Learning-Python VS Python

Hi guys, we have just completed the basic module of the Learning Python Course.

Answers as usual in the learning python repository

import time import requests import asyncio import aiohttp urls = [ 'https://example.com', 'https://httpbin.org/get', 'https://python.org' ] # Synchronous version def sync_fetch(): for url in urls: response = requests.get(url) print(f"{url} fetched with {len(response.text)} characters") # Async version async def async_fetch(): async with aiohttp.ClientSession() as session: tasks = [session.get(url) for url in urls] responses = await asyncio.gather(*tasks) for i, resp in enumerate(responses): text = await resp.text() print(f"{urls[i]} fetched with {len(text)} characters") if __name__ == "__main__": print("Running synchronous fetch") start = time.perf_counter() sync_fetch() duration_sync = time.perf_counter() - start print(f"Synchronous fetching took {duration_sync:.2f} seconds\n") print("Running asynchronous fetch") start = time.perf_counter() asyncio.run(async_fetch()) duration_async = time.perf_counter() - start print(f"Asynchronous fetching took {duration_async:.2f} seconds")

import threading import requests import time def fetch_url(url): response = requests.get(url) return len(response.content) urls = [ "https://python.org", "https://github.com", "https://stackoverflow.com", "https://pypi.org", "https://docs.python.org", ] # Single-threaded start = time.time() for url in urls: fetch_url(url) single_time = time.time() - start print(f"Single-threaded: {single_time:.2f}s") # Multi-threaded start = time.time() threads = [] for url in urls: t = threading.Thread(target=fetch_url, args=(url,)) t.start() threads.append(t) for t in threads: t.join() multi_time = time.time() - start print(f"Multi-threaded: {multi_time:.2f}s") print(f"Speedup: {single_time / multi_time:.1f}x")

import asyncio import aiohttp async def fetch_url(session, url): async with session.get(url) as response: return await response.text() async def main(): urls = [ 'https://example.com', 'https://httpbin.org/get', 'https://python.org' ] async with aiohttp.ClientSession() as session: tasks = [fetch_url(session, url) for url in urls] pages = await asyncio.gather(*tasks) # Fetch all pages concurrently for i, html in enumerate(pages): print(f"Page {i+1} length: {len(html)}") asyncio.run(main())

Next, ensure you have Python 3 installed locally on your PC. Once that's done, proceed to install the following libraries:

It is the year 2025, everybody and their grandma have asked ChatGPT about the meaning of life. While we cannot be sure whether it generated a hallucinated answer, we do know that LLMs are developed using Python. Data scientists today are expected to work with AI/ML models and therefore Python (see below), effectively settling the age-old "Python vs. R" debate.

If you need to install Python, download it from the official Python website or consider using Anaconda or Miniconda, which include essential tools for data science and AI development.

Visit python.org

Go to the official Python website: https://python.org

Tool Why you need it Install Python ≥ 3.10 The lingua franca of ML brew install python or https://python.org pandas Data wrangling swiss‑army knife pip install pandas scikit‑learn Classic ML algorithms & utilities pip install scikit-learn Jupyter / VS Code Notebooks Interactive coding & charts pip install notebook or VS Code Python ext matplotlib Lightweight plotting pip install matplotlib