code: def get_grouper(
      obj: NDFrameT,
      key=None,
      axis: Axis = 0,
      level=None,
      sort: bool = True,
      observed: bool = False,
      validate: bool = True,
      dropna: bool = True,
  ) -> tuple[ops.BaseGrouper, frozenset[Hashable], NDFrameT]:
      """
      Create and return a BaseGrouper, which is an internal
      mapping of how to create the grouper indexers.
      This may be composed of multiple Grouping objects, indicating
      multiple groupers
  
      Groupers are ultimately index mappings. They can originate as:
      index mappings, keys to columns, functions, or Groupers
  
      Groupers enable local references to axis,level,sort, while
      the passed in axis, level, and sort are 'global'.
  
      This routine tries to figure out what the passing in references
      are and then creates a Grouping for each one, combined into
      a BaseGrouper.
  
      If observed & we have a categorical grouper, only show the observed
      values.
  
      If validate, then check for key/level overlaps.
  
      """
      group_axis = obj._get_axis(axis)
  
      # validate that the passed single level is compatible with the passed
      # axis of the object
      if level is not None:
          # TODO: These if-block and else-block are almost same.
          # MultiIndex instance check is removable, but it seems that there are
          # some processes only for non-MultiIndex in else-block,
          # eg. `obj.index.name != level`. We have to consider carefully whether
          # these are applicable for MultiIndex. Even if these are applicable,
          # we need to check if it makes no side effect to subsequent processes
          # on the outside of this condition.
          # (GH 17621)
          if isinstance(group_axis, MultiIndex):
              if is_list_like(level) and len(level) == 1:
                  level = level[0]
  
              if key is None and is_scalar(level):
                  # Get the level values from group_axis
                  key = group_axis.get_level_values(level)
                  level = None
  
          else:
              # allow level to be a length-one list-like object
              # (e.g., level=[0])
              # GH 13901
              if is_list_like(level):
                  nlevels = len(level)
                  if nlevels == 1:
                      level = level[0]
                  elif nlevels == 0:
                      raise ValueError("No group keys passed!")
                  else:
                      raise ValueError(
                          "multiple levels only valid with MultiIndex"
                      )
  
              if isinstance(level, str):
                  if obj._get_axis(axis).name != level:
                      raise ValueError(
                          f"level name {level} is not the name "
                          f"of the {obj._get_axis_name(axis)}"
                      )
              elif level > 0 or level < -1:
                  raise ValueError(
                      "level > 0 or level < -1 only valid with MultiIndex"
                  )
  
              # NOTE: `group_axis` and `group_axis.get_level_values(level)`
              # are same in this section.
              level = None
              key = group_axis
  
      # a passed-in Grouper, directly convert
      if isinstance(key, Grouper):
          grouper, obj = key._get_grouper(obj, validate=False)
          if key.key is None:
              return grouper, frozenset(), obj
          else:
              return grouper, frozenset({key.key}), obj
  
      # already have a BaseGrouper, just return it
      elif isinstance(key, ops.BaseGrouper):
          return key, frozenset(), obj
  
      if not isinstance(key, list):
          keys = [key]
          match_axis_length = False
      else:
          keys = key
          match_axis_length = len(keys) == len(group_axis)
  
      # what are we after, exactly?
      any_callable = any(
          callable(g) or isinstance(g, dict) for g in keys
      )
      any_groupers = any(
          isinstance(g, (Grouper, Grouping)) for g in keys
      )
      any_arraylike = any(
          isinstance(g, (list, tuple, Series, Index, np.ndarray))
          for g in keys
      )
  
      # is this an index replacement?
      if (
          not any_callable
          and not any_arraylike
          and not any_groupers
          and match_axis_length
          and level is None
      ):
          if isinstance(obj, DataFrame):
              all_in_columns_index = all(
                  g in obj.columns or g in obj.index.names for g in keys
              )
          else:
              assert isinstance(obj, Series)
              all_in_columns_index = all(
                  g in obj.index.names for g in keys
              )
  
          if not all_in_columns_index:
              keys = [com.asarray_tuplesafe(keys)]
  
      if isinstance(level, (tuple, list)):
          if key is None:
              keys = [None] * len(level)
          levels = level
      else:
          levels = [level] * len(keys)
  
      groupings: list[Grouping] = []
      exclusions: set[Hashable] = set()
  
      # if the actual grouper should be obj[key]
      def is_in_axis(key) -> bool:
          if not _is_label_like(key):
              if obj.ndim == 1:
                  return False
  
              # items -> .columns for DataFrame, .index for Series
              items = obj.axes[-1]
              try:
                  items.get_loc(key)
              except (KeyError, TypeError, InvalidIndexError):
                  # TypeError shows up here if we pass e.g. an Index
                  return False
  
          return True
  
      # if the grouper is obj[name]
      def is_in_obj(gpr) -> bool:
          if not hasattr(gpr, "name"):
              return False
          if using_copy_on_write():
              # For the CoW case, we check the references to determine if the
              # series is part of the object
              try:
                  obj_gpr_column = obj[gpr.name]
              except (KeyError, IndexError, InvalidIndexError):
                  return False
              if isinstance(gpr, Series) and isinstance(
                  obj_gpr_column, Series
              ):
                  return gpr._mgr.references_same_values(  # type: ignore[union-attr]
                      obj_gpr_column._mgr, 0  # type: ignore[arg-type]
                  )
              return False
          try:
              return gpr is obj[gpr.name]
          except (KeyError, IndexError, InvalidIndexError):
              # IndexError reached in e.g. test_skip_group_keys when we pass
              #  lambda here
              # InvalidIndexError raised on key-types inappropriate for index,
              #  e.g. DatetimeIndex.get_loc(tuple())
              return False
  
      for gpr, level in zip(keys, levels):
          if is_in_obj(gpr):  # df.groupby(df['name'])
              in_axis = True
              exclusions.add(gpr.name)
  
          elif is_in_axis(gpr):  # df.groupby('name')
              if obj.ndim != 1 and gpr in obj:
                  if validate:
                      obj._check_label_or_level_ambiguity(
                          gpr, axis=axis
                      )
                  in_axis, name, gpr = True, gpr, obj[gpr]
                  if gpr.ndim != 1:
                      # non-unique columns; raise here to get the name in the
                      # exception message
                      raise ValueError(
                          f"Grouper for '{name}' not 1-dimensional"
                      )
                  exclusions.add(name)
              elif obj._is_level_reference(gpr, axis=axis):
                  in_axis, level, gpr = False, gpr, None
              else:
                  raise KeyError(gpr)
          elif isinstance(gpr, Grouper) and gpr.key is not None:
              # Add key to exclusions
              exclusions.add(gpr.key)
              in_axis = True
          else:
              in_axis = False
  
          # create the Grouping
          # allow us to passing the actual Grouping as the gpr
          ping = (
              Grouping(
                  group_axis,
                  gpr,
                  obj=obj,
                  level=level,
                  sort=sort,
                  observed=observed,
                  in_axis=in_axis,
                  dropna=dropna,
              )
              if not isinstance(gpr, Grouping)
              else gpr
          )
  
          groupings.append(ping)
  
      if len(groupings) == 0 and len(obj):
          raise ValueError("No group keys passed!")
      if len(groupings) == 0:
          groupings.append(
              Grouping(
                  Index([], dtype="int"), np.array([], dtype=np.intp)
              )
          )
  
      # create the internals grouper
      grouper = ops.BaseGrouper(
          group_axis, groupings, sort=sort, dropna=dropna
      )
      return grouper, frozenset(exclusions), obj
  
imports: from __future__ import annotations
  from typing import TYPE_CHECKING, Hashable, Iterator, final
  import warnings
  import numpy
  from pandas._config import using_copy_on_write
  from pandas._typing import ArrayLike, Axis, NDFrameT, npt
  from pandas.errors import InvalidIndexError
  from pandas.util._decorators import cache_readonly
  from pandas.util._exceptions import find_stack_level
  from pandas.core.dtypes.common import is_categorical_dtype, is_list_like, is_scalar
  from pandas.core import algorithms
  from pandas.core.arrays import Categorical, ExtensionArray
  import pandas.core.common
  from pandas.core.frame import DataFrame
  from pandas.core.groupby import ops
  from pandas.core.groupby.categorical import recode_for_groupby
  from pandas.core.indexes.api import CategoricalIndex, Index, MultiIndex
  from pandas.core.series import Series
  from pandas.io.formats.printing import pprint_thing
label_desc: Use image node_id 1 for calling a global function with example usage: get_grouper(obj, key, axis, level, sort, observed, validate, dropna) and returns: grouper,  frozenset,  obj, True, grouper,  frozenset,  obj, grouper,  frozenset,  obj, key,  frozenset,  obj, False, False, unknown, False, gpr, False, False, False