Immutability and Python

Introducing Pyrsistent

Disclaimer

Some of the stuff mentioned here is specific for CPython.

For other interpreters other rules may apply.

What is immutability?

Something is immutable if it cannot be changed once created.

Lets keep it simple:

Why immutability in programming?

  • Cognitive offload for the developer
  • Safe and simple invariance checking
  • Safe and fast sharing, within and between threads
  • Safe and fast reuse
  • Hashable
  • Runtime efficiency

Why not?

  • Runtime efficiency
  • Habits
  • Language support

Immutability classes (WAT?)

  • Immutable by convention
  • Apparent immutability
  • True immutability

Immutability in Python

No constant references

Base types

>>> x = 17
>>> y = 17
>>> x is y
True
>>> y = 1700
>>> x = 1700
>>> x is y
False

Numbers and strings are immutable

Collections

tuple, frozenset and namedtuple, that's about it...

>>> tuple() is tuple()
True
>>> list() is list()
False

Gets messy and inefficient when you want to evolve the content

>>> t1 = (1, 2, 3, 4, 5)
>>> t2 = t1[:2] + tuple(17) + t1[3:]
# or
>>> l1 = list(t1)
>>> l1[2] = 17
>>> t2 = tuple(l1)

Enter Pyrsistent

Immutable collections that are easy to evolve

a.k.a. persistent data structures

a.k.a. functional data structures

Pyrsistent eco system

a = apparent immutability

c = immutability by convention

Examples

>>> students = freeze([{'name': 'Ann', 'grade': 4.1}, {'name': 'Bob', 'grade': 2.1}])
>>> students_v2 = students.set_in((1, 'grade'), 1.9)
>>> students
pvector([pmap({'grade': 4.1, 'name': 'Ann'}), pmap({'grade': 2.1, 'name': 'Bob'})])
>>> students_v2
pvector([pmap({'grade': 4.1, 'name': 'Ann'}), pmap({'grade': 1.9, 'name': 'Bob'})])
>>> thaw(students_v2)
[{'grade': 4.1, 'name': 'Ann'}, {'grade': 1.9, 'name': 'Bob'}]
>>> Point = pclass('x, y', name='Point')
>>> p = Point(1, 2)
>>> p2 = p.set(x=3)
>>> p
Point(x=1, y=2)
>>> p2
Point(x=3, y=2)
>>> v1 = pvector([1, 2, 3, 4])
>>> v1 == v(1, 2, 3, 4)
True
>>> v1[1]
2
>>> v1[1:3]
pvector([2, 3])
>>> v3 = v1.set(1, 5)
>>> v3
pvector([1, 5, 3, 4])
>>> v1
pvector([1, 2, 3, 4])
>>> pvector(x + 1 for x in v1)
pvector([2, 3, 4, 5])
>>> m1 = pmap({'a':1, 'b':2})
>>> m1 == m(a=1, b=2)
True
>>> m1['a']
1
>>> m1.b
2
>>> m1.items()
[('a', 1), ('b', 2)]
>>> m1.set('a', 3)
pmap({'a': 3, 'b': 2})
>>> m1
pmap({'a': 1, 'b': 2})

Structural reuse

>>> v1 = v(0, 1, 2, 3, 4, 5, 6, 7, 8)
>>> v1
pvector([0, 1, 2, 3, 4, 5, 6, 7, 8])
>>> v2 = v1.set(5, 'beef')
>>> v2
pvector([0, 1, 2, 3, 4, 'beef', 6, 7, 8])
>>> v1
pvector([0, 1, 2, 3, 4, 5, 6, 7, 8])

Get it:

Contribute:

Docs:

pip install pyrsistent

Thank you!

Immutability and Python

By Tobias Gustafsson

Immutability and Python

A brief introduction to Pythons take on (or rather lack of) immutability followed by a compressed description of Pyrsistent. Pyrsistent is a library that tries to provide some of the pieces missing in the Python standard library for convinient work with immutable data structures.

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