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
نمایش بیشتر📈 تحلیل کانال تلگرام Learn Python Coding
کانال Learn Python Coding (@pythonre) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 40 049 مشترک است و جایگاه 3 238 را در دسته فناوری و برنامهها و رتبه 9 700 را در منطقه الهند دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 40 049 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 26 اوت, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 182 و در ۲۴ ساعت گذشته برابر -10 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 2.93% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 1.12% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 1 172 بازدید دریافت میکند. در اولین روز معمولاً 447 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 3 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند math, harvard, oxford, supervision, waybienad تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“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”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 27 اوت, 2026)، کانال همواره بهروز و دارای دسترسی بالاست. تحلیلها نشان میدهد مخاطبان بهطور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته فناوری و برنامهها تبدیل کردهاند.
add() adds an element to the set, update() combines several elements, and intersection() helps quickly find common values between data sets.
In the picture — the main methods and operations for working with set: addition, removal, union, intersection, difference, and set checks.
Save it to not lose it!
#Python #SetMethods #Coding #DataScience #Programming #HelloEncyclo
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👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHOsafe = dict(config)
MappingProxyType creates a read-only proxy over a dictionary — writing through it becomes impossible, but the data is not copied.
readonly["debug"] = True # TypeError
At the same time, the proxy remains alive: if the original dictionary changes, the changes will automatically be reflected in the read-only view.
config["debug"] = True
This is especially useful for configurations, internal APIs, overall state, and data protection within libraries.
def get_settings():
return MappingProxyType(settings)
🔥 MappingProxyType allows you to provide a read-only view of the dictionary without copying and without the risk of mutation through the returned object.
#Python #Immutable #DataProtection #MappingProxyType #ProgrammingTips #NoCopy
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👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHOfrom collections import Counter
# Initial list with duplicate elements
logs = ["error", "info", "error", "warning", "error", "info"]
# 1. Instantly count the number of occurrences
count_dict = Counter(logs)
print(count_dict) # Counter({'error': 3, 'info': 2, 'warning': 1})
# 2. Get the most frequent elements (Top-2)
print(count_dict.most_common(2)) # [('error', 3), ('info', 2)]
# 3. Set math for counters
clicks_day1 = Counter(item=4, banner=2)
clicks_day2 = Counter(item=1, banner=5)
# Combine the results of two days in a single operation
print(clicks_day1 + clicks_day2) # Counter({'banner': 7, 'item': 5})
Forget about manual loops and dictionaries 🚫🔄
When you need to count the frequency of words in a text, the distribution of log types, or popular products in a store, developers usually create an empty dictionary and write a loop with a check if key not in dict: dict[key] = 1. The Counter class takes all this dirty work on itself and makes it as efficient as possible.
— Automatic initialization: You no longer need to check if a key exists in the dictionary. If the element is not there, Counter will not throw a KeyError, but simply return 0. 🛡️
— Finding leaders without sorting: The most_common(k) method returns a list of the k most frequently occurring elements. Under the hood, Python uses optimized heap algorithms, which work much faster than a full dictionary sort via sorted(). 🏆
— Mathematical operations: You can add, subtract, intersect, and merge Counter objects. This turns them into a powerful tool for aggregating metrics and analytics from different data sources in a few lines of code. ➕➖
#Python #DataScience #Coding #Programming #Automation #DevOps
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