When applying multiple filters to a series in Pandas, it's better to break the condition into several lines:
Such code is easier to read, write, and maintain. π οΈβ¨
As a result, the value:
25
will be selected,
since it is both greater than 20 and an odd number. π―
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s = pd.Series([10, 15, 20, 25, 30])
s.loc[
(s > 20) &
(s % 2 == 1)
]
Such code is easier to read, write, and maintain. π οΈβ¨
As a result, the value:
25
will be selected,
since it is both greater than 20 and an odd number. π―
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# How to Implement a Decorator with Parameters Using a Class in Python
You can create a parameterized decorator in Python by using a class that implements the
## Example Implementation
## Explanation
1. Class Definition: Define a class that will serve as the decoratorinit.
2. **
3. **
You can create a parameterized decorator in Python by using a class that implements the
__call__ method. The class acts as the decorator factory, where the __init__ method stores the parameters, call__call__ method applies the decorator logic to the target function.## Example Implementation
class my_decorator:
def __init__(self, param):
self.param = param
def __call__(self, func):
def wrapper(*args, **kwargs):
print(f"Decorator parameter: {self.param}")
return func(*args, **kwargs)
return wrapper
@my_decorator("Hello")
def say_hello(name):
print(f"Hello, {name}!")
say_hello("World")
## Explanation
1. Class Definition: Define a class that will serve as the decoratorinit.
2. **
__init__**: Store the parameters passed to the decoracall.3. **
__call__**: Make the instance callable. This method receives the function being decorated and returns the wrappWrapperrapper**: The inner function executes the actual decorator logic before or after calling the original function.β€4
Cheat sheet on Python Data Types π
Python Data Types β the main data types in Python.
π’ Numbers β numerical types (int, float, complex)
βοΈ Bool β logical values (True, False)
π String β text strings
π List β mutable ordered collections
π Tuple β immutable ordered collections
π² Set β unique unordered elements
ποΈ Dict β collections of "key-value" pairs.
Helps to quickly orient yourself in data types and choose the appropriate structure for storing information π‘
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Python Data Types β the main data types in Python.
π’ Numbers β numerical types (int, float, complex)
βοΈ Bool β logical values (True, False)
π String β text strings
π List β mutable ordered collections
π Tuple β immutable ordered collections
π² Set β unique unordered elements
ποΈ Dict β collections of "key-value" pairs.
Helps to quickly orient yourself in data types and choose the appropriate structure for storing information π‘
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Python is like New Year. π You can pass a tuple to
#Python #Programming #TechTips #Coding #DevCommunity #LearnToCode
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startswith and endswith. π»π#Python #Programming #TechTips #Coding #DevCommunity #LearnToCode
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Variables in Python are stickers, not boxes.
A variable doesn't store a value, but points to it. If you change a list, both variables will see the change. This makes sense with stickers. But with boxes, it's magic: two boxes mysteriously change simultaneously.
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#Python #Programming #Variables #Coding #Tech #DataScience
A variable doesn't store a value, but points to it. If you change a list, both variables will see the change. This makes sense with stickers. But with boxes, it's magic: two boxes mysteriously change simultaneously.
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GitHub
GitHub - nightblure/Python-backend-knowledge-base: Knowledge base for python backend developers
Knowledge base for python backend developers. Contribute to nightblure/Python-backend-knowledge-base development by creating an account on GitHub.
βοΈ Python Backend Knowledge Base β a large knowledge base for developers!
This repository has gathered in one place everything a Python backend developer encounters: from basic concepts to more complex topics related to architecture, databases, APIs, and the structure of server applications. The material is well-structured, so it's convenient to use not only for learning new topics but also as a reference during work.
I'll leave a link: https://github.com/nightblure/Python-backend-knowledge-baseπ±
This repository has gathered in one place everything a Python backend developer encounters: from basic concepts to more complex topics related to architecture, databases, APIs, and the structure of server applications. The material is well-structured, so it's convenient to use not only for learning new topics but also as a reference during work.
I'll leave a link: https://github.com/nightblure/Python-backend-knowledge-base
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What useful functions are there in the functools module?
Among the most popular ones: lru_cache for caching results, partial for partial application of arguments, wraps for preserving metadata in decorators and cmp_to_key for transforming a comparison function into a sorting key πβ¨
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Among the most popular ones: lru_cache for caching results, partial for partial application of arguments, wraps for preserving metadata in decorators and cmp_to_key for transforming a comparison function into a sorting key πβ¨
# functools module usage
from functools import lru_cache, partial, wraps, cmp_to_key
#Python #functools #coding #programming #softwaredev #tech
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