Python programming language is one of the most used programming languages, as it is used widely in the field of software and data analysis, web development, etc. It is said to be a user-friendly programing language, as the syntax for it is very simple to write and easy to understand for a beginner programmer. Python programming language is rich in libraries that can be imported easily and used to perform many different operations. In the year 1989, Guido van Rossum is the one who introduced python programming language.
It is also used in web applications; web applications like the Django and Flask frameworks are created using python. Compared to any programming language, the syntax in python is much easier. Python programming language is most widely used language in today’s technology. Many colleges and institutions have introduced python in their syllabus so that the students need to learn python.
The biggest advantage of the python programming language is that it has a good collection of libraries widely used in machine learning, web frameworks, test frameworks, multimedia, image processing, and many more applications. The latest version of the python programming language available is python 3 which is the most updated version of the python programming language.
A Python library called Marshmallow can translate between different complex data types and Python data types. It is a strong data conversion and validation tool. In order to convert complicated datatypes, such as objects, to and from native Python datatypes, marshmallow is an ORM/ODM/framework-independent module. Now we will, demonstrate how to validate a straightforward bookmarks API that lets users save their favorite URLs along with a brief description of each website. We will be using the Marshmallow framework.
When working with data, it is frequently necessary to transform information between different data structures. A Python package called Marshmallow translates sophisticated data types to the language's default data types and the other way around.
Among the built-in data types that the Python interpreter supports are integers, booleans, tuples, lists, dictionaries, floats, sets, and arrays. These are crucial for programmers who wish to build complicated applications that can handle a variety of operations.Marshmallow has the benefit of being compatible with any database technology. Platform independence is usually advantageous for developers.
Using the following technologies, we will further develop Marshmallow:
- Marshmallow-sqlalchemy is a SQL Object Relational Mapper extension for SQLAlchemy.
- It is simple to utilize Marshmallow with Flask thanks to the Flask-marshmallow extension. Additionally, it creates linkages and URLs for Marshmallow objects.
Implementation of Marshmallow in Flask
We will first create a BookMarkModel class before creating our bookmark API. The database engine will be contacted using this class to obtain information about the relationships, fields, and table structures. Additionally, a BookMarkSchema class will be added so that our model's data can be serialised and deserialized. The /src/app.py file in the cloned repository contains these classes.
We are using SQLAlchemy to demonstrate how Marshmallow parses data from Python types to serialised objects. The deserialized items from the database can be converted to appropriate Python data types after the serialised objects have been placed in the database.
# AddingSQLAlchemy to our appliation application.config['SQLALCHEMY_TRACK_MODI'] = Falseapplication.config['SQLALCHEMY_DB_URI'] = 'sqlite:///' + os.path.join(BASE_DIR, 'db.sqlite3') db = SQLAlchemy(application) # Adding Marshmallow to the application marsh_mallow = Marshmallow(application) # Create the API model (SQLAlchemy) classBookMarkModel(db.Model): pass # Create schema to the appliction (marshmallow) classBookMarkSchema(ma.Schema): classMeta: pass book_Mark_Schema = BookMarkSchema() book_Marks_Scehma = BookMarkSchema(many = True)
Using SQLite by default, this code sample first connects SQLAlchemy to our application. When a URL is set up, it establishes a connection to that SQL database. The snipped then launches Marshmallow to serialise and deserialize data as it is transmitted from our models and received by the snipped.
When interacting with a single bookmark, the book_Mark = BookMarkSchema() schema is in charge of deserializing a single dataset (the POST, READ, and UPDATE routes). For example, to get all desired bookmarks, book_Marks = BookMarkSchema(many =True) is used to deserialize a list of items in the collection.
A Python library called Marshmallow can translate between different complex data types and Python data types. It is a strong data conversion and validation tool. In order to convert complicated datatypes, such as objects, to and from native Python datatypes, marshmallow is an ORM/ODM/framework-independent module.