Learn Python Coding

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Learn Python through simple, practical examples and real coding ideas. Clear explanations, useful snippets, and hands-on learning for anyone starting or improving their programming skills. Admin: @HusseinSheikho || @Hussein_Sheikho

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Канал Learn Python Coding (@pythonre) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 39 105 подписчиков, занимая 3 510 место в категории Технологии и приложения и 10 621 место в регионе Индия.

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С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 39 105 подписчиков.

Согласно последним данным от 04 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 481, а за последние 24 часа — 16, при этом общий охват остаётся высоким.

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“Learn Python through simple, practical examples and real coding ideas. Clear explanations, useful snippets, and hands-on learning for anyone starting or improving their programming skills. Admin: @HusseinSheikho || @Hussein_Sheikho”

Благодаря высокой частоте обновлений (последние данные получены 05 июня, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Технологии и приложения.

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Архив постов

39 105

Why in Python it is better to check None using is 🐍 In Python, you should not write obj == None, even if sometimes it works the same ⚠️ The reason is that == calls the comparison method eq, which can be overridden in the class — and then the behavior becomes unpredictable 🎲 For example:

class Weird:
    def eq(self, other):
        return True  # always says "equal"

obj = Weird()

print(obj == None)  # True
print(obj is None)  # False

Here obj == None gives a false result due to custom logic 🤔 Instead: obj is None is checks the identity of the object and cannot be overridden. Since None is a singleton, such a check is always correct and predictable ✅ Conclusion: to check for None always use is None — it is the right and safe approach 🛡️ ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A #Python #Programming #Coding #SoftwareDevelopment #TechTips #DevCommunity

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🚀 HelloEncyclo Presale is LIVE! Master the skills that matter — Gen-AI, Data Science, Machine Learning and more — all in one place. 🎁 First 250 members get a flat 40% OFF Use code: PRESALE-BOOK-WAVE-2GFG ✅ 13 full courses live right now ✅ 40+ more dropping in the next 2–3 weeks ✅ Complete library within 2 months — built and refined by industry experts ✅ 15-day money-back guarantee — don't love it? Get a full refund. ⚠️ Coupon works only after you log in with Gmail, and it's valid once per member. 👉 Log in now and start learning: https://helloencyclo.com Don't wait — the 40% deal disappears after the first 250 seats. 🔥

39 105

❤️ Architecture Patterns — an informative repository on backend architecture in Python! Here, they excellently demonstrate how to properly separate application logic, work with complex architecture, build a scalable backend, and maintain a codebase in an adequate state as the project grows. Instead of dry theory, the authors gradually build a full-fledged application and show how the architecture evolves as the project grows. I'll leave a link: https://github.com/cosmicpython/book #Python #Backend #Architecture #Coding #DevCommunity #OpenSource ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

39 105

Data validation with Pydantic! 🐍✨ In the early stages of development, data validation usually doesn't cause problems. In many Python projects, validation initially looks simple:

if not isinstance(age, int):
    raise ValueError("age must be an int")

But then come email, JSON from APIs, query parameters, nested objects, configs, nullable fields, and type conversion. At some point, the code turns into a set of if/else and manual checks. For such tasks, Pydantic is often used. Installation:

pip install pydantic
pip install "pydantic[email]"

Create a model:

from pydantic import BaseModel

class User(BaseModel):
    name: str
    age: int

Now the data is validated automatically:

user = User(
    name="Alex",
    age="30"
)

print(user.age)
print(type(user.age))

The result: 30 <class 'int'> Pydantic will automatically convert the string "30" to an int. If you pass an incorrect value, you'll get a ValidationError:

User(
    name="Alex",
    age="test"
)

This is especially convenient when working with APIs, JSON, query parameters, and incoming data from outside. A common production case is checking email:

from pydantic import BaseModel, EmailStr

class User(BaseModel):
    email: EmailStr

User(email="alex@test.com")

If the email is invalid, Pydantic will throw a ValidationError. You can set default values:

from pydantic import BaseModel

class Config(BaseModel):
    host: str = "localhost"
    port: int = 5432

And allow None:

from pydantic import BaseModel

class User(BaseModel):
    nickname: str | None = None

This field becomes optional. A practical example is processing an API response:

from pydantic import BaseModel

class Product(BaseModel):
    id: int
    title: str
    price: float

data = {
    "id": "1",
    "title": "Keyboard",
    "price": "99.5"
}

product = Product(**data)

print(product)

The types will be automatically converted. For nested model structures, you can combine:

from pydantic import BaseModel

class Address(BaseModel):
    city: str
    zip_code: str

class User(BaseModel):
    name: str
    address: Address

user = User(
    name="Alex",
    address={
        "city": "Berlin",
        "zip_code": "10115"
    }
)

print(user)

The nested object will also be validated. Serialization in Pydantic v2:

print(user.model_dump())
print(user.model_dump_json())

Pydantic is actively used in FastAPI, ETL, microservices, data pipelines, and API clients. For working with environment variables in Pydantic v2, a separate package is usually used:

pip install pydantic-settings

It's important to understand: Pydantic is not an ORM and does not replace business logic. Its task is to validate data, convert types, and describe schemas. 🔥 Pydantic significantly reduces the amount of manual data validation and makes processing incoming structures more predictable. #Python #Pydantic #DataValidation #FastAPI #Coding #DevOps ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

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Why is enumerate() used in Python? 🤔 It allows you to simultaneously obtain the value of an element and its index when iterating through a list. 📊 This is more convenient and more readable than manually working with a counter. ✅

for i, item in enumerate(items):
    print(i, item)

#Python #Coding #Programming #Dev #Tech #Code

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"Introduction to Algorithms" 📘 - an outstanding university resource for everyone studying algorithms and computer science. 🎓💻 The book covers computational complexity, data structures, algorithms on graphs, dynamic programming, divide-and-conquer methods, greedy algorithms, randomized algorithms, and many mathematical foundations of modern computer science. 🧮📊🔍 What's particularly valuable here is the combination of mathematical rigor and practical algorithmic thinking. 🧠✨ This is one of those books that greatly change the approach to problem analysis, efficiency, and computing itself. 🚀🛠 An essential tool in the library of any developer and engineer working in the field of computer science. 🏗💾 https://www.cs.mcgill.ca/~akroit/math/compsci/Cormen%20Introduction%20to%20Algorithms.pdf 🔗 #Algorithms #ComputerScience #Programming #CSStudent #TechEducation #DevTools

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If you're working with data pipelines, these repositories are very useful: 🚀📊 ibis: A Python API that allows you to write queries once and run them on different data backends, such as DuckDB, BigQuery, and Snowflake. 🐍🔗 https://github.com/ibis-project/ibis pygwalker: Instantly turns a DataFrame into an interactive UI for visual data exploration. 📈🖥️ https://github.com/Kanaries/pygwalker katana: A fast and scalable web crawler, often used for security testing and large-scale data collection/search. 🕷️🔒 https://github.com/projectdiscovery/katana #dataengineering #python #opensource #devtools #dataviz #security

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📂 Reminder about Python map()! map() — a built-in function that applies the specified function to each element of an iterable object (list, tuple, set, etc.). The picture shows the basic syntax, an example of use with lambda, and a typical case — data transformation without a manual for loop. Save it to quickly remember the syntax! 🐍💻🗺️ #Python #Coding #Programming #LearnToCode #DevTips #Tech

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"Open Data Structures" is another very useful free resource for anyone studying data structures and algorithms. 📚✨ The book discusses the implementation and analysis of basic structures: array-based lists, linked lists, hash tables, binary trees, red-black trees, heaps, sorting algorithms, graphs, and data structures for working with integers. 🔍🧮 This is a full-fledged open textbook for studying one of the fundamental topics of computer science and a good reference that's worth keeping on hand. 💻🌟 https://opendatastructures.org/ods-python.pdf 📄 👉 @PythonRe #DataStructures #Algorithms #Python #ComputerScience #OpenSource #Learning

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Do you know that Python can shift sequences without slicing and creating new lists? 🤔 When you need to cyclically shift data, many use slicing:

data = data[-1:] + data[:-1]

But deque.rotate() does this at the level of the data structure and usually works more efficiently for cyclical operations. 🚀

q.rotate(1)

A negative value rotates the queue in the other direction. ⬅️

q.rotate(-2)

This is useful for ring buffers, task schedulers, cyclical queues, and round-robin algorithms. 🔄

workers.rotate(-1)

🔥 deque.rotate() allows you to implement cyclical data structures without manual index logic and without creating new lists. 💡 #Python #Programming #Deque #CodingTips #Tech #DevCommunity