Dependency Injection in Python Programming

Tags
18 March 2023
Complete Guide for CTO & IT Directors
Microservices under X-Ray Three books image Download free ebook

Dependency Injection (DI) is a design pattern used in software development to reduce coupling between components and improve code maintainability, testability, and scalability. In this blog post, we will explore the concept of Dependency Injection, its advantages in Python, how to implement it, and best practices for using it effectively.

What is Dependency Injection (DI)?

Dependency Injection (DI) is a design pattern that allows components to be loosely coupled by providing them with their dependencies from external sources, rather than having them create their own dependencies. There are three types of Dependency Injection:

  • Constructor Injection
  • Setter Injection
  • Interface Injection

Constructor Injection passes dependencies through a component’s constructor, while Setter Injection uses setters or properties to inject dependencies. Interface Injection uses an interface or abstract class to define the contract for Dependency Injection.

Why use Dependency Injection in Python?

Dependency Injection is essential in Python because it simplifies code maintenance, testing, and scalability. With DI, code modules can be changed, updated, or replaced without affecting the other modules that depend on them. This modularity reduces the risk of introducing bugs or breaking changes into the codebase. Additionally, DI makes unit testing easier because it allows for better isolation of components during testing. Lastly, DI promotes code scalability, as it allows for new components to be added without requiring a complete overhaul of the codebase.

Implement Dependency Injection in Python

There are several libraries and frameworks available for implementing DI in Python. Popular choices include Django, Flask, and more. These frameworks provide pre-built functionality for handling Dependency Injection. However, it is also possible to create your own DI container in Python using any of the three types of Dependency Injection mentioned earlier.

We’ll focus on one particular dependency injection framework – Dependency Injector. You can find it in this GitHub repository.

Dependency Injector framework

The Dependency Injector is a framework that helps to assemble and inject dependencies in Python applications, making it easier to write modular and maintainable code. With the dependency injection pattern, objects are relieved of the responsibility of assembling dependencies, as the Dependency Injector takes on that responsibility. The framework provides a container and providers that facilitate the objects’ assembly, and when an object is needed, a Provide marker is placed as the default value of a function argument, which the framework assembles and injects automatically.

Here’s an example credited to Dependency Injector, a dependency injection framework for Python by Roman Mogylatov.

from dependency_injector import containers, providers
from dependency_injector.wiring import Provide, inject


class Container(containers.DeclarativeContainer):

    config = providers.Configuration()

    api_client = providers.Singleton(
        ApiClient,
        api_key=config.api_key,
        timeout=config.timeout,
    )

    service = providers.Factory(
        Service,
        api_client=api_client,
    )


@inject
def main(service: Service = Provide[Container.service]) -> None:
    ...


if __name__ == "__main__":
    container = Container()
    container.config.api_key.from_env("API_KEY", required=True)
    container.config.timeout.from_env("TIMEOUT", as_=int, default=5)
    container.wire(modules=[__name__])

    main()  # <-- dependency is injected automatically

    with container.api_client.override(mock.Mock()):
        main()  # <-- overridden dependency is injected automatically

The framework’s use is illustrated in the code example, where the Service dependency is injected automatically when the main() function is called. During testing, the container.api_client.override() method is called to replace the real API client with a mock, and when main() is called, the mock is injected automatically. Any provider can be overridden with another provider, making it easier to re-configure projects for different environments.

The Dependency Injector’s use of explicit definition for dependency injections consolidates object assembling in a container, making it easier to understand and change how an application works. The testability benefit of the Dependency Injector is opposed to monkey-patching, a technique in Python that is too fragile and unstable for use outside of testing code for re-configuring projects for different environments. Instead of monkey-patching, the Dependency Injector patches the interface, resulting in a more stable approach.

Benefits of Dependency Injector framework

Dependency Injection principle can provide businesses with several advantages that can enhance the overall efficiency of their software development processes.

Increased flexibility

By enabling loose coupling of components, it provides flexibility in the system’s functionality, allowing for easy extension or modification of the software without affecting other modules. This can lead to faster and more agile development cycles, allowing businesses to keep up with the rapidly evolving market demands.

Enhanced testability

Dependency Injection improves testability by allowing easy injection of mock objects instead of real ones. This not only speeds up testing but also reduces the risk of introducing bugs into the codebase, ensuring higher quality of the final product.

Improved clarity and maintainability

Dependency Injection makes dependencies more explicit, providing a clear overview of the application structure, which facilitates better control and maintainability. By defining all components and dependencies explicitly in a container, businesses can ensure that their software development team has a clear understanding of the application architecture and can make changes with ease, leading to better maintainability and reducing the overall cost of software development.

Best practices for Dependency Injection in Python

When using Dependency Injection in Python, it is important to follow best practices to keep your code maintainable, scalable, and testable. One best practice is to use Dependency Injection selectively. Not every component requires Dependency Injection, and overusing it can lead to overly complex code. Another best practice is to avoid circular dependencies, where two components depend on each other. Circular dependencies can lead to runtime errors that are difficult to diagnose. It is also important to keep DI code clean and easy to understand. This means following naming conventions, using comments where necessary, and keeping code organized.

NG Logic and Python

NG Logic is a firm believer in using best practices in software development, and Dependency Injection is a software design pattern to build robust, modular, and maintainable code.

We stay up-to-date with the latest trends and best practices in software development. Python is a rapidly evolving language, and we keep abreast of new features, libraries, and frameworks to provide the best possible solutions for our clients.

Do you have a project that requires Python experts? Let’s set up a meeting.

Latest Posts

Scrum: How to Work Together

With the popularity of the scrum framework among software development teams, it’s growingly important to learn how a scrum team works to meet its goals. Scrum Process Overview Scrum is an agile project management framework widely used in IT but can be applied to other fields as well. The framework facilitates the management of complex […]

/
event storming

Event Storming: How to Boost Your Software Development Process with a Simple Technique?

Event storming is a dynamic workshop technique that supports domain-driven design in software development. It can boost the team’s efficiency and reduce error risk, minimizing the back-and-forth in the development lifecycle. If you haven’t been living under a rock, you’re probably familiar with the concept of brainstorming. It’s a widely used term for the process […]

/
rails vs sinatra

Rails vs Sinatra

In the rapidly evolving world of software development, web frameworks have become essential tools for building robust and scalable web applications. These frameworks provide a structured environment that streamlines the development process, offering pre-written code, libraries, and guidelines that help developers avoid repetitive coding tasks, thus significantly enhancing productivity and ensuring best practices. Within the […]

/
android webstockets

Introduction to Android WebSocket

WebSockets have become a pivotal technology in enabling real-time communication for Android apps, offering a dynamic way to send and receive messages instantaneously. This technology facilitates a persistent connection between the client (Android app) and the server, bypassing the traditional HTTP request-response model to allow continuous data flow through a single TCP connection. The WebSocket […]

/
smart contracts audit

Introduction to Smart Contract Audits

In the blockchain world, smart contracts are key to decentralized applications (dApps), automating transactions and enforcing agreements without intermediaries. These contracts handle significant digital assets and perform crucial operations, making their security paramount. Smart contract audits are thus essential, scrutinizing the contract’s code for vulnerabilities to prevent potential security breaches. These audits are crucial for […]

/
What is Python Used for in Finance

Embracing the Essence of Scrum: The Indispensable Values for Agile Teams

In the ever-evolving landscape of project management, Agile methodologies like Scrum have become the cornerstone for many teams striving for adaptability and efficiency. While Scrum offers a comprehensive framework and great agile tools, it is the underlying values that truly breathe life into the process. During The Sprint What Scrum Value Must The Team Demonstrate […]

/
Related posts
rails vs sinatra

Rails vs Sinatra

In the rapidly evolving world of software development, web frameworks have become essential tools for building robust and scalable web applications. These frameworks provide a structured environment that streamlines the development process, offering pre-written code, libraries, and guidelines that help developers avoid repetitive coding tasks, thus significantly enhancing productivity and ensuring best practices. Within the […]

/
rxjs react

RxJs & React: Reactive State Management

In the ever-evolving realm of web development, the quest for efficient, scalable, and maintainable tools never ends. Two such tools, React and RxJS, have garnered significant attention in the recent past. React, the brainchild of Facebook focuses on crafting intuitive user interfaces by leveraging a component-based architecture. On the other hand, RxJS offers a fresh […]

/
css class override

CSS Class Override: How To Add Custom Styles The Right Way?

In CSS, class overriding allows developers and designers to control web page styles. Find out how it works and how to use it for adding custom styles. CSS (Cascading Style Sheets) is a language used to style documents written in markup languages, such as HTML, XHTML, or SVG. It defines styles for web pages and […]

/
angular advantage

Advantages of Angular in Web Development

Angular is one of the most widely used frameworks for building amazing UIs. It can speed up the development process and save a lot of costs. Find out about its features, key advantages, and limitations. Angular is a leading open-source front-end framework for developing web applications and one of the most popular software development tools […]

/
django vs flask

Django vs. Flask. Which framework will work better for your web development project?

Flask and Django are the top two Python frameworks for web development. They are different in many ways, but both can provide great results in the hands of skilled software engineers. We’ve compared Flask vs. Django to figure out what their superpowers are. The Python programming language has been experiencing a rapid rise in popularity […]

/
dependency injection python

Dependency Injection in Python Programming

Dependency Injection (DI) is a design pattern used in software development to reduce coupling between components and improve code maintainability, testability, and scalability. In this blog post, we will explore the concept of Dependency Injection, its advantages in Python, how to implement it, and best practices for using it effectively. What is Dependency Injection (DI)? […]

/
Talk with experts

We look forward to hearing from you to start expanding your business together.

Email icon [email protected] Phone icon +1 (888) 413 3806