class_docstr: A pickler to persist of big data efficiently.
  
  The main features of this object are:
  
   * persistence of numpy arrays in separate .npy files, for which
     I/O is fast.
  
   * optional compression using Zlib, with a special care on avoid
     temporaries.
class_docstr_tok: ["A","pickler","to","persist","of","big","data","efficiently",".","The","main","features","of","this","object","are",":","*","persistence","of","numpy","arrays","in","separate",".npy","files",",","for","which","I\/O","is","fast",".","*","optional","compression","using","Zlib",",","with","a","special","care","on","avoid","temporaries","."]
code: def close(self):
      if self.compress:
          with open(self._filename, "wb") as zfile:
              write_zfile(zfile, self.file.getvalue(), self.compress)
  
imports: import traceback
  import os
  import zlib
  import warnings
  import dill
  import pickle
  from io import BytesIO
label_desc: Use image node_id 4 for calling the NumpyPickler obj's underlying member method code with example usage: obj.close() without return types