98.5K
COComment ( #python ) for code
Flow for more ( @codingpythonic )
#programming #coding #pythondeveloper #codinglife #pythonprogramming #learntocode
@codes.student
#Trio Python Library Update
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REUseful Python Libraries.!!
@rengatechnologies
#python #pythonlibraries #learnpython #kovilpatti #sivakasi
@rengatechnologies
75.5K
CYPython Libraries🚀
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@cyfotok_tamil
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ARYour AI coding assistant might be a career bottleneck in disguise.
Anthropic just released a new research paper to investigate how AI impact skill formation. The study focused on engineers learning Trio, a Python library for asynchronous programming, to see if AI speed comes at the cost of technical mastery.
The Experiment Design
Engineers were split into 2 groups. The control group coded by hand using traditional documentation. The treatment group had access to an AI assistant with full codebase context and a nudge to move as fast as possible. Both groups were evaluated on four specific criteria: debugging, code reading, low level code writing, and conceptual understanding.
The Technical Results
The AI group finished only two minutes faster on average which was not statistically significant. However, their comprehension scores were a disaster. The AI group averaged 50 percent on the evaluation versus 67 percent for the manual group. The Cohen d effect size was 0.738, indicating a substantial negative impact on learning.
The biggest failure point was debugging. Scores in this category plummeted because users who offloaded the logic to AI never developed the mental model required to find and fix errors when the code failed.
The Patterns they observed:
Anthropic identified distinct ways developers interact with AI that determine if they actually learn
Low scoring patterns included AI Delegation where users let the bot write everything, Progressive Reliance where they started manual but gave up, and Iterative Debugging where they let the AI fix its own mistakes without understanding why.
High scoring patterns included Conceptual Inquiry where users only asked the AI to explain principles, and Generation then Comprehension where they generated code but then grilled the AI on the logic afterward.
The takeaway is clear. Efficiency without engagement is a trap. If you are not using AI to explain the why you are effectively de-skilling yourself in real time.
PS- If you are still reading this, comment “Old School Coder” so that I know you’re the real deal!
#ai #vibecoding #anthropic #artificialintelligence #technews
@arnitly
13.8K
WO📌Top 10 Python Libraries - AI/ML/Data 👩🏻💻☕️
1. MCP Python SDK & FastMCP - connect LLMs to external data sources
2. Token-Oriented Object Notation (TOON) - compact JSON encoding for LLMs
3. Deep Agents - framework for building sophisticated LLM agents
4. smolagents - agent framework that executes actions as code
5. LlamaIndex Workflows - building complex AI workflows with ease
6. Batchata - unified batch processing for AI providers
7. MarkItDown - convert any file to clean Markdown
8. Data Formulator - AI-powered data exploration through natural language
9. LangExtract - extract key details from any document
10. GeoAI - bridging AI and geospatial data analysis
Source: tryolabs.com
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#datascience #python #setup #fyp #datascientist
@woman.engineer
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PYCan you solve this Python challenge?
Test your Python skills and logical thinking with this short quiz.
Leave your answer in the comments and check if you got it right.
Subscribe for regular Python coding questions and improve your problem-solving abilities.
These challenges are great for daily practice, coding interviews, and learning by doing.
Run the quiz in your computer!
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#Developer #Learning #Tech
@python.challenges
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BAPattern programs in python
Follow @basic_python for more content on computer science, programming, technology, and Python language
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@basic_python
379.3K
ZUPython Quiz 🐍
What will be the output?
Comment your answer
I’ll DM you the correct one 👇
#PythonTrick #PythonQuiz #LearnPython #CodePuzzle #DeveloperLife
@zuhrah.tech
49.1K
MAPython libraries that you will use in every ML project you create…pretty much 😂🥹
#machinelearning #python
@mar_antaya
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HEDay 4: Understanding Libraries in Python 📚
Welcome to day 4 of learning python in 30 days😃
Libraries in Python are like collections of pre-written code that you can use to make your coding easier, just like using a recipe to cook faster and better 🍲
Here are 10 essential libraries and their uses:
1. Requests - for making HTTP requests 🌐
2. BeautifulSoup - for web scraping 🕸️
3. NumPy - for numerical computations 🔢
4. Pandas - for data manipulation 🗂️
5. Matplotlib - for creating visualizations 📊
6. Scikit-learn - for machine learning 🤖
7. TensorFlow - for deep learning 🧠
8. Flask - for building web applications 🌟
9. Pygame - for game development 🎮
10.Turtle - for drawing and Graphics 📈
For the complete lecture and hands-on activity, check out my YouTube channel ! Make sure to subscribe and press the bell icon 🔔 to stay updated.
Don’t forget to follow me here on Instagram for more updates and coding tips! 🚀
#Python #PythonLibraries #LearnPython #Coding #Programming #Tech #LearnToCode #30DaysOfPython #Day4 #freecourse #onlinecoaching #learntocode #ai
[ai, learn to code, free python course, technology, digital, coding, beginner coding ]
@helloworld_avani
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NIPython Day-1❤️🔥
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#python #telugumemes #learningisfun #learnpython #coder #programming #codinglife #development #pythoncode #learntocode #learnintelugu #teachingintelugu #30daysofcode
@niihaaarrrr
2.2M
DUMany find Python unsuitable for mobile apps due to limited library support. While the future is uncertain, current options are lacking. #Python #MobileAppDevelopment #Programming #Tech #SoftwareDevelopment
@durgajobsinfo
✨ #Trio Python Library Update Entdeckungsleitfaden
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