expose row_limit

README.md

@@ -9,7 +9,7 @@ Use of this project with Salesforce is subject to the [TERMS OF USE](./TERMS_OF_
 ## Prerequisites
 
 - **Python 3.11 only** (currently supported version - if your system version is different, we recommend using [pyenv](https://github.com/pyenv/pyenv) to configure 3.11)
-- [Azul Zulu OpenJDK 17.x](https://www.azul.com/downloads/?version=java-17-lts&package=jdk#zulu)
+- JDK 17
 - Docker support like [Docker Desktop](https://docs.docker.com/desktop/)
 - A salesforce org with some DLOs or DMOs with data and this feature enabled (it is not GA)
 - An [External Client App](#creating-an-external-client-app)

src/datacustomcode/client.py

@@ -185,29 +185,31 @@ def _new_function_client(cls) -> Client:
         )
         return cls._instance
 
-    def read_dlo(self, name: str) -> PySparkDataFrame:
+    def read_dlo(self, name: str, row_limit: int = 1000) -> PySparkDataFrame:
         """Read a DLO from Data Cloud.
 
         Args:
             name: The name of the DLO to read.
+            row_limit: Maximum number of rows to fetch (default: 1000).
 
         Returns:
             A PySpark DataFrame containing the DLO data.
         """
         self._record_dlo_access(name)
-        return self._reader.read_dlo(name)
+        return self._reader.read_dlo(name, row_limit=row_limit)
 
-    def read_dmo(self, name: str) -> PySparkDataFrame:
+    def read_dmo(self, name: str, row_limit: int = 1000) -> PySparkDataFrame:
         """Read a DMO from Data Cloud.
 
         Args:
             name: The name of the DMO to read.
+            row_limit: Maximum number of rows to fetch (default: 1000).
 
         Returns:
             A PySpark DataFrame containing the DMO data.
         """
         self._record_dmo_access(name)
-        return self._reader.read_dmo(name)
+        return self._reader.read_dmo(name, row_limit=row_limit)
 
     def write_to_dlo(
         self, name: str, dataframe: PySparkDataFrame, write_mode: WriteMode, **kwargs

src/datacustomcode/io/reader/base.py

@@ -15,20 +15,31 @@
 from __future__ import annotations
 
 from abc import abstractmethod
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Union
 
 from datacustomcode.io.base import BaseDataAccessLayer
 
 if TYPE_CHECKING:
     from pyspark.sql import DataFrame as PySparkDataFrame, SparkSession
+    from pyspark.sql.types import AtomicType, StructType
 
 
 class BaseDataCloudReader(BaseDataAccessLayer):
     def __init__(self, spark: SparkSession):
         self.spark = spark
 
     @abstractmethod
-    def read_dlo(self, name: str) -> PySparkDataFrame: ...
+    def read_dlo(
+        self,
+        name: str,
+        schema: Union[AtomicType, StructType, str, None] = None,
+        row_limit: int = 1000,
+    ) -> PySparkDataFrame: ...
 
     @abstractmethod
-    def read_dmo(self, name: str) -> PySparkDataFrame: ...
+    def read_dmo(
+        self,
+        name: str,
+        schema: Union[AtomicType, StructType, str, None] = None,
+        row_limit: int = 1000,
+    ) -> PySparkDataFrame: ...

tests/io/reader/test_query_api.py

@@ -277,3 +277,27 @@ def test_read_dmo_with_schema(
         reader_without_init.spark.createDataFrame.assert_called_once()
         args, _ = reader_without_init.spark.createDataFrame.call_args
         assert args[1] is custom_schema
+
+    def test_read_dlo_with_custom_row_limit(
+        self, reader_without_init, mock_connection, mock_pandas_dataframe
+    ):
+        """Test read_dlo method with custom row_limit."""
+        reader_without_init._conn = mock_connection
+
+        reader_without_init.read_dlo("test_dlo", row_limit=50)
+
+        mock_connection.get_pandas_dataframe.assert_called_once_with(
+            SQL_QUERY_TEMPLATE.format("test_dlo", 50)
+        )
+
+    def test_read_dmo_with_custom_row_limit(
+        self, reader_without_init, mock_connection, mock_pandas_dataframe
+    ):
+        """Test read_dmo method with custom row_limit."""
+        reader_without_init._conn = mock_connection
+
+        reader_without_init.read_dmo("test_dmo", row_limit=25)
+
+        mock_connection.get_pandas_dataframe.assert_called_once_with(
+            SQL_QUERY_TEMPLATE.format("test_dmo", 25)
+        )

tests/test_client.py

@@ -25,11 +25,11 @@ class MockDataCloudReader(BaseDataCloudReader):
 
     CONFIG_NAME = "MockDataCloudReader"
 
-    def read_dlo(self, name: str) -> DataFrame:
+    def read_dlo(self, name: str, schema=None, row_limit: int = 1000) -> DataFrame:
         df = MagicMock(spec=DataFrame)
         return df
 
-    def read_dmo(self, name: str) -> DataFrame:
+    def read_dmo(self, name: str, schema=None, row_limit: int = 1000) -> DataFrame:
         df = MagicMock(spec=DataFrame)
         return df
 
@@ -153,7 +153,7 @@ def test_read_dlo(self, reset_client, mock_spark, mock_proxy):
         client = Client(reader=reader, writer=writer, proxy=mock_proxy)
         result = client.read_dlo("test_dlo")
 
-        reader.read_dlo.assert_called_once_with("test_dlo")
+        reader.read_dlo.assert_called_once_with("test_dlo", row_limit=1000)
         assert result is mock_df
         assert "test_dlo" in client._data_layer_history[DataCloudObjectType.DLO]
 
@@ -166,7 +166,7 @@ def test_read_dmo(self, reset_client, mock_spark, mock_proxy):
         client = Client(reader=reader, writer=writer, proxy=mock_proxy)
         result = client.read_dmo("test_dmo")
 
-        reader.read_dmo.assert_called_once_with("test_dmo")
+        reader.read_dmo.assert_called_once_with("test_dmo", row_limit=1000)
         assert result is mock_df
         assert "test_dmo" in client._data_layer_history[DataCloudObjectType.DMO]
 
@@ -238,7 +238,7 @@ def test_read_pattern_flow(self, reset_client, mock_spark, mock_proxy):
         df = client.read_dlo("source_dlo")
         client.write_to_dlo("target_dlo", df, WriteMode.APPEND)
 
-        reader.read_dlo.assert_called_once_with("source_dlo")
+        reader.read_dlo.assert_called_once_with("source_dlo", row_limit=1000)
         writer.write_to_dlo.assert_called_once_with(
             "target_dlo", mock_df, WriteMode.APPEND
         )
@@ -253,13 +253,41 @@ def test_read_pattern_flow(self, reset_client, mock_spark, mock_proxy):
         df = client.read_dmo("source_dmo")
         client.write_to_dmo("target_dmo", df, WriteMode.MERGE)
 
-        reader.read_dmo.assert_called_once_with("source_dmo")
+        reader.read_dmo.assert_called_once_with("source_dmo", row_limit=1000)
         writer.write_to_dmo.assert_called_once_with(
             "target_dmo", mock_df, WriteMode.MERGE
         )
 
         assert "source_dmo" in client._data_layer_history[DataCloudObjectType.DMO]
 
+    def test_read_dlo_with_row_limit(self, reset_client, mock_spark, mock_proxy):
+        """Test that row_limit parameter is passed through to reader."""
+        reader = MagicMock(spec=BaseDataCloudReader)
+        writer = MagicMock(spec=BaseDataCloudWriter)
+        mock_df = MagicMock(spec=DataFrame)
+        reader.read_dlo.return_value = mock_df
+
+        client = Client(reader=reader, writer=writer, proxy=mock_proxy)
+        result = client.read_dlo("test_dlo", row_limit=500)
+
+        reader.read_dlo.assert_called_once_with("test_dlo", row_limit=500)
+        assert result is mock_df
+        assert "test_dlo" in client._data_layer_history[DataCloudObjectType.DLO]
+
+    def test_read_dmo_with_row_limit(self, reset_client, mock_spark, mock_proxy):
+        """Test that row_limit parameter is passed through to reader."""
+        reader = MagicMock(spec=BaseDataCloudReader)
+        writer = MagicMock(spec=BaseDataCloudWriter)
+        mock_df = MagicMock(spec=DataFrame)
+        reader.read_dmo.return_value = mock_df
+
+        client = Client(reader=reader, writer=writer, proxy=mock_proxy)
+        result = client.read_dmo("test_dmo", row_limit=100)
+
+        reader.read_dmo.assert_called_once_with("test_dmo", row_limit=100)
+        assert result is mock_df
+        assert "test_dmo" in client._data_layer_history[DataCloudObjectType.DMO]
+
 
 # Add tests for DefaultSparkSessionProvider
 class TestDefaultSparkSessionProvider: