With the growing interest in blockchain, the choice of technologies for creating blockchain solutions is becoming one of the main issues. Python is often ranked among the top tools for creating blockchain-based projects. According to StackOverflow’s 2019 developer survey, this programming language entered the top 5 most popular languages ​​among developers. Moreover, according to the TIOBE rating, Python ranks as the second most popular programming language as of June 2021. So let's see how exactly this technology is attracting engineers around the world and what role it plays in blockchain development.

Blockchain development without complications

The first thing you hear about Python most often is that it's pretty simple. It is easy to learn so even novice developers can contribute to the development of open-source projects. To understand how this simplicity benefits blockchain developers, let's go through the process of building blockchains.

So, to build a blockchain, we need to create blocks and ensure their interaction. Each block has its own structure, which contains an index, timestamp in Unix time, transactions list, proof, and previous block hash. Creating and linking these blocks may seem like a daunting task, but Python's syntax allows you to create a simple blockchain with just a few dozen lines of code. Python frameworks like Flask and Requests greatly simplify the development process. For example, Flask makes it easy to create APIs.

In fact, it is enough to find a guide to creating a blockchain in Python on the Internet and get started. The instructions only take a few minutes to read, because with Python you don't have to write a lot of code. For instance, the most frequently mentioned example is that you don't need to worry about adding curly brackets or keywords because, in Python, white spaces signify code blocks. So yes, the combination of simplicity and flexibility makes Python a great solution for building blockchains.

No need to waste time compiling your code

This is one of the reasons why blockchain developers prefer Python over, say, C++. Python doesn’t require compilation before launch, which simplifies the process of fixing bugs. Instead of stopping the app, editing the source code, compiling it, and restarting the program, it’s now enough to fix the error and simply restart the app. In addition, it doesn’t affect the performance of the programming language. The point is that Python has a feature of re-compiling the code that uses various techniques to optimize performance. Therefore, when developing a blockchain in Python, you don’t need to look for a compromise between speed and expended resources.

Python has free packages for blockchain developers

What could be better for a developer than ready-made solutions that speed up the process of creating a product? Python has a ton of libraries and ready-made tools for blockchain development. Many of them are available for free in the official repositories. For example, Hashlib allows you to implement many secure hashing algorithms that are crucial for blockchains. I already mentioned Flask, which simplifies the API creation process so that different users can initiate transactions and create blocks. Requests library will be needed to send a request to build a new transaction and add it to the block. Python also has solutions for specific ecosystems. For example, Populus is an efficient smart contract development environment for the Ethereum blockchain.

So what's the verdict?

Blockchain is extremely demanding on programming languages. To create a truly high-quality blockchain, you must be sure that you are using secure, scalable, and at the same time reliable technology that can withstand heavy loads. Python meets these requirements in many ways, and the Python community is actively developing the blockchain direction. The fact that this programming language is now on the rise in popularity also contributes to its choice for the development of blockchain solutions. If we are talking about a universal programming language that can be used to work with multiple platforms, then Python is the best option.