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Learn Python Coding

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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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

Yuqori yangilanish chastotasi (oxirgi ma’lumot 07 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

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📱 Cheat Sheet for Beautiful Soup 4 Beautiful Soup — a library for extracting data from HTML and XML files, which is perfect for web scraping. 1. Installation
pip install beautifulsoup4
2. Import
from bs4 import BeautifulSoup
import requests
3. Basic parsing
html_doc = "<html><body><p class='text'>Hello, world!</p></body></html>"
soup = BeautifulSoup(html_doc, 'html.parser')  # or 'lxml', 'html5lib'
print(soup.p.text)  # Hello, world!
4. Finding elements
# First found element
first_p = soup.find('p')

# Search by class or attribute
text_elem = soup.find('p', class_='text')
text_elem = soup.find('p', {'class': 'text'})

# All elements
all_p = soup.find_all('p')
all_text_class = soup.find_all(class_='text')
5. Working with attributes and text
a_tag = soup.find('a')
print(a_tag['href&#39])    # value of the href attribute
print(a_tag.get_text()) # text inside the tag
print(a_tag.text)       # alternative
6. Navigating the tree
# Moving to parent, children, siblings
parent = soup.p.parent
children = soup.ul.children
next_sibling = soup.p.next_sibling

# Finding the previous/next element
prev_elem = soup.find_previous('p')
next_elem = soup.find_next('div')
7. Parsing a real page
response = requests.get('https://example.com')
soup = BeautifulSoup(response.text, 'html. parser')
title = soup.title.text
links = [a['href'] for a in soup.find_all('a', href=True)]
8. CSS selectors
# More powerful and concise search
items = soup.select('div.content > p.text')
first_item = soup.select_one('a.button')
tags: #cheat_sheet #useful https://t.me/DataScience4

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In Python 3.15, there will be a fully immutable dictionary. A new public immutable type, frozendict, is added to the builtins module. It is expected that frozendict will be "safe by design", because it prevents any unintended changes. This is useful not only for the CPython standard library, but also for third-party maintainers: you can rely on a reliable immutable dictionary type. Why is this needed at all: ▪️Do you want to use a map as a key in another dict or put it in a set? A regular dict is not allowed, but a frozendict is (if the values are also hashable). ▪️ @functools.lru_cache() and arguments-dictionaries: it's difficult with a dict, but normal with a frozendict. ▪️Defaults in function arguments: instead of a "mutable default", you can give frozendict(...) and not get surprises. How it looks in the API: ▪️The constructor "like a dict": frozendict(), frozendict(**kwargs), frozendict(mapping) or iterable pairs, plus you can mix with **kwargs. ▪️The order of insertion is preserved (as in a regular dict). ▪️The hash does not depend on the order of elements (logic via frozenset(items)), and the comparison is also based on the content, not on the order. ▪️There is a union via | and an "update" |= (but |= does not mutate the object, but creates a new one). ▪️.copy() in CPython essentially returns the same object (shallow), and if you need deep copying, then copy.deepcopy(). An important point: frozendict is NOT inherited from dict. This is done on purpose, so that you can't bypass the "immutability" by calling dict.__setitem__ and similar tricks. And a bonus for the stdlib: the authors have marked places where you can replace constant/public maps with frozendict (including where MappingProxyType is now used). 👉 @DataScience4

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third-party libraries | Python Best Practices ✨ 📖 Guidelines and best practices for choosing and using third-party libraries in your Python code. 🏷️ #Python

✨ Automate Python Data Analysis With YData Profiling ✨ 📖 Automate exploratory data analysis by transforming DataFrames into
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✨ Quiz: Python's tuple Data Type: A Deep Dive With Examples ✨ 📖 Practice Python tuples: create, access, and unpack immutable
Quiz: Python's tuple Data Type: A Deep Dive With Examples ✨ 📖 Practice Python tuples: create, access, and unpack immutable sequences to write safer, clearer code. Reinforce basics and avoid common gotchas. Try the quiz. 🏷️ #intermediate #python

refactoring | Python Best Practices ✨ 📖 Guidelines and best practices for refactoring your Python code. 🏷️ #Python

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