Table of Contents
2, Pro Slicing
3. Swap without Temp
4. Magic of F-string
5. Get the index
6. Sorted list based on Another List
7. Reversing Dictionaries
8. Multi-threading
9. The element that appears the most in the list
10. Split line
11. Mapping List to Dictionary
12. Parsing the spreadsheet
Home Backend Development Python Tutorial 12 essential code snippets you must know about Python programming

12 essential code snippets you must know about Python programming

Apr 26, 2023 pm 03:52 PM
python code

12 个用于日常编程的杀手级 Python 代码片段

1. Regular expressions

Regular expressions are the best technology in Python for matching patterns, searching and replacing strings, validating strings, etc. Now you don't need to use loops and lists for this kind of work.

Check out the following regular expression snippet code example for validating email format:

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# Regular Expression Check Mail

import re

def Check_Mail(email):

 pattern = re.compile(r'([A-Za-z0-9]+[.-_])*[A-Za-z0-9]+@[A-Za-z0-9-]+(.[A-Z|a-z]{2,})+')

 if re.fullmatch(pattern, email):

 print("valid")

 else:

 print("Invalid")

Check_Mail("codedev101@gmail.com") #valid

Check_Mail("codedev101-haider@uni.edu")#Invalid

Check_Mail("code-101-work@my.net") # Invalid

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2, Pro Slicing

This simple code snippet will Helps you slice your lists like a pro. Check out the sample code below:

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# Pro Slicing

# list[start:end:step]

mylist = [1, 2, 3, 5, 5, 6, 7, 8, 9, 12]

mail ="codedev-medium@example.com"

print(mylist[4:-3]) # 5 6 7

print(mail[8 : 14]) # medium

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3. Swap without Temp

Are you using the Temp variable to swap two data, as in Python you don't need to use it? In this code snippet, I will share with you how to swap two data variables without using temp.

View the code below:

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# Swap without Temp

i = 134

j = 431

[i, j] = [j, i]

print(i) #431

print(j) #134

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4. Magic of F-string

We may use the format() method or the "%" method to Variables in the format string. This code will introduce you to F-strings, which are much better than the other format.

Look at the sample code below:

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# Magic of f-String

# Normal Method

name = "Codedev"

lang = "Python"

data = "{} is writing article on {}".format(name, lang)

print(data)

# Pro Method with f-string

data = f"{name} is writing article on {lang}"

print(data

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5. Get the index

Now you no longer need a Loop to find the index of a specific element. You can do this using the index() method on the list.

Look at the code below:

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# Get Index

x = [10 ,20, 30, 40, 50]

print(x.index(10)) # 0

print(x.index(30)) # 4

print(x.index(50)) # 2

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6. Sorted list based on Another List

This code snippet will show you how to sort the list based on another list Sort the list. This snippet comes very handy when you need to sort based on the desired position.

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# Sort List based on another List

list1 =["a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m"]

list2 = [ 0, 1, 1, 1, 2, 2, 0, 1, 1, 3, 4]

C = [x for _, x in sorted(zip(list2, list1), key=lambda pair: pair[0])]

print(C) # ['a', 'g', 'b', 'c', 'd', 'h', 'i', 'e', 'f', 'j', 'k']

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7. Reversing Dictionaries

Now you don’t need to loop to reverse any dictionary. This snippet code will reverse the dictionary the second time the snippet code is tried.

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# Invert the Dictionary

def Invert_Dictionary(data):

 return{value: key for key, value in data.items()}

data = {"A": 1, "B":2, "C": 3}

invert = Invert_Dictionary(data)

print(invert) # {1: 'A', 2: 'B', 3: 'C'}

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8. Multi-threading

Multi-threading will help you run Python functions in parallel at the same time. Suppose you want to execute 5 functions simultaneously without waiting for each function to complete.

View the following code snippet:

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# Multi-threading

import threading

def func(num):

 for x in range(num):

 print(x)

if __name__ == "__main__":

 t1 = threading.Thread(target=func, args=(10,))

 t2 = threading.Thread(target=func, args=(20,))

 t1.start()

 t2.start()

 t1.join()

 t2.join()

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9. The element that appears the most in the list

This code snippet will simply count the number of occurrences in the list most elements. I've shown two ways to do this.

Check it out below:

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# Element Occur most in List

from collections import Counter

mylst = ["a", "a", "b", "c", "a", "b","b", "c", "d", "a"]

# Method 1

def occur_most1(mylst):

 return max(set(mylst), key=mylst.count)

print(occur_most1(mylst)) # a

# Method 2

# Much Faster then Method 1

def occur_most2(mylst):

 data = Counter(mylst)

 return data.most_common(1)[0][0]

print(occur_most2(mylst)) # a

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10. Split line

Have a raw text in progressive format and want to split it into several lines . This code snippet will solve your problem in just a second.

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# Split lines

data1 = """Hello to

Python"""

data2 = """Programming

Langauges"""

print(data1.split("n")) # ['Hello to', 'Python']

print(data2.split("n")) # ['Programming', ' Langauges']

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11. Mapping List to Dictionary

This code snippet will help you convert any two lists into dictionary format. To understand how it works, take a look at the code below:

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# Map List into Dictionary

def Convert_to_Dict(k, v):

 return dict(zip(k, v))

k = ["a", "b", "c", "d", "e"]

v = [1, 2, 3, 4, 5]

print(Convert_to_Dict(k, v)) # {'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5}

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12. Parsing the spreadsheet

Now you don’t need Pandas or any other external Python package to parse the spreadsheet . Python has a built-in CSV module and this code will show you how to use it.

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# Parse Spreadsheet

import csv

#Reading

with open("test.csv", "r") as file:

 csv_reader = csv.reader(file)

 for row in csv_reader:

 print(row)

file.close()

#Writing

header = ["ID", "Languages"]

csv_data = [234, "Python", 344, "JavaScript", 567, "Dart"]

with open("test2.csv", 'w', newline="") as file:

 csv_writer = csv.writer(file)

 csv_writer.writerow(header)

 csv_writer.writerows(csv_data)

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