What is Meta in Django and why is it needed?
Answer:
Django uses metaclasses to retrieve information from Meta when creating a model and configure its operation in the ORM and admin interface. There's no need to override the mechanism — it's enough to define the class Meta within the class.
tags: #interview
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Forwarded from Machine Learning with Python
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We're sharing a cool resource for learning about neural networks, offering clear, step-by-step instruction with dynamic visualizations and easy-to-understand explanations.
In addition, you'll find many other useful materials on machine learning on the site.
Find and use it — https://mlu-explain.github.io/neural-networks/
tags: #AI #ML #PYTHON
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Master Python in 2025: Build 101 Projects, Learn Socket Programming , Automation, Data Analysis, OpenCV and OOP....
🏷 Category: development
🌍 Language: English (US)
👥 Students: 6,622 students
⭐️ Rating: 4.3/5.0 (143 reviews)
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Python for Beginners & Beyond: Learn to Code with Real-World Projects...
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Why is
list.sort() faster than sorted(list), if the same list is being sorted?Answer:
The sorted(list) function creates a new sorted list, which requires additional memory allocation and copying of elements before sorting, which can increase time and memory overhead.
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Python tip:
A shallow copy (copy.copy()) copies the object itself, but not its nested elements.
A deep copy (copy.deepcopy()) copies both the object and all its nested structures.
Therefore, with a shallow copy, changes in the nested elements are reflected in the original, while with a deep copy, they are not.
https://news.1rj.ru/str/DataScienceQ
A shallow copy (copy.copy()) copies the object itself, but not its nested elements.
A deep copy (copy.deepcopy()) copies both the object and all its nested structures.
Therefore, with a shallow copy, changes in the nested elements are reflected in the original, while with a deep copy, they are not.
https://news.1rj.ru/str/DataScienceQ
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The methods getitem() and setitem() allow to implement access to object elements by index or key, just like in lists or dictionaries.
__getitem__() is called when accessing obsetitem __setitem__() — when assigning obj[key] = value. It allows to emulate the behavior of built-in collections.
✈️ https://news.1rj.ru/str/DataScienceQ
class CustomContainer:
def __getitem__(self, key):
return self.data[key] # Returns the value by key/index
def __setitem__(self, key, value):
self.data[key] = value # Sets the value by key/index
__getitem__() is called when accessing obsetitem __setitem__() — when assigning obj[key] = value. It allows to emulate the behavior of built-in collections.
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🔗 Python Tuple Basics: A Quick Guide 👍
Do you know what a Python tuple is? 🤔 In this article, we'll explore the basics of tuples in Python. Let's dive right in!
What are Python Tuples?
------------------------
Tuples are immutable collections of values that can be thought of as lists, but with more structure and safety. They're created using square brackets
Creating a Tuple
----------------
You can create a tuple by enclosing elements in parentheses
This creates a tuple with three values: 1, 2, and 3. You can also use the
Accessing Tuple Elements
---------------------------
Tuples have two ways to access elements: indexing and slicing.
* Indexing is used with square brackets
* Slicing is used with square brackets
Common Features and Gotchas
------------------------------
Tuples have some useful features, such as:
* Immutable: Tuples cannot be modified once created.
* Ordered: Tuples maintain the order of elements.
However, they also come with a few gotchas, such as:
* Performance overhead: Creating or accessing tuples can incur performance penalties.
When working with tuples in Python, keep these best practices in mind:
* Use tuples for immutable data where possible.
* Avoid using tuple unpacking to assign values from one variable to another.
* Be mindful of performance when creating or accessing large number of tuples.
By following this quick guide to Python tuples, you'll be well on your way to understanding the basics of tuples and how they can enhance your Python programming experience. 📚
Check it out for more resources: [https://realpython.com/python-tuple/](https://realpython.com/python-tuple/)
Do you know what a Python tuple is? 🤔 In this article, we'll explore the basics of tuples in Python. Let's dive right in!
What are Python Tuples?
------------------------
Tuples are immutable collections of values that can be thought of as lists, but with more structure and safety. They're created using square brackets
[] and elements are separated by commas.Creating a Tuple
----------------
You can create a tuple by enclosing elements in parentheses
(). For example:my_tuple = (1, 2, 3)
This creates a tuple with three values: 1, 2, and 3. You can also use the
tuple() function to convert a list into a tuple:values = [1, 2, 3]
my_tuple = tuple(values)
print(my_tuple) # (1, 2, 3)
Accessing Tuple Elements
---------------------------
Tuples have two ways to access elements: indexing and slicing.
* Indexing is used with square brackets
[] to access individual elements. For example:my_tuple = (1, 2, 3)
print(my_tuple[0]) # prints 1
* Slicing is used with square brackets
[] to extract a subset of elements. For example:my_tuple = (1, 2, 3)
print(my_tuple[1:3]) # prints (2, 3)
Common Features and Gotchas
------------------------------
Tuples have some useful features, such as:
* Immutable: Tuples cannot be modified once created.
* Ordered: Tuples maintain the order of elements.
However, they also come with a few gotchas, such as:
* Performance overhead: Creating or accessing tuples can incur performance penalties.
When working with tuples in Python, keep these best practices in mind:
* Use tuples for immutable data where possible.
* Avoid using tuple unpacking to assign values from one variable to another.
* Be mindful of performance when creating or accessing large number of tuples.
By following this quick guide to Python tuples, you'll be well on your way to understanding the basics of tuples and how they can enhance your Python programming experience. 📚
Check it out for more resources: [https://realpython.com/python-tuple/](https://realpython.com/python-tuple/)
Realpython
Python's tuple Data Type: A Deep Dive With Examples – Real Python
In Python, a tuple is a built-in data type that allows you to create immutable sequences of values. The values or items in a tuple can be of any type. This makes tuples pretty useful in those situations where you need to store heterogeneous data, like that…
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FastAPI: Speed, Developer Experience, and More 🚀
🏆 Starting with FastAPI: A Popular Python Web Framework
---------------------------------------------------------
FastAPI is an open-source web framework for building APIs with Python. It provides automatic validation, serialization, and interactive documentation through standard Python type hints.
Choosing the Right Framework for Your Project:
-----------------------------------------------
| Use Case | Pick FastAPI | Pick Flask or Django |
| --- | --- | --- |
| Building a Web App | ✅ | — |
| Full-Stack Web Framework | — | — |
Key Features:
* Speed: FastAPI is built on top of Python 3.7+, with a focus on performance and scalability.
* Developer Experience: Easy-to-use API documentation, auto-generated documentation, and support for asynchronous programming.
* Built-in Features: Automatic JSON serialization and deserialization, support for WebSockets and gRPC.
Start Building Your API Today! 💻
Learn more about FastAPI and how to get started with building your own APIs. Check out this free online course: https://futurecoder.io/ 🚀
🏆 Starting with FastAPI: A Popular Python Web Framework
---------------------------------------------------------
FastAPI is an open-source web framework for building APIs with Python. It provides automatic validation, serialization, and interactive documentation through standard Python type hints.
Choosing the Right Framework for Your Project:
-----------------------------------------------
| Use Case | Pick FastAPI | Pick Flask or Django |
| --- | --- | --- |
| Building a Web App | ✅ | — |
| Full-Stack Web Framework | — | — |
Key Features:
* Speed: FastAPI is built on top of Python 3.7+, with a focus on performance and scalability.
* Developer Experience: Easy-to-use API documentation, auto-generated documentation, and support for asynchronous programming.
* Built-in Features: Automatic JSON serialization and deserialization, support for WebSockets and gRPC.
Start Building Your API Today! 💻
Learn more about FastAPI and how to get started with building your own APIs. Check out this free online course: https://futurecoder.io/ 🚀
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Stop using
In Python, when you write:
you're not directly checking if
Yes, in many cases, the result will be the same as for the code:
But the behavior of these two variants is different, and this difference is important.
When you use:
Python calls the
If
Example:
Here, it can be seen that
Therefore, when using
On the other hand, when you write:
you're using the
The
❤️ Therefore, it is always recommended, and this is best practice, to use
👉 https://news.1rj.ru/str/DataScienceQ
if obj == None, use if obj is NoneIn Python, when you write:
obj == None
you're not directly checking if
obj is the value None. Instead, you're asking if the object is equal to None.Yes, in many cases, the result will be the same as for the code:
obj is None
But the behavior of these two variants is different, and this difference is important.
When you use:
obj == None
Python calls the
__eq__ method on the object. That is, the object itself decides what it means to be "equal to None". And this method can be overridden.If
obj is an instance of a class in which __eq__ is implemented so that when compared with None, it returns True (even if the object is not actually None), then obj == None may mistakenly give True.Example:
class Weird:
def __eq__(self, other):
return True # Always asserts that it's equal
obj = Weird()
print(obj == None) # True
print(obj is None) # False
Here, it can be seen that
obj == None returns True due to the custom behaeqf the __eq__ operator in the class.Therefore, when using
obj == None, the result is not always predictable.On the other hand, when you write:
obj is None
you're using the
is operator, which cannot be overridden. This means that the result will always be the same and predictable.The
is operator checks the identity of objects, that is, whether two references point to the same object. Since None is a singleton (the only instance), obj is None is the correct and most efficient way to perform such a check.obj is None instead of obj == None for predictability and efficiency.Please open Telegram to view this post
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