chore: import upstream snapshot with attribution

application/parser/file/tabular_parser.py

@@ -0,0 +1,221 @@
+"""Tabular parser.
+
+Contains parsers for tabular data files.
+
+"""
+from pathlib import Path
+from typing import Any, Dict, List, Union
+
+from application.parser.file.base_parser import BaseParser
+
+
+class CSVParser(BaseParser):
+    """CSV parser.
+
+    Args:
+        concat_rows (bool): whether to concatenate all rows into one document.
+            If set to False, a Document will be created for each row.
+            True by default.
+
+    """
+
+    def __init__(self, *args: Any, concat_rows: bool = True, **kwargs: Any) -> None:
+        """Init params."""
+        super().__init__(*args, **kwargs)
+        self._concat_rows = concat_rows
+
+    def _init_parser(self) -> Dict:
+        """Init parser."""
+        return {}
+
+    def parse_file(self, file: Path, errors: str = "ignore") -> Union[str, List[str]]:
+        """Parse file.
+
+        Returns:
+            Union[str, List[str]]: a string or a List of strings.
+
+        """
+        try:
+            import csv
+        except ImportError:
+            raise ValueError("csv module is required to read CSV files.")
+        text_list = []
+        with open(file, "r") as fp:
+            csv_reader = csv.reader(fp)
+            for row in csv_reader:
+                text_list.append(", ".join(row))
+        if self._concat_rows:
+            return "\n".join(text_list)
+        else:
+            return text_list
+
+
+class PandasCSVParser(BaseParser):
+    r"""Pandas-based CSV parser.
+
+    Parses CSVs using the separator detection from Pandas `read_csv`function.
+    If special parameters are required, use the `pandas_config` dict.
+
+    Args:
+        concat_rows (bool): whether to concatenate all rows into one document.
+            If set to False, a Document will be created for each row.
+            True by default.
+
+        col_joiner (str): Separator to use for joining cols per row.
+            Set to ", " by default.
+
+        row_joiner (str): Separator to use for joining each row.
+            Only used when `concat_rows=True`.
+            Set to "\n" by default.
+
+        pandas_config (dict): Options for the `pandas.read_csv` function call.
+            Refer to https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html
+            for more information.
+            Set to empty dict by default, this means pandas will try to figure
+            out the separators, table head, etc. on its own.
+            
+        header_period (int): Controls how headers are included in output:
+            - 0: Headers only at the beginning
+            - 1: Headers in every row
+            - N > 1: Headers every N rows
+            
+        header_prefix (str): Prefix for header rows. Default is "HEADERS: ".
+    """
+
+    def __init__(
+            self,
+            *args: Any,
+            concat_rows: bool = True,
+            col_joiner: str = ", ",
+            row_joiner: str = "\n",
+            pandas_config: dict = {},
+            header_period: int = 20,
+            header_prefix: str = "HEADERS: ",
+            **kwargs: Any
+    ) -> None:
+        """Init params."""
+        super().__init__(*args, **kwargs)
+        self._concat_rows = concat_rows
+        self._col_joiner = col_joiner
+        self._row_joiner = row_joiner
+        self._pandas_config = pandas_config
+        self._header_period = header_period
+        self._header_prefix = header_prefix
+
+    def _init_parser(self) -> Dict:
+        """Init parser."""
+        return {}
+
+    def parse_file(self, file: Path, errors: str = "ignore") -> Union[str, List[str]]:
+        """Parse file."""
+        try:
+            import pandas as pd
+        except ImportError:
+            raise ValueError("pandas module is required to read CSV files.")
+
+        df = pd.read_csv(file, **self._pandas_config)
+        headers = df.columns.tolist()
+        header_row = f"{self._header_prefix}{self._col_joiner.join(headers)}"
+
+        if not self._concat_rows:
+            return df.apply(
+                lambda row: (self._col_joiner).join(row.astype(str).tolist()), axis=1
+            ).tolist()
+        
+        text_list = []
+        if self._header_period != 1:
+            text_list.append(header_row)
+        
+        for i, row in df.iterrows():
+            if (self._header_period > 1 and i > 0 and i % self._header_period == 0):
+                text_list.append(header_row)
+            text_list.append(self._col_joiner.join(row.astype(str).tolist()))
+            if self._header_period == 1 and i < len(df) - 1:
+                text_list.append(header_row)
+
+        return self._row_joiner.join(text_list)
+
+
+class ExcelParser(BaseParser):
+    r"""Excel (.xlsx) parser.
+
+    Parses Excel files using Pandas `read_excel` function.
+    If special parameters are required, use the `pandas_config` dict.
+
+    Args:
+        concat_rows (bool): whether to concatenate all rows into one document.
+            If set to False, a Document will be created for each row.
+            True by default.
+
+        col_joiner (str): Separator to use for joining cols per row.
+            Set to ", " by default.
+
+        row_joiner (str): Separator to use for joining each row.
+            Only used when `concat_rows=True`.
+            Set to "\n" by default.
+
+        pandas_config (dict): Options for the `pandas.read_excel` function call.
+            Refer to https://pandas.pydata.org/docs/reference/api/pandas.read_excel.html
+            for more information.
+            Set to empty dict by default, this means pandas will try to figure
+            out the table structure on its own.
+            
+        header_period (int): Controls how headers are included in output:
+            - 0: Headers only at the beginning (default)
+            - 1: Headers in every row
+            - N > 1: Headers every N rows
+            
+        header_prefix (str): Prefix for header rows. Default is "HEADERS: ".
+    """
+
+    def __init__(
+            self,
+            *args: Any,
+            concat_rows: bool = True,
+            col_joiner: str = ", ",
+            row_joiner: str = "\n",
+            pandas_config: dict = {},
+            header_period: int = 20,
+            header_prefix: str = "HEADERS: ",
+            **kwargs: Any
+    ) -> None:
+        """Init params."""
+        super().__init__(*args, **kwargs)
+        self._concat_rows = concat_rows
+        self._col_joiner = col_joiner
+        self._row_joiner = row_joiner
+        self._pandas_config = pandas_config
+        self._header_period = header_period
+        self._header_prefix = header_prefix
+
+    def _init_parser(self) -> Dict:
+        """Init parser."""
+        return {}
+
+    def parse_file(self, file: Path, errors: str = "ignore") -> Union[str, List[str]]:
+        """Parse file."""
+        try:
+            import pandas as pd
+        except ImportError:
+            raise ValueError("pandas module is required to read Excel files.")
+
+        df = pd.read_excel(file, **self._pandas_config)
+        headers = df.columns.tolist()
+        header_row = f"{self._header_prefix}{self._col_joiner.join(headers)}"
+        
+        if not self._concat_rows:
+            return df.apply(
+                lambda row: (self._col_joiner).join(row.astype(str).tolist()), axis=1
+            ).tolist()
+        
+        text_list = []
+        if self._header_period != 1:
+            text_list.append(header_row)
+
+        for i, row in df.iterrows():
+            if (self._header_period > 1 and i > 0 and i % self._header_period == 0):
+                text_list.append(header_row)
+            text_list.append(self._col_joiner.join(row.astype(str).tolist()))
+            if self._header_period == 1 and i < len(df) - 1:
+                text_list.append(header_row)
+        return self._row_joiner.join(text_list)