code: def from_dataframe(df: DataFrameObject, allow_copy=True) -> pa.Table:
      """
      Build a ``pa.Table`` from any DataFrame supporting the interchange protocol.
  
      Parameters
      ----------
      df : DataFrameObject
          Object supporting the interchange protocol, i.e. `__dataframe__`
          method.
      allow_copy : bool, default: True
          Whether to allow copying the memory to perform the conversion
          (if false then zero-copy approach is requested).
  
      Returns
      -------
      pa.Table
  
      Examples
      --------
      >>> import pyarrow
      >>> from pyarrow.interchange import from_dataframe
  
      Convert a pandas dataframe to a pyarrow table:
  
      >>> import pandas as pd
      >>> df = pd.DataFrame({
      ...         "n_attendees": [100, 10, 1],
      ...         "country": ["Italy", "Spain", "Slovenia"],
      ...     })
      >>> df
         n_attendees   country
      0          100     Italy
      1           10     Spain
      2            1  Slovenia
      >>> from_dataframe(df)
      pyarrow.Table
      n_attendees: int64
      country: large_string
      ----
      n_attendees: [[100,10,1]]
      country: [["Italy","Spain","Slovenia"]]
      """
      if isinstance(df, pa.Table):
          return df
      elif isinstance(df, pa.RecordBatch):
          return pa.Table.from_batches([df])
  
      if not hasattr(df, "__dataframe__"):
          raise ValueError("`df` does not support __dataframe__")
  
      return _from_dataframe(
          df.__dataframe__(allow_copy=allow_copy), allow_copy=allow_copy
      )
  
file_path: arrow/python/pyarrow/interchange/from_dataframe.py
imports: from __future__ import annotations
  from typing import Any, Tuple
  from pyarrow.interchange.column import DtypeKind, ColumnBuffers, ColumnNullType
  import pyarrow
  import re
  import pyarrow.compute
  from pyarrow.interchange.column import Dtype
label_desc: Use image node_id 1 for calling a global function with example usage: from_dataframe(df, allow_copy) and returns: _from_dataframe, df, pa