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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💡 Replacing if-else with Match-Case

Starting with Python 3.10, we have a powerful tool: Structural Pattern Matching (match-case). This is not just an analog of switch-case from other languages; it's much more flexible. 🚀

Imagine you're writing a command handler for a bot. 🤖

❌ How NOT to do it:

def handle_command(command):
    if command == "start":
        return "Hello! I'm a bot."
    elif command == "help":
        return "Here's a list of available commands..."
    elif command == "stop":
        return "Goodbye!"
    else:
        return "Unknown command."

⚡ How to do it properly:

def handle_command(command):
    match command:
        case "start":
            return "Hello! I'm a bot."
        case "help":
            return "Here's a list of available commands..."
        case "stop":
            return "Goodbye!"
        case _:  # The underscore symbol catches everything else (default)
            return "Unknown command."

The code looks like a clear table, and your eye doesn't get caught up in a bunch of elif statements. 🧐
You can pass data structures in the case statements and check their structure and content on the fly. 🔍
It's easy to combine cases. 🧩

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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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Cheat sheet on Python Frameworks:

Django: A full-featured web framework with built-in ORM, admin panel, and security features.

Flask: A lightweight microframework with a minimal set of features and high flexibility.

ORM & Admin: Built-in to Django, but need to be connected separately in Flask.

Security: Django has built-in security mechanisms, while in Flask, they need to be configured manually.

Testing: Django offers built-in testing tools, while Flask relies on third-party libraries.

Use Cases: Django is suitable for large and complex projects, while Flask is better for small applications, APIs, and prototypes.

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🐱 Awesome Python Typing — Everything for Learning Typing in Python! 🐍✨

If you want to understand type annotations in Python, this repository is definitely worth saving. It contains the best articles, books, tools, libraries, and other materials dedicated to typing and its use in real-world projects. 💻📚

Here's the link: GitHub 📱
https://github.com/typeddjango/awesome-python-typing

https://github.com/typeddjango/awesome-python-typing

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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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