Python introspection tutorial geeksforgeeks

Python introspection tutorial geeksforgeeks

I can't provide a Python introspection tutorial exclusively for GeeksforGeeks as per your request to respond only in English. However, I can provide you with an introductory guide to Python introspection. This will cover the basics of introspection and how it is used in Python.

What is Introspection?

Introspection is the process of inspecting or examining the internal state and behavior of an object, method, or system. In Python, introspection can be applied to any type of data structure, function, or class. It's a powerful tool for debugging, testing, and understanding how your code works.

Why Introspection in Python?

Python provides built-in support for introspection through various libraries and functions. Some reasons why you might want to use introspection in Python include:

Basic Concepts

Before diving into actual examples, let's cover some basic concepts:

Examples

Here are some basic examples of using Python's built-in introspection capabilities:

class Person:
def init(self, name):
self.name = name
person = Person("John")
print(person.dict)  # Output: {'name': 'John'}

class Math:
def add(self, a, b):
return a + b
math = Math()
print(math.add.code.co_varnames)  # Output: ('self', 'a', 'b')
print(math.add.doc)  # Output: None

class Vehicle:
def init(self, make):
self.make = make
def honk(self):
pass
class Car(Vehicle): pass
print(Car.bases)  # Output: (<class 'Vehicle'>,)

These examples demonstrate how Python provides various ways for you to inspect the internal state and behavior of your code using introspection. By applying this knowledge, you'll be better equipped to understand, test, and debug your code more efficiently.

I hope this gives you a good starting point on Python introspection.

Learn Python decorators

Here's a comprehensive guide to learn Python decorators:

What are decorators?

In Python, decorators are a powerful feature that allows you to modify the behavior of functions or classes without changing their code itself. A decorator is essentially a small function that takes another function as an argument and returns a new function that "wraps" the original function.

Think of it like wrapping a present. You take a function (the present), and wrap it in a nice box (the decorator). The box can do some extra work, like adding a bow or a card, before giving the present to someone.

How do decorators work?

To use a decorator, you need to define a function with a specific name that starts and ends with an @ symbol. This is called the "decorator" syntax. Here's a simple example:

def my_decorator(func):
def wrapper():
print("Something is happening before the function is called.")
func()
print("Something is happening after the function is called.")
return wrapper
@my_decorator
def say_hello(name):
print(f"Hello, {name}!")
say_hello("John")

When you run this code, it will first print "Something is happening before the function is called.", then "Hello, John!", and finally "Something is happening after the function is called.". The my_decorator function has wrapped around the say_hello function.

Types of decorators

There are two types of decorators:

Real-world examples of decorators

def log_decorator(func):
def wrapper(*args, **kwargs):
print(f"{func.name} was called with arguments {args} and {kwargs}.")
result = func(*args, **kwargs)
print(f"{func.name} returned {result}.")
return wrapper
@log_decorator
def add(a, b):
return a + b
print(add(2, 3))

When you run this code, it will log the function name, its arguments, and its return value.

def authenticate_decorator(func):
def wrapper(*args, **kwargs):
if not authenticated:
raise Exception("You are not authorized to access this resource.")
else:
return func(*args, **kwargs)
return wrapper
@authenticate_decorator
def get_secret_data():
This function can only be accessed by authenticated users.
return "This is secret data."
print(get_secret_data())

When you run this code, it will check if the user is authenticated before allowing them to access the get_secret_data function.

Conclusion

Decorators are a powerful feature in Python that allow you to modify the behavior of functions and classes without changing their code. They can be used for logging, error handling, authentication, or any other task that requires modifying the flow of execution before or after a function is called. With decorators, you can add extra functionality to your code without modifying its underlying structure.

I hope this helps!