Object Interning

Python optimizes memory usage by reusing identical immutable objects through interning and caching.

String Interning

Concept

String interning shares identical strings in memory, reducing memory usage and enabling fast identity comparisons.

a = "hello"
b = "hello"
print(a is b)  # True (same object)
print(id(a) == id(b))  # True

Auto-Interning Rules

Python automatically interns strings that look like identifiers:

# Auto-interned (identifier-like)
a = "hello"
b = "hello"
print(a is b)  # True

a = "hello_world"
b = "hello_world"
print(a is b)  # True

Strings with spaces or special characters may not be auto-interned:

# May not be interned
a = "hello world!"
b = "hello world!"
print(a is b)  # May be False
print(a == b)  # Always True (same value)

Explicit Interning

Use sys.intern() to force interning:

import sys

s1 = sys.intern("any string with spaces!")
s2 = sys.intern("any string with spaces!")
print(s1 is s2)  # True (forced interning)

When to Use Explicit Interning

import sys

# Useful for repeated string comparisons
keys = [sys.intern(key) for key in many_keys]

# Fast identity check instead of value comparison
if key is interned_key:  # Faster than key == interned_key
    pass

---

Integer Caching

CPython Caching Range

CPython caches small integers in the range [-5, 256]:

# Cached integers
a = 100
b = 100
print(a is b)  # True (same cached object)

a = 256
b = 256
print(a is b)  # True (still cached)

# Non-cached integers
a = 257
b = 257
print(a is b)  # May be False (different objects)
print(a == b)  # True (same value)

a = -6
b = -6
print(a is b)  # May be False

Why This Range?

Small integers are used frequently in programs (loop counters, indices, etc.), so caching them: - Reduces memory usage - Improves performance - Avoids repeated object creation

Important Warning

Never rely on integer caching for logic!

# WRONG - Don't do this
if x is 100:  # May not work as expected
    pass

# CORRECT - Always use ==
if x == 100:  # Always works correctly
    pass

---

Other Cached Objects

Singletons

# None, True, False are singletons
a = None
b = None
print(a is b)  # Always True

a = True
b = True
print(a is b)  # Always True

Empty Immutables

# Empty tuple is cached
a = ()
b = ()
print(a is b)  # True

# Empty frozenset is cached
a = frozenset()
b = frozenset()
print(a is b)  # True

---

Summary

Type	Interning/Caching	Range/Condition
Strings	Auto/Explicit	Identifier-like / sys.intern()
Integers	Auto	[-5, 256]
None	Always	Singleton
True/False	Always	Singletons
Empty tuple	Auto	()

Key points: - Interning saves memory by sharing objects - Use == for value comparison, is for identity - Don't rely on caching in program logic - Use sys.intern() for explicit string interning - Caching is an implementation detail, not guaranteed