class_docstr: Handler for files
class_docstr_tok: ["Handler","for","files"]
docstr: @TODO: Use python-magic to simplify the function and detect the file types as the xlsx example
  This gets a file either url or local file and defines what the format is as well as dialect
  :param file: file path or url
  :return: data_io, format, dialect
code: def _get_data_io(file_path):
      """
      @TODO: Use python-magic to simplify the function and detect the file types as the xlsx example
      This gets a file either url or local file and defines what the format is as well as dialect
      :param file: file path or url
      :return: data_io, format, dialect
      """
  
      data = BytesIO()
      data_str = None
      dialect = None
  
      try:
          with open(file_path, "rb") as fp:
              data = BytesIO(fp.read())
      except Exception as e:
          error = "Could not load file, possible exception : {exception}".format(
              exception=e
          )
          logger.error(error)
          raise ValueError(error)
  
      suffix = Path(file_path).suffix.strip(".").lower()
      if suffix not in ("csv", "json", "xlsx", "parquet"):
          if FileHandler.is_it_parquet(data):
              suffix = "parquet"
          elif FileHandler.is_it_xlsx(file_path):
              suffix = "xlsx"
  
      if suffix == "parquet":
          return data, "parquet", dialect
  
      if suffix == "xlsx":
          return data, "xlsx", dialect
  
      if suffix == "txt":
          return data, "txt", dialect
  
      if suffix == "pdf":
          return data, "pdf", dialect
  
      byte_str = data.read()
      # Move it to StringIO
      try:
          # Handle Microsoft's BOM "special" UTF-8 encoding
          if byte_str.startswith(codecs.BOM_UTF8):
              data_str = StringIO(byte_str.decode("utf-8-sig"))
          else:
              file_encoding_meta = from_bytes(
                  byte_str[: 32 * 1024],
                  steps=32,  # Number of steps/block to extract from my_byte_str
                  chunk_size=1024,  # Set block size of each extraction)
                  explain=False,
              )
              best_meta = file_encoding_meta.best()
              errors = "strict"
              if best_meta is not None:
                  encoding = file_encoding_meta.best().encoding
  
                  try:
                      data_str = StringIO(
                          byte_str.decode(encoding, errors)
                      )
                  except UnicodeDecodeError:
                      encoding = "utf-8"
                      errors = "replace"
  
                      data_str = StringIO(
                          byte_str.decode(encoding, errors)
                      )
              else:
                  encoding = "utf-8"
                  errors = "replace"
  
                  data_str = StringIO(byte_str.decode(encoding, errors))
      except Exception:
          logger.error(traceback.format_exc())
          logger.error("Could not load into string")
  
      if suffix not in ("csv", "json"):
          if FileHandler.is_it_json(data_str):
              suffix = "json"
          elif FileHandler.is_it_csv(data_str):
              suffix = "csv"
  
      if suffix == "json":
          return data_str, suffix, dialect
  
      if suffix == "csv":
          try:
              dialect = FileHandler._get_csv_dialect(data_str)
              if dialect:
                  return data_str, "csv", dialect
          except Exception:
              logger.error("Could not detect format for this file")
              logger.error(traceback.format_exc())
  
      data_str.seek(0)
      data.seek(0)
  
      # No file type identified
      return data, None, dialect
  
imports: import codecs
  import csv
  import json
  import os
  import tempfile
  import traceback
  from io import BytesIO, StringIO
  from pathlib import Path
  from urllib.parse import urlparse
  import magic
  import pandas
  import requests
  from charset_normalizer import from_bytes
  from mindsdb_sql import parse_sql
  from mindsdb_sql.parser.ast import DropTables, Select
  from mindsdb_sql.parser.ast.base import ASTNode
  from langchain.text_splitter import RecursiveCharacterTextSplitter
  from langchain.document_loaders import TextLoader
  from mindsdb.api.executor.utilities.sql import query_df
  from mindsdb.integrations.libs.base import DatabaseHandler
  from mindsdb.integrations.libs.response import RESPONSE_TYPE
  from mindsdb.integrations.libs.response import HandlerResponse
  from mindsdb.integrations.libs.response import HandlerStatusResponse
  from mindsdb.utilities import log
label_desc: Use image node_id 12 for calling the FileHandler obj's underlying member method code with example usage: obj._get_data_io(file_path) and returns: data,  None,  dialect, data,  str,  dialect, data,  str,  dialect, data,  str,  dialect, data,  str,  dialect, data_str,  suffix,  dialect, data_str,  str,  dialect