Adventures in Machine Learning

Mastering Data Identification: Using type() and isinstance() functions

Every day, we use various methods to secure our data. Hashing is one such method, which is widely used to save sensitive information in a way that it is not easily convertible to its original form.

This article explores various aspects of hashing that you need to know, including error handling for hashing strings, the difference between hash.digest() and hash.hexdigest(), and how to pass bytes objects to hash using Python. Error Handling for Hashing Strings:

Encoding Strings:

One of the primary functions of hashing is to convert an input string into a hashed value which is impossible to convert back to the initial string.

However, if you need to hash a string, you should first encode it to a byte object using the encode() method, which takes the string and a hashing algorithm as its arguments. Passing Bytes Object:

To pass your bytes object to the hash function, you can use the b” prefix, which creates a bytes object in Python.

Alternatively, you can use the str.encode() method, where string is the argument that requires encoding. Using digest() and hexdigest():

After passing your byte object, you need to calculate the hash value.

There are two ways to retrieve the hash value-

Using the digest() method that returns the hash output as bytes object.

Using the hexdigest() method that returns the hash output as a string object.

Difference between hash.digest() and hash.hexdigest():

Purpose and Functionality of digest() method:

The digest() method computes the message-digest as a bytes object after passing the specified byte object to the hash object update() method. The output length of the digest depends on the type/size of the hash function selected.

Purpose and Functionality of hexdigest() method:

The hexdigest() method returns the message digest as a string object containing only hexadecimal digits. Hexadecimal digits are characters in the range of 0-9 and a-f.

Conclusion:

Hashing is a great way to secure data. However, it is essential to know the proper method to convert the string input to a hash value.

In this article, we explored how to pass bytes object to hash using various methods in Python. We also saw the difference between digest() and hexdigest() methods used to retrieve the hash output.

By following these steps, you can successfully hash your data and keep it secure.In programming, variables are used to store data and allow it to be accessed and manipulated across the code. However, it can sometimes be challenging to identify the type of data that is stored in a particular variable, especially in larger and more complex code.

In this article, we will explore two ways you can identify the type of data stored in variables: using the type() class and using the isinstance() function. Using type() class:

The type() class is a built-in Python function that you can use to determine the type of an object.

To use the type() class, you simply pass the variable to the function as an argument, and it will return the type of the object. For example, consider the following code, which stores the value of 10 in an integer variable named my_variable:

“`

my_variable = 10

print(type(my_variable))

“`

When we run this code, we will get the following output:

“`

“`

In this case, the type() class has identified that the data stored in the variable is an integer and returns the type as ‘int’. Another example is when you store text in a variable named my_string:

“`

my_string = “Hello, World!”

print(type(my_string))

“`

The output will be:

“`

“`

In this example, the type() class has detected that the data stored in the variable is a string and returns “str” as the type. Using isinstance() function:

The isinstance() function is another built-in Python function that performs a similar task to type().

However, it is more versatile and lets you identify if an object is of a specific class or subclass. To use the isinstance() function, you pass the variable and the class you want to compare it to, and it will return

True if the variable is of that class or subclass, and False if not. For example, consider a code that stores an integer in a variable named my_variable, and we want to check if it’s an integer:

“`

my_variable = 10

print(isinstance(my_variable, int))

“`

The output will be:

“`

True

“`

In this case, the isinstance() function has identified that the data stored in the variable is true and returns

True as the output. Similarly, we may have a list of data that we want to confirm is a list, we write:

“`

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

print(isinstance(my_list, list))

“`

The output will be:

“`

True

“`

In this example, the isinstance() function has identified that the data stored in the variable is a list and returns

True as the output. Conclusion:

Identifying data stored in variables in a program is a necessary step in working with data.

In this article, we explored two ways to identify the type of data stored in variables: using the type() class and using the isinstance() function. By using these functions, developers can confidently identify and manipulate data to achieve their desired outcome.

In conclusion, identifying data stored in variables using type() class and isinstance() function is essential in programming. The type() function reveals the type of the object when passed as an argument to the function.

Conversely, the isinstance() function is more flexible and lets you identify if an object is of a specific class or subclass. Knowing the types of data stored in a variable is crucial to any programmer trying to manipulate the data.

Identifying the stored data in a variable ensures that the program performs as expected, and the developer can confidently and efficiently modify the data. All programming beginners must master this basic concept to avoid errors in their codes.

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