Skip to main content

dir, __dict__ and help method in Python

 


Learning Sections          show

dir, __dict__, and help Method in Python

Python provides several built-in functions and attributes that are useful for introspection and understanding objects and their attributes. Three such tools are dir(), __dict__, and help().

1. dir()

The dir() function returns a list of the attributes and methods of an object. It can be used on any object to see its properties.


# Using dir() on a list
example_list = [1, 2, 3]
print(dir(example_list))
    

Output: ['__add__', '__class__', '__contains__', ... , 'append', 'clear', 'copy', ...]


2. __dict__

The __dict__ attribute is a dictionary representation of an object's attributes. It shows the object's attributes and their values.


# Define a simple class
class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

# Create an instance of the class
person = Person('John', 30)
print(person.__dict__)
    

Output: {'name': 'John', 'age': 30}


3. help()

The help() function is used to display the documentation of modules, functions, classes, and methods. It provides a quick way to get information about Python objects.


# Using help() on a list
help(example_list)
    

Output: (Displays the documentation and available methods of the list object)

Popular posts from this blog

Generators in Python

  Learning Sections          show Generators in Python Generators are a special type of iterator in Python that allow you to iterate over a sequence of items without storing them all in memory at once. They are useful for generating large sequences of data on-the-fly, or for processing data in a memory-efficient manner. Creating Generators In Python, generators are created using generator functions or generator expressions: # Generator function def my_generator ( n ): for i in range ( n ): yield i # Generator expression my_generator = ( i for i in range ( 10 )) A generator function uses the yield keyword to yield values one at a time, while a generator expression creates an anonymous generator. Iterating Over Generators You can iterate over the values produced by a generator using a for loop: for value in my_generator ( 5 ): print ( value ) This w...

Walrus Operator in Python

  Learning Sections          show Walrus Operator in Python The walrus operator ( := ) is a new assignment operator introduced in Python 3.8. It allows you to assign values to variables as part of an expression, making certain constructs more concise. Basic Usage The basic syntax for the walrus operator is: variable_name := expression Here, variable_name is assigned the value of expression , and the result of the expression is also returned. Example: Simplifying Code Consider the following example where we find and print the length of a list if it's greater than 3: # Without walrus operator my_list = [ 1 , 2 , 3 , 4 ] if len ( my_list ) > 3 : length = len ( my_list ) print ( length ) # With walrus operator my_list = [ 1 , 2 , 3 , 4 ] if ( length := len ( my_list )) > 3 : print ( length ) In the second example, the walrus operator assigns the result of len(my...

Lambda Functions in Python

  Learning Sections          show Lambda Functions in Python Lambda functions, also known as anonymous functions, are small, unnamed functions defined with the lambda keyword. They can have any number of arguments but only one expression. Lambda functions are often used for short, throwaway functions that are not needed elsewhere in the code. 1. Basic Syntax The syntax for a lambda function is: lambda arguments : expression Example: add = lambda x , y : x + y print ( add ( 2 , 3 )) # Output: 5 2. Using Lambda with Built-in Functions Lambda functions are commonly used with built-in functions like map() , filter() , and sorted() . Example with map() : numbers = [ 1 , 2 , 3 , 4 , 5 ] squared = map ( lambda x : x ** 2 , numbers ) print ( list ( squared )) # Output: [1, 4, 9, 16, 25] Example with filter() : numbers = [ 1 , 2 , 3 , 4 , 5 ] even = filter ( lambd...