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@s19110 s19110 commented Sep 26, 2025

Addresses issue #714

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@myteron myteron left a comment

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provided example01.py code in the md for the obsevered issues around numbers and strings to explain memory optimistation related isses.

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Suggstion for first sentence:

Prevent unexpected results by knowing what comparisment operators do such as == and is actually do.

After the existing first sentence we shall also explain:

Python falls back to comparing objects id() if the `eq implementation is missing for a custom class.

In Python, the `==` operator is implemented by the `__eq__` method on an object [[python.org data model 2023](https://docs.python.org/3/reference/datamodel.html?highlight=__eq__#object.__eq__)]. For built-in types like `int` and `str`, the comparison is implemented in the interpreter. The main issue comes when implementing custom classes, where the default implementation compares object references using the `is` operator. The `is` operator compares the identities of the objects, equivalent to `id(obj1) == id(obj2)`. The `id` function is built into Python, and in the CPython interpreter, the standard implementation, it returns the object's memory address [[de Langen 2023](https://realpython.com/python-is-identity-vs-equality/)].

You want to implement the `__eq__` method on a class if you believe you ever want to compare it to another object or find it in a list of objects. Actually, it is so common that the `dataclasses.dataclass` decorator by default implements it for you [[dataclasses — Data Classes — Python 3.11.4 documentation](https://docs.python.org/3/library/dataclasses.html#dataclasses.dataclass)].

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@myteron myteron Oct 1, 2025

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Be aware of Python's memory optimization for strings and numbers as demonstrated in example01.py code.
Python tries to avoid allocating more memory for the same string. Numbers -5 to 256 are so frequently used that they are pre-reserved.

# SPDX-FileCopyrightText: OpenSSF project contributors
# SPDX-License-Identifier: MIT
""" Code Example """

print("-" * 10 + "Memory optimization with strings" + 10 * "-")
a = "foobar"
b = "foobar"
c = ''.join(["foo", "bar"])
print(f"a is b: {a} is {b}?", a is b)
print(f"a is c: {a} is {c}?", a is c)
print(f"a == c: {a} == {c}?", a == c)
print(f"size? len(a)={len(a)} len(b)={len(b)} len(c)={len(c)}")

print("-" * 10 + "Memory optimization with numbers" + 10 * "-")
a = b = 256 
print (f"{a} is {b}?", a is b)
a = b = 257
print (f"{a} is {b}?", a is b)

print("-" * 10 + "Memory optimization with numbers in a loop" + 10 * "-")
a = b = 255
while(a is b):
    a += 1 
    b += 1
    print (f"{a} is {b}?", a is b)

The example01.py code output:

a is b: foobar is foobar? True
a is c: foobar is foobar? False
a == c: foobar == foobar? True
size? len(a)=6 len(b)=6 len(c)=6
----------Memory optimisation with numbers----------
256 is 256? True
257 is 257? True
----------Memory optimisation with numbers in a loop----------
256 is 256? True
257 is 257? False

The first print statement illustrates Python's memory optimization for strings.
See id(a) and id(b) printing the same object number compared to id{c} printing a different id for t he same string.

The example in the middle creates same object number as a = b = 257 tells python that it can used the same memory.

The last print statements in example01.py illustrate Python's memory optimization for numbers between -5 to 256. Python needs to allocate new objects for numbers greater then 256. Note that the behavior of Python for numbers between -5 and 256 change depending on how its run. Following code changes behavior when run via interactive Python shell or in a file:

example02.py:

a = 256
b = 256
print(a is b)
a = 257
b = 257
print(a is b)

Using an interactive Python shell will print True and False while running the code in a python script will print True and True as the runtime has optimized the code to preserve memory.

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