Microservices have evolved as a crucial paradigm in modern software development, offering scalability, flexibility, and efficient administration of complex systems. Python microservices are tiny, self-contained apps that execute specified tasks and enable flexible deployment and scalability. This modular software architecture method reduces component connection, increasing flexibility and predictability throughout development.
Python is a versatile and strong programming language, and Flask GRPC is a lightweight website framework that enables us to construct online apps quickly. They form a potent combo for building microservices. We will walk you through the process of developing microservices step by step in this post, offering code samples and descriptions along the way.
It is critical to implement a microservices Python framework correctly. When developing a framework to support mission-critical applications, you must guarantee it is robust and developer-friendly. In this fantastic blog, you’ll learn how to do just that. This comprehensive knowledge will make you more worthwhile to emerging companies.
Continue reading to learn more amazing facts about Python GRPC, and we will also discuss the Docker alist using microservices.
Table of Contents
What are Microservices?
Microservices architecture is a method of developing programs that divides them into more minor, loosely linked services. This design offers scalability, adaptability, and maintainability.
Assume a developer works for a popular e-commerce business that offers a variety of things online. The firm employs several hundred people. Each developer receives to build code for a back-end web development feature or a specific product, such as adding an item to a shopping cart, generating suggestions, processing payment transactions, or interacting with warehouse history.
Consider how difficult it would turn out to combine all of the code into a single extensive application. How difficult might that seem to grasp? How long would testing take? It is indeed difficult, especially if the company attempts to expand rapidly. Python Microservices can do this task perfectly.
It would be vastly preferable if code matching to modular product characteristics were, well, modular.
Why Use Microservices?
Consider working at Online Books For Yourself, a well-known e-commerce firm that sells textbooks online. Several hundred developers work for the firm. Each developer is responsible for building code for a particular product or the back-end feature, such as maintaining the user’s cart, making suggestions, processing payment actions, or interacting with warehouse inventories.
Now consider if you’d prefer the whole code in one extensive application. Is it difficult to grasp? How long would testing take? How would you maintain the sanity of the code and relational schemas? It would be difficult, especially given the company’s need to hurry.
Wouldn’t it be preferable if the code matching to modular product attributes was modular? A cart microservice for cart management. A microservice for inventory management.
In the following sections, you’ll explore some of the benefits of separating Python code under microservices.
- Modularity
Code updates frequently follow the route of least resistance. Your favorite online publications For Your CEO wants to implement a new buy_two_get_one_free_promo. You are a part of a group tasked with launching it as soon as feasible. Examine what happens when all of your code appears within a single application.
As the most knowledgeable engineer on your team, you suggest adding a few lines of code to the cart logic to check whether there are a maximum of two books in the cart. If this is the case, deduct the cost of the inexpensive book from the shopping cart total. You create the Python Microservices pull request.
You should email folks who haven’t taken advantage of the promotion. Include that as well. As a result, keeping all of your code in one program might be risky in the long term. Boundaries are sometimes necessary.
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- Flexibility
The most fundamental benefit of microservices is flexibility. The code may be written in many languages by the developer. We may also separately grow the microservices. In the following part, we will develop example microservices.
Each microservice can also be scaled separately. As a running example, you’ll use a web app and a Suggestions microservice in this course.
Your web application will almost certainly be I/O bound, retrieving data from a database and possibly loading themes or files from a disk. A Suggestions microservice may be CPU-constrained if it performs a lot of numerical crunching. It makes sense to execute these two Python microservices on separate hardware platforms.
After a few years, the transactions database became too huge and had to be replaced with an entirely novel shared database. All of those references have to be updated. Unfortunately, the database is now referenced across the codebase. You believe that adding all of those references was much too simple.
- Robustness
If we combine all the code into one program, we must also deploy it all simultaneously. It might prove a significant threat. When we try to alter the code, it might bring the entire site down.
- Ownership
This is especially true in large corporations with a high turnover rate. People probably have ideas about how the code should appear, but it’s difficult to enforce since anyone can change it, and everybody is moving swiftly.
Python Microservices provide you control over your code when a single codebase circulates across several personnel who come and go. There is no obvious concept for the code’s architecture. Microservices assist in providing an unambiguous goal for the code, ensuring it remains clean and organized. It also specifies who is responsible for adding functionality to code or making modifications when anything goes wrong.
How to Build Microservices With Python?
Let’s have a look at configuring our development environment.
Step 1 – Download Python and Flask.
First, make sure Python has been set up on your computer. The most recent version is available for download from the Python website. Open the console or command line after installing Python and install Flask utilizing pip, the Python GRPC Server package supervisor, by entering the following command:
Step 2 – Build a Flask application.
Now that Flask has been installed, let’s build a simple Flask application. Import the Flask module into a new Python file. Then, build a Flask object and provide a route for handling incoming requests. Add a simple function that returns the message “Hello, World!” as the response. The file should be saved as ‘app.py’:
We load the Flask component and construct a Flask object recognized as ‘app’ in this code sample. On the root URL (“/”), we build a route decorator and link it with the ‘hello()’ function. Flask will run this method and return its outcome when an inquiry arrives at the root URL.
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- Creating Microservices from the Application
Now that we’ve created a basic Flask app let’s break it down into microservices. We will build two Python microservices: one for identifying users and another for managing product data.
Step 1 – Microservice for User Authentication
Make a new Python file called ‘auth_service.py’ and import the required modules. Create a Flask app and define a user registration route. Create a function that receives user input and saves it to a database. Add handling of errors and validation logic as needed. Here’s an illustration:
In the preceding code snippet, we establish a new Flask app for the user identification microservice. On the “/register” URL, we build a route decorator and connect it with the register ()’ method. Moreover, this function accepts JSON-formatted user data, verifies it, saves it in a database, and produces a success message.
Step 2: Microservice Product Management
Create another Python file called ‘product_service.py’ and similarly set up a Flask program. Create, read, update, and delete product data using defined routes. To handle such tasks, implement matching functions. Here’s an illustration:
We develop a Flask application for the excellent management microservice in this code sample. Routes for generating, reading, updating, and removing product data are specified. Moreover, each passage is paired with a function that performs the related operation. According to the process, these routines return suitable messages.
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- Interacting with Microservices
Given that we have two, let’s look at how two Python microservices may connect utilizing HTTP calls and RESTful APIs.
Step 1: Make HTTP Requests
We may employ Python’s ‘requests’ package to send HTTP requests across microservices. Run the subsequent command to install it:
Moreover, the above command downloads the requests package, which enables us to issue HTTP requests from Python programs.
Step 2: Creating API Requests
When a new product is generated, let’s change our product administration microservice to send an API call to the user identification microservice. To the ‘create_product()’ method, add the following code:
Conclusion
If you have an app concept and want to create it utilizing the microservices framework, research the most prevalent frameworks and technologies and select one according to the features you want, the skills of your team, and the resources available. Business logic and capabilities are critical here, therefore consider microservices apps if you have complicated systems, desire continuous delivery, and want certain features such as synchronous interaction. In other circumstances, implementing microservices using Python may be too expensive.
Moreover, microservices architecture has grown in popularity as a method for creating scalable and resilient software applications. Additionally, python microservices design simplifies system maintenance and scaling by separating the application into discrete, independently deployable services.
FAQs (Frequently Asked Questions)
Is FASTAPIA Microservice?
In a microservice design, automated OpenAPI documentation generation by Fast API is critical. In addition, it provides developers with a uniform perspective of the system’s APIs. As a result, development organizations can more easily understand and make use of the services that microservices offer.
Is Python Good For Microservices?
Python is one of a small number of programming languages that can be used in a microservices architecture. In addition, it has the advantages of an active community, improved prototyping, and developer popularity. Languages other than Chinese may have contrived to get around this in some way or another.
Is Django Based On Microservices?
Django is a popular, elegant Python web framework known for its ease of use and scalability. But its rich feature set, excellent records, and large community base make it an ideal platform for building microservices.