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

#Python #WebDevelopment #GitHub #Coding #API #Tech

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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.

💡🐍🎮 #Python #Coding #Beginners #Game #Learning #Tech

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How to create an object from a dictionary with dot access — without classes and dataclasses?

When you're working with JSON, configurations, or APIs, constant access via dict['key'] clutters the code and worsens readability:

data = {"host": "localhost", "port": 5432}
data["host"]

SimpleNamespace gives the same result, but with dot access:

cfg = SimpleNamespace(**data)
print(cfg.host)

In this case, the object remains dynamic, and you can add fields:

cfg.debug = True

However, the keys must be valid attribute names, and this only works for flat dictionaries (nesting is not converted).

🔥Convenient for prototyping, testing, and simple data.

#Python #DataStructures #SimpleNamespace #CodingTips #DevTools #Programming

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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))

#Python #LambdaFunctions #DataScience #Coding #Programming #TechTips

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😍 learnxinyminutes — a brief and informative reference guide!

A convenient cheat sheet that allows you to quickly get acquainted with the basics of Python or refresh your knowledge before work. On one page, the key constructs of the language are collected: variables, functions, classes, collections, exception handling, etc. The format is as compact as possible, with a minimum of theory and a maximum of practical examples.

📌 I'll leave a link: learnxinyminutes.com

#Python #LearnToCode #Programming #CheatSheet #WebDev #CodingLife

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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

#Python #Programming #FluentPython #Developer #Tech #Coding

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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. 🎯

#Pandas #Python #DataScience #Coding #Programming #DataAnalysis

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Learn AI Python Machine Learning Data Science Big Data

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Replit Python Programming+Python Bootcamp Beginner Tutorial

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