In Python, the 'is' operator is commonly utilized for testing the equality of strings. However, its implementation stands out from other equality operators like '__eq__'. This article explores the intricacies of how 'is' operates within Python.
Unlike '__eq__,' which checks for content equality, 'is' assesses identity. When dealing with strings, this signifies that 'is' determines if the two strings occupy the same memory location.
The challenge arises when trying to mimic 'is' behavior in custom classes. Defining a '__is__' method does not suffice, as Python expects a specific implementation. To align with Python's expectations, it's crucial to understand the nature of interning in strings.
Interning involves storing string objects in a central cache, ensuring that multiple references to the same string point to a single shared instance. This optimization enhances performance by reducing memory consumption and improving speed.
In Python, string literals like 'abc' are automatically interned. Thus, (('abc' == 'abc') and ('abc' is 'abc')) evaluate to True. However, for custom strings, interning must be explicitly performed.
The following example illustrates the difference between 'is' and '__eq__' with interned and non-interned strings:
<code class="python">>>> s = 'str' >>> s is 'str' True >>> class MyString: ... def __init__(self): ... self.s = 'string' ... def __eq__(self, s): ... return self.s == s ... >>> m = MyString() >>> m is 'string' False >>> sys.intern(m) is 'string' # After interning, 'is' returns True True</code>
To summarize, 'is' checks for object identity in Python, comparing memory locations. For strings, this implies that interning plays a substantial role. Interned strings share the same memory address, allowing 'is' to correctly determine equality. When implementing 'is' in custom classes, ensuring that interning is appropriately handled is essential to replicate Python's behavior.
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