Learn Python Coding
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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Channel Learn Python Coding (@pythonre) in the English language segment is an active participant. Currently, the community unites 39 123 subscribers, ranking 3 502 in the Technologies & Applications category and 10 597 in the India region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 39 123 subscribers.
According to the latest data from 05 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 458 over the last 30 days and by 21 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 2.68%. Within the first 24 hours after publication, content typically collects 1.04% reactions from the total number of subscribers.
- Post reach: On average, each post receives 1 048 views. Within the first day, a publication typically gains 405 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
- Thematic interests: Content is focused on key topics such as math, harvard, oxford, supervision, waybienad.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“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”
Thanks to the high frequency of updates (latest data received on 07 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.
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']) # 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/DataScience4frozendict 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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