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When writing a C extension for Python, you might need to raise an exception if something goes wrong in your C code. Python provides a special C API that helps you to raise errors in a way that works just like regular Python exceptions.This is helpful because even if your code is written in C for better performance, users can still handle errors using Python's normal try...except blocks. It makes your extension feel just like any other Python module.Using Python C API to Raise ExceptionsIn C extensions for Python, you can raise exceptions using the Python C API functions like ... Read More
In Python, the assert statement is used for debugging purposes. It tests whether a condition in your program returns True, and if not, it raises an AssertionError. This helps you catch bugs early by verifying that specific conditions are met while the code is executing. Understanding the Assert Statement The assert statement is used to verify that a given condition is true during execution. If the condition evaluates to False, the program stops and throws an AssertionError, optionally displaying a message. Example: Assertion without a message In this example, we are asserting that 5 is greater than 3, which is ... Read More
In Python, a KeyError exception occurs when a dictionary key that does not exist is accessed. This can be avoided by using proper error handling with the try and except blocks, which can catch the error and allow the program to continue running. Understanding KeyError in Python A KeyError is raised when you try to access a key that doesn't exist in a dictionary. It is one of the built-in exceptions that can be handled by Python's try and except blocks. Example: Accessing a non-existent key In this example, we are attempting to access a key that does not exist ... Read More
In Python, the try, except, and finally blocks are used to handle exceptions. These blocks allow you to catch errors that occur during the execution of a program and respond accordingly, which helps to prevent your program from crashing. Try and Except Blocks The try block contains code that might raise an exception. If an exception occurs, the except block handles it, preventing the program from crashing. Example: Handling ZeroDivisionError In this example, we are dividing a number by zero, which raises an exception and is handled by the except block - try: result = ... Read More
In Python, you need to use the built-in json module to work with JSON data. When you want to return data from a function in JSON format, you can use the json.dumps() function to convert a Python dictionary (or similar object) into a JSON string. This is helpful when making APIs, sending data in web responses, or saving organized data in files. Using json.dumps() Function The json.dumps function is used to convert a Python object (like a dictionary or list) into a JSON-formatted string. Syntax Following is its basic syntax - json.dumps(python_object) Where python_object is usually a dictionary or list ... Read More
When you write tests in Python, it is important to make sure that your function raises the correct exception for invalid input or unexpected conditions. This helps to confirm that your code handles errors properly. You can test exceptions using the following ways in python − Using the try-except blocks manually Using the unittest module Using the pytest module Using try-except Block One of the basic ways to test for exceptions is by manually using a try-except block. This allows you to execute code and catch any exceptions that occur. If the function doesn't raise the ... Read More
Camel case and snake case are ways of writing words together when we are programming. In camel case, we write words together without spaces and we start each new word with a capital letter except for the first word. For example, if we want to write a variable name for someone's date of birth, we can write it like this: dateOfBirth. In snake case, we write words together with an underscore symbol between them, and all the letters are lowercase. For example, if we want to write a variable name for someone's home address, we can write it like this: ... Read More
In Python, when you pass arguments to a function, they are passed by object reference. This means the function gets a reference (or pointer) to the actual object, not a copy of it. However, how this reference affects the object depends on whether the object is mutable or immutable. Mutable objects (like lists, dictionaries, and sets) can be changed inside the function. If you modify a mutable object inside the function, the changes will affect the original object outside the function as well. Immutable objects (like numbers, strings, and tuples) cannot be changed. If you try to modify ... Read More
In Python, you can pass optional parameters to functions, allowing you to call a function with fewer arguments than specified. Optional parameters are useful for providing default values when certain arguments are not provided. Python provides different ways to define optional parameters, including default values, variable-length argument lists, and keyword arguments. Using Default Arguments One common way to pass optional parameters is by setting default values for the parameters in the function definition. If no argument is passed for those parameters during the function call, the default value is used. Example In the following example, the greet() function has an ... Read More
As the name implies, an argument with a variable length can take on a variety of values. You define a variable argument using a '*', for example *args, to show that the function can take a variable number of arguments. Observations on Python's variable-length arguments are as follows - The designation "*args" for variable length arguments is not required. The only thing needed is *; the variable name can be anything, like *names or *numbers. You can send zero or more arguments to a function using a variable length argument. ... Read More