Functions: Miscellaneous

Hi, I heard you say don’t put [] at the end of the code, what is the purpose of brackets, or may i ask, when or when not to use brackets? I know they’re used to create a list, but what other scenarios do we need to use them? Sorry if i missed your explanation of this…

Hi. Can you point me to the time that you’re referring to for some context? [] will typically be used to either create a list (whether in a comprehension or direct assignment, but also for indexing elements or slices. They’re often used to access dictionary items:

my_dict["one"] = "Ein"
print(my_dict["one"])

but using the .get() method of the dictionary is generally a safer way to work.

Hi Darren,

I should’ve made note of the reference to which video at which time when you indicated it, but you are correct, you could’ve been simply referring to the context in which you used the []. I didn’t make note of it, so I’d at least have to go through the module again and listen. But, your explanation actually answers what I was asking. Thanks!!

it is very clear explanation.Thanks

at time 5:30 it was. What Darren meant was not to use pow() as a dict value, rather pow without (). print(eval(calc, {‘pow’:pow()})) would not allow to use the function itself.

Hi Darren, when checking if too strings are the same, why bother hashing them first? Does python not allow direct comparisons between the strings themselves? Could you not print(moby_1 == moby_2) ?

@jckichuk, Python does allow direct comparisons, but in his example the usage of a direct comparison on a book’s contents would not have made sense, I believe, when it comes to performance. It should be much quicker to hash and then compare whether they are identical.

Well then what’s the difference of using between id() and hash()?

@pamizu2 It’s a question of identity versus value. You can have two distinct string objects at different memory addresses but having the same value, for example:

>>> a = "Hello world"
>>> b = "Hello world"
>>> id(a) == id(b)  # Same as "a is b"
False
>>> hash(a) == hash(b)  # Same as "a == b"
True

The id() tells you the object’s identity, which is guaranteed to be unique among simultaneously existing objects. In CPython, it’s the memory address of the object.

The hash() function, on the other hand, calculates a number based on the object’s value. In more complex data types, hashing may sometimes consider only a few attributes of the object to calculate that number.

Hello guys,

Thank you for creating such a useful summary of the most commonly used functions. My question is about the hash() function:

am I right saying that this function accepts immutable data types only, such as tuples, strings, frozensets? The logic behind this would be that the output of the hash() function cannot relate to something which is mutable in the first place, e.g. a list or a dict? If I try this code: print(hash({'a':1, 'b':2})) I get

TypeError: unhashable type: 'dict'

But if I pass a string or a tuple to the hash() function then I get a proper hash value associated with it:

print(hash((1,'test'))

-7658849480319937646

Thank you!

@DoubleA Mutability and hashability are distinct but related concepts.

The hash() function only cares about the latter, so it can accept mutable objects such as instances of your custom class:

>>> class Person:
...     def __init__(self, name):
...         self.name = name
...     def __hash__(self):
...         return hash(self.name)
... 
>>> jdoe = Person("Joe")
>>> hash(jdoe)
-6168151968020744048
>>> jdoe.name = "Bob"
>>> hash(jdoe)
4782845501210272724

An object passed to hash() can change its internal state at any time, which may or may not result in a different hash value depending on how the .__hash__() method was implemented.

Python’s built-in types that are mutable don’t implement hashing, which makes them unhashable.

Hi! can you explain what each thing is doing? For scopes, you never explained what a global scope and local is, just how to access it and it was really confusing!

@Natasha Kaplan Check out these additional resources to learn more about scopes in Python:

• Python Scope & the LEGB Rule: Resolving Names in Your Code
• Namespaces and Scope in Python