20 Python Tips Everyone must Know | Python Theme month

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1. Arrange using itertools

In this program, we import a built-in module called Itertools. Using Itertools, you can find all permutations of a given string. There are many methods in Itertools, and you can try combinations and other methods.

import itertools
name= 'Python'
for i in itertools.permutations(name):
    print(i)                                                                        
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2. Single-line conditional expressions

This conditional expression was added to Python version 2.5. This can be used with the A if condition else B syntax. First, the condition is evaluated and returned based on its Boolean value. If true, return A; otherwise, if false, return B.

x=10
y=100
res = x if x>y else y
print(f"The greater number is {res}")    
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3. Reverse the string

In this program, we use the extension slice to reverse the string, which uses the [begin:end:step] syntax. So when we skip the start, end, and step, we pass (-1) as the value. This reverses the given string.

string = "medium"
reverse_string = string[::-1]
print(f"The reversed string is {reverse_string}")  
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4. Use Assert to handle exceptions

Exception handling is a very important concept in programming. Prints the error statement using the assert keyword and the given condition. If the given condition is not true, it prints an error message and terminates the program.

x = int(input("enter a number to divide ")) 
assert x<=-1 and x>0.'Number should be greater than 0' 
ans = 100/x 
print(f'The output is {ans}')
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5. Split multiple inputs

Split () is one of the string methods that splits a string into a list. The default delimiter used in this method is space. In this program, instead of creating three repeating lines for the input operation, you replace them with one.

a,b,c = input("Enter the value for a, b, c :").split()
print(a)
print(b)
print(c)    
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6. Use zip() transpose

The Zip function takes any number of iterable objects from different columns and aggregates the corresponding tuples. The asterisk (*) operator is used to decompress the list. The list is later changed to the transpose of the given list.

matrix=[[1.2], [3.4], [5.6]]
trans=zip( *matrix)
print(list(trans))   
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7. Resource context Manager

Resource management is one of the most important tasks in programming. Accessing and releasing files, locks, and other resources is a busy business. If resources are not shut down correctly, several problems can result, including memory leaks. To solve this problem, instead of using the open and close methods every time, use the context manager shown in the code snippet.

with open("demo.txt", mode="w") as file:
    file.write('Hola! ')  
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8. The underscore is used as the separator

When using large numbers in a program, using underscores instead of commas as separators can improve readability. Python syntax does not recognize underscores. It is represented by an underscore, represents numbers in the preferred format, and is readable.

x = 10 _000_000_000
print(f" It is Ten Billion: {x}")                                                       
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9. Try the f string format

The F string format was introduced in Python 3.6. It is the easiest way to format a string. Using the F-string format instead of the traditional format makes the code easier to understand.

Name = input("Enter your name ")
print(f'Hello{Name}! This is a Python Example')    
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10. Swap integers with this trick

Note that swapping integers is done without the use of temporary variables. Python evaluates expressions from left to right, but in assignment, the right side is evaluated first. This creates tuples for the right-hand variables (b and a), whose values are assigned from the left-hand variables. This process facilitates the exchange of variables.

a,b = input("Enter the value for a, b :").split()
a,b = b,a
print(a,b) 
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11. Use lambda instead of functions

Lambda is one of the most powerful functions, also known as anonymous functions. It does not require a name or function definition or return statement. Ordinary functions use the def keyword, while lambda functions use the lambda keyword. It works like a function, except it only applies to one expression.

x = lambda a, b : a + b
print(x(1.2))  
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12. No loop for multiple prints

In this program, we try to print statements in a single line instead of using loops multiple times. The asterisk (*) enables you to print the statement a specified number of times.

print("This is a Python example to print this 100 times\n" *100) 
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13. Unpack strings into variables

A sequence or a string can be unwrapped into different variables. In this program, the Python string letters are unpacked into variables. The output of the program will be P, y, t.

name='Python'
a,b,c,d,e,f =name
print(a)
print(b)
print(c)                                                                          
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14. Use Map to understand lists

In this program, we try to add elements to the list. To do this, we use lambda functions in combination with map and List Comprehension. The output of this program will be [12, 15, 18].

num1=[1.2.3]
num2= [4.5.6]
num3=[7.8.9]
result= map(lambda x,y,z:x+y+z,num1,num2,num3)
print(list(result))  
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15. Delete duplicates from the list

In this program, we try to remove duplicates from the list. One thing to remember is that collections are not allowed to repeat. We pass the list to set() and change it to a list again, removing all duplicate elements from the list.

old_list = [1.2.2.3.3.4.5.5.6]
new_list = list(set(old_list))
print(new_list)     
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16. Print conditions in statements

This program is interesting and contains quite a few operations. First, the input method is executed, and then the input value is changed to an integer. It then checks the condition and returns a Boolean value. If it returns a non-zero number, an odd number will be the output, or if it returns zero, then an even number will be the output.

print("odd" if int(input("enter the value")) %2 else "even")  
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17. Conditional list All and Any

In this program, we examine the list of conditions one at a time. There are two functions: all() and any(). As the name implies, when we use all(), all conditions must be true. And when any() is used, the block is executed even if one of the conditions is true.

Marks = 350
Percentage = 60
Passed = 5
Conditions = [Marks>200, Percentage>50,Passed>4]
if(all(Conditions)):
    print("Hired for a company A")
elif(any(Conditions)):
    print("Hired for a company B")
else:
    print("Rejected")   
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18. Merge the two dictionaries

This one is now deprecated

In this program, we try to merge two dictionaries. Please note that in this program, you can use “|” to merge operator.

Household = {'Groceries':'100'.'Electricity':'150'}
Travel = {'Food':'50'.'Accomodation':'122'.'Transport':'70'}
Expense = Household | Travel
print(Expense)  
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19. Check the execution time

Check the execution time of the program by importing the timeit package. In this program, the execution time to form a list of 1 to 1000.

import timeit
execution_time = timeit.timeit('list (range (0) 1100)')
print(execution_time)    
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20. Check the library

In this program, we try to check the library of the function. All itertools properties and modules are printed using this program.

import itertools
print(dir(itertools))  
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