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The contents of /python-deepdive/Part 2/Section 04 - Iterables and Iterators/05 - Example 2 - Cyclic Iterators.ipynb are duplicated in the last section of
/python-deepdive/Part 2/Section 04 - Iterables and Iterators/04 - Example 1 - Consuming Iterators Manually.ipynb

Sir which is better for competitive programming - Python or C++
Sir urgent help needed
Pls guide me through it

In the below notebook
https://github.com/fbaptiste/python-deepdive/blob/master/Part%201/Section%2004%20-%20Numeric%20Types/02%20-%20Integers%20-%20Operations.ipynb

It is mentioned that "int vs int in exponentiation, i.e result of 3 ** 2 always results in an int.
However this is always not true because of negative exponents ( 3 **-2).

In file Part 1/Section 02 - A Quick Refresher/07 - Classes.ipynb, in the 2nd paragraph after Cell 1, the word, should is spelt as shgoudl.

Note that using self is just a convention (although a good one, and you shgoudl use it to make your code more understandable by others), you could really call it whatever (valid) name you choose.

In the following file, /python-deepdive/Part 2/Section 05 - Project 2/01 - Project - Description.ipynb, the line just before the code blocks begin reads,

Code from Previous Project

However, the code presented is actually the solution to the current project.

In Part 2 > Section 06 - Generators > 05-Generator Expressions.ipynb at cell number 34, the following expression is used

((i * j for j in range(start, stop + 1)) for i in range(start, stop + 1))

as an equivalent to the following expression

[[i * j for j in range(start, stop + 1)] for i in range(start, stop + 1)]

But they will not generate the same result. The first expression will result in the following functions,

def mult_list():
    global start, stop
    for i in range(start, stop + 1):
        def inner():
            global start, stop
            nonlocal i
            for j in range(start, stop + 1):
                yield i * j

        yield inner()

we can see that the inner function is a closure, and i is the free variable. So the value of i which will be used to create the generator, is 10, which results in the following

[10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
[10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
[10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
[10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
[10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
[10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
[10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
[10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
[10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
[10, 20, 30, 40, 50, 60, 70, 80, 90, 100]

But the very first expression [[i * j for j in range(start, stop + 1)] for i in range(start, stop + 1)] results the following

[[1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
 [2, 4, 6, 8, 10, 12, 14, 16, 18, 20],
 [3, 6, 9, 12, 15, 18, 21, 24, 27, 30],
 [4, 8, 12, 16, 20, 24, 28, 32, 36, 40],
 [5, 10, 15, 20, 25, 30, 35, 40, 45, 50],
 [6, 12, 18, 24, 30, 36, 42, 48, 54, 60],
 [7, 14, 21, 28, 35, 42, 49, 56, 63, 70],
 [8, 16, 24, 32, 40, 48, 56, 64, 72, 80],
 [9, 18, 27, 36, 45, 54, 63, 72, 81, 90],
 [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]]

I was wondering if there is any fix to this!!!

In file Part 1/Section 02 - A Quick Refresher/04 - The While Loop.ipynb the word repeatg seems to be a typo.

While Loops

The while loop is a way to repeatg a block of code as long as a specified condition is met.

while : code block ...

In the following file, /python-deepdive/Part 2/Section 06 - Generators/02 - Example - Fibonacci Sequence.ipynb, the following line is unclear:

but we'll still run in Python's maximum recursion depth
I was going to change it to,
but we'll still run into Python's maximum recursion depth
but that still sounded a bit off. I'll let you decide.

Notebook 09 - Python's Built-In Iterables and Iterators.ipynb in Part 2/Section 04 - Iterables and Iterators needs to come before notebook 07 - Sorting Iterables.ipynb. The video on sorting comes after the video on built-ins.

In the directory, /python-deepdive/Part 2/Section 08 - Iteration Tools/,
02 - Slicing Iterables.ipynb
and
03 - Slicing Iterables.ipynb
are duplicates.

Hi Fred.
At the end of the file Part 3/Section 05 - Sets/06 - Frozen Sets.ipynb, we created a custom function for memoization replacing the lru_cache.

The second version of it is:

We can even tweak this to effectively provide more efficient caching when the order of positional arguments is not important either:

def memoizer(fn):
    cache = {}
    def inner(*args, **kwargs):
        key = frozenset(args) | frozenset(kwargs.items())
        if key in cache:
            return cache[key]
        else:
            result = fn(*args, **kwargs)
            cache[key] = result
            return result
    return inner

@memoizer
def adder(*args):
    print('calculating...')
    return sum(args)

I just wanted to note that this cache mechanism won't work if we have duplicate arguments. That set (frozenset actually) removes the duplicate arguments.

Take a look at this example:

print(adder(1, 2, 2))
print(adder(1, 1, 2))  # 5 !!

You may add a note that arguments should be different for this to work.
Thanks.