Python/ django
по всем вопросам @haarrp @itchannels_telegram - 🔥 все ит каналы @ai_machinelearning_big_data -ML @ArtificialIntelligencedl -AI @datascienceiot - 📚 @pythonlbooks РКН: clck.ru/3FmxmM
Show more📈 Analytical overview of Telegram channel Python/ django
Channel Python/ django (@pythonl) in the Russian language segment is an active participant. Currently, the community unites 59 997 subscribers, ranking 2 202 in the Technologies & Applications category and 10 246 in the Russia region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 59 997 subscribers.
According to the latest data from 11 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -568 over the last 30 days and by -5 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 6.98%. 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 4 188 views. Within the first day, a publication typically gains 1 867 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 22.
- 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 @haarrp
@itchannels_telegram - 🔥 все ит каналы
@ai_machinelearning_big_data -ML
@ArtificialIntelligencedl -AI
@datascienceiot - 📚
@pythonlbooks
РКН: clck.ru/3Fmxm...”
Thanks to the high frequency of updates (latest data received on 12 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.
Apache Kafka и RabbitMQ.
• Github
@pythonlpip install -U clarifai
Импортировать наборы данных вместе с аннотациями.
- Создавать приложения, входы, наборы данных и выполнять прогнозирование моделей.
- Доступ к моделям, рабочим процессам и другим LLM от сообщества Clarifai с помощью всего нескольких строк кода.
• Github
Demo
@pythonl
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