diff --git a/.github/workflows/build-wheels.yml b/.github/workflows/build-wheels.yml
index dd694e3..73d5e8f 100644
--- a/.github/workflows/build-wheels.yml
+++ b/.github/workflows/build-wheels.yml
@@ -67,6 +67,7 @@ jobs:
             extras: "uv"
           env:
             CIBW_ARCHS: ${{ matrix.cibw_arch }}
+            CIBW_SKIP: "cp313t-*"
 
         - uses: actions/upload-artifact@v4
           with:
@@ -80,7 +81,7 @@ jobs:
       - uses: actions/checkout@v4
 
       - name: Install uv and set the Python version
-        uses: astral-sh/setup-uv@v7
+        uses: astral-sh/setup-uv@v8.3.2
         with:
           python-version: 3.12
           enable-cache: true
@@ -113,7 +114,7 @@ jobs:
         run: ls -l dist
 
       - name: Install uv and set the Python version
-        uses: astral-sh/setup-uv@v7
+        uses: astral-sh/setup-uv@v8.3.2
         with:
           python-version: 3.12
           # No caching needed for publish step
diff --git a/.github/workflows/unittests.yml b/.github/workflows/unittests.yml
index 9ee0dd8..01bf9e3 100644
--- a/.github/workflows/unittests.yml
+++ b/.github/workflows/unittests.yml
@@ -39,7 +39,7 @@ jobs:
       - uses: actions/checkout@v4
 
       - name: Set up Cargo registry cache
-        uses: actions/cache@v3
+        uses: actions/cache@v4
         with:
           path: ~/.cargo/registry
           key: ${{ runner.os }}-cargo-registry-${{ hashFiles('**/Cargo.lock') }}
@@ -47,7 +47,7 @@ jobs:
             ${{ runner.os }}-cargo-registry-
 
       - name: Set up Cargo build cache
-        uses: actions/cache@v3
+        uses: actions/cache@v4
         with:
           path: target
           key: ${{ runner.os }}-cargo-build-${{ hashFiles('**/Cargo.lock') }}
@@ -55,8 +55,9 @@ jobs:
             ${{ runner.os }}-cargo-build-
 
       - name: Install uv and set the Python version
-        uses: astral-sh/setup-uv@v7
+        uses: astral-sh/setup-uv@v8.3.2
         with:
+          version: "latest"
           python-version: ${{ matrix.python-version }}
           enable-cache: true
 
@@ -106,4 +107,4 @@ jobs:
           FAST_MSSQL_TEST_DB_PASSWORD: "YourStrong@Password"
           FAST_MSSQL_TEST_SERVER: "localhost"
           FAST_MSSQL_TEST_PORT: "1433"
-          FAST_MSSQL_TEST_DATABASE: "master"
+          FAST_MSSQL_TEST_DATABASE: "master"
\ No newline at end of file
diff --git a/Cargo.lock b/Cargo.lock
index 6597d84..39b991f 100644
--- a/Cargo.lock
+++ b/Cargo.lock
@@ -126,9 +126,9 @@ checksum = "1fd0f2584146f6f2ef48085050886acf353beff7305ebd1ae69500e27c67f64b"
 
 [[package]]
 name = "bytes"
-version = "1.11.1"
+version = "1.12.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1e748733b7cbc798e1434b6ac524f0c1ff2ab456fe201501e6497c8417a4fc33"
+checksum = "8ae3f5d315924270530207e2a68396c3cc547f6dca3fbdca317cfb1a51edb593"
 
 [[package]]
 name = "cc"
@@ -162,9 +162,9 @@ checksum = "613afe47fcd5fac7ccf1db93babcb082c5994d996f20b8b159f2ad1658eb5724"
 
 [[package]]
 name = "chrono"
-version = "0.4.44"
+version = "0.4.45"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c673075a2e0e5f4a1dde27ce9dee1ea4558c7ffe648f576438a20ca1d2acc4b0"
+checksum = "1aa79e62e7697b8e29b513a68abacf485adcd1fe8284a4316c5ae868e6633327"
 dependencies = [
  "iana-time-zone",
  "js-sys",
@@ -294,7 +294,7 @@ dependencies = [
 
 [[package]]
 name = "fastmssql_core"
-version = "0.7.3"
+version = "0.7.4"
 dependencies = [
  "ahash",
  "bb8",
@@ -915,9 +915,9 @@ dependencies = [
 
 [[package]]
 name = "pyo3"
-version = "0.28.3"
+version = "0.29.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "91fd8e38a3b50ed1167fb981cd6fd60147e091784c427b8f7183a7ee32c31c12"
+checksum = "cd274650b21d4bfc26a0a47587962c1edb425f69287324355cd040c3ea66071c"
 dependencies = [
  "chrono",
  "libc",
@@ -930,9 +930,9 @@ dependencies = [
 
 [[package]]
 name = "pyo3-async-runtimes"
-version = "0.28.0"
+version = "0.29.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9e7364a95bf00e8377bbf9b0f09d7ff9715a29d8fcf93b47d1a967363b973178"
+checksum = "b3ef68daa7316a3fac65e5e18b2203f010346de1c1c53456811a2624673ab046"
 dependencies = [
  "futures-channel",
  "futures-util",
@@ -944,18 +944,18 @@ dependencies = [
 
 [[package]]
 name = "pyo3-build-config"
-version = "0.28.3"
+version = "0.29.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e368e7ddfdeb98c9bca7f8383be1648fd84ab466bf2bc015e94008db6d35611e"
+checksum = "c5e2a7d2f0d013342f295c048ad19237add5154a55b1c5a254c0ec93d4109078"
 dependencies = [
  "target-lexicon",
 ]
 
 [[package]]
 name = "pyo3-ffi"
-version = "0.28.3"
+version = "0.29.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7f29e10af80b1f7ccaf7f69eace800a03ecd13e883acfacc1e5d0988605f651e"
+checksum = "ca85c467da1bbc8d866eea5deff9cf29ea5f7785054a17da36e65bda9c05845b"
 dependencies = [
  "libc",
  "pyo3-build-config",
@@ -963,9 +963,9 @@ dependencies = [
 
 [[package]]
 name = "pyo3-macros"
-version = "0.28.3"
+version = "0.29.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "df6e520eff47c45997d2fc7dd8214b25dd1310918bbb2642156ef66a67f29813"
+checksum = "9ac53762fd065daa3194dd09337a38bd793a188100fd1a9304c4ab312d901771"
 dependencies = [
  "proc-macro2",
  "pyo3-macros-backend",
@@ -975,13 +975,12 @@ dependencies = [
 
 [[package]]
 name = "pyo3-macros-backend"
-version = "0.28.3"
+version = "0.29.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c4cdc218d835738f81c2338f822078af45b4afdf8b2e33cbb5916f108b813acb"
+checksum = "4ca3a1557399783172dc5bf39cfca835157732532cba56b71d2292161e53b362"
 dependencies = [
  "heck",
  "proc-macro2",
- "pyo3-build-config",
  "quote",
  "syn",
 ]
@@ -1008,9 +1007,9 @@ dependencies = [
 
 [[package]]
 name = "quinn-proto"
-version = "0.11.14"
+version = "0.11.15"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "434b42fec591c96ef50e21e886936e66d3cc3f737104fdb9b737c40ffb94c098"
+checksum = "4fcb935c5bec503c2f0e306bdd3e58bb9029dcb14fa8d9ac76e3a5256ac0763e"
 dependencies = [
  "aws-lc-rs",
  "bytes",
@@ -1098,9 +1097,9 @@ dependencies = [
 
 [[package]]
 name = "reqwest"
-version = "0.13.3"
+version = "0.13.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "62e0021ea2c22aed41653bc7e1419abb2c97e038ff2c33d0e1309e49a97deec0"
+checksum = "219c5811de6525e5416c7d5d53bb656d3afdbc6c5af816e0802bcfa42dbdc1c3"
 dependencies = [
  "base64 0.22.1",
  "bytes",
@@ -1453,9 +1452,9 @@ checksum = "0c790de23124f9ab44544d7ac05d60440adc586479ce501c1d6d7da3cd8c9cf5"
 
 [[package]]
 name = "smallvec"
-version = "1.15.1"
+version = "1.15.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "67b1b7a3b5fe4f1376887184045fcf45c69e92af734b7aaddc05fb777b6fbd03"
+checksum = "8ed6a63f02c8539c91a8685a86f4099661ba3da017932f6ebbea6de3f0fa7c90"
 
 [[package]]
 name = "socket2"
@@ -1787,9 +1786,9 @@ checksum = "b6c140620e7ffbb22c2dee59cafe6084a59b5ffc27a8859a5f0d494b5d52b6be"
 
 [[package]]
 name = "uuid"
-version = "1.23.1"
+version = "1.23.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ddd74a9687298c6858e9b88ec8935ec45d22e8fd5e6394fa1bd4e99a87789c76"
+checksum = "bf80a72845275afea99e7f2b434723d3bc7e38470fcd1c7ed39a599c73319a53"
 dependencies = [
  "js-sys",
  "wasm-bindgen",
diff --git a/Cargo.toml b/Cargo.toml
index 3eeb2b1..1e57739 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "fastmssql_core"
-version = "0.7.3"
+version = "0.7.4"
 edition = "2024"
 
 [lib]
@@ -27,24 +27,24 @@ debug = true               # Keep debug info for development
 opt-level = 2
 
 [dependencies]
-pyo3 = { version = "0.28.3", features = ["extension-module", "abi3-py311", "chrono"] }
-pyo3-async-runtimes = { version = "0.28.0", features = ["tokio", "tokio-runtime"] }
+pyo3 = { version = "0.29.0", features = ["extension-module", "abi3-py311", "chrono"] }
+pyo3-async-runtimes = { version = "0.29.0", features = ["tokio", "tokio-runtime"] }
 tokio = { version = "1.52.3", features = ["rt-multi-thread", "net", "sync", "time", "io-util", "process"] }
 tokio-util = { version = "0.7.18", features = ["compat"] }
 tiberius = { version = "0.12.3", features = ["chrono", "tds73", "rustls"], default-features = false }
 bb8 = "0.9.1"
 
-chrono = { version = "0.4.44" }
-uuid = { version = "1.23.1" }
+chrono = { version = "0.4.45" }
+uuid = { version = "1.23.4" }
 ahash = "0.8.12"              # Faster hashing algorithm (used in optimized_types.rs)
-smallvec = "1.15.1"          # Stack-allocated vectors for small collections
+smallvec = "1.15.2"          # Stack-allocated vectors for small collections
 mimalloc = { version = "0.1.52", default-features = false } # Microsoft's fast memory allocator
 slab = "0.4.12"              # Pinned sub-dependency due to CVE-2025-55159
-bytes = "1.11.1"             # Pinned sub-dependency due to CVE-2026-25541
-quinn-proto = "0.11.14"      # Pinned sub-dependency due to CVE-2026-31812
+bytes = "1.12.0"             # Pinned sub-dependency due to CVE-2026-25541
+quinn-proto = "0.11.15"      # Pinned sub-dependency due to CVE-2026-31812
 
 # Azure authentication dependencies
-reqwest = { version = "0.13.3", features = ["json", "form", "rustls"], default-features = false }
+reqwest = { version = "0.13.4", features = ["json", "form", "rustls"], default-features = false }
 serde_json = "1.0.150"
 
 
diff --git a/README.md b/README.md
index e780ca3..fa66437 100644
--- a/README.md
+++ b/README.md
@@ -28,7 +28,6 @@ Great for data ingestion, bulk inserts, and large-scale query workloads.
 - Thread‑safe: safe to use in concurrent apps
 - Cross‑platform: Windows, macOS, Linux
 - Batch operations: high-performance bulk inserts and batch query execution
-- Apache Arrow support
 
 ## Installation
 
@@ -38,14 +37,6 @@ Great for data ingestion, bulk inserts, and large-scale query workloads.
 pip install fastmssql
 ```
 
-### Optional dependencies
-
-**Apache Arrow support** (for `to_arrow()` method):
-
-```bash
-pip install fastmssql[arrow]
-```
-
 ### Prerequisites
 
 - Python 3.11 to 3.14
@@ -352,42 +343,6 @@ async def main_fetching():
 asyncio.run(main_fetching())
 ```
 
-### Apache Arrow
-
-Convert query results to Apache Arrow tables for efficient bulk data processing and interoperability with data science tools:
-
-```python
-import asyncio
-from fastmssql import Connection
-
-async def main():
-    conn_str = "Server=localhost;Database=master;User Id=myuser;Password=mypass"
-    async with Connection(conn_str) as conn:
-        # Execute query and convert to Arrow
-        result = await conn.query("SELECT id, name, salary FROM employees")
-        arrow_table = result.to_arrow()
-        
-        # Arrow Table enables:
-        # - Efficient columnar storage and compute
-        # - Integration with Pandas, DuckDB, Polars
-        # - Parquet/ORC serialization
-        df = arrow_table.to_pandas()  # Convert to pandas DataFrame
-        print(df)
-        
-        # Write to Parquet for long-term storage
-        import pyarrow.parquet as pq
-        pq.write_table(arrow_table, "employees.parquet")
-        
-        # Or use with DuckDB for analytical queries
-        import duckdb
-        result = duckdb.from_arrow(arrow_table).filter("salary > 50000").execute()
-        print(result.fetchall())
-```
-
-**Requirements**: Install PyArrow with `pip install pyarrow`
-
-Note: Results are converted eagerly into Arrow arrays. For very large datasets, consider chunking queries or using iteration-based processing instead.
-
 ### Connection pooling
 
 Tune the pool to fit your workload. Constructor signature:
diff --git a/pyproject.toml b/pyproject.toml
index a09781d..bd964df 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "maturin"
 
 [project]
 name = "fastmssql"
-version = "0.7.3"
+version = "0.7.4"
 
 description = "A high-performance async Python library for Microsoft SQL Server built on Rust for heavy workloads and low latency."
 readme = "README.md"
@@ -69,14 +69,14 @@ Repository = "https://github.com/Rivendael/FastMssql"
 "Bug Tracker" = "https://github.com/Rivendael/FastMssql/issues"
 Documentation = "https://github.com/Rivendael/FastMssql#readme"
 
-[project.optional-dependencies]
-arrow = ["pyarrow>=13.0.0"]
-
 [tool.maturin]
 features = ["pyo3/abi3-py311"]
 module-name = "fastmssql"
 python-source = "python"
-include = ["fastmssql.pyi"]
+include = [
+    "python/fastmssql/*.pyi",
+    "python/fastmssql/py.typed",
+]
 
 [tool.pytest.ini_options]
 minversion = "6.0"
@@ -109,9 +109,6 @@ filterwarnings = [
     "ignore::PendingDeprecationWarning",
 ]
 
-[tool.uv]
-required-version = ">=0.9.7"
-
 [tool.cibuildwheel]
 build-frontend = "build[uv]"
 build = "cp311-* cp312-* cp313-* cp313t-* cp314-* cp314t-*"
@@ -142,18 +139,16 @@ MACOSX_DEPLOYMENT_TARGET = "10.15"
 
 [dependency-groups]
 dev = [
-    "ruff>=0.15.11",
-    "pytest==9.0.3",
-    "pytest-asyncio==1.3.0",
+    "ruff>=0.15.20",
+    "pytest==9.1.1",
+    "pytest-asyncio==1.4.0",
     "pytest-timeout==2.4.0",
     "psutil==7.2.2",            # For memory and process monitoring in stress tests
     "pytest-xdist==3.8.0",
-    "maturin==1.13.1",
+    "maturin==1.14.1",
     "python-dotenv==1.2.2",
-    "cibuildwheel[uv]>=3.4.1",
+    "cibuildwheel[uv]>=4.1.0",
     "wheel==0.47.0",
-    "filelock==3.29.0",
-    "pyarrow==23.0.1",
+    "filelock==3.29.5",
     "uvloop==0.22.1"
-
 ]
diff --git a/fastmssql.pyi b/python/fastmssql/fastmssql.pyi
similarity index 96%
rename from fastmssql.pyi
rename to python/fastmssql/fastmssql.pyi
index 650920a..b56b5e4 100644
--- a/fastmssql.pyi
+++ b/python/fastmssql/fastmssql.pyi
@@ -9,11 +9,9 @@ High-performance Rust-backed Python driver for SQL Server with:
 - Memory-efficient result handling
 """
 
-from typing import Any, Coroutine, Dict, List, Optional, Tuple, TYPE_CHECKING
+from typing import Any, Coroutine, Dict, List, Optional, Tuple
 from enum import StrEnum
-
-if TYPE_CHECKING:
-    import pyarrow
+from .fastmssql import _RustConnection, _RustTransaction
 
 class PoolConfig:
     """
@@ -126,6 +124,7 @@ class SqlError(Exception):
         except SqlError as e:
             print(e.code, e.message, e.state)
     """
+
     code: int
     message: str
     state: int
@@ -140,6 +139,7 @@ class SqlConnectionError(Exception):
         host: Redirect target host for routing errors, if available.
         port: Redirect target port for routing errors, if available.
     """
+
     message: Optional[str]
     host: Optional[str]
     port: Optional[int]
@@ -152,6 +152,7 @@ class TlsError(Exception):
     Attributes:
         message: Human-readable error description.
     """
+
     message: str
     ...
 
@@ -162,6 +163,7 @@ class ProtocolError(Exception):
     Attributes:
         message: Human-readable error description.
     """
+
     message: str
     ...
 
@@ -172,6 +174,7 @@ class ConversionError(Exception):
     Attributes:
         message: Human-readable error description.
     """
+
     message: str
     ...
 
@@ -359,26 +362,6 @@ class QueryStream:
         """
         ...
 
-    def to_arrow(self) -> pyarrow.Table:
-        """
-        Convert query results to Apache Arrow Table.
-
-        Converts all rows to an Apache Arrow Table with column-oriented storage,
-        enabling efficient bulk data processing and integration with data analysis tools.
-
-        Returns:
-            pyarrow.Table: Column-oriented result representation with schema metadata
-
-        Raises:
-            ImportError: If PyArrow is not installed
-            RuntimeError: If conversion fails (empty results from Tiberius may lack schema info)
-
-        Note:
-            All rows are converted eagerly into Arrow arrays and loaded into memory.
-            For very large result sets, consider processing in batches.
-        """
-        ...
-
 class Parameter:
     """
     Parameter object for SQL queries with optional type hints.
@@ -489,6 +472,7 @@ class Parameters:
 
 class AzureCredentialType(StrEnum):
     """Azure credential type constants for authentication."""
+
     SERVICE_PRINCIPAL: str = "ServicePrincipal"
     MANAGED_IDENTITY: str = "ManagedIdentity"
     ACCESS_TOKEN: str = "AccessToken"
@@ -510,9 +494,7 @@ class AzureCredential:
 
     @staticmethod
     def service_principal(
-        client_id: str,
-        client_secret: str,
-        tenant_id: str
+        client_id: str, client_secret: str, tenant_id: str
     ) -> AzureCredential:
         """
         Create Azure credential for Service Principal authentication.
@@ -763,7 +745,7 @@ class Connection:
         """
         ...
 
-    async def __aenter__(self) -> Connection:
+    async def __aenter__(self) -> _RustConnection:
         """Async context manager entry (initializes pool)."""
         ...
 
@@ -894,7 +876,7 @@ class Transaction:
         """Return True if the underlying connection is currently established."""
         ...
 
-    async def __aenter__(self) -> Transaction:
+    async def __aenter__(self) -> _RustTransaction:
         """Async context manager entry (begins transaction)."""
         ...
 
@@ -905,7 +887,7 @@ class Transaction:
 class TypedNull(StrEnum):
     """Class to store a typed null value
 
-    This is required as some SQL Server features such as stored procedures etc. sometimes require type information for which is 
+    This is required as some SQL Server features such as stored procedures etc. sometimes require type information for which is
     not possible for nulls when just using `None`. In such cases, SQL Server will complain about being unable to cast 'tinyint'
     to the desired data type.
 
diff --git a/python/fastmssql/py.typed b/python/fastmssql/py.typed
new file mode 100644
index 0000000..e69de29
diff --git a/src/arrow_conversion.rs b/src/arrow_conversion.rs
deleted file mode 100644
index 4c196bb..0000000
--- a/src/arrow_conversion.rs
+++ /dev/null
@@ -1,271 +0,0 @@
-use crate::type_mapping;
-use crate::types::ColumnInfo;
-use pyo3::prelude::*;
-use pyo3::types::PyDict;
-use std::sync::Arc;
-use tiberius::ColumnType;
-
-/// Cache of frequently-used Arrow type objects to avoid repeated PyArrow imports and object creation
-struct ArrowTypeCache {
-    int64: Py<PyAny>,
-    float64: Py<PyAny>,
-    string: Py<PyAny>,
-    bool_: Py<PyAny>,
-    binary: Py<PyAny>,
-    null: Py<PyAny>,
-    date32: Py<PyAny>,
-    /// Reference to pyarrow module for creating complex types (Decimal, Timestamp, etc.)
-    pyarrow: Py<PyModule>,
-}
-
-impl ArrowTypeCache {
-    fn new(py: Python) -> PyResult<Self> {
-        let pyarrow = py.import("pyarrow")?;
-        Ok(ArrowTypeCache {
-            int64: pyarrow.getattr("int64")?.call0()?.unbind(),
-            float64: pyarrow.getattr("float64")?.call0()?.unbind(),
-            string: pyarrow.getattr("string")?.call0()?.unbind(),
-            bool_: pyarrow.getattr("bool_")?.call0()?.unbind(),
-            binary: pyarrow.getattr("binary")?.call0()?.unbind(),
-            null: pyarrow.getattr("null")?.call0()?.unbind(),
-            date32: pyarrow.getattr("date32")?.call0()?.unbind(),
-            pyarrow: pyarrow.unbind(),
-        })
-    }
-}
-
-/// Maps SQL column types to corresponding Arrow types, using a shared cache to minimize imports.
-/// This avoids repeated PyArrow module imports and provides consistent type mapping.
-fn get_arrow_type_with_cache(
-    col_type: ColumnType,
-    cache: &ArrowTypeCache,
-    py: Python,
-) -> PyResult<Py<PyAny>> {
-    let arrow_type = match col_type {
-        // Integer types: all mapped to int64 for consistency
-        ColumnType::Int1
-        | ColumnType::Int2
-        | ColumnType::Int4
-        | ColumnType::Int8
-        | ColumnType::Intn => cache.int64.clone_ref(py),
-
-        // Floating point types
-        ColumnType::Float4 | ColumnType::Float8 | ColumnType::Floatn => cache.float64.clone_ref(py),
-
-        // String types
-        ColumnType::NVarchar
-        | ColumnType::NChar
-        | ColumnType::BigVarChar
-        | ColumnType::BigChar
-        | ColumnType::Text
-        | ColumnType::NText
-        | ColumnType::Guid
-        | ColumnType::Xml => cache.string.clone_ref(py),
-
-        // Boolean type
-        ColumnType::Bit | ColumnType::Bitn => cache.bool_.clone_ref(py),
-
-        // Money types: decimal128 with precision 38, scale 4
-        ColumnType::Money | ColumnType::Money4 => {
-            let pyarrow = cache.pyarrow.bind(py);
-            let args = pyo3::types::PyTuple::new(py, &[38i32, 4i32])?;
-            let decimal_method = pyarrow.getattr("decimal128")?;
-            decimal_method.call1(args)?.unbind()
-        }
-
-        // Decimal/Numeric types: decimal128 with precision 38, scale 10
-        ColumnType::Decimaln | ColumnType::Numericn => {
-            let pyarrow = cache.pyarrow.bind(py);
-            let args = pyo3::types::PyTuple::new(py, &[38i32, 10i32])?;
-            let decimal_method = pyarrow.getattr("decimal128")?;
-            decimal_method.call1(args)?.unbind()
-        }
-
-        // DateTime types: timestamp with microsecond precision
-        ColumnType::Datetime
-        | ColumnType::Datetimen
-        | ColumnType::Datetime2
-        | ColumnType::Datetime4
-        | ColumnType::DatetimeOffsetn => {
-            let pyarrow = cache.pyarrow.bind(py);
-            let timestamp_method = pyarrow.getattr("timestamp")?;
-            timestamp_method.call1(("us",))?.unbind()
-        }
-
-        // Date type: date32 (days since UNIX epoch)
-        ColumnType::Daten => cache.date32.clone_ref(py),
-
-        // Time type: time64 with microsecond precision
-        ColumnType::Timen => {
-            let pyarrow = cache.pyarrow.bind(py);
-            let time_method = pyarrow.getattr("time64")?;
-            time_method.call1(("us",))?.unbind()
-        }
-
-        // Binary types
-        ColumnType::BigVarBin | ColumnType::BigBinary | ColumnType::Image => {
-            cache.binary.clone_ref(py)
-        }
-
-        // Special types: stored as binary
-        ColumnType::SSVariant | ColumnType::Udt => cache.binary.clone_ref(py),
-
-        // Null type
-        ColumnType::Null => cache.null.clone_ref(py),
-    };
-
-    Ok(arrow_type)
-}
-
-/// Converts SQL query results into Arrow arrays, one per column.
-///
-/// This function handles the critical conversion of tiberius Row data to PyArrow arrays.
-/// Key optimizations:
-/// - ArrowTypeCache reused across all columns (single pyarrow import)
-/// - Pre-allocated vectors sized to row count
-/// - Type casting explicitly used only for Money, Decimal, and DateTime (types requiring schema info)
-/// - Clear error messages showing problematic column for debugging
-///
-/// # Arguments:
-/// - `rows`: Raw SQL result rows
-/// - `column_info`: Column metadata (names, types)
-/// - `py`: Python interpreter context
-///
-/// # Returns: Vector of PyArrow arrays (one per column), suitable for `arrow_arrays_to_pyarrow_table()`
-pub fn build_arrow_columns(
-    rows: &[Option<tiberius::Row>],
-    column_info: &Arc<ColumnInfo>,
-    py: Python,
-) -> PyResult<Vec<Py<PyAny>>> {
-    let pyarrow = py.import("pyarrow")?;
-    let array_class = pyarrow.getattr("array")?;
-    let cache = ArrowTypeCache::new(py)?;
-
-    let num_columns = column_info.names.len();
-    let num_rows = rows.len();
-    let mut columns = Vec::with_capacity(num_columns);
-
-    // Handle empty result sets: create properly-typed empty arrays
-    if num_rows == 0 {
-        for (col_idx, col_type) in column_info.column_types.iter().enumerate() {
-            let arrow_type = get_arrow_type_with_cache(*col_type, &cache, py).map_err(|e| {
-                pyo3::exceptions::PyRuntimeError::new_err(format!(
-                    "Failed to determine Arrow type for column {}: {}",
-                    col_idx, e
-                ))
-            })?;
-            let empty_list = pyo3::types::PyList::empty(py);
-            let array = array_class
-                .call((empty_list, arrow_type), None)
-                .map_err(|e| {
-                    pyo3::exceptions::PyRuntimeError::new_err(format!(
-                        "Failed to create empty Array for column {}: {}",
-                        col_idx, e
-                    ))
-                })?;
-            columns.push(array.unbind());
-        }
-        return Ok(columns);
-    }
-
-    // Process each column
-    for col_idx in 0..num_columns {
-        let col_type = column_info.column_types[col_idx];
-        let mut column_values = Vec::with_capacity(num_rows);
-
-        // Convert values for this column across all rows
-        for (row_idx, row_opt) in rows.iter().enumerate() {
-            let value = if let Some(row) = row_opt {
-                type_mapping::sql_to_python(row, col_idx, col_type, py).map_err(|e| {
-                    pyo3::exceptions::PyRuntimeError::new_err(format!(
-                        "Column '{}' (idx {}), Row {}: {}",
-                        &column_info.names[col_idx], col_idx, row_idx, e
-                    ))
-                })?
-            } else {
-                py.None()
-            };
-            column_values.push(value);
-        }
-
-        let py_list = pyo3::types::PyList::new(py, &column_values).map_err(|e| {
-            pyo3::exceptions::PyRuntimeError::new_err(format!(
-                "Failed to create Python list for column {}: {}",
-                col_idx, e
-            ))
-        })?;
-        let arrow_type = get_arrow_type_with_cache(col_type, &cache, py).map_err(|e| {
-            pyo3::exceptions::PyRuntimeError::new_err(format!(
-                "Failed to determine Arrow type for column {}: {}",
-                col_idx, e
-            ))
-        })?;
-
-        // Use explicit type for complex types that require schema specification.
-        // PyArrow can infer types for simple types (int, float, string, bool) but needs
-        // explicit schemas for Decimal, Timestamp, and similar types to ensure correct precision/scale.
-        let array = match col_type {
-            ColumnType::Money
-            | ColumnType::Money4
-            | ColumnType::Decimaln
-            | ColumnType::Numericn
-            | ColumnType::Datetime
-            | ColumnType::Datetimen
-            | ColumnType::Datetime2
-            | ColumnType::Datetime4
-            | ColumnType::DatetimeOffsetn => {
-                // Explicit type required for proper schema specification
-                array_class.call((py_list, &arrow_type), None)
-            }
-            _ => {
-                // PyArrow can reliably infer types for these
-                array_class.call1((py_list,))
-            }
-        }
-        .map_err(|e| {
-            pyo3::exceptions::PyRuntimeError::new_err(format!(
-                "Failed to create Arrow array for column {}: {}",
-                col_idx, e
-            ))
-        })?;
-
-        columns.push(array.unbind());
-    }
-
-    Ok(columns)
-}
-
-/// Constructs a PyArrow Table from pre-built columns and names.
-///
-/// PyArrow Table construction maps column names to Arrow arrays. This function
-/// handles the final assembly step after column conversion.
-///
-/// # Arguments:
-/// - `column_names`: Ordered list of column names from query results
-/// - `arrays`: Arrow arrays (one per column, order must match names)
-/// - `py`: Python interpreter context
-///
-/// # Returns: A PyArrow Table object suitable for use in Python
-pub fn arrow_arrays_to_pyarrow_table(
-    column_names: &[String],
-    arrays: Vec<Py<PyAny>>,
-    py: Python,
-) -> PyResult<Py<PyAny>> {
-    let pyarrow = py.import("pyarrow")?;
-    let table_class = pyarrow.getattr("table")?;
-
-    let dict = PyDict::new(py);
-    for (name, array) in column_names.iter().zip(arrays.iter()) {
-        dict.set_item(name, array).map_err(|e| {
-            pyo3::exceptions::PyRuntimeError::new_err(format!(
-                "Failed to add column '{}' to PyArrow table: {}",
-                name, e
-            ))
-        })?;
-    }
-
-    let table = table_class.call1((dict,)).map_err(|e| {
-        pyo3::exceptions::PyRuntimeError::new_err(format!("Failed to create PyArrow Table: {}", e))
-    })?;
-    Ok(table.unbind())
-}
diff --git a/src/lib.rs b/src/lib.rs
index 53fa76f..ab3ca91 100644
--- a/src/lib.rs
+++ b/src/lib.rs
@@ -5,7 +5,6 @@ static GLOBAL: mimalloc::MiMalloc = mimalloc::MiMalloc;
 
 use pyo3::prelude::*;
 
-mod arrow_conversion;
 mod azure_auth;
 mod batch;
 mod connection;
diff --git a/src/types.rs b/src/types.rs
index 8e127c6..8660f9d 100644
--- a/src/types.rs
+++ b/src/types.rs
@@ -1,9 +1,9 @@
 use crate::type_mapping;
 use ahash::AHashMap as HashMap;
 use pyo3::exceptions::{PyException, PyRuntimeError};
-use pyo3::{create_exception, exceptions::PyValueError};
 use pyo3::prelude::*;
 use pyo3::types::PyDict;
+use pyo3::{create_exception, exceptions::PyValueError};
 use std::sync::Arc;
 use tiberius::{ColumnType, Row, error::Error as TError};
 
@@ -30,20 +30,16 @@ pub fn create_sql_error(err: TError, base: &'static str) -> PyErr {
                 exc
             })
         }
-        TError::Io { kind: _, message } => {
-            Python::attach(|py| {
-                let exc = SqlConnectionError::new_err(format!("{base}: {message}"));
-                let _ = exc.value(py).setattr("message", message.as_str());
-                exc
-            })
-        }
-        TError::Tls(msg) => {
-            Python::attach(|py| {
-                let exc = TlsError::new_err(format!("{base}: {msg}"));
-                let _ = exc.value(py).setattr("message", msg.as_str());
-                exc
-            })
-        }
+        TError::Io { kind: _, message } => Python::attach(|py| {
+            let exc = SqlConnectionError::new_err(format!("{base}: {message}"));
+            let _ = exc.value(py).setattr("message", message.as_str());
+            exc
+        }),
+        TError::Tls(msg) => Python::attach(|py| {
+            let exc = TlsError::new_err(format!("{base}: {msg}"));
+            let _ = exc.value(py).setattr("message", msg.as_str());
+            exc
+        }),
         TError::Routing { host, port } => {
             let message = format!("server redirected to {host}:{port}");
             Python::attach(|py| {
@@ -81,7 +77,7 @@ pub fn create_sql_error(err: TError, base: &'static str) -> PyErr {
                 exc
             })
         }
-        _ => PyRuntimeError::new_err(format!("{base}: {err}"))
+        _ => PyRuntimeError::new_err(format!("{base}: {err}")),
     }
 }
 
@@ -466,18 +462,6 @@ impl PyQueryStream {
     pub fn fetchall(&mut self, py: Python<'_>) -> PyResult<Py<PyAny>> {
         self.all(py)
     }
-
-    /// Convert query results to an Apache Arrow Table
-    pub fn to_arrow(&self, py: Python<'_>) -> PyResult<Py<PyAny>> {
-        let column_info = self
-            .column_info
-            .as_ref()
-            .ok_or_else(|| PyValueError::new_err("No column information available"))?;
-
-        let arrays = crate::arrow_conversion::build_arrow_columns(&self.tiberius_rows, column_info, py)?;
-
-        crate::arrow_conversion::arrow_arrays_to_pyarrow_table(&column_info.names, arrays, py)
-    }
 }
 
 impl PyQueryStream {
diff --git a/tests/test_arrow_support.py b/tests/test_arrow_support.py
deleted file mode 100644
index b8fd8d4..0000000
--- a/tests/test_arrow_support.py
+++ /dev/null
@@ -1,530 +0,0 @@
-import pytest
-from conftest import Config
-
-try:
-    import pyarrow as pa
-except ImportError:
-    pa = None
-
-try:
-    from fastmssql import Connection
-except ImportError:
-    pytest.fail("fastmssql not available - run 'maturin develop' first")
-
-
-# Skip all Arrow tests if PyArrow is not available
-pytestmark = pytest.mark.skipif(pa is None, reason="PyArrow not installed")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_basic_to_arrow_conversion(test_config: Config):
-    """Test basic conversion of query results to Arrow table."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query("SELECT 1 as test_value, 'hello' as text_value")
-
-            assert result.has_rows(), "Expected result to have rows"
-
-            arrow_table = result.to_arrow()
-
-            assert isinstance(arrow_table, pa.Table), "Expected PyArrow Table object"
-
-            assert arrow_table.column_names == [
-                "test_value",
-                "text_value",
-            ], "Column names mismatch"
-
-            assert arrow_table.num_rows == 1, "Expected 1 row"
-            assert arrow_table["test_value"][0].as_py() == 1
-            assert arrow_table["text_value"][0].as_py() == "hello"
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_with_integers(test_config: Config):
-    """Test Arrow conversion with various integer types."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query(
-                """
-                SELECT
-                    CAST(42 as TINYINT) as tiny_int,
-                    CAST(1000 as SMALLINT) as small_int,
-                    CAST(100000 as INT) as reg_int,
-                    CAST(9223372036854775800 as BIGINT) as big_int
-                """
-            )
-
-            arrow_table = result.to_arrow()
-
-            assert arrow_table.num_rows == 1
-            assert arrow_table["tiny_int"][0].as_py() == 42
-            assert arrow_table["small_int"][0].as_py() == 1000
-            assert arrow_table["reg_int"][0].as_py() == 100000
-            assert arrow_table["big_int"][0].as_py() == 9223372036854775800
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_with_floating_point(test_config: Config):
-    """Test Arrow conversion with floating point numbers."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query(
-                """
-                SELECT
-                    CAST(3.14 as FLOAT) as float_val,
-                    CAST(2.71828 as REAL) as real_val
-                """
-            )
-
-            arrow_table = result.to_arrow()
-
-            assert arrow_table.num_rows == 1
-            float_val = arrow_table["float_val"][0].as_py()
-            assert float_val is not None
-            real_val = arrow_table["real_val"][0].as_py()
-            assert real_val is not None
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_with_strings(test_config: Config):
-    """Test Arrow conversion with string data types."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query(
-                """
-                SELECT
-                    'varchar data' as varchar_col,
-                    N'nvarchar data' as nvarchar_col,
-                    'fixed char' as char_col
-                """
-            )
-
-            arrow_table = result.to_arrow()
-
-            assert arrow_table.num_rows == 1
-            assert arrow_table["varchar_col"][0].as_py() == "varchar data"
-            assert arrow_table["nvarchar_col"][0].as_py() == "nvarchar data"
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_with_booleans(test_config: Config):
-    """Test Arrow conversion with boolean data."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query(
-                """
-                SELECT
-                    CAST(1 as BIT) as true_val,
-                    CAST(0 as BIT) as false_val
-                """
-            )
-
-            arrow_table = result.to_arrow()
-
-            assert arrow_table.num_rows == 1
-            assert arrow_table["true_val"][0].as_py()
-            assert not arrow_table["false_val"][0].as_py()
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_with_nulls(test_config: Config):
-    """Test Arrow conversion with NULL values."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query(
-                """
-                SELECT
-                    NULL as null_int,
-                    NULL as null_string,
-                    1 as not_null,
-                    NULL as another_null
-                """
-            )
-
-            arrow_table = result.to_arrow()
-
-            assert arrow_table.num_rows == 1
-            assert arrow_table["null_int"][0].as_py() is None
-            assert arrow_table["null_string"][0].as_py() is None
-            assert arrow_table["not_null"][0].as_py() == 1
-            assert arrow_table["another_null"][0].as_py() is None
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_with_dates(test_config: Config):
-    """Test Arrow conversion with date and datetime types."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query(
-                """
-                SELECT
-                    CAST('2024-02-13' as DATE) as date_val,
-                    CAST('2024-02-13 14:30:45' as DATETIME) as datetime_val
-                """
-            )
-
-            arrow_table = result.to_arrow()
-
-            assert arrow_table.num_rows == 1
-            assert "date_val" in arrow_table.column_names
-            assert "datetime_val" in arrow_table.column_names
-            date_val = arrow_table["date_val"][0].as_py()
-            assert date_val is not None
-            datetime_val = arrow_table["datetime_val"][0].as_py()
-            assert datetime_val is not None
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_with_decimals(test_config: Config):
-    """Test Arrow conversion with DECIMAL and MONEY types."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query(
-                """
-                SELECT
-                    CAST(123.45 as DECIMAL(10, 2)) as decimal_val,
-                    CAST(99.99 as MONEY) as money_val
-                """
-            )
-
-            arrow_table = result.to_arrow()
-
-            assert arrow_table.num_rows == 1
-            # Verify columns exist
-            assert "decimal_val" in arrow_table.column_names
-            assert "money_val" in arrow_table.column_names
-            # These should be present in the table
-            _ = arrow_table["decimal_val"][0].as_py()
-            # Money values come through as Decimal objects
-            money_val = arrow_table["money_val"][0].as_py()
-            assert money_val is not None
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_multiple_rows(test_config: Config):
-    """Test Arrow conversion with multiple rows."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query(
-                """
-                SELECT 1 as id, 'first' as name
-                UNION ALL
-                SELECT 2, 'second'
-                UNION ALL
-                SELECT 3, 'third'
-                """
-            )
-
-            arrow_table = result.to_arrow()
-
-            assert arrow_table.num_rows == 3
-            assert arrow_table["id"][0].as_py() == 1
-            assert arrow_table["id"][1].as_py() == 2
-            assert arrow_table["id"][2].as_py() == 3
-            assert arrow_table["name"][0].as_py() == "first"
-            assert arrow_table["name"][1].as_py() == "second"
-            assert arrow_table["name"][2].as_py() == "third"
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_many_columns(test_config: Config):
-    """Test Arrow conversion with many columns."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query(
-                """
-                SELECT 
-                    1 as col1, 2 as col2, 3 as col3, 4 as col4, 5 as col5,
-                    6 as col6, 7 as col7, 8 as col8, 9 as col9, 10 as col10
-                """
-            )
-
-            arrow_table = result.to_arrow()
-
-            assert arrow_table.num_rows == 1
-            assert len(arrow_table.column_names) == 10
-            for i in range(1, 11):
-                assert arrow_table[f"col{i}"][0].as_py() == i
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_schema_types(test_config: Config):
-    """Test that Arrow schema has correct types."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query(
-                """
-                SELECT
-                    1 as int_col,
-                    CAST(3.14 as REAL) as float_col,
-                    'text' as string_col,
-                    CAST(1 as BIT) as bool_col
-                """
-            )
-
-            arrow_table = result.to_arrow()
-            schema = arrow_table.schema
-
-            # Verify schema field types
-            assert schema.field("int_col").type == pa.int64()
-            # Float columns might be float32 or float64 depending on REAL vs FLOAT
-            assert schema.field("float_col").type in [pa.float32(), pa.float64()]
-            assert schema.field("string_col").type == pa.string()
-            # Note: bool_ might be stored as int or other type depending on pyarrow version
-            assert schema.field("bool_col").type in [pa.bool_(), pa.int64()]
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_column_names_preserved(test_config: Config):
-    """Test that column names are correctly preserved in Arrow table."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query(
-                """
-                SELECT
-                    1 as FirstColumn,
-                    2 as SecondColumn,
-                    3 as ThirdColumn
-                """
-            )
-
-            arrow_table = result.to_arrow()
-
-            assert "FirstColumn" in arrow_table.column_names
-            assert "SecondColumn" in arrow_table.column_names
-            assert "ThirdColumn" in arrow_table.column_names
-            assert len(arrow_table.column_names) == 3
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_large_dataset(test_config: Config):
-    """Test Arrow conversion with larger dataset."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            # Generate 100+ rows
-            result = await conn.query(
-                """
-                WITH Numbers AS (
-                    SELECT 1 as num
-                    UNION ALL SELECT 2 UNION ALL SELECT 3 UNION ALL SELECT 4 UNION ALL SELECT 5
-                    UNION ALL SELECT 6 UNION ALL SELECT 7 UNION ALL SELECT 8 UNION ALL SELECT 9 UNION ALL SELECT 10
-                    UNION ALL SELECT 11 UNION ALL SELECT 12 UNION ALL SELECT 13 UNION ALL SELECT 14 UNION ALL SELECT 15
-                    UNION ALL SELECT 16 UNION ALL SELECT 17 UNION ALL SELECT 18 UNION ALL SELECT 19 UNION ALL SELECT 20
-                )
-                SELECT n1.num * 10 + n2.num as value FROM Numbers n1, Numbers n2 WHERE n1.num <= 5
-                """
-            )
-
-            arrow_table = result.to_arrow()
-
-            # Should have at least 100 rows
-            assert arrow_table.num_rows >= 100
-            assert len(arrow_table.column_names) == 1
-            assert arrow_table.column_names[0] == "value"
-            # Verify data exists
-            for i in range(min(10, arrow_table.num_rows)):
-                assert arrow_table["value"][i].as_py() is not None
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_pyarrow_methods(test_config: Config):
-    """Test that returned Arrow table supports PyArrow methods."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query(
-                """
-                SELECT 1 as id, 'test' as name
-                UNION ALL
-                SELECT 2, 'data'
-                """
-            )
-
-            arrow_table = result.to_arrow()
-
-            # Test PyArrow methods
-            assert arrow_table.num_rows == 2
-            assert arrow_table.num_columns == 2
-
-            # Test column access methods
-            col1 = arrow_table.column("id")
-            assert len(col1) == 2
-
-            # Test iteration
-            for i in range(arrow_table.num_rows):
-                row = arrow_table.take([i])
-                assert row.num_rows == 1
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_with_parameterized_query(test_config: Config):
-    """Test Arrow conversion with parameterized queries."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query(
-                "SELECT @P1 as param_value, @P2 as param_string",
-                [42, "test string"],
-            )
-
-            arrow_table = result.to_arrow()
-
-            assert arrow_table.num_rows == 1
-            assert arrow_table["param_value"][0].as_py() == 42
-            assert arrow_table["param_string"][0].as_py() == "test string"
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_null_handling_comprehensive(test_config: Config):
-    """Test comprehensive null value handling in Arrow conversion."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query(
-                """
-                SELECT
-                    NULL as null_int,
-                    NULL as null_float,
-                    NULL as null_string,
-                    1 as val1,
-                    'notNull' as val2,
-                    NULL as val3,
-                    42 as val4
-                """
-            )
-
-            arrow_table = result.to_arrow()
-
-            assert arrow_table.num_rows == 1
-
-            # Check nulls
-            assert arrow_table["null_int"][0].as_py() is None
-            assert arrow_table["null_float"][0].as_py() is None
-            assert arrow_table["null_string"][0].as_py() is None
-
-            # Check non-nulls
-            assert arrow_table["val1"][0].as_py() == 1
-            assert arrow_table["val2"][0].as_py() == "notNull"
-            assert arrow_table["val3"][0].as_py() is None
-            assert arrow_table["val4"][0].as_py() == 42
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_mixed_types_single_row(test_config: Config):
-    """Test Arrow conversion with mixed data types in single row."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query(
-                """
-                SELECT
-                    1 as int_col,
-                    CAST(3.14 as REAL) as float_col,
-                    'mixed' as string_col,
-                    CAST(1 as BIT) as bool_col,
-                    NULL as null_col,
-                    CAST(99.99 as MONEY) as money_col
-                """
-            )
-
-            arrow_table = result.to_arrow()
-
-            assert arrow_table.num_rows == 1
-            assert len(arrow_table.column_names) == 6
-
-            # Verify each column
-            assert arrow_table["int_col"][0].as_py() == 1
-            float_val = arrow_table["float_col"][0].as_py()
-            assert float_val is not None
-            assert arrow_table["string_col"][0].as_py() == "mixed"
-            # Bool might be stored as int(1) or bool(True)
-            bool_val = arrow_table["bool_col"][0].as_py()
-            assert bool_val in [True, 1]
-            assert arrow_table["null_col"][0].as_py() is None
-            # Money value should be present
-            money_val = arrow_table["money_col"][0].as_py()
-            assert money_val is not None
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_arrow_consistency_with_rows(test_config: Config):
-    """Test that Arrow conversion is consistent with rows() data."""
-    try:
-        async with Connection(test_config.connection_string) as conn:
-            result = await conn.query(
-                """
-                SELECT 1 as id, 'first' as name
-                UNION ALL
-                SELECT 2, 'second'
-                """
-            )
-
-            # Get traditional rows
-            rows = result.rows()
-
-            # Reset and get Arrow
-            result_arrow = await conn.query(
-                """
-                SELECT 1 as id, 'first' as name
-                UNION ALL
-                SELECT 2, 'second'
-                """
-            )
-            arrow_table = result_arrow.to_arrow()
-
-            # Verify consistency
-            assert len(rows) == arrow_table.num_rows
-
-            for i, row in enumerate(rows):
-                assert row["id"] == arrow_table["id"][i].as_py()
-                assert row["name"] == arrow_table["name"][i].as_py()
-    except Exception as e:
-        pytest.fail(f"Test failed: {e}")
diff --git a/uv.lock b/uv.lock
index bd6c427..d7ff5b1 100644
--- a/uv.lock
+++ b/uv.lock
@@ -45,7 +45,7 @@ wheels = [
 
 [[package]]
 name = "cibuildwheel"
-version = "3.4.1"
+version = "4.1.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "bashlex" },
@@ -56,14 +56,11 @@ dependencies = [
     { name = "filelock" },
     { name = "humanize" },
     { name = "packaging" },
-    { name = "patchelf", marker = "(platform_machine == 'aarch64' and sys_platform == 'darwin') or (platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'arm64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" },
     { name = "platformdirs" },
-    { name = "pyelftools" },
-    { name = "wheel" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/63/b7/39dd5772a7893639e614a33c3e372eb1ca3792a536de5c5aff6d1bddc25b/cibuildwheel-3.4.1.tar.gz", hash = "sha256:c3ba783013e190849bb2d22e49359a911e368daebab8b02e3996320ab9315d34", size = 366686, upload-time = "2026-04-02T13:59:01.22Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/3f/ae/135d31add82bb22eb49e3828726e71150be45013802becb2992956b8e655/cibuildwheel-4.1.0.tar.gz", hash = "sha256:aac6f526c0c06039feedd09f9bbceb989ab244ef0543eaea84c8abdeafb81858", size = 446157, upload-time = "2026-06-12T16:04:02.921Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/73/3f/20c00404a019b19f1d317f78a8364db3d86021c6c921d0969d1be9067051/cibuildwheel-4.1.0-py3-none-any.whl", hash = "sha256:b9dabe7713f16aec4e7064d031daa2da010e7431d58964e0b97b3eb346952454", size = 164664, upload-time = "2026-06-12T16:04:01.25Z" },
 ]
 
 [package.optional-dependencies]
@@ -103,21 +100,15 @@ wheels = [
 
 [[package]]
 name = "fastmssql"
-version = "0.7.3"
+version = "0.7.4"
 source = { editable = "." }
 
-[package.optional-dependencies]
-arrow = [
-    { name = "pyarrow" },
-]
-
 [package.dev-dependencies]
 dev = [
     { name = "cibuildwheel", extra = ["uv"] },
     { name = "filelock" },
     { name = "maturin" },
     { name = "psutil" },
-    { name = "pyarrow" },
     { name = "pytest" },
     { name = "pytest-asyncio" },
     { name = "pytest-timeout" },
@@ -129,33 +120,30 @@ dev = [
 ]
 
 [package.metadata]
-requires-dist = [{ name = "pyarrow", marker = "extra == 'arrow'", specifier = ">=13.0.0" }]
-provides-extras = ["arrow"]
 
 [package.metadata.requires-dev]
 dev = [
-    { name = "cibuildwheel", extras = ["uv"], specifier = ">=3.4.1" },
-    { name = "filelock", specifier = "==3.29.0" },
-    { name = "maturin", specifier = "==1.13.1" },
+    { name = "cibuildwheel", extras = ["uv"], specifier = ">=4.1.0" },
+    { name = "filelock", specifier = "==3.29.5" },
+    { name = "maturin", specifier = "==1.14.1" },
     { name = "psutil", specifier = "==7.2.2" },
-    { name = "pyarrow", specifier = "==23.0.1" },
-    { name = "pytest", specifier = "==9.0.3" },
-    { name = "pytest-asyncio", specifier = "==1.3.0" },
+    { name = "pytest", specifier = "==9.1.1" },
+    { name = "pytest-asyncio", specifier = "==1.4.0" },
     { name = "pytest-timeout", specifier = "==2.4.0" },
     { name = "pytest-xdist", specifier = "==3.8.0" },
     { name = "python-dotenv", specifier = "==1.2.2" },
-    { name = "ruff", specifier = ">=0.15.11" },
+    { name = "ruff", specifier = ">=0.15.20" },
     { name = "uvloop", specifier = "==0.22.1" },
     { name = "wheel", specifier = "==0.47.0" },
 ]
 
 [[package]]
 name = "filelock"
-version = "3.29.0"
+version = "3.29.5"
 source = { registry = "https://pypi.org/simple" }
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 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/4a/e3/f1fae3647d170919c2cf2a898e77e7d1a4e5c7cae0aed7bb4bd3f5ebff6f/filelock-3.29.5-py3-none-any.whl", hash = "sha256:8af830889ba3a0ffcefbd6c7d2af8a54012058103771f2e10848222f476a1693", size = 45073, upload-time = "2026-07-03T03:50:30.445Z" },
 ]
 
 [[package]]
@@ -178,23 +166,23 @@ wheels = [
 
 [[package]]
 name = "maturin"
-version = "1.13.1"
+version = "1.14.1"
 source = { registry = "https://pypi.org/simple" }
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