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58 lines
1.8 KiB
Python
58 lines
1.8 KiB
Python
"""Pandas Excel reader.
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Pandas parser for .xlsx files.
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"""
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from pathlib import Path
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from typing import Any, Dict, List, Optional
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from llama_index.readers.base import BaseReader
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from llama_index.readers.schema.base import Document
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class PandasExcelReader(BaseReader):
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r"""Pandas-based CSV parser.
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Parses CSVs using the separator detection from Pandas `read_csv`function.
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If special parameters are required, use the `pandas_config` dict.
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Args:
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pandas_config (dict): Options for the `pandas.read_excel` function call.
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Refer to https://pandas.pydata.org/docs/reference/api/pandas.read_excel.html
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for more information. Set to empty dict by default, this means defaults will be used.
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"""
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def __init__(
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self,
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*args: Any,
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pandas_config: dict = {},
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**kwargs: Any
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) -> None:
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"""Init params."""
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super().__init__(*args, **kwargs)
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self._pandas_config = pandas_config
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def load_data(
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self, file: Path, column_name: str, extra_info: Optional[Dict] = None
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) -> List[Document]:
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"""Parse file and extract values from a specific column.
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Args:
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file (Path): The path to the Excel file to read.
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column_name (str): The name of the column to use when creating the Document objects.
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Returns:
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List[Document]: A list of`Document objects containing the values from the specified column in the Excel file.
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"""
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import pandas as pd
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df = pd.read_excel(file, **self._pandas_config)
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text_list = df[column_name].astype(str).tolist()
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if self._concat_rows:
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return [Document((self._row_joiner).join(text_list), extra_info=extra_info)]
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else:
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return [Document(text, extra_info=extra_info) for text in text_list]
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