Merge pull request #296 from capitalone/develop

v0.6.1

locopy/database.py

@@ -18,6 +18,9 @@
 
 import time
 
+import pandas
+import polars
+
 from locopy.errors import CredentialsError, DBError
 from locopy.logger import INFO, get_logger
 from locopy.utility import read_config_yaml
@@ -188,25 +191,25 @@ def column_names(self):
         except Exception:
             return [column[0].lower() for column in self.cursor.description]
 
-    def to_dataframe(self, size=None):
+    def to_dataframe(self, df_type="pandas", size=None):
         """Return a dataframe of the last query results.
 
-        This imports Pandas in here, so that it's not needed for other use cases.  This is just a
-        convenience method.
-
         Parameters
         ----------
+        df_type: Literal["pandas","polars"], optional
+            Output dataframe format. Defaults to pandas.
+
         size : int, optional
             Chunk size to fetch.  Defaults to None.
 
         Returns
         -------
-        pandas.DataFrame
+        pandas.DataFrame or polars.DataFrame
             Dataframe with lowercase column names.  Returns None if no fetched
             result.
         """
-        import pandas
-
+        if df_type not in ["pandas", "polars"]:
+            raise ValueError("df_type must be ``pandas`` or ``polars``.")
         columns = self.column_names()
 
         if size is None:
@@ -220,7 +223,11 @@ def to_dataframe(self, size=None):
 
         if len(fetched) == 0:
             return None
-        return pandas.DataFrame(fetched, columns=columns)
+
+        if df_type == "pandas":
+            return pandas.DataFrame(fetched, columns=columns)
+        elif df_type == "polars":
+            return polars.DataFrame(fetched, schema=columns, orient="row")
 
     def to_dict(self):
         """Generate dictionaries of rows.

locopy/redshift.py

@@ -21,8 +21,13 @@
 """
 
 import os
+from functools import singledispatch
 from pathlib import Path
 
+import pandas as pd
+import polars as pl
+import polars.selectors as cs
+
 from locopy.database import Database
 from locopy.errors import DBError, S3CredentialsError
 from locopy.logger import INFO, get_logger
@@ -537,14 +542,14 @@ def insert_dataframe_to_table(
         verbose=False,
     ):
         """
-        Insert a Pandas dataframe to an existing table or a new table.
+        Insert a Pandas or Polars dataframe to an existing table or a new table.
 
         `executemany` in psycopg2 and pg8000 has very poor performance in terms of running speed.
         To overcome this issue, we instead format the insert query and then run `execute`.
 
         Parameters
         ----------
-        dataframe: Pandas Dataframe
+        dataframe: pandas.DataFrame or polars.DataFrame
             The pandas dataframe which needs to be inserted.
 
         table_name: str
@@ -567,8 +572,6 @@ def insert_dataframe_to_table(
 
 
         """
-        import pandas as pd
-
         if columns:
             dataframe = dataframe[columns]
 
@@ -599,9 +602,15 @@ def insert_dataframe_to_table(
             self.execute(create_query)
             logger.info("New table has been created")
 
-        logger.info("Inserting records...")
-        for start in range(0, len(dataframe), batch_size):
-            # create a list of tuples for insert
+        # create a list of tuples for insert
+        @singledispatch
+        def get_insert_tuple(dataframe, start, batch_size):
+            """Create a list of tuples for insert."""
+            pass
+
+        @get_insert_tuple.register(pd.DataFrame)
+        def get_insert_tuple_pandas(dataframe: pd.DataFrame, start, batch_size):
+            """Create a list of tuples for insert when dataframe is pd.DataFrame."""
             to_insert = []
             for row in dataframe[start : (start + batch_size)].itertuples(index=False):
                 none_row = (
@@ -617,9 +626,43 @@ def insert_dataframe_to_table(
                     + ")"
                 )
                 to_insert.append(none_row)
-            string_join = ", ".join(to_insert)
-            insert_query = (
-                f"""INSERT INTO {table_name} {column_sql} VALUES {string_join}"""
+            return to_insert
+
+        @get_insert_tuple.register(pl.DataFrame)
+        def get_insert_tuple_polars(dataframe: pl.DataFrame, start, batch_size):
+            """Create a list of tuples for insert when dataframe is pl.DataFrame."""
+            to_insert = []
+            dataframe = dataframe.with_columns(
+                dataframe.select(cs.numeric().fill_nan(None))
             )
-            self.execute(insert_query, verbose=verbose)
+            for row in dataframe[start : (start + batch_size)].iter_rows():
+                none_row = (
+                    "("
+                    + ", ".join(
+                        [
+                            "NULL"
+                            if val is None
+                            else "'" + str(val).replace("'", "''") + "'"
+                            for val in row
+                        ]
+                    )
+                    + ")"
+                )
+                to_insert.append(none_row)
+            return to_insert
+
+        logger.info("Inserting records...")
+        try:
+            for start in range(0, len(dataframe), batch_size):
+                to_insert = get_insert_tuple(dataframe, start, batch_size)
+                string_join = ", ".join(to_insert)
+                insert_query = (
+                    f"""INSERT INTO {table_name} {column_sql} VALUES {string_join}"""
+                )
+                self.execute(insert_query, verbose=verbose)
+        except TypeError:
+            raise TypeError(
+                "DataFrame to insert must either be a pandas.DataFrame or polars.DataFrame."
+            ) from None
+
         logger.info("Table insertion has completed")

locopy/snowflake.py

@@ -21,8 +21,13 @@
 """
 
 import os
+from functools import singledispatch
 from pathlib import PurePath
 
+import pandas as pd
+import polars as pl
+import polars.selectors as cs
+
 from locopy.database import Database
 from locopy.errors import DBError, S3CredentialsError
 from locopy.logger import INFO, get_logger
@@ -396,7 +401,7 @@ def unload(
     def insert_dataframe_to_table(
         self, dataframe, table_name, columns=None, create=False, metadata=None
     ):
-        """Insert a Pandas dataframe to an existing table or a new table.
+        """Insert a Pandas or Polars dataframe to an existing table or a new table.
 
         In newer versions of the
         python snowflake connector (v2.1.2+) users can call the ``write_pandas`` method from the cursor
@@ -408,8 +413,8 @@ def insert_dataframe_to_table(
 
         Parameters
         ----------
-        dataframe: Pandas Dataframe
-            The pandas dataframe which needs to be inserted.
+        dataframe: Pandas or Polars Dataframe
+            The pandas or polars dataframe which needs to be inserted.
 
         table_name: str
             The name of the Snowflake table which is being inserted.
@@ -423,8 +428,6 @@ def insert_dataframe_to_table(
         metadata: dictionary, optional
             If metadata==None, it will be generated based on data
         """
-        import pandas as pd
-
         if columns:
             dataframe = dataframe[columns]
 
@@ -433,10 +436,39 @@ def insert_dataframe_to_table(
         string_join = "(" + ",".join(["%s"] * len(all_columns)) + ")"
 
         # create a list of tuples for insert
-        to_insert = []
-        for row in dataframe.itertuples(index=False):
-            none_row = tuple(None if pd.isnull(val) else str(val) for val in row)
-            to_insert.append(none_row)
+        @singledispatch
+        def get_insert_tuple(dataframe):
+            """Create a list of tuples for insert."""
+            pass
+
+        @get_insert_tuple.register(pd.DataFrame)
+        def get_insert_tuple_pandas(dataframe: pd.DataFrame):
+            """Create a list of tuples for insert when dataframe is pd.DataFrame."""
+            to_insert = []
+            for row in dataframe.itertuples(index=False):
+                none_row = tuple(None if pd.isnull(val) else str(val) for val in row)
+                to_insert.append(none_row)
+            return to_insert
+
+        @get_insert_tuple.register(pl.DataFrame)
+        def get_insert_tuple_polars(dataframe: pl.DataFrame):
+            """Create a list of tuples for insert when dataframe is pl.DataFrame."""
+            to_insert = []
+            dataframe = dataframe.with_columns(
+                dataframe.select(cs.numeric().fill_nan(None))
+            )
+            for row in dataframe.iter_rows():
+                none_row = tuple(None if val is None else str(val) for val in row)
+                to_insert.append(none_row)
+            return to_insert
+
+        # create a list of tuples for insert
+        try:
+            to_insert = get_insert_tuple(dataframe)
+        except TypeError:
+            raise TypeError(
+                "DataFrame to insert must either be a pandas.DataFrame or polars.DataFrame."
+            ) from None
 
         if not create and metadata:
             logger.warning("Metadata will not be used because create is set to False.")
@@ -468,7 +500,7 @@ def insert_dataframe_to_table(
         self.execute(insert_query, params=to_insert, many=True)
         logger.info("Table insertion has completed")
 
-    def to_dataframe(self, size=None):
+    def to_dataframe(self, df_type="pandas", size=None):
         """Return a dataframe of the last query results.
 
         This is just a convenience method. This
@@ -479,16 +511,25 @@ def to_dataframe(self, size=None):
 
         Parameters
         ----------
+        df_type: Literal["pandas","polars"], optional
+            Output dataframe format. Defaults to pandas.
+
         size : int, optional
             Chunk size to fetch.  Defaults to None.
 
         Returns
         -------
-        pandas.DataFrame
+        pandas.DataFrame or polars.DataFrame
             Dataframe with lowercase column names.  Returns None if no fetched
             result.
         """
+        if df_type not in ["pandas", "polars"]:
+            raise ValueError("df_type must be ``pandas`` or ``polars``.")
+
         if size is None and self.cursor._query_result_format == "arrow":
-            return self.cursor.fetch_pandas_all()
+            if df_type == "pandas":
+                return self.cursor.fetch_pandas_all()
+            elif df_type == "polars":
+                return pl.from_arrow(self.cursor.fetch_arrow_all())
         else:
-            return super().to_dataframe(size)
+            return super().to_dataframe(df_type=df_type, size=size)