Pandas on Spark refactor

.github/workflows/test-package.yml

@@ -19,11 +19,10 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: [3.8, 3.9, '3.10', '3.11']
-        spark-version: [3.1.3, 3.2.4, 3.3.4, 3.4.2, 3.5.0]
+        python-version: [3.9, '3.10', '3.11']
+        spark-version: [3.2.4, 3.3.4, 3.4.2, 3.5.1]
+        pandas-version: [2.2.1, 1.5.3]
         exclude:
-          - python-version: '3.11'
-            spark-version: 3.1.3
           - python-version: '3.11'
             spark-version: 3.2.4
           - python-version: '3.11'
@@ -51,6 +50,7 @@ jobs:
         python -m pip install --upgrade pip
         python -m pip install pytest pytest-spark pypandoc
         python -m pip install pyspark==${{ matrix.spark-version }}
+        python -m pip install pandas==${{ matrix.pandas-version }}
         python -m pip install .[dev]
     - name: Test with pytest
       run: |
@@ -62,7 +62,8 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: [3.8, 3.9, '3.10', '3.11']
+        python-version: [3.9, '3.10', '3.11']
+
     env:
       PYTHON_VERSION: ${{ matrix.python-version }}
 
@@ -88,7 +89,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: [3.8, 3.9, '3.10', '3.11']
+        python-version: [3.9, '3.10', '3.11']
     env:
       PYTHON_VERSION: ${{ matrix.python-version }}
 

README.md

@@ -38,16 +38,44 @@ pip install datacompy[ray]
 
 ```
 
-### In-scope Spark versions
-Different versions of Spark play nicely with only certain versions of Python below is a matrix of what we test with
+### Legacy Spark Deprecation
+
+#### Starting with version 0.12.0
+
+The original ``SparkCompare`` implementation differs from all the other native implementations. To align the API better, and keep behaviour consistent we are deprecating ``SparkCompare`` into a new module ``LegacySparkCompare``
+
+If you wish to use the old SparkCompare moving forward you can
+
+```python
+import datacompy.legacy.LegacySparkCompare
+``` 
+
+#### Supported versions and dependncies
+
+Different versions of Spark, Pandas, and Python interact differently. Below is a matrix of what we test with. 
+With the move to Pandas on Spark API and compatability issues with Pandas 2+ we will for the mean time note support Pandas 2 
+with the Pandas on Spark implementation. Spark plans to support Pandas 2 in [Spark 4](https://issues.apache.org/jira/browse/SPARK-44101)
+
+With version ``0.12.0``:
+- Not support Pandas ``2.0.0`` For the native Spark implemention
+- Spark ``3.1`` support will be dropped
+- Python ``3.8`` support is dropped
+
+
+|             | Spark 3.2.4 | Spark 3.3.4 | Spark 3.4.2 | Spark 3.5.1 |
+|-------------|-------------|-------------|-------------|-------------|
+| Python 3.9  | ✅           | ✅           | ✅           | ✅           |
+| Python 3.10 | ✅           | ✅           | ✅           | ✅           |
+| Python 3.11 | ❌           | ❌           | ✅           | ✅           |
+| Python 3.12 | ❌           | ❌           | ❌           | ❌           |
+
+
+|               | Pandas < 1.5.3 | Pandas >=2.0.0 |
+|---------------|----------------|----------------|
+| Native Pandas | ✅              | ✅              |
+| Native Spark  | ✅              | ❌              |
+| Fugue         | ✅              | ✅              |
 
-|             | Spark 3.1.3  | Spark 3.2.3 | Spark 3.3.4 | Spark 3.4.2 | Spark 3.5.0 |
-|-------------|--------------|-------------|-------------|-------------|-------------|
-| Python 3.8  | ✅           | ✅           | ✅           | ✅          | ✅          |
-| Python 3.9  | ✅           | ✅           | ✅           | ✅          | ✅          |
-| Python 3.10 | ✅           | ✅           | ✅           | ✅          | ✅          |
-| Python 3.11 | ❌           | ❌           | ❌           | ✅          | ✅          |
-| Python 3.12 | ❌           | ❌           | ❌           | ❌          | ❌          |
 
 
 > [!NOTE]
@@ -56,7 +84,7 @@ Different versions of Spark play nicely with only certain versions of Python bel
 ## Supported backends
 
 - Pandas: ([See documentation](https://capitalone.github.io/datacompy/pandas_usage.html))
-- Spark: ([See documentation](https://capitalone.github.io/datacompy/spark_usage.html))
+- Spark (Pandas on Spark API): ([See documentation](https://capitalone.github.io/datacompy/spark_usage.html))
 - Polars (Experimental): ([See documentation](https://capitalone.github.io/datacompy/polars_usage.html))
 - Fugue is a Python library that provides a unified interface for data processing on Pandas, DuckDB, Polars, Arrow,
   Spark, Dask, Ray, and many other backends. DataComPy integrates with Fugue to provide a simple way to compare data

datacompy/__init__.py

@@ -13,7 +13,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-__version__ = "0.11.3"
+__version__ = "0.12.0"
 
 from datacompy.core import *
 from datacompy.fugue import (
@@ -25,4 +25,4 @@
     unq_columns,
 )
 from datacompy.polars import PolarsCompare
-from datacompy.spark import NUMERIC_SPARK_TYPES, SparkCompare
+from datacompy.spark import SparkCompare