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Learn Python Coding

Learn Python Coding

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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

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“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”

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🔰 Convert Images to PDF using Python
🔰 Convert Images to PDF using Python

This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visua
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

Important Python Functions
Important Python Functions

🐍 Tip of the day for experienced Python developers 📌 Use decorators with parameters — a powerful technique for logging, control, caching, and custom checks. Example: a logger that can set the logging level with an argument:

import functools
import logging

def log(level=logging.INFO):
   def decorator(func):
       @functools.wraps(func)
       def wrapper(*args, **kwargs):
           logging.log(level, f"Call {func.__name__} with args={args}, kwargs={kwargs}")
           return func(*args, **kwargs)
       return wrapper
   return decorator

@log(logging. DEBUG)
def compute(x, y):
   return x + y
✅ Why you need it: The decorator is flexibly adjustable; Suitable for prod tracing and debugging in maiden; Retains the signature and docstring thanks to @functools.wraps. ⚠️ Tip: avoid nesting >2 levels and always write tests for decorator behavior. Python gives you tools that look like magic, but work stably if you know how to use them.

8. Set up the user interface and trigger the main function. • Provides an input field for the user's question • Triggers the
8. Set up the user interface and trigger the main function. • Provides an input field for the user's question • Triggers the main function when the user clicks "Get Answer"

7. Define the main function to run all LLMs and aggregate results. • Runs all reference models asynchronously • Displays indi
7. Define the main function to run all LLMs and aggregate results. • Runs all reference models asynchronously • Displays individual responses in expandable sections • Aggregates responses using the aggregator model • Streams the aggregated response.

6. Implement the LLM call function. • Asynchronously calls the LLM with the user's prompt • Returns the model name and its re
6. Implement the LLM call function. • Asynchronously calls the LLM with the user's prompt • Returns the model name and its response

5. Define the models and aggregator system prompt. • Specifies the LLMs to be used for generating responses • Defines the agg
5. Define the models and aggregator system prompt. • Specifies the LLMs to be used for generating responses • Defines the aggregator model and its system prompt

4. Initialize Together AI clients. • Sets up Together API key as an environment variable • Initializes both synchronous and a
4. Initialize Together AI clients. • Sets up Together API key as an environment variable • Initializes both synchronous and asynchronous Together clients

3. Set up the Streamlit app and API key input. • Creates a title for the app • Adds a secure input field for the Together API
3. Set up the Streamlit app and API key input. • Creates a title for the app • Adds a secure input field for the Together API key

2. Import necessary libraries • Streamlit for the web interface • asyncio for asynchronous operations • Together AI for LLM i
2. Import necessary libraries • Streamlit for the web interface • asyncio for asynchronous operations • Together AI for LLM interactions

1. Install the necessary Python Libraries Run the following commands from your terminal to install the required libraries:
1. Install the necessary Python Libraries Run the following commands from your terminal to install the required libraries:

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🔰 Python for Everything
🔰 Python for Everything

This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visua
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

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