Are strings pooled in Python?

Does Python have a pool of all strings and are they (strings) singletons there?开发者_C百科

More precise, in the following code, are one or two strings created in memory?

a = str(num)
b = str(num)

---

Strings are immutable in Python, so the implementation can decide whether to intern (that's a term often associated with C#, meaning that some strings are stored in a pool) strings or not.

In your example, you're dynamically creating strings. CPython does not always look into the pool to detect whether the string is already there - it also doesn't make sense because you first have to reserve memory in order to create the string, and then compare it to the pool content (inefficient for long strings).

But for strings of length 1, CPython does look into the pool (cf. "stringobject.c"):

static PyStringObject *characters[UCHAR_MAX + 1];

...

PyObject *
PyString_FromStringAndSize(const char *str, Py_ssize_t size)
{

...

    if (size == 1 && str != NULL &&
    (op = characters[*str & UCHAR_MAX]) != NULL)
    {
        #ifdef COUNT_ALLOCS
            one_strings++;
        #endif

        Py_INCREF(op);
        return (PyObject *)op;
    }

...

So:

a = str(num)
b = str(num)
print a is b # <-- this will print False in most cases (but try str(1) is str(1))

But when using constant strings directly in your code, CPython uses the same string instance:

a = "text"
b = "text"
print a is b # <-- this will print True

---

In general, strings are not interned in Python, but they do sometimes seem to be:

>>> str(5) is str(5)
True
>>> str(50) is str(50)
False

This isn't uncommon in Python, where common objects might be optimized in ways that unusual ones are not:

>>> int(5+0) is int(5+0)
True
>>> int(50+0) is int(50+0)
True
>>> int(500+0) is int(500+0)
False

And keep in mind, all of these sorts of details will differ between implementations of Python, and even between versions of the same implementation.

---

Strings are not interned in general. In your example two strings will be created (with the exception of values between 0 and 9). To test this we can use the is operator to see if the two strings are the same object:

>>> str(1056) is str(1056)
False

---

the constant of pool in python distinguish small integer pool and large integer pool, and the small integer pool is range in [-5, 257); and other integers in the large integer pool. In Cython, if defines a linked-list to store this data, where fetch the data becomes very convenient and fast.

# ifndef NSMALLPOSINTS
    # define NSMALLPOSINTS 257
# endif

# ifndef NSMALLNEGINTS
    # define NSMALLNEGINTS 5
# endif

# if NSMALLPOSINTS + NSMALLNEGINTS > 0
    static PyIntObject * small_ints[NSMALLPOSINTS + NSMALLNEGINTS];
# endif

BTW: the integer 257 maybe stranger; if two objects that they have the same values are in the same field, their address may be or not be the same, it depends on the context of process; whereas, if they are in the different fields, their addresses must be difference

and by the way, according to string type, cython also provide a constant pool that the length of string should be one, whereas it may be not the same object

a = str(11)
b = str(11)
print a == b      # True 
print a is b      # False

c = str("A")
d = str("A")   
print c == d    # True
print c is d    # True

aa = 12
bb = 12
print aa == bb    # True
print aa is bb    # True

cc = 333
dd = 333
print cc == dd    # True
print cc is dd    # False

comparing their addresses, is transparently getting the ahead solutions