class_docstr: Hasher with special logic for handling Pandas and numpy object dtype arrays.
class_docstr_tok: ["Hasher","with","special","logic","for","handling","Pandas","and","numpy","object","dtype","arrays","."]
code: def save(self, obj):
      if (
          isinstance(obj, self.np.ndarray)
          and obj.dtype.hasobject
          and obj.ndim >= 1
          and prod(obj.shape) > 1000
      ):
          try:
              meta = self._get_numpy_metadata_tuple(obj)
              super().save(self.pd.util.hash_array(self.np.ravel(obj)))
              obj = meta
          except TypeError:
              pass
      super().save(obj)
  
imports: import hashlib
  import pickle
  import struct
  import sys
  import tempfile
  import time
  import traceback
  from pathlib import Path
  from typing import TYPE_CHECKING, Union
  from joblib.hashing import Hasher, Pickler
  from joblib.memory import MemorizedFunc, MemorizedResult, Memory, NotMemorizedResult, _format_load_msg, filter_args, format_call, format_signature, format_time, get_func_name
  from xxhash import xxh128
label_desc: Use image node_id 2 for calling the FastPandasHasher obj's underlying member method code with example usage: obj.save(obj) without return types