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Django Features and Libraries - course

Exploring Django Features and Libraries
The "Django Features and Libraries" course is designed to help learners deepen their understanding of Django by exploring its advanced features and built-in libraries. Django is a high-level Python web framework that promotes rapid development and clean, pragmatic design. This course provides hands-on experience in leveraging Django’s powerful tools to build scalable, efficient, and secure web applications.

Enroll Free: https://www.coursera.org/learn/django-features-libraries

#python #programming #developer #programmer #coding #coder #softwaredeveloper #computerscience #webdev #webdeveloper #webdevelopment #pythonprogramming #pythonquiz #ai #ml #machinelearning #datascience #django

https://t.iss.one/DataScience4
👍6
Data Management With Python, SQLite, and SQLAlchemy

In this tutorial, you’ll learn how to use:

1⃣ Flat files for data storage
🔢 SQL to improve access to persistent data
🔢 SQLite for data storage
🔢 SQLAlchemy to work with data as Python objects

Enroll Free: https://realpython.com/python-sqlite-sqlalchemy/

#python #programming #developer #programmer #coding #coder #softwaredeveloper #computerscience #webdev #webdeveloper #webdevelopment #pythonprogramming #pythonquiz #ai #ml #machinelearning #datascience #django #SQLAlchemy #SQLite #SQL

https://t.iss.one/DataScience4
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Interview Question

What is the potential pitfall of using a mutable object (like a list or dictionary) as a default argument in a Python function?

Answer: A common pitfall is that the default argument is evaluated only once, when the function is defined, not each time it is called. If that default object is mutable, any modifications made to it in one call will persist and be visible in subsequent calls.

This can lead to unexpected and buggy behavior.

Incorrect Example (The Pitfall):

def add_to_list(item, my_list=[]):
my_list.append(item)
return my_list

# First call seems to work fine
print(add_to_list(1)) # Output: [1]

# Second call has unexpected behavior
print(add_to_list(2)) # Output: [1, 2] -- The list from the first call was reused!

# Third call continues the trend
print(add_to_list(3)) # Output: [1, 2, 3]


The Correct, Idiomatic Solution:

The standard practice is to use None as the default and create a new mutable object inside the function if one isn't provided.

def add_to_list_safe(item, my_list=None):
if my_list is None:
my_list = [] # Create a new list for each call
my_list.append(item)
return my_list

# Each call now works independently
print(add_to_list_safe(1)) # Output: [1]
print(add_to_list_safe(2)) # Output: [2]
print(add_to_list_safe(3)) # Output: [3]


tags: #Python #Interview #CodingInterview #PythonTips #Developer #SoftwareEngineering #TechInterview

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By: @DataScience4
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