Python Internals: Understanding Python data model (I)

Python sees everything as object. Every object has an identity, value and a type. Object identity and type are invariable.

Object type determines if value is mutable or otherwise.

Lifetime of object is based on reference count mechanism.

Object Container

Object containers are: list, dictionary, tuple, set. Containers keep reference (object identity) to objects. Mutability of container is based on references. The value of the referred object could be mutable.

Let’s see how they behave:

from sys import getrefcount

a = 1
b = 1

list1 = [] 
list2 = [] 

t1 = (a, b)
t2 = (a, b)

# a and b share reference to same object ID 
print "a=", id(a)
print "b=", id(b)

# Constant 1 has ref count of +2 (a and b)
print "getrefcount(1)=", getrefcount(1)

# Constant 1 has ref count of +3 now (a,b and c)
c = 1
print "getrefcount(1)=", getrefcount(1)

# Decrement the object ref count
del c
print "getrefcount(1)=", getrefcount(1)

# Default ref count of an unused new integer object is 3. But, why?
print "getrefcount(999999)=", getrefcount(999999)

print ""

# Mutable objects like list do not refer to same object ID, even
# though value of objects are same!
print "list1=", id(list1)
print "list2=", id(list2)
print "getrefcount(list1)=", getrefcount(list1)
print "getrefcount(list2)=", getrefcount(list2)

print ""

print "t1=", id(t1)
print "t2=" ,id(t2)

# Containers have default ref count of 2
print "getrefcount(t1)=", getrefcount(t1)
print "getrefcount(t2)=", getrefcount(t2)

# Changing contained object values do not modiy immutable container
a = 3
b = 10

print "t1=", id(t1)
print "t2=" ,id(t2)

# String literals are constant and are referred to like numbers
s1 = "hello"
s2 = "hello"

# s1 and s2 refer to same object
print "s1=", id(s1)
print "s2=" ,id(s2)
print "getrefcount(hello)=", getrefcount("hello")

# The first use of a literal uses 3 ref count
print "getrefcount(hello!!)=", getrefcount("hello!!")

s3 = "hello!"
print "getrefcount(hello!)=", getrefcount("hello!")