca6e2c51e8501fa97b2225c5f4deb4d4e43550f8e61e"},
+    {file = "mkdocs_material-9.6.12.tar.gz", hash = "sha256:add6a6337b29f9ea7912cb1efc661de2c369060b040eb5119855d794ea85b473"},
 ]
 
 [package.dependencies]
 babel = ">=2.10,<3.0"
 backrefs = ">=5.7.post1,<6.0"
 colorama = ">=0.4,<1.0"
-jinja2 = ">=3.0,<4.0"
+jinja2 = ">=3.1,<4.0"
 markdown = ">=3.2,<4.0"
 mkdocs = ">=1.6,<2.0"
 mkdocs-material-extensions = ">=1.3,<2.0"
@@ -3027,18 +3085,18 @@ files = [
 
 [[package]]
 name = "notebook"
-version = "7.3.3"
+version = "7.4.0"
 description = "Jupyter Notebook - A web-based notebook environment for interactive computing"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "notebook-7.4.0-py3-none-any.whl", hash = "sha256:005fd21f4db6093a7b739b17df5fe60597811adb07e8255f458db4035d208e3a"},
+    {file = "notebook-7.4.0.tar.gz", hash = "sha256:581d88f83709d90ce738dfd1d759892b96e3cbbc9c4a989912ed6c6a08f0d3e8"},
 ]
 
 [package.dependencies]
 jupyter-server = ">=2.4.0,<3"
-jupyterlab = ">=4.3.6,<4.4"
+jupyterlab = ">=4.4.0rc0,<4.5"
 jupyterlab-server = ">=2.27.1,<3"
 notebook-shim = ">=0.2,<0.3"
 tornado = ">=6.2.0"
@@ -3067,37 +3125,37 @@ test = ["pytest", "pytest-console-scripts", "pytest-jupyter", "pytest-tornasync"
 
 [[package]]
 name = "numba"
-version = "0.61.0"
+version = "0.61.2"
 description = "compiling Python code using LLVM"
 optional = false
 python-versions = ">=3.10"
 files = [
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 [package.extras]
-docs = ["furo", "olefile", "sphinx (>=8.1)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinxext-opengraph"]
+docs = ["furo", "olefile", "sphinx (>=8.2)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinxext-opengraph"]
 fpx = ["olefile"]
 mic = ["olefile"]
+test-arrow = ["pyarrow"]
 tests = ["check-manifest", "coverage (>=7.4.2)", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout", "trove-classifiers (>=2024.10.12)"]
 typing = ["typing-extensions"]
 xmp = ["defusedxml"]
@@ -3636,13 +3705,13 @@ twisted = ["twisted"]
 
 [[package]]
 name = "prompt-toolkit"
-version = "3.0.50"
+version = "3.0.51"
 description = "Library for building powerful interactive command lines in Python"
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 ]
 
 [package.dependencies]
@@ -3757,19 +3826,20 @@ files = [
 
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-version = "2.10.6"
+version = "2.11.3"
 description = "Data validation using Python type hints"
 optional = false
-python-versions = ">=3.8"
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 [package.dependencies]
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-pydantic-core = "2.27.2"
+pydantic-core = "2.33.1"
 typing-extensions = ">=4.12.2"
+typing-inspection = ">=0.4.0"
 
 [package.extras]
 email = ["email-validator (>=2.0.0)"]
@@ -3777,111 +3847,110 @@ timezone = ["tzdata"]
 
 [[package]]
 name = "pydantic-core"
-version = "2.27.2"
+version = "2.33.1"
 description = "Core functionality for Pydantic validation and serialization"
 optional = false
-python-versions = ">=3.8"
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 scikit-learn = ">=0.18"
 scipy = ">=1.0"
 
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 [package.extras]
@@ -4001,13 +4116,13 @@ diagrams = ["jinja2", "railroad-diagrams"]
 
 [[package]]
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+version = "1.1.399"
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 [package.dependencies]
@@ -4104,13 +4219,13 @@ six = ">=1.5"
 
 [[package]]
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 [package.extras]
@@ -4132,13 +4247,13 @@ dev = ["backports.zoneinfo", "black", "build", "freezegun", "mdx_truly_sane_list
 
 [[package]]
 name = "pytz"
-version = "2025.1"
+version = "2025.2"
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 ]
 
 [[package]]
@@ -4260,104 +4375,104 @@ pyyaml = "*"
 
 [[package]]
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 [package.dependencies]
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-    {file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
+    {file = "typing_extensions-4.13.2-py3-none-any.whl", hash = "sha256:a439e7c04b49fec3e5d3e2beaa21755cadbbdc391694e28ccdd36ca4a1408f8c"},
+    {file = "typing_extensions-4.13.2.tar.gz", hash = "sha256:e6c81219bd689f51865d9e372991c540bda33a0379d5573cddb9a3a23f7caaef"},
 ]
 
+[[package]]
+name = "typing-inspection"
+version = "0.4.0"
+description = "Runtime typing introspection tools"
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "typing_inspection-0.4.0-py3-none-any.whl", hash = "sha256:50e72559fcd2a6367a19f7a7e610e6afcb9fac940c650290eed893d61386832f"},
+    {file = "typing_inspection-0.4.0.tar.gz", hash = "sha256:9765c87de36671694a67904bf2c96e395be9c6439bb6c87b5142569dcdd65122"},
+]
+
+[package.dependencies]
+typing-extensions = ">=4.12.0"
+
 [[package]]
 name = "tzdata"
-version = "2025.1"
+version = "2025.2"
 description = "Provider of IANA time zone data"
 optional = false
 python-versions = ">=2"
 files = [
-    {file = "tzdata-2025.1-py2.py3-none-any.whl", hash = "sha256:7e127113816800496f027041c570f50bcd464a020098a3b6b199517772303639"},
-    {file = "tzdata-2025.1.tar.gz", hash = "sha256:24894909e88cdb28bd1636c6887801df64cb485bd593f2fd83ef29075a81d694"},
+    {file = "tzdata-2025.2-py2.py3-none-any.whl", hash = "sha256:1a403fada01ff9221ca8044d701868fa132215d84beb92242d9acd2147f667a8"},
+    {file = "tzdata-2025.2.tar.gz", hash = "sha256:b60a638fcc0daffadf82fe0f57e53d06bdec2f36c4df66280ae79bce6bd6f2b9"},
 ]
 
 [[package]]
@@ -5578,13 +5732,13 @@ dev = ["flake8", "flake8-annotations", "flake8-bandit", "flake8-bugbear", "flake
 
 [[package]]
 name = "urllib3"
-version = "2.3.0"
+version = "2.4.0"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "urllib3-2.3.0-py3-none-any.whl", hash = "sha256:1cee9ad369867bfdbbb48b7dd50374c0967a0bb7710050facf0dd6911440e3df"},
-    {file = "urllib3-2.3.0.tar.gz", hash = "sha256:f8c5449b3cf0861679ce7e0503c7b44b5ec981bec0d1d3795a07f1ba96f0204d"},
+    {file = "urllib3-2.4.0-py3-none-any.whl", hash = "sha256:4e16665048960a0900c702d4a66415956a584919c03361cac9f1df5c5dd7e813"},
+    {file = "urllib3-2.4.0.tar.gz", hash = "sha256:414bc6535b787febd7567804cc015fee39daab8ad86268f1310a9250697de466"},
 ]
 
 [package.extras]
@@ -5722,13 +5876,13 @@ test = ["websockets"]
 
 [[package]]
 name = "widgetsnbextension"
-version = "4.0.13"
+version = "4.0.14"
 description = "Jupyter interactive widgets for Jupyter Notebook"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "widgetsnbextension-4.0.13-py3-none-any.whl", hash = "sha256:74b2692e8500525cc38c2b877236ba51d34541e6385eeed5aec15a70f88a6c71"},
-    {file = "widgetsnbextension-4.0.13.tar.gz", hash = "sha256:ffcb67bc9febd10234a362795f643927f4e0c05d9342c727b65d2384f8feacb6"},
+    {file = "widgetsnbextension-4.0.14-py3-none-any.whl", hash = "sha256:4875a9eaf72fbf5079dc372a51a9f268fc38d46f767cbf85c43a36da5cb9b575"},
+    {file = "widgetsnbextension-4.0.14.tar.gz", hash = "sha256:a3629b04e3edb893212df862038c7232f62973373869db5084aed739b437b5af"},
 ]
 
 [[package]]
@@ -5822,4 +5976,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.13"
-content-hash = "2905ece63aba1f6f63ce2b18aae19d04aeacfe3758222e4b2695735831d1b180"
+content-hash = "5be8f2d753c345a597fc603c302f38b56f7e4483afe006af1b378638e39825b1"
diff --git a/pyproject.toml b/pyproject.toml
index c10e35b2a5..dd3ff737a8 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -83,6 +83,7 @@ typing-extensions = "^4.12.2"
 azure-cosmos = "^4.9.0"
 azure-identity = "^1.19.0"
 azure-storage-blob = "^12.24.0"
+pyodbc = "^5.2.0"
 
 future = "^1.0.0" # Needed until graspologic fixes their dependency
 typer = "^0.15.1"
diff --git a/tests/unit/config/utils.py b/tests/unit/config/utils.py
index 6de8e97395..006ab43eaa 100644
--- a/tests/unit/config/utils.py
+++ b/tests/unit/config/utils.py
@@ -149,6 +149,10 @@ def assert_update_output_configs(actual: OutputConfig, expected: OutputConfig) -
     assert expected.container_name == actual.container_name
     assert expected.storage_account_blob_url == actual.storage_account_blob_url
     assert expected.cosmosdb_account_url == actual.cosmosdb_account_url
+    assert expected.database_name == actual.database_name
+    assert expected.database_server_name == actual.database_server_name
+    assert expected.autogenerate_tables == actual.autogenerate_tables
+    assert expected.client_id == actual.client_id
 
 
 def assert_cache_configs(actual: CacheConfig, expected: CacheConfig) -> None: