Do you know that Python allows you to get all the object's attributes with one function without additional code? 🐍

When you need to quickly check the state of an object, many manually access the attributes or dig into __dict__.

But for this, Python already has a built-in function vars().

vars(obj)

It returns a dictionary of all the object's attributes, including the current state of the instance.

{'x': 10}

This is useful for debugging, logging, serialization, ORM, and analyzing the runtime state of objects.

print(vars(user))

Also, vars() works with modules, classes, and any objects with dict.


vars(module)


🔥 vars()` — a rather underrated tool for quickly analyzing the state of objects during execution.

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Python there is a small convenience that not everyone knows about: in startswith and endswith you can pass an tuple of values directly

This allows you to check multiple options with one call, without long conditions and unnecessary code

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3 quick ways to merge dictionaries in Python 🐍

1️⃣ The operator | (Python 3.9+) — the most modern and elegant way. Creates a new dictionary.

dict1 = {'a': 1, 'b': 2}
dict2 = {'b': 99, 'c': 4}

combined = dict1 | dict2
# Result: {'a': 1, 'b': 99, 'c': 4} (values of the second dictionary replace the first)

2️⃣ The in-place update operator |= (Python 3.9+) — if you need to modify the first dictionary in place.

dict1 |= dict2

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250+ Python DSA Coding Practice Test [Questions & Answers]

Python DSA Coding Interview Questions and Answers (Solution Code with Detailed Explanations) | Coding Practice Exercises…

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**Today we will examine __call__ — a data filter object!** 🧠

It allows a class instance to work as a function, preserving the state and filtering rules. ⚙️

Let's create a filter for numbers that only passes even ones and strictly greater than a specified threshold:

class EvenFilter:
    def __init__(self, threshold):
        self.threshold = threshold

    def __call__(self, numbers):
        return [n for n in numbers if n % 2 == 0 and n > self.threshold]

Let's use the filter in practice:

f = EvenFilter(5)
nums = [1, 4, 6, 7, 10]
print(f(nums))  # [6, 10]

Now each instance can have its own rules:

f2 = EvenFilter(8)
print(f2(nums))  # [10]

🔥 So, __call__ turns an object into a "smart function" with memory and customizable logic. 💡

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collections.Counter — counting elements in a single line. 📊

Counting elements without loops with Counter 🔄

Do you need to count how many times each word appears in a text or how many duplicates there are in a list? Don't reinvent the wheel with for loops and dictionaries. The built-in collections module will do everything for you. 🚀

🛠 Code:

from collections import Counter

words = ["apple", "banana", "apple", "cherry", "banana", "apple"]
word_counts = Counter(words)

print(word_counts)
# Output: Counter({'apple': 3, 'banana': 2, 'cherry': 1})

# Bonus: the top 2 most frequent elements
print(word_counts.most_common(2))
# Output: [('apple', 3), ('banana', 2)]

Ideal for basic data analysis and solving tasks on LeetCode. 💻

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Search for a substring in Python 🐍

In this example, two simple ways of finding a substring in a string are shown, which allow to solve the task without unnecessary code 💻

# Example implementation
def find_substring(text, sub):
    return text.find(sub)

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What's the difference between is and == in Python?

The == operator checks whether the values of two objects are equal. In contrast, is determines whether variables refer to same object in memory. That is, == compares the content, while is checks the identity of the objects 🐍🔍

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✨ Unpacking the remaining elements 🧩

Sometimes you need to extract the first and last elements from a list, while grouping everything in the middle separately. Instead of struggling with slicing ([1:-1]), use the asterisk (*). ⭐️

data = ["CEO", "Middle Python Dev", "Junior Dev", "QA", "HR"]

# The asterisk automatically collects everything "extra" into a separate list.
boss, *team, hr = data

print(boss)    # CEO
print(team)    # ['Middle Python Dev', 'Junior Dev', 'QA']
print(hr)      # HR

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Python Practice Tests: 210+ Questions Basics to Advanced

210+ Python questions: fundamentals, OOP, libraries & advanced concepts. Ace your interview & certification prep.…

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Python allows you to create enumerations that are also regular strings!

Previously, when working with APIs, JSON, and configurations, it was often necessary to manually extract the value from an Enum.

For example:

class Status(Enum):
    ACTIVE = "active"

When serializing, you would get an enumeration object:
Status.ACTIVE

rather than a regular string:
"active"

In Python 3.11, StrEnum was introduced to solve this problem.

from enum import StrEnum

class Status(StrEnum):
    ACTIVE = "active"
    BLOCKED = "blocked"

Now, the value can be used wherever a string is expected:

json.dumps({"status": Status.ACTIVE})

The result:
{"status": "active"}

At the same time, the advantages of enumerations are preserved:
Status.ACTIVE
Status.BLOCKED

You cannot accidentally pass an incorrect value:
Status("unknown")

will result in an error.

🔥 StrEnum allows you to combine the strict typing of enumerations with the convenience of regular strings, without manual conversion when working with APIs, JSON, and configurations.

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