class_docstr: Persistent map/dict. Tries to follow the same naming conventions as the built in dict where feasible.
  
  Do not instantiate directly, instead use the factory functions :py:func:`m` or :py:func:`pmap` to
  create an instance.
  
  Was originally written as a very close copy of the Clojure equivalent but was later rewritten to closer
  re-assemble the python dict. This means that a sparse vector (a PVector) of buckets is used. The keys are
  hashed and the elements inserted at position hash % len(bucket_vector). Whenever the map size exceeds 2/3 of
  the containing vectors size the map is reallocated to a vector of double the size. This is done to avoid
  excessive hash collisions.
  
  This structure corresponds most closely to the built in dict type and is intended as a replacement. Where the
  semantics are the same (more or less) the same function names have been used but for some cases it is not possible,
  for example assignments and deletion of values.
  
  PMap implements the Mapping protocol and is Hashable. It also supports dot-notation for
  element access.
  
  Random access and insert is log32(n) where n is the size of the map.
  
  The following are examples of some common operations on persistent maps
  
  >>> m1 = m(a=1, b=3)
  >>> m2 = m1.set('c', 3)
  >>> m3 = m2.remove('a')
  >>> m1
  pmap({'a': 1, 'b': 3})
  >>> m2
  pmap({'a': 1, 'c': 3, 'b': 3})
  >>> m3
  pmap({'c': 3, 'b': 3})
  >>> m3['c']
  3
  >>> m3.c
  3
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code: def __contains__(self, key):
      return self._contains(self._buckets, key)
  
imports: from ._compat import Mapping, Hashable
  from itertools import chain
  import six
  from pyrsistent._pvector import pvector
  from pyrsistent._transformations import transform
label_desc: Use image node_id 6 for calling the PMap obj's underlying member method code with example usage: obj.__contains__(key) and returns: self