📂 Reminder on Python set — set methods!

For example, add() adds an element to the set, update() combines several elements, and intersection() helps quickly find common values between data sets.

In the picture — the main methods and operations for working with set: addition, removal, union, intersection, difference, and set checks.

Save it to not lose it!

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10 GitHub Repositories for Web Development in Python 🐍

Explore the best Python web development repositories for building APIs, full-stack web apps, dashboards, machine learning demos, internal tools, and interactive Python-based user interfaces. 🔥

https://www.kdnuggets.com/10-github-repositories-for-web-development-in-python

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Guessing numbers

This project for beginners in Python is a fun game that generates a random number (within a certain range) that the user must guess after receiving hints.

For each incorrect guess, the user receives additional hints, but at the cost of reducing their overall score.

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What are lambda functions in Python?

Lambda functions — are anonymous functions, which are created using the lambda keyword. They can accept any number of arguments, but contain only one expression, the result of which is automatically returned.

They are most often used for short operations, for example during sorting, filtering or data processing.

# Example:
sorted_data = sorted(data, key=lambda x: x[1])
filtered_data = list(filter(lambda x: x > 0, numbers))

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👍 Fluent Python — practical examples from one of the best Python books!

Here, the language's capabilities are explained, which many only know superficially. The material focuses not on basic syntax, but on a deep understanding and proper use of its capabilities in real projects. There are many examples of working with objects, collections, functions, decorators, generators, async code, and Python's internal logic.

I'll leave a link: https://github.com/fluentpython/example-code-2e

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What is the difference between copy() and deepcopy() in Python?

copy() creates a shallow copy of the object: nested elements remain shared between both copies. In contrast, deepcopy() recursively copies all nested objects, making the new structure completely independent. This is particularly important when working with mutable data

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When applying multiple filters to a series in Pandas, it's better to break the condition into several lines:

s = pd.Series([10, 15, 20, 25, 30])

s.loc[
    (s > 20) &
    (s % 2 == 1)
]

Such code is easier to read, write, and maintain. 🛠️✨

As a result, the value:
25
will be selected,
since it is both greater than 20 and an odd number. 🎯

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