Voluptuous Python – A Data Validation Library

In this article, we will discuss the voluptuous python library, why we prefer it, how to install it, what is XML and JSON, what is data validation, and some frequently asked questions about this library.

Introduction to Voluptuous Python Library

Python libraries are reusable code sets that we may use in our programs without having to rewrite the complete application. Tensorflow, Numpy, Keras, PyTorch, Scikit-Learn, and the voluptuous python library are just a few of the over 137,000 libraries available in Python.

A data validation library in Python is called a voluptuous library. The primary goal of voluptuous in Python is to verify data of various kinds of Python, such as JSON and XML.

What is Data Validation?

Data validation is required before importing modules or doing preprocessing in a program. Data validation is an important process that assesses the data’s quality and correctness. It guarantees that the information presented is correct and clear. In a summary, to ensure that the input provided is correct. When we use data for analysis, we do data validation to verify that our results are correct. Let’s have to look at some examples:

  • Data should be free from null values
  • The range of values should be consistent
  • The records stored should be distinct and unique
  • The data type is valid
  • Meets the required constraints


eXtensible Markup Language is the abbreviation for XML. It’s a markup language that comes in useful when we only need to work with a little quantity of data and don’t want to use a SQL database. Python is a popular programming language for web development and data research. As a result, there’s a good probability you’ll have to work with XML data. When working with XML data, Python offers two major interfaces. Simple API for XML (SAX) and Document Object Model API are the two APIs (DOM).


JavaScript Object Notation is an abbreviation for JSON. In Python, there is a built-in module called JSON that is used to interact with JSON data. In Python, JSON is a data format for representing structured data. The JSON data format is most commonly used when talking between a web application and a server. JSON is stored in the form of a string in Python. Its primary function is to send text-based data over a network. JSON, like a Python dictionary, represents things as key-value pairs.

Voluptuous Python as a Data Validation Library

Voluptuous is a Python data validation library that is mostly used for verifying JSON and XML data in Python.

There are three main goals of the voluptuous Python library are:

  1. Simplifying the data
  2. Providing support while handling complex data structures
  3. Providing useful error messages

It is important to accept and use just the data that is necessary while rejecting the rest. Furthermore, we do not always know what sort of data we will obtain when retrieving data from the database. Voluptuous is used to solve the difficulties mentioned above. It allows users to only accept data in a specific format.

Why Prefer Voluptuous Python Library Over Other Validation Libraries?

Python has a large number of validation libraries. The following are some of the reasons why voluptuous is preferable to others.

  • Simple to use. There is no need to create a subclass. Only a function has to be use
  • Accepts basic Python data structures
  • Errors are easy to handle by calling exceptions
  • Provides consistency
  • Nested data structures are treated like other data types.

Example of Voluptuous Python Library

First, we have to install the Voluptuous Library before importing.

pip install voluptuous

The Voluptuous Library will now be import. Next, we’ll import the ‘Schema’ interface from voluptuous.

from voluptuous import Schema

The schema is a Python tree-like structure where nodes are pattern match against related trees of values, according to the python documentation.

Nodes can be values, types, or callables in this case. To put it another way, the schema is the data structure that we expect. An array of integers, a dictionary, or an array of dictionaries can be use.

Let’s have a look at a school-record schema.

schema = Schema({
  'name': str,
  'sid': int,
  'marks': int,

As a result, the above-mentioned schema specifies the data that the API requires. However, there are some issues with this schema as well. It does not, for example, disclose all of the API’s limitations. As a result, we’ll need to create a new schema for the restrictions. The maximum length of the value name should be 20, the maximum length of the value sid should be 3, and the minimum value of marks should be 60. So now we’ll go over the schema in further detail.

We’ll need to import Required, All, Length, and Range from voluptuous first.

from voluptuous import Required, All, Length, Range

So now, we shall define the new schema.

schema = Schema({
   Required('name'): All(str, Length(min=1, max=20)),
   'sid': All(int, Range(min=1, max=20)),
   'marks': All(int, Range(min=60)),

We shall create an Exception. Since the name is define as a string value, we shall raise an exception if the value entered is not a string.

  schema({'name': 903})
  raise AssertionError('MultipleInvalid not raised')
except MultipleInvalid as e:
  exc = e
str(exc) == "Expected string value for dictionary value @ data['name']"

We shall create an Exception. Since the name is define as a string value, we shall raise an exception if the Similarly, we create another exception because the name must be at least one character in length.

  schema({'name': ''})
  raise AssertionError('MultipleInvalid not raised')
except MultipleInvalid as e:
  exc = e
  str(exc) == "length of value must be at least 1 for dictionary value @ data['name']"


What is Cerberus in Python?

Cerberus is a Python library that is both strong and easy. It is use to validate data. It’s simple to expand, allowing users to add unique validation.

What are other Data Validation libraries in python?

There are additional data validation packages in Python besides voluptuous. Cerberus, Colandar, Schema, Valideer, and Schematics are a few of them.

What is a validator in python?

The validator is a Python library with over 60 methods for validating the type and contents of input values.


That’s all for this article if you have any confusion contact us through our website or email us at [email protected] or by using LinkedIn.

Suggested articles:

  1. How to create a virtual environment in Python?

Leave a Comment