Revert "Rebase to 302"

CHANGELOG.md

@@ -1,64 +1,24 @@
 # Release History
 
-# 3.0.2 (2024-01-25)
-
-- SQLAlchemy dialect now supports table and column comments (thanks @cbornet!)
-- Fix: SQLAlchemy dialect now correctly reflects TINYINT types (thanks @TimTheinAtTabs!)
-- Fix: `server_hostname` URIs that included `https://` would raise an exception
-- Other: pinned to `pandas<=2.1` and `urllib3>=1.26` to avoid runtime errors in dbt-databricks (#330)
-
-## 3.0.1 (2023-12-01)
-
-- Other: updated docstring comment about default parameterization approach (#287)
-- Other: added tests for reading complex types and revised docstrings and type hints (#293)
-- Fix: SQLAlchemy dialect raised DeprecationWarning due to `dbapi` classmethod (#294)
-- Fix: SQLAlchemy dialect could not reflect TIMESTAMP_NTZ columns (#296)
-
-## 3.0.0 (2023-11-17)
-
-- Remove support for Python 3.7
-- Add support for native parameterized SQL queries. Requires DBR 14.2 and above. See docs/parameters.md for more info.
-- Completely rewritten SQLAlchemy dialect
-  - Adds support for SQLAlchemy >= 2.0 and drops support for SQLAlchemy 1.x
-  - Full e2e test coverage of all supported features
-  - Detailed usage notes in `README.sqlalchemy.md`
-  - Adds support for:
-    - New types: `TIME`, `TIMESTAMP`, `TIMESTAMP_NTZ`, `TINYINT`
-    - `Numeric` type scale and precision, like `Numeric(10,2)`
-    - Reading and writing `PrimaryKeyConstraint` and `ForeignKeyConstraint`
-    - Reading and writing composite keys
-    - Reading and writing from views
-    - Writing `Identity` to tables (i.e. autoincrementing primary keys)
-    - `LIMIT` and `OFFSET` for paging through results
-    - Caching metadata calls
-- Enable cloud fetch by default. To disable, set `use_cloud_fetch=False` when building `databricks.sql.client`.
-- Add integration tests for Databricks UC Volumes ingestion queries
-- Retries:
-  - Add `_retry_max_redirects` config
-  - Set `_enable_v3_retries=True` and warn if users override it
-- Security: bump minimum pyarrow version to 14.0.1 (CVE-2023-47248)
+## 2.9.4 (Unreleased)
 
 ## 2.9.3 (2023-08-24)
 
 - Fix: Connections failed when urllib3~=1.0.0 is installed (#206)
 
 ## 2.9.2 (2023-08-17)
 
-__Note: this release was yanked from Pypi on 13 September 2023 due to compatibility issues with environments where `urllib3<=2.0.0` were installed. The log changes are incorporated into version 2.9.3 and greater.__
-
 - Other: Add `examples/v3_retries_query_execute.py` (#199)
 - Other: suppress log message when `_enable_v3_retries` is not `True` (#199)
 - Other: make this connector backwards compatible with `urllib3>=1.0.0` (#197)
 
 ## 2.9.1 (2023-08-11)
 
-__Note: this release was yanked from Pypi on 13 September 2023 due to compatibility issues with environments where `urllib3<=2.0.0` were installed.__
-
 - Other: Explicitly pin urllib3 to ^2.0.0 (#191)
 
 ## 2.9.0 (2023-08-10)
 
-- Replace retry handling with DatabricksRetryPolicy. This is disabled by default. To enable, set `_enable_v3_retries=True` when creating `databricks.sql.client` (#182)
+- Replace retry handling with DatabricksRetryPolicy. This is disabled by default. To enable, set `enable_v3_retries=True` when creating `databricks.sql.client` (#182)
 - Other: Fix typo in README quick start example (#186)
 - Other: Add autospec to Client mocks and tidy up `make_request` (#188)
 

CONTRIBUTING.md

@@ -107,8 +107,6 @@ End-to-end tests require a Databricks account. Before you can run them, you must
 export host=""
 export http_path=""
 export access_token=""
-export catalog=""
-export schema=""
 ```
 
 Or you can write these into a file called `test.env` in the root of the repository:
@@ -143,11 +141,6 @@ The `PySQLLargeQueriesSuite` namespace contains long-running query tests and is
 The `PySQLStagingIngestionTestSuite` namespace requires a cluster running DBR version > 12.x which supports staging ingestion commands.
 
 The suites marked `[not documented]` require additional configuration which will be documented at a later time.
-
-#### SQLAlchemy dialect tests
-
-See README.tests.md for details.
-
 ### Code formatting
 
 This project uses [Black](https://pypi.org/project/black/).

README.md

@@ -3,15 +3,15 @@
 [![PyPI](https://img.shields.io/pypi/v/databricks-sql-connector?style=flat-square)](https://pypi.org/project/databricks-sql-connector/)
 [![Downloads](https://pepy.tech/badge/databricks-sql-connector)](https://pepy.tech/project/databricks-sql-connector)
 
-The Databricks SQL Connector for Python allows you to develop Python applications that connect to Databricks clusters and SQL warehouses. It is a Thrift-based client with no dependencies on ODBC or JDBC. It conforms to the [Python DB API 2.0 specification](https://www.python.org/dev/peps/pep-0249/) and exposes a [SQLAlchemy](https://www.sqlalchemy.org/) dialect for use with tools like `pandas` and `alembic` which use SQLAlchemy to execute DDL. Use `pip install databricks-sql-connector[sqlalchemy]` to install with SQLAlchemy's dependencies. `pip install databricks-sql-connector[alembic]` will install alembic's dependencies.
+The Databricks SQL Connector for Python allows you to develop Python applications that connect to Databricks clusters and SQL warehouses. It is a Thrift-based client with no dependencies on ODBC or JDBC. It conforms to the [Python DB API 2.0 specification](https://www.python.org/dev/peps/pep-0249/) and exposes a [SQLAlchemy](https://www.sqlalchemy.org/) dialect for use with tools like `pandas` and `alembic` which use SQLAlchemy to execute DDL.
 
 This connector uses Arrow as the data-exchange format, and supports APIs to directly fetch Arrow tables. Arrow tables are wrapped in the `ArrowQueue` class to provide a natural API to get several rows at a time.
 
 You are welcome to file an issue here for general use cases. You can also contact Databricks Support [here](help.databricks.com).
 
 ## Requirements
 
-Python 3.8 or above is required.
+Python 3.7 or above is required.
 
 ## Documentation
 
@@ -47,7 +47,8 @@ connection = sql.connect(
   access_token=access_token)
 
 cursor = connection.cursor()
-cursor.execute('SELECT :param `p`, * FROM RANGE(10)', {"param": "foo"})
+
+cursor.execute('SELECT * FROM RANGE(10)')
 result = cursor.fetchall()
 for row in result:
   print(row)