Can We Use Python to Create a Successful MVP?
Can We Use Python to Create a Successful MVP? Absolutely! The ease of the syntax, established libraries and powerful framework make Python the perfect language to create your minimum viable product.
Building a Minimum Viable Product (MVP) is the easiest way to understand whether a product idea will work or not.
42% of startups fail because they build products that the market doesn’t need. An MVP can help to avoid this situation. Testing the idea can provide valuable insights, which can then be used as the foundation for progress. Often, companies struggle to define a technology stack for their MVP.
We will talk about how Python software development is a great way to test a product idea. But before that, let’s understand a little bit about MVP.
What is an MVP (Minimum Viable Product)?
A minimum viable product (MVP) is a product with enough features to test with the end-users. It is used to get feedback from a group of people about the positive aspects and shortcomings.
An MVP in web development is also known as the prototype or the first release of the product. It attracts early adopters and is the best way to validate a product idea.
Existing companies can test an MVP for new products, while startups can create a prototype for their new business idea.
Source: Clever Road (used with permission)
What is the MVP Development Process?
MVP development starts by incorporating only the basic features in the app. It involves a demonstration of what the product will look like.
There are minimum features in the application, so the initial development stage is quick and smooth. (Read also: Diving into Dev: The Software Development Life Cycle.)
The steps to build an MVP are as follows:
1. Conduct Market Research
Contrary to the popular misconception that MVPs don’t need market research, it is really important to do that. Before building, the product idea must fulfill some market need. Otherwise, the MVP won’t work.
2. Outline the Product
Clearly express what the MVP will be. Make sure you can answer these questions succinctly. What features will it have? How can users access the prototype? Why would someone download the app? How much budget is required to build the MVP?
3. Define the Design Flow
The next step is to understand the design of the MVP. Startups need to also define the user flow to ensure that every feature gets tested. The purpose should be to identify how the user navigates from one step to another.
4. Developing the MVP
Identify the features and functionalities and start building the MVP. Developing MVPs requires product engineering experts who can supervise everything - from ideation to release. Build a mobile or web MVP, whichever is convenient.
5. Monitor and Improve
Once you develop the MVP, it is time to monitor the launch and see how it goes. Improve upon the product by receiving and responding to feedback from the end users. Understand how customers react to the product and then make appropriate changes.
Common mistakes to avoid when developing your MVP include attempting to solve the wrong problem with your product, not understanding the people that will use it and misinterpreting the feedback you receive.
Python App Development: Is it Good for Developing MVPs?
Google’s search trends for 2019 placed Python as the second most sought programming language online. It is a powerful programming language that has multiple use cases - it is wonderful for web development, game development, GUI development, and more. (Read also: Why Older Programming Languages Still Got Game.)
Should companies that are building an MVP consider Python development?
There are many data science-based startups that use Python in their technology stack. Modern advancements are driving them to use the dynamic programming language to build MVPs for:
- Internet of Things (IoT).
- Artificial Intelligence.
- Data Analytics.
- Web Crawlers.
- Application Programming Interfaces (APIs).
Some of the top startups that use Python for software development include:
- Cureatr - A medication management platform to access patient data in real-time.
- Stripe - An online payment platform for sending and receiving payments in the US.
- Ometria - A platform to manage customer journeys using AI-based analytics.
Python is highly useful in building MVPs for SaaS products. Today, many companies use the programming language to build new solutions or upgrade their existing products.
Top Reasons to Use Python to Create an MVP
As of August, 2021 Python was the second best programming language, with a market share of 11.86%. It saw a growth of 2.17% over July 2021. The programming language is now a top choice for developers and companies alike. (Read also: Python Programming Language: An Introduction.)
Here are the top reasons to choose Python for creating a successful MVP:
1. Easy Syntax
The Python programming language has syntax similar to that of the English language. Even beginners can start learning the language and catch on quickly.
It is one of the major reasons Python is perfect for MVP software development. Easy coding can reduce the time to code and provide a prototype much quicker than complex programming languages.
2. Extensive Libraries
Did you know that there are 150,000+ packages in Python’s repository? There are enough libraries for string operations, service tools, operating system interfaces, and protocols.
There’s no need for developers to write code for a lot of things. The packages help to add functionalities without going through a lot of hassle.
A lot of programming tasks that require massive coding are already scripted in the form of libraries.
3. Powerful Frameworks
Python has some of the best frameworks for building web applications. Django, Flask, CherryPy, web2Py, and more are the leaders.
Startups can build all types of products using Python frameworks. Whether they want an MVP for web applications or a single page application, there is a framework to build that.
Django is mostly used for Python software development. It is a batteries-included framework that provides enough capabilities to quickly develop web apps.
Apart from these three reasons, Python also has various third-party integrations, libraries for data science, and portability - that makes it perfect for MVP development.
Building an MVP takes a lot of work. However, a Python development company provides the right tools and techniques to build a quick prototype.
Today, MVPs are important for technically advanced companies. Python is a programming language that offers capabilities to build applications for data science, AI, analytics, and more. By taking advantage of these benefits, startups may find themselves not needing to invest in and learn different technologies over and over, a benefit in itself.