Learn Python Coding
الذهاب إلى القناة على Telegram
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
إظهار المزيد
الشبكة:📈 نظرة تحليلية على قناة تيليجرام Learn Python Coding
تُعد قناة Learn Python Coding (@pythonre) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 40 900 مشتركاً، محتلاً المرتبة 3 279 في فئة التكنولوجيات والتطبيقات والمرتبة 9 343 في منطقة الهند.
📊 مؤشرات الجمهور والحراك
منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 40 900 مشتركاً.
بحسب آخر البيانات بتاريخ 25 أكتوبر, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 455، وفي آخر 24 ساعة بمقدار 3، مع بقاء الوصول العام مرتفعاً.
- حالة التحقق: غير موثّقة
- معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 3.41%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 1.49% من ردود الفعل نسبةً إلى إجمالي المشتركين.
- وصول المنشورات: يحصل كل منشور على متوسط 1 395 مشاهدة. وخلال اليوم الأول يجمع عادةً 608 مشاهدة.
- التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 2.
- الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل math, harvard, oxford, supervision, waybienad.
📝 الوصف وسياسة المحتوى
يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
“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”
بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 26 أكتوبر, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.
40 900
المشتركون
+324 ساعات
+277 أيام
+45530 أيام
أرشيف المشاركات
40 900
Repost from Machine Learning with Python
This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages
✅ https://t.me/addlist/8_rRW2scgfRhOTc0
✅ https://t.me/Codeprogrammer
40 900
👩💻 heapq.merge(): Combining sorted data!
If you have multiple sources of data that are already sorted, you don't need to collect them into a single collection and sort them again.
heapq.merge() combines such sources into a single, ordered iterator.
In this guide:
• We will combine multiple sorted sequences;
• We will explore lazy processing of large data sources;
• We will configure comparison using the key argument;
• We will combine data sorted in reverse order.
This is especially useful when working with logs, files, and query results, where each source already provides data in the correct order.
#Python #heapq #DataProcessing #CodingTips #Programming #Algorithms
✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A40 900
Repost from Machine Learning with Python
This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages
✅ https://t.me/addlist/8_rRW2scgfRhOTc0
✅ https://t.me/Codeprogrammer
40 900
📌 Marking Deprecated Code in Python: deprecated()
In large projects, old functions are not always immediately removed. They are often left for compatibility, but it's important to warn developers that they should no longer be used.
Previously,
warnings.warn()was often used for this purpose:
import warnings
def old_api():
warnings.warn(
"Use new_api()",
DeprecationWarning
)deprecated()decorator has been introduced:
from warnings import deprecated
@deprecated("Use new_api()")
def old_api():
return "old"@deprecated("Use NewClient")
class OldClient:
pass
40 900
Do not violate the Single Responsibility Principle 🎯
A function should do one thing, and do it well.
This function does too much:
def calculate_final_total(
price: float,
quantity: int,
discount_rate: float,
tax_rate: float
) -> float:
# Calculate the subtotal
subtotal = price * quantity
# Apply the discount
discounted_amount = subtotal * (1 - discount_rate)
# Calculate the tax
final_total = discounted_amount * (1 + tax_rate)
return final_totaldef calculate_subtotal(price: float, quantity: int) -> float:
return price * quantity
def apply_discount(subtotal: float, discount: float) -> float:
return subtotal * (1 - discount)
def calculate_tax(amount: float, tax_rate: float) -> float:
return amount * (1 + tax_rate)40 900
Here's a small fact about Python 🐍
The
:= operator is called the "walrus" because the symbols resemble the eyes and tusks of a walrus 🦭
It was introduced in Python 3.8 and allows you to assign a value to a variable and use it directly within the expression at the same time.
For example:
while (line := input("Say something: ")) != "quit":
print(f"You said: {line}")input(), and then check it.
Have you ever used the := operator in your code?
#Python #Programming #WalrusOperator #Coding #TechFacts #Python3
✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A40 900
Get Up to 500MB of Residential Proxy Traffic for Your Python Projects 🐍
Building a web scraper with Python?
ThorData helps developers collect public web data while handling proxy rotation, geo-targeting, and access restrictions.
✅ Residential IPs across 190+ countries
✅ Country, city, and ASN-level targeting
✅ Rotating and sticky sessions
✅ HTTP(S) and SOCKS5 support
✅ Works with Requests, Scrapy, Selenium, and Playwright
🎁 Exclusive offer for Machine Learning with Python members
Eligible new users can receive up to 500MB of residential proxy traffic for testing.
Use channel code: PYTHONSCRAPE
👉 Start your test:
https://www.thordata.com/?ls=MQiAFqAo&lk=ps-02
Available to eligible new users. The actual trial traffic may vary, up to a maximum of 500MB.
40 900
Repost from Machine Learning with Python
📚 7 Best Websites to Learn Computer Science Subjects for Free
Struggling with subjects like DSA, DBMS, OS or Computer Networks? These free resources can make learning much easier
1. GeeksforGeeks 🧑💻
• DSA, DBMS, OS, CN and more
• Notes, articles, problems and tutorials
🔗 https://www.geeksforgeeks.org/
2. freeCodeCamp 🎓
• Programming, web development, Python and more
• Free courses with hands-on learning
🔗 https://www.freecodecamp.org/
3. CS50 by Harvard 🧠
• Excellent introduction to computer science
• Covers programming, algorithms, memory, databases and more
🔗 https://cs50.harvard.edu/
4. Neso Academy 📖
• Detailed lectures on OS, CN, DBMS, DSA and other CSE subjects
• Great for concept-based learning
🔗 https://www.youtube.com/@nesoacademy
5. W3Schools 🌐
• Learn HTML, CSS, JavaScript, SQL, Python and more
• Simple explanations with interactive examples
🔗 https://www.w3schools.com/
6. MIT OpenCourseWare 🎓
• University-level computer science courses
• Lectures, assignments and study material
🔗 https://ocw.mit.edu/
7. roadmap.sh 🗺
• Structured roadmaps for different tech careers
• Useful for planning what to learn next
🔗 https://roadmap.sh/
💾 Save this list for your next semester
40 900
🚀Round 2 – 14-Day CCNA & CCNP Study Sprint!
Our first 21-Day Sprint was a huge success — we saw amazing check-ins, great discussions, and a community that truly learned together. 🙌
Now we're back with a faster, tighter 14-Day Sprint — same energy, same prizes, easier to finish! 💪
📅 Sprint Period: Sep 14 – Sep 27 (UTC+8)
📝 How It Works:
① DM admin: "I'M IN + cert name" (e.g., I'M IN CCNA 200-301)
② Check in 12 out of 14 days → win prizes 🎁
🏆 Prizes (First come, first served!):
1️⃣ $10 SPOTO Universal Coupon ×2
2️⃣ Cisco SD-Access Training ($150 value) ×1
3️⃣ Cisco SD-WAN Training ($150 value) ×1
4️⃣ CCNA Training Pro Package ($59.99 value) ×10
5️⃣ Free Cisco Learning Pack – unlimited for all finishers 🎁
✅ Referral Bonus: Invite a friend → Get FREE EXAM DEMO
💻 DM admin to register: https://wa.me/8619559123054
JOIN 14 Days Study Sprint: https://chat.whatsapp.com/KZrAj2HZ3Y5K9UhhNhrApf
40 900
🧲 Your agent writes the tool. You keep the terminal closed.
You know the shape of the script before you open the editor. The hour goes to argparse, a retry wrapper, a rate limiter you have written eleven times already.
Create your own AI agent inside Telegram in about a minute, and create small tools with it right in the chat.
▫️ describe a tool in a sentence and it writes, runs and returns the working script
▫️ ships a mini-app inside Telegram — a form, a converter, a dashboard, no deploy and no hosting
▫️ drop in a traceback or a repo link and get the fix, not a lecture
▫️ swap the model per task with one command, so cheap work runs cheap
▫️ remembers your stack, your conventions and your project for months
▫️ voice in, answer back — describe the task on the way home, read the result when you are back
Setup takes a minute: open the link, start the free trial, name your agent.
30 days free, no card needed.
🧲 Create your agent
40 900
🌈 2026 Job-Seeker Toolkit – Free Interview & IT Cert Resources
🔥The 2026 hiring market is shifting fast. We've put together a 100% free resource bundle covering #Cisco, #AWS, #PMP, #AI, #Python, #Excel, and #Cybersecurity — including:
✅Q&A banks & mock exams
✅Behavioral interview guides
✅Technical deep-dives for coding & infrastructure roles
✅Real-world project scenarios
Perfect for Software Developer Jobs, IT Internships, and Python Projects practice.
🎯 Interview Question Bank → https://bit.ly/4A6m0hM
🪜 Online Free Course For Python & Excel→https://bit.ly/46bUzWm
📘 Free Cert E‑Book → https://bit.ly/4xXkAVx
☁️ Free AI Materials → https://bit.ly/4xMBLJd
📊 Cloud Study Guide → https://bit.ly/4cAQ8rN
🧠 Free Mock Exam → https://bit.ly/4xcp3Cx
Tag a friend who's job-hunting or grinding Python projects — let's ace it together! 💪
🧠 Join Study Community:
https://chat.whatsapp.com/DcpVeYSV6xNJzdBQU9eRyU
❄️ 1-on-1 support: https://wa.link/gyvbek
40 900
Creating Nested Dictionary Values using `setdefault()` 🔥
When grouping data, it's often necessary to check if a key exists, create a container for it, and then add a value.
For example, distributing users by role. Without special methods, this usually involves a separate key check.
users = [
("admin", "alex"),
("user", "max"),
("admin", "kate"),
]
groups = {}
for role, name in users:
if role not in groups:
groups[role] = []
groups[role].append(name)setdefault() method allows you to perform this operation directly when accessing the dictionary. If the key exists, it returns its current value. If the key is missing, the provided value is written to the dictionary and then returned:
groups = {}
for role, name in users:
groups.setdefault(
role,
[],
).append(name)print(groups)
# {
# 'admin': ['alex', 'kate'],
# 'user': ['max']
# }setdefault() is called, even if the key already exists. Therefore, you should avoid creating expensive objects or performing functions with side effects there:
value = cache.setdefault(
key,
build_value(),
)build_value() will be called before the method itself is executed. If the value creation should only happen when the key is missing, it's better to use an explicit check or a suitable data structure, such as defaultdict.
🔥 setdefault() is well-suited for compactly initializing simple mutable containers when grouping and aggregating data. However, it's important to remember that the provided value is evaluated regardless of whether the key exists.
#Python #Coding #Dicts #Programming #CodeTips #DevLife
✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
