Ultimate guide to Python frameworks for building scalable microservices.pdf

Ultimate guide to Python frameworks for
building scalable microservices
Python has been the most iconic sidekick for all IT developers across the
globe. Its enormous popularity amongst programming languages takes up a
29.6% market share. The Popularity of Programming Language Index, (Yes,
it's a real thing!) states that Python’s fame has increased by 8.7% during the
past five years. Especially, when IT giants like Google and Netflix trust a
language for their dependability and security then it surely puts the nail on the
awesomeness of Python!
The evolution of architecture in the software development industry has seen a
massive shift towards scalability and agility. One such approach out of those
has been microservices. When the trendiness of microservice architecture
pairs with the awesomeness of Python, it brings out an incredible combination
in the tech landscape.
However, if you haven’t explored this killer duo yet? Or, if you are planning to
find a scalable architecture for your firm then this blog will be super handy for
you!
In this blog, you’ll get to explore Python frameworks, their types suitable for
microservice development, which business can benefit most out of Python
microservices, and Key factors apart from Python that can influence
microservice scalability. Let’s begin your microservice journey.
What are Python frameworks?
Python frameworks are like pre-built toolkits that help in the process of
building software applications. Instead of starting from scratch, app
developers can easily get a structured foundation with essential components
and tools through Python frameworks. This saves time and effort of
companies, allowing developers to focus on new features & updates of their
applications.
The developers get free from various hectic responsibilities such as database
manipulation, URL routing, and user authentication through frameworks. In

such a way Python developers focus only on the precise elements of their
projects leading to a more streamlined app development lifecycle.
Why choose Python frameworks for developing scalable
microservice?
Python frameworks are highly important for the creation of scalable
microservices. They provide tools and features that help specifically in
empowering the modular and flexible nature of microservices architecture.
Here’s a detailed insight on Python frameworks contributing to microservices
scalability:
1. Modularity and flexibility: Python frameworks like Flask and FastAPI are
lightweight and modular. It helps developers to build microservices that
are small, focused, and easy to manage.

2. Asynchronous capabilities: Various Python frameworks such as FastAPI
and Tornado make use of asynchronous programming. This means
microservices can handle multiple requests concurrently without
blocking. It aids in building scalable systems that can efficiently manage
high volumes of traffic.
3. Ease of integration: Python frameworks are known for their simplicity
and ease of integration with other tools and services. This makes it
easier to connect microservices with databases, message queues, and
other components of the system.
4. Community and ecosystem: Python inherently being a classic
programming language offers a wide range of libraries and extensions
that can be used to add functionalities like caching, logging, and
monitoring, which are essential for maintaining and scaling
microservices.
5. Automated testing and CI/CD: Python’s compatibility with testing
frameworks and CI/CD tools makes sure that microservices can be
tested, deployed, and scaled in an automated, reliable manner.
These features make Python frameworks a powerful choice for developing
microservices that are not only scalable but also maintainable, resilient, and
secure.
Types of Python frameworks based on use cases

Though, expert Python developers can bombard you with tons of framework
types. But based on utilities, there are 5 types of Python frameworks with
examples that you should know, as follows:
1. Full-stack frameworks
Full-stack frameworks, as the name suggests provide a complete solution that
includes everything necessary to build web applications. It offers features like-

form validation, template engines, ORM (Object-Relational Mapping), and
security measures.
Examples: Django, Pyramid
2. Microframeworks
Microframeworks are lightweight frameworks that provide the basic tools
needed for web development. It does not enforce any particular pattern. They
are proven ideal for developers who prefer flexibility and simplicity.
Examples: Flask, Bottle
3. Asynchronous frameworks
Asynchronous frameworks are designed to handle asynchronous
programming( it is a technique that allows a program to run multiple tasks at
once, while still being responsive to other events). It proves useful particularly
for applications that require high concurrency, such as real-time applications
or those dealing with a lot of I/O operations.
Examples: FastAPI, Tornado
4. API-first frameworks
API-first frameworks focus majorly on building APIs rather than traditional web
applications. Their main tasks include performance and efficiency optimization
in handling HTTP requests and responses.
Examples: Falcon, Hug
5. WebSocket frameworks
WebSocket frameworks provide built-in support for WebSocket protocol. It
also helps in real-time, bi-directional communication between clients and
servers.
Examples: Sanic, Django Channels

These frameworks cover a broad spectrum of use cases, allowing Python
developers to choose the one that best fits the requirements of their
application, whether it's for a full-scale web app, a simple API, or a
microservice architecture-based app.
Out of these creating scalable microservices with Python is what we are going
to dig further. Let’s explore some of the most popular Python frameworks that
can give you a heads-up!
10 Best Python frameworks for scalable microservices
When building scalable microservices in Python, choosing the right framework
is very crucial, as different frameworks suit different applications based on
their use cases & features.

Here’s a detailed overview of several Python frameworks, their suitability for
different application types, and their scalability potential, for your ease of
understanding:
1. Flask
Flask is a lightweight and flexible micro-framework that provides developers
with the essential tools to get started quickly in app development. It’s simple
and does not impose particular architectural patterns, giving space for
extensive customization.
● Scalability: Flask is ideal for smaller applications and APIs, where quick
development is kept on priority. However, for larger applications,
developers need to integrate additional tools like Gunicorn for managing
multiple requests and ensuring scalability.
● Suitability: Flask is best suited for small to medium-sized applications
where rapid development and flexibility are of prime concern. It’s also
popular for building RESTful APIs.
2. Django
Django is a complete web framework that includes an ORM, authentication,
admin interface, and more. Python developers looking for a framework for
complex, database-driven websites can always trust this framework.
● Scalability: Django is more heavyweight compared to other Python
frameworks. Though, use of proper database optimization, caching, and
horizontal scaling strategies can solve this minor hassle effectively.
Though Django requires more initial setup.
● Suitability: Django is ideal for large-scale, enterprise-level applications
that require an all-in-one framework. It’s also suitable for projects where
security, scalability, and rapid development are required on a larger
scale.
3. FastAPI
FastAPI is a modern, high-performance web framework for building APIs,
utilizing Python-type hints and asynchronous programming for speed.

● Scalability: FastAPI’s design emphasizes performance and scalability,
making it suitable for high-load applications that need to handle many
concurrent requests. Its async capabilities and integration with tools like
Starlette make it highly scalable for microservices.
● Suitability: FastAPI is perfect for high-performance APIs and real-time
applications where speed and scalability are necessarily needed.
Modern microservices architectures are its trendiest zing!
4. Tornado
Tornado is Python’s asynchronous networking library and web framework. It is
designed to handle a large number of simultaneous connections in a
non-blocking manner. Many microservices applications are built with this
Python framework.
● Scalability: Tornado’s non-blocking I/O model allows it to scale to
thousands of open connections. It is highly suitable for applications
requiring long-lived connections.
● Suitability: Tornado is perfectly suited for real-time applications such as
chat applications or streaming services that require managing multiple
connections in a single instance.
5. Pyramid
Pyramid is a general-purpose web framework known for its flexibility and
modularity. It allows developers to start small and scale up as needed.
● Scalability: Pyramid can scale well with the right architecture and
third-party tools. However Pyramid needs a lot of setup and
configuration in comparison to other frameworks of Python.

● Suitability: Pyramid is best for medium to large-scale applications where
flexibility and the ability to customize the framework are essential. It’s
also a good choice for projects that start small but may grow in
complexity over time.
6. Sanic
Sanic is a Python 3.7+ web server and web framework that’s designed for
fast, asynchronous applications.
● Scalability: Sanic’s asynchronous capabilities make it scalable for
handling large volumes of concurrent requests, similar to FastAPI.
● Suitability: Sanic is suited for real-time, high-performance APIs where
low latency and high throughput are required. It’s also effective for
building scalable microservices with Python framework as its backbone.
7. Bottle
Bottle is a very lightweight micro-framework, ideal for small web applications
and quick prototypes. It’s a single-file framework, making it incredibly easy to
use and deploy.
● Scalability: Bottle is not designed for large-scale applications, but it can
be scaled with external tools such as WSGI servers and load balancers.
● Suitability: Bottle is best suited for small projects, prototypes, and
practical purposes, where simplicity and ease of use are more important
than scalability.
8. Falcon
Falcon is a minimalist web framework focused on building fast APIs. Its main
power is being lightweight and performant, making it an excellent choice for
high-performance applications.
● Scalability: Falcon’s lean architecture makes it scalable for
high-performance applications, but it also requires additional tools.

● Suitability: Falcon is ideal for high-performance RESTful APIs where
speed is a critical factor. It’s used in microservices applications where
every millisecond counts.
9. CherryPy
CherryPy is an object-oriented web framework that allows developers to build
web applications.
● Scalability: It is known for being scaled horizontally by running multiple
processes and using a load balancer.
● Suitability: CherryPy is suitable for small to medium-sized applications
where ease of use and simplicity are primarily important.
10. Quart
Quart is an ASGI framework that replicates the Flask API but supports async.
It waits for handling asynchronous tasks, combining Flask’s ease of use with
modern async capabilities.
● Scalability: Quart’s asynchronous nature makes it scalable for
applications that require concurrent request handling.
● Suitability: Quart is ideal for modern web applications that need to scale
while using Flask’s simplicity and API structure deploying Python
microservices in production.
Benefits of Python framework for microservices

When considering frameworks for building scalable microservices, Python is
preferred by many experts due to several compelling reasons. Here are 5 key
benefits of Python frameworks for developing microservices that make it a
prime choice:
1. Custom frameworks for microservices
Python offers a diverse set of frameworks like Flask, Django, FastAPI, and
Tornado, each with unique strengths custom to different types of
microservices. As stated above, FastAPI is best suited for high-performance
API. This way developers can choose the best tool for the specific needs of
their microservices architecture gaining more scalability and performance in
the applications.
2. Simplicity and ease of use
Python’s syntax is always clean and readable, which significantly reduces the
complexity involved in writing and maintaining code. Eventually, it also yields

quicker development times and easier debugging. All these add-ons from
Python frameworks sync well with the core nature of microservices
environments where services need to be independently developed, tested,
and deployed.
3. Strong ecosystem & libraries
As everyone knows, Python possesses a vast array of libraries and tools that
support microservices development. Ranging from asynchronous
programming tools like asyncio to RESTful frameworks like Falcon and Flask
offers developers ease of integration. Whereas a rich set of resources also
reduces the need to build functionality from scratch aiding in the development
timeline.
4. Asynchronous programming support
Frameworks like FastAPI and Tornado offer native support for asynchronous
programming, which is highly essential for building scalable microservices.
Asynchronous code helps in managing multiple operations without waiting for
each task to complete sequentially. This, in turn, helps businesses acquire
high concurrency, such as real-time data processing services, enhancing
scalability and responsiveness in applications.
5. Community support & evolution
Python has a vibrant and active community that continually contributes to its
development and improvement. Such massive support guarantees that
Python frameworks meet the latest industry trends and best practices.
Whereas the extensive documentation, tutorials, and forums, also make it
easier for developers to resolve issues and stay updated with the latest
advancements.
Also read: Microservices architecture with Python: Building scalable and
maintainable systems

Which business can benefit from Python frameworks for
microservices?
After understanding so much about Python, if you’re deploying Python
microservices in production and want to explore whether your business can
benefit most from this revolutionary technology? then here is a list that can
help you make the final decision:
1. Tech Startups: Quickly build and iterate on services because of Python’s
simplicity and microservice’s highly flexible capabilities.
2. E-commerce Platforms: High or drastic changes in traffic won’t be a
hustle anymore for e-commerce businesses as microservices offer
independent scaling.
3. Fintech Companies: Under the secure, compliant microservices with
Python's robust security features, fintech businesses can easily flourish
& upgrade with time.
4. Healthcare Providers: Healthtech apps can easily handle complex data
integrations and real-time processing with efficiency through Python
microservices.
5. IoT Companies: The ability of Python to manage data from diverse
sources in real-time can immensely benefit IoT firms which require
instantly responding systems.
Basically, all evolving sectors can take advantage of microservices
architecture built with Python frameworks. Business growth isn’t that hard
anymore! You just need to find the right tools and pair them with the right
technologies.
Key factors affecting microservices scalability besides Python
frameworks

Surely, all the above information signaled that Python frameworks bring
scalability to microservices. But, it's not the sole determinant. Here are a few
more essential factors influencing microservices scalability apart from Python
that you should keep in mind:
● Service granularity: Microservices facilitate breaking applications into
smaller independent units for more granular scaling. But when larger
microservices arrive in this situation then it's quite challenging to scale
independently.
● Asynchronous communication: Using asynchronous communication
patterns like message queues between microservices significantly
enhances scalability by decoupling services and rooting the parallel
processing.

● Data management: Proper management of strategies is highly
necessary. Especially processes like caching, distributed databases,
and event sourcing, highly impact on scalability of microservices and
require meticulous management.
● Infrastructure optimization: Making use of cloud-native technologies,
containerization, and serverless functions majorly influences scalability
and resource utilization.
● Monitoring and observability: Detailed monitoring and observability tools
identify performance issues and optimize resource allocation leading to
scalable and resilient microservices.
Conclusion
Python frameworks in combination with microservices architecture yield a
simple and rich ecosystem full of asynchronous capabilities, and scalability for
businesses. Whether you’re developing lightweight APIs or handling
high-concurrency tasks, Python frameworks always fit in to offer you an
incredible solution. Make sure you keep all the considerations of the Python
framework for microservices development discussed above in line such as its
suitability for applications, its utility, and sync with a variety of businesses.
Though the Python framework is a crucial factor in microservices scalability,
but it is just one piece of the puzzle. Other factors, such as service granularity,
architecture design, data management, and how well the services are
containerized, orchestrated, and optimized, also play significant roles.
Choosing a lightweight, asynchronous framework of Python combined with the
effective use of cloud-native tools, can help guarantee scalable microservices.
Still, if you’ve got a large, complex system that can’t be easily managed then
hiring Python developers holding expertise in microservices would be the
correct decision. The future of application development lies in microservices,
and Python frameworks are its best sidekick. Embrace the power of Python
and bring the potential of scalable microservices to your business today.

Ultimate guide to Python frameworks for building scalable microservices.pdf

Ultimate guide to Python frameworks for building scalable microservices.pdf

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