What will be the output of the following code?
import numpy as np
numbers = np.array([1, 2, 3])
new_numbers = numbers + 1
print(new_numbers.tolist())
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  Python Question / Quiz;
What is the output of the following Python code, and why? 🤔🚀 Comment your answers below! 👇
What is the output of the following Python code, and why? 🤔🚀 Comment your answers below! 👇
#python #programming #developer #programmer #coding #coder #softwaredeveloper #computerscience #webdev #webdeveloper #webdevelopment #pythonprogramming #pythonquiz #ai #ml #machinelearning #datascience
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  Python Question / Quiz;
What is the output of the following Python code, and why? 🤔🚀 Comment your answers below! 👇
What is the output of the following Python code, and why? 🤔🚀 Comment your answers below! 👇
#python #programming #developer #programmer #coding #coder #softwaredeveloper #computerscience #webdev #webdeveloper #webdevelopment #pythonprogramming
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👍2
  🧠 What is a Generator in Python?  
A generator is a special type of iterator that produces values lazily—one at a time, and only when needed—without storing them all in memory.
---
❓ How do you create a generator?
✅ Correct answer:
Option 1: Use the
🔥 Simple example:
When you call this function:
Each time you call
---
⛔ Why are the other options incorrect?
- Option 2 (class with
It works, but it’s more complex. Using
- Options 3 & 4 (
Loops are not generators themselves. They just iterate over iterables.
---
💡 Pro Tip:
Generators are perfect when working with large or infinite datasets. They’re memory-efficient, fast, and clean to write.
---
📌 #Python #Generator #yield #AdvancedPython #PythonTips #Coding
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A generator is a special type of iterator that produces values lazily—one at a time, and only when needed—without storing them all in memory.
---
❓ How do you create a generator?
✅ Correct answer:
Option 1: Use the
yield keyword inside a function.🔥 Simple example:
def countdown(n):
while n > 0:
yield n
n -= 1
When you call this function:
gen = countdown(3)
print(next(gen)) # 3
print(next(gen)) # 2
print(next(gen)) # 1
Each time you call
next(), the function resumes from where it left off, runs until it hits yield, returns a value, and pauses again.---
⛔ Why are the other options incorrect?
- Option 2 (class with
__iter__ and __next__):  It works, but it’s more complex. Using
yield is simpler and more Pythonic.- Options 3 & 4 (
for or while loops):  Loops are not generators themselves. They just iterate over iterables.
---
💡 Pro Tip:
Generators are perfect when working with large or infinite datasets. They’re memory-efficient, fast, and clean to write.
---
📌 #Python #Generator #yield #AdvancedPython #PythonTips #Coding
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  Question 1 (Intermediate):  
In Python, which of these is the correct way to create a virtual environment?
A)
B)
C)
D)
#Python #Development #VirtualEnv #Coding
In Python, which of these is the correct way to create a virtual environment?
A)
python create venv  B)
python -m venv myenv  C)
pip install virtualenv  D)
conda make env  #Python #Development #VirtualEnv #Coding
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  Forwarded from Data Science Jupyter Notebooks
  
🔥 Trending Repository: tech-interview-handbook
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==================================
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📝 Description: 💯 Curated coding interview preparation materials for busy software engineers
🔗 Repository URL: https://github.com/yangshun/tech-interview-handbook
🌐 Website: https://www.techinterviewhandbook.org
📖 Readme: https://github.com/yangshun/tech-interview-handbook#readme
📊 Statistics:
🌟 Stars: 130K stars
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🍴 Forks: 15.8K forks
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🏷️ Related Topics:
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