code: def get_join_indices(
      df: pd.DataFrame,
      right: Union[pd.DataFrame, pd.Series],
      conditions: list[tuple[str]],
      keep: Literal["first", "last", "all"] = "all",
      use_numba: bool = False,
      force: bool = False,
  ) -> tuple[np.ndarray, np.ndarray]:
      """Convenience function to return the matching indices from an inner join.
  
      !!! info "New in version 0.27.0"
  
      Args:
          df: A pandas DataFrame.
          right: Named Series or DataFrame to join to.
          conditions: List of arguments of tuple(s) of the form
              `(left_on, right_on, op)`, where `left_on` is the column
              label from `df`, `right_on` is the column label from `right`,
              while `op` is the operator.
              The `col` class is also supported. The operator can be any of
              `==`, `!=`, `<=`, `<`, `>=`, `>`. For multiple conditions,
              the and(`&`) operator is used to combine the results
              of the individual conditions.
          use_numba: Use numba, if installed, to accelerate the computation.
          keep: Choose whether to return the first match, last match or all matches.
          force: If `True`, force the non-equi join conditions
              to execute before the equi join.
  
      Returns:
          A tuple of indices for the rows in the dataframes that match.
      """
      return _conditional_join_compute(
          df=df,
          right=right,
          conditions=conditions,
          how="inner",
          sort_by_appearance=False,
          df_columns=None,
          right_columns=None,
          keep=keep,
          use_numba=use_numba,
          indicator=False,
          force=force,
          return_matching_indices=True,
      )
  
imports: from __future__ import annotations
  import operator
  import warnings
  from typing import Any, Hashable, Literal, Optional, Union
  import numpy
  import pandas
  import pandas_flavor
  from pandas.api.types import is_datetime64_dtype, is_dtype_equal, is_extension_array_dtype, is_numeric_dtype, is_timedelta64_dtype
  from pandas.core.reshape.merge import _MergeOperation
  from janitor.functions.utils import _generic_func_cond_join, _JoinOperator, _keep_output, col, greater_than_join_types, less_than_join_types
  from janitor.utils import check, check_column, find_stack_level
label_desc: Use image node_id 13 for calling a global function with example usage: get_join_indices(df, right, conditions, keep, use_numba, force) and returns: _conditional_join_compute