The First version of Django was released in 2005. It is implemented in Python, still on the market, and still gaining more and more users every year. The framework follows the Zen of Python and describes itself as “the web framework for perfectionists with deadlines”. It’s true: in each aspect it tries to help developers and encourages them not to invent the wheel all over again. It’s open source and has a huge, ready-to-help community.

Creating a digital product may require integrating it with third-party companies and products (for example PayPal or Dotpay) as well as a variety of different systems, technologies, and existing databases. Is Python easy to integrate? How to leverage the power of Python when it comes to the integration process? Read a  guide for entrepreneurs and product owners. 

Common in applications that range from risk management to cryptocurrencies, Python has become one of the most popular programming languages for Fintech Companies. Its simplicity and robust modeling capabilities make it an excellent tool for researchers, analysts, and traders.

Stanisław Zalewski is a Senior Python Developer, responsible for building high quality Python applications that meet clients’ needs, supporting colleagues with his knowledge and experience, and helping with recruitment to the Python team. He feels right at home here and works towards a promotion to the leader position. He didn’t join Netguru the usual way, but through a merger between Netguru and Bitcraft, Stanisław’s previous company. According to him, the change was fast and smooth, and he’s happy to be where he is today.

Startups planning a product development process need to consider many factors when it comes to picking the right programming language. Often working on a tight budget, startups must carefully consider: the speed of development, the popularity of language, the cost of developers, libraries, integrations, security, scalability, and stability. It is for these reasons that your best bet will be to go for a robust and established technology such as Python. 

The Python programming language is one of the most popular technologies among developers, the second most loved and the first most wanted. Why? Because it fits modern software development perfectly. In this article, I'll tell you all you need to know about Python.

How to choose the best technology for creating a CMS? We will help you decide which factors you should consider before making a decision and we'll analyze if Python is a good option as a programming language.

Python and Ruby are two established and widely used programming languages for developing websites and web apps. Both technologies can be used to build and manage sites and applications of any complexity and functionality. YouTube and Google were both built using Python – pretty impressive, right? But some other awesome sites were built with Ruby such as Twitter, Groupon, GitHub and Hulu.  In this article we help you decide what will be best for you.

According to the Bureau of Labor Statistics, the projected employment of software developers is over 4 times bigger than that of other occupations. In the current talent shortage scenario, companies are doing their best to attract and retain software developers. What does this mean for you, the candidate?

Building a fintech product is no easy task – but the reward is also significant. Successful fintech companies such as Revolut, Stripe or Coinbase, reach multi-billion-dollar valuations and enjoy global customer recognition. However, in order for your business to become the next fintech unicorn, you first need to build a modern, reliable, and fully featured application.

Python is one of the hottest languages on the tech scene right now. Why? Well, it’s easy to learn, code in, and apply to different problems. No wonder that developers and businesses alike love it. At the same time, a technological breakthrough is changing the world of software and business – the ability to process huge amounts of data and glean useful insights from it. What do Python and big data have to do with each other? Well, the former happens to be the perfect tool to process the latter. How so? Read on to find out!

Organizations that want to thrive on the current market need to ride the wave of digital transformation. Smart enterprises are now investing in enterprise application development services for boosting their financial operations, improving their employees’ productivity, and managing their resources with top efficiency in mind. When it comes to bespoke software development, Python is one of the top technologies in the field.

Python has been growing rapidly in comparison to other programming languages. There are a few reasons behind it – it’s fast, secure, battle-tested by top tech players and, more importantly, it’s getting more and more attention in the data science world. At Netguru, one of our core values is innovation. We want to work with the most effective solutions that match our clients’ needs. That’s why we couldn’t ignore the power of Python.

Python is one of the best and most popular programming languages on the technology market. Thanks to its power and versatility, it can be used for a range of applications – from simple scripts, to data analysis, to machine learning (ML). Which is why in 2018, we decided to include both Python and ML in our core tech stack at Netguru. During this intense year, we have grown our Python team to 11 experienced developers and built a number of applications using the language. Some examples include:

In order to create easily maintainable websites, a lot of companies decide to use content management systems (CMS). This way a lot of features like adding content, authorizing, and administration can be easily taken care of without a lot of programming knowledge. There are a lot of CMSs and they vary a lot, but most of them share the same idea of giving the user the ability to manage his website the easiest way possible. The most popular CMSs are created in PHP and one of them is Drupal, the third-most popular system. It is mostly used to create knowledge bases and business blogs. However, if we look at the recent popularity of programming languages, we can easily notice that Python is gaining more and more popularity and PHP is going the other way. In this case, we will take a look at three Python-based CMSs and compare them with Drupal and see what comes of it.

Python frameworks can be divided into a few areas as Python is a very diverse language and can be used in various fields. Each of these fields has its own frameworks, some of which are more popular than others. One of the most popular fields Python is applied in is web development, which we will focus on today.

In the world of app development, performance optimization is a never-ending, yet necessary, job. One that can be fairly rewarding - and not only in terms of developers’ personal satisfaction... First and foremost, better performance very often leads to higher conversion and user retention rates, which is directly connected with profit gains.

With artificial intelligence becoming smarter and smarter, the interest in NLP (natural language processing) has also been growing rapidly. Utilizing and developing the technology that helps machines understand and process human language has become a hot topic in many industries, because it has the potential to finally fill the gap in human-computer interactions.

Fintech continues to be one of the most exciting sectors for growth and innovation. However, when it comes to software development, due to the complexity of building robust and secure applications that are compliant with stringent financial industry regulations yet still provide a seamless, highly functional, and beautiful user experience, it’s crucial that the right tools are used for the job.

"The fastest-growing use of Python is for data science, machine learning, and academic research" - says a StackOverflow analysis. These are actually the biggest trends in tech recently. As we can read, "Python became a common choice for that purpose". Why did people fall in love with this general purpose programming language for research and data science? Well, there are many reasons.