prep release 0.9.0 (#552)

* prep release 0.9.0

* allow double quotes

Author: joe-clickhouse

CHANGELOG.md

@@ -22,36 +22,47 @@ instead of being passed as ClickHouse server settings. This is in conjunction wi
 The supported method of passing ClickHouse server settings is to prefix such arguments/query parameters with`ch_`.
 
 ## UNRELEASED
-- Add support for lightweight `DELETE` in sqlalchemy. Closes [#382](https://github.com/ClickHouse/clickhouse-connect/issues/382)
-- Added client connection option `rename_response_column` (default `None`) that allows the user to define how response columns are automatically renamed according to a predefined scheme. Helpful for stripping alias prefixes, etc. in potentially complex queries. Closes [#228](https://github.com/ClickHouse/clickhouse-connect/issues/228)
-- Add third-party library identifiers (name/version) in the User-Agent, e.g. pandas/2.2.5. Users can opt out by changing the common setting `send_integration_tags` to `False`.
-- Added support for form encoding query parameters when using HTTP interface. This addresses [#342](https://github.com/ClickHouse/clickhouse-connect/issues/342). Query parameters can now be sent as form-encoded data in the request body by setting `form_encode_query_params=True` when creating the client. This is particularly useful for queries with large parameter payloads that might exceed URL length limits.
-- Added Polars support for Arrow-based query and insert methods (query_df_arrow, query_df_arrow_stream, insert_df_arrow). This initial implementation provides basic dataframe conversion through the Arrow format, similar to how we support the pyarrow-backed pandas dataframes. Closes [#111](https://github.com/ClickHouse/clickhouse-connect/issues/111) and [#542](https://github.com/ClickHouse/clickhouse-connect/issues/542)
+
+
+## 0.9.0, 2025-09-16
+
+### Breaking Changes
+- **WARNING: BREAKING CHANGE** — Removed support for sqlalchemy 1.3 which reached its EOL in 2021. The minimum required version is now 1.4.40.
+- **WARNING: BREAKING CHANGE** — Behavior for reading from IPv6 columns has changed:
+  - With `read_format='native'`, the client will **always** return [`ipaddress.IPv6Address`](https://docs.python.org/3/library/ipaddress.html#ipaddress.IPv6Address) objects, even for IPv4-mapped addresses (e.g., `"::ffff:192.168.1.1"`). Previously, the client returned [`ipaddress.IPv4Address`](https://docs.python.org/3/library/ipaddress.html#ipaddress.IPv4Address) objects for these cases. This change enforces type consistency and avoids surprising implicit conversions. If your application requires IPv4 objects, you can explicitly convert using the [`ipv4_mapped`](https://docs.python.org/3/library/ipaddress.html#ipaddress.IPv6Address.ipv4_mapped) attribute of `IPv6Address`.
+  - With `read_format='string'`, the client will **always** return IPv6 string representations, e.g., `"::ffff:192.168.1.1"` instead of `"192.168.1.1"`, for the same reasons as above. If you require only the IPv4 string, you can parse or truncate this in your application code.
+  - Closes [#493](https://github.com/ClickHouse/clickhouse-connect/issues/493)
+
+### Major Features
 - Added support for SQLAlchemy 2.x. The minimum required version is 1.4.40. Closes [#263](https://github.com/ClickHouse/clickhouse-connect/issues/263)
-  - **WARNING: BREAKING CHANGE**: Removed support for sqlalchemy 1.3 which reached its EOL in 2021.
+- Added Polars support for Arrow-based query and insert methods (`query_df_arrow`, `query_df_arrow_stream`, `insert_df_arrow`). This initial implementation provides basic dataframe conversion through the Arrow format, similar to how we support the pyarrow-backed pandas dataframes. Closes [#111](https://github.com/ClickHouse/clickhouse-connect/issues/111) and [#542](https://github.com/ClickHouse/clickhouse-connect/issues/542)
 - Added support for querying/inserting pyarrow-backed DataFrames:
   - `query_df_arrow()`: returns a pandas DataFrame with PyArrow dtype backend. Note that Arrow data types are preserved without additional conversions.
   - `query_df_arrow_stream()`: Streaming version of `query_df_arrow()` for processing large result sets.
   - `insert_df_arrow()`: Optimized insertion method for pandas DataFrames with PyArrow backend, which should provide better performance than standard `insert_df()`.
+- Added Time and Time64 type support. Closes [#509](https://github.com/ClickHouse/clickhouse-connect/issues/509)
+- Support for both pandas 1.x and 2.x.
+- Added support for Nullable(JSON) types
+- Added support for BFloat16 types
+
+### Improvements
+- Add support for lightweight `DELETE` in sqlalchemy. Closes [#382](https://github.com/ClickHouse/clickhouse-connect/issues/382)
+- Added support for `SELECT`/`JOIN` operations via SQLAlchemy's core API (table operations and explicit statements--not ORM sessions-based queries)
+- Added client connection option `rename_response_column` (default `None`) that allows the user to define how response columns are automatically renamed according to a predefined scheme. Helpful for stripping alias prefixes, etc. in potentially complex queries. Closes [#228](https://github.com/ClickHouse/clickhouse-connect/issues/228)
+- Add third-party library identifiers (name/version) in the User-Agent, e.g. pandas/2.2.5. Users can opt out by changing the common setting `send_integration_tags` to `False`.
+- Added support for form encoding query parameters when using HTTP interface. This addresses [#342](https://github.com/ClickHouse/clickhouse-connect/issues/342). Query parameters can now be sent as form-encoded data in the request body by setting `form_encode_query_params=True` when creating the client. This is particularly useful for queries with large parameter payloads that might exceed URL length limits.
 - Added support for special [interval types](https://clickhouse.com/docs/en/sql-reference/data-types/special-data-types/interval). Closes [#391](https://github.com/ClickHouse/clickhouse-connect/issues/391)
-- Added new common setting option "preserve_pandas_datetime_resolution" (default is `False`) allowing pandas 2.x users to opt into (when set to `True`) using the additional pandas 2.x datetime64/timedelta64 resolutions of "s", "ms", "us". If set to `False` or using  pandas 1.x, all datetime64/timedelta64 resolutions will be coerced to "ns". (See [here](https://pandas.pydata.org/docs/whatsnew/v2.0.0.html#construction-with-datetime64-or-timedelta64-dtype-with-unsupported-resolution) for more info). Closes [#165](https://github.com/ClickHouse/clickhouse-connect/issues/165) and [#531](https://github.com/ClickHouse/clickhouse-connect/issues/531)
-- Support for both pandas 1.x and 2.x
-- Added pandas 1.x/2.x compatibility tests to CI
+- Added new common setting option "preserve_pandas_datetime_resolution" (default is `False`) allowing pandas 2.x users to opt into (when set to `True`) using the additional pandas 2.x datetime64/timedelta64 resolutions of "s", "ms", "us". If set to `False` or using pandas 1.x, all datetime64/timedelta64 resolutions will be coerced to "ns". (See [here](https://pandas.pydata.org/docs/whatsnew/v2.0.0.html#construction-with-datetime64-or-timedelta64-dtype-with-unsupported-resolution) for more info). Closes [#165](https://github.com/ClickHouse/clickhouse-connect/issues/165) and [#531](https://github.com/ClickHouse/clickhouse-connect/issues/531)
 - Tightens up type consistency of date-like objects when using `query_df`
-- Fixes problem with df inserts of Time and Time64 types. Closes [#524](https://github.com/ClickHouse/clickhouse-connect/issues/524)
-- Added Time and Time64 type support and relevant tests. Closes [#509](https://github.com/ClickHouse/clickhouse-connect/issues/509)
-- **WARNING: BREAKING CHANGE** — Behavior for reading from IPv6 columns has changed:
-  - With `read_format='native'`, the client will **always** return [`ipaddress.IPv6Address`](https://docs.python.org/3/library/ipaddress.html#ipaddress.IPv6Address) objects, even for IPv4-mapped addresses (e.g., `"::ffff:192.168.1.1"`). Previously, the client returned [`ipaddress.IPv4Address`](https://docs.python.org/3/library/ipaddress.html#ipaddress.IPv4Address) objects for these cases. This change enforces type consistency and avoids surprising implicit conversions. If your application requires IPv4 objects, you can explicitly convert using the [`ipv4_mapped`](https://docs.python.org/3/library/ipaddress.html#ipaddress.IPv6Address.ipv4_mapped) attribute of `IPv6Address`.
-  - With `read_format='string'`, the client will **always** return IPv6 string representations, e.g., `"::ffff:192.168.1.1"` instead of `"192.168.1.1"`, for the same reasons as above. If you require only the IPv4 string, you can parse or truncate this in your application code.
-  - Closes [#493](https://github.com/ClickHouse/clickhouse-connect/issues/493)
-- When writing to an IPv6 column type, the client will "promote" IPv4 addresses to IPv4-mapped IPv6 addresses to prevent write errors: Closes [#498](https://github.com/ClickHouse/clickhouse-connect/issues/498)
+- When writing to an IPv6 column type, the client will "promote" IPv4 addresses to IPv4-mapped IPv6 addresses to prevent write errors. Closes [#498](https://github.com/ClickHouse/clickhouse-connect/issues/498)
 - Changed `AsyncClient.settings` typing to `Optional[Dict[str, Any]]` to accept None inputs.
 - Added more robust error handling and tests. Closes [#508](https://github.com/ClickHouse/clickhouse-connect/issues/508)
-- Fixed an AttributeError on `http.client` when importing `clickhouse_connect` under certain circumstances
-- Added support for Nullable(JSON) types
-- Added support for BFloat16 types
 - Replace the use of deprecated `datetime.utcfromtimestamp`
 
+### Bug Fixes
+- Fixed an AttributeError on `http.client` when importing `clickhouse_connect` under certain circumstances
+- Fixes problem with df inserts of Time and Time64 types. Closes [#524](https://github.com/ClickHouse/clickhouse-connect/issues/524)
+
 ## 0.8.18, 2025-06-24
 
 ### Improvements

README.md

@@ -2,11 +2,12 @@
 
 A high performance core database driver for connecting ClickHouse to Python, Pandas, and Superset
 
-* Pandas DataFrames
+* Pandas DataFrames (numpy and arrow-backed)
 * Numpy Arrays
 * PyArrow Tables
+* Polars DataFrames
 * Superset Connector
-* SQLAlchemy 1.3 and 1.4 (limited feature set)
+* SQLAlchemy Core (select, joins, lightweight deletes; limited feature set)
 
 ClickHouse Connect currently uses the ClickHouse HTTP interface for maximum compatibility.
 
@@ -16,7 +17,7 @@ ClickHouse Connect currently uses the ClickHouse HTTP interface for maximum comp
 pip install clickhouse-connect
 ```
 
-ClickHouse Connect requires Python 3.8 or higher.
+ClickHouse Connect requires Python 3.9 or higher. We officially test against Python 3.9 through 3.13.
 
 ### Superset Connectivity
 
@@ -30,9 +31,17 @@ When creating a Superset Data Source, either use the provided connection dialog,
 
 ### SQLAlchemy Implementation
 
-ClickHouse Connect incorporates a minimal SQLAlchemy implementation (without any ORM features) for compatibility with
-Superset. It has only been tested against SQLAlchemy versions 1.3.x and 1.4.x, and is unlikely to work with more
-complex SQLAlchemy applications.
+ClickHouse Connect includes a lightweight SQLAlchemy dialect implementation focused on compatibility with **Superset**
+and **SQLAlchemy Core**.
+
+Supported features include:
+- Basic query execution via SQLAlchemy Core
+- `SELECT` queries with `JOIN`s
+- Lightweight `DELETE` statements
+
+The implementation does not include ORM support and is not intended as a full SQLAlchemy dialect. While it can support
+a range of Core-based applications beyond Superset, it may not be suitable for more complex SQLAlchemy applications
+that rely on full ORM or advanced dialect functionality.
 
 ### Asyncio Support
 
@@ -42,4 +51,4 @@ See the [run_async example](./examples/run_async.py) for more details.
 ### Complete Documentation
 
 The documentation for ClickHouse Connect has moved to
-[ClickHouse Docs](https://clickhouse.com/docs/integrations/python) 
+[ClickHouse Docs](https://clickhouse.com/docs/integrations/python)

clickhouse_connect/__version__.py

@@ -1 +1 @@
-version = '0.8.18'
+version = "0.9.0"

setup.py

@@ -37,7 +37,7 @@ def run_setup(try_c: bool = True):
     else:
         with open(os.path.join(project_dir, 'clickhouse_connect', '__version__.py'), encoding='utf-8') as version_file:
             file_version = version_file.read().strip()
-            match = re.search(r"version\s*=\s*'(.+)'", file_version)
+            match = re.search(r"version\s*=\s*['\"](.+)['\"]", file_version)
             if match is None:
                 raise ValueError(f'invalid version {file_version} in clickhouse_connect/__version__.py')
             version = match.group(1)