Python/ django
по всем вопросам @workakkk @itchannels_telegram - 🔥 все ит каналы @ai_machinelearning_big_data -ML @ArtificialIntelligencedl -AI @datascienceiot - 📚 @pythonlbooks РКН: clck.ru/3FmxmM
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📈 Analytical overview of Telegram channel Python/ django
Channel Python/ django (@pythonl) in the Russian language segment is an active participant. Currently, the community unites 58 382 subscribers, ranking 2 244 in the Technologies & Applications category and 10 292 in the Russia region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 58 382 subscribers.
According to the latest data from 04 November, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -248 over the last 30 days and by -10 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 5.91%. Within the first 24 hours after publication, content typically collects 3.11% reactions from the total number of subscribers.
- Post reach: On average, each post receives 3 452 views. Within the first day, a publication typically gains 1 813 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 17.
- Thematic interests: Content is focused on key topics such as github, claude, контекст, архитектура, api.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“по всем вопросам @workakkk
@itchannels_telegram - 🔥 все ит каналы
@ai_machinelearning_big_data -ML
@ArtificialIntelligencedl -AI
@datascienceiot - 📚
@pythonlbooks
РКН: clck.ru/3Fm...”
Thanks to the high frequency of updates (latest data received on 05 November, 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 --upgrade translatepy
List of Built-in Services
- Microsoft Bing Translator
- DeepL
- Google Translate
- LibreTranslate
- Microsoft Translator
- MyMemory
- Reverso
- Translate.com
- Yandex Translate
⚙️ Github
@pythonl
import pandas as pd
now = pd.Timestamp.now()
print("Add a day:", now + pd.offsets.DateOffset(days=1))
print("Add a week:", now + pd.offsets.DateOffset(weeks=1))
print("Add a month:", now + pd.offsets.DateOffset(months=1))
print("Add an hour:", now + pd.offsets.DateOffset(hours=1))
print("Add a day, replace the hour:", now + pd.offsets.DateOffset(days=1, hour=13))
print("Add a month, normalize:", now + pd.offsets.DateOffset(month=1, normalize=True))
print("Add 2 days across DST change:", pd.Timestamp("2022-11-05 00:00:00", tz="America/Chicago") + pd.offsets.DateOffset(days=2))
print("Add 2 days across DST change (with Timedelta, no adjustment):", pd.Timestamp("2022-11-05 00:00:00", tz="America/Chicago") + pd.Timedelta(days=2))
https://www.wrighters.io/use-pandas-dateoffsets-for-easy-date-manipulation/
@pythonl