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Python learning resources Beginner to advanced Python guides, cheatsheets, books and projects. For data science, backend and automation. Join 👉 https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatascientist

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Python Functions You definitely Need to Know
Python Functions You definitely Need to Know

#PyQuiz What's the output of bool('False')?
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#PyQuiz What is the type of type in Python?
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Wait, why did all functions return 2? The lambdas don’t capture the value of i at each loop iteration, they capture the varia
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Wait, why did all functions return 2? The lambdas don’t capture the value of i at each loop iteration, they capture the variable itself. By the time you call the functions, the loop has finished, and i is left at its final value, 2. This is called late binding and can cause unexpected behavior when creating closures inside loops. So as a quick tip, Bind the current value at definition time using a default argument(like shown in the second image) Then each lambda remembers its own i value independently.

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#PyQuiz How many values can a return statement rerurn?
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Feels off? It's because all your objects share one variable (without you realizing it) At first glance, it seems like every o
Feels off? It's because all your objects share one variable (without you realizing it) At first glance, it seems like every object should start fresh, right? But in this case, count is a class variable, which means it’s shared by all instances of the class. Every time you create a new Counter(), you’re actually incrementing the same shared variable not something unique to each object. If your goal is to give each object its own value, define it like this instead
class Counter:
    def __init__(self):
        self.count = 1
Now, each instance has its own count, stored on the object itself . no sharing, no surprises.

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#PyQuiz What does None==0 return?
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Looks weird? You're not alone. Python caches small integers between -5 and 256 for performance. So a and b point to the same
Looks weird? You're not alone. Python caches small integers between -5 and 256 for performance. So a and b point to the same object. But x and y are different objects, even though they have the same value. This is part of Python's internal optimization. It’s not about math. it’s about memory references under the hood. Bottom Line? Use == when you care about value, not identity. print(x == y) # True ✅ Because sometimes is isn’t what you think it is 😉

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DATABASES
DATABASES

TOP PYTHON MODULES
TOP PYTHON MODULES

Adding Elements of a List
Adding Elements of a List