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from typing import Any, Iterator, Literal
from langchain_core.documents import Document
from langchain_community.document_loaders.base import BaseLoader
class BaseDataFrameLoader(BaseLoader):
def __init__(self, data_frame: Any, *, page_content_column: str = "text"):
"""Initialize with dataframe object.
Args:
data_frame: DataFrame object.
page_content_column: Name of the column containing the page content.
Defaults to "text".
"""
self.data_frame = data_frame
self.page_content_column = page_content_column
def lazy_load(self) -> Iterator[Document]:
"""Lazy load records from dataframe."""
for _, row in self.data_frame.iterrows():
text = row[self.page_content_column]
metadata = row.to_dict()
metadata.pop(self.page_content_column)
yield Document(page_content=text, metadata=metadata)
class DataFrameLoader(BaseDataFrameLoader):
"""Load `Pandas` DataFrame."""
def __init__(
self,
data_frame: Any,
page_content_column: str = "text",
engine: Literal["pandas", "modin"] = "pandas",
):
"""Initialize with dataframe object.
Args:
data_frame: Pandas DataFrame object.
page_content_column: Name of the column containing the page content.
Defaults to "text".
"""
try:
if engine == "pandas":
import pandas as pd
elif engine == "modin":
import modin.pandas as pd
else:
raise ValueError(
f"Unsupported engine {engine}. Must be one of 'pandas', or 'modin'."
)
except ImportError as e:
raise ImportError(
"Unable to import pandas, please install with `pip install pandas`."
) from e
if not isinstance(data_frame, pd.DataFrame):
raise ValueError(
f"Expected data_frame to be a pd.DataFrame, got {type(data_frame)}"
)
super().__init__(data_frame, page_content_column=page_content_column)
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