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Published: 20/12/2022

Python: a quick and effective programming language for businesses

Since the rise of the first programming language, software and web development have grown and evolved significantly. Programming languages are used widely in several aspects of life, business, and society. Programming is at the heart of technological advancement, from data science through game development to data visualization and machine learning. One of the most popular programming languages is Python. Its popularity can be justified by different aspects, like its versatility and approachability. Python programming language is among those that are easy to learn. Discover how Python can be the right programming language for various business purposes.

What is Python? A powerful programming language

Python is a script, open-source programming language created by Guido van Rossum in the late 1980s. It’s a high-level programming language. It’s an open-source, dynamically typed, garbage-collected programming language that supports multiple programming paradigms. These include structured (mainly procedural), object-oriented and functional programming. Other paradigms can receive support via extensions, including design by contract and logic programming. Python interpreter then runs the written program.

Open source means the code can be freely inspected, modified, and enhanced, thus creating new language use. At the same time, the garbage collecting function automatically frees up the memory space allocated to objects no longer needed by the program. It ensures that a program does not exceed its memory quota or reach a point where it can no longer function.

Since its humble beginnings, Python has developed rapidly and features many improvements, making it one of the most popular startup programming languages. Python programming is helpful in different business and development sectors, including machine learning, data analysis, artificial intelligence, data science, and more.

Python programming is making its mark on emerging tech and machine learning development, as it can address big data collection, processing, and visualization needs. It can help collect a large amount of data for machine learning purposes and analyze data. Since it’s one of the most versatile programming languages, it can find several applications in business.

Python is a popular programming language also because it’s a language that is easy to learn, thus making it one of the most common choices among beginner programmers.

Never programmed before? Worry not! Python is easy to learn

A significant part of the popularity of Python programming language is that programmers can quickly learn it from scratch. Not all programming languages can offer a comparable level of complexity without making it overly complicated. While other programming languages often involve complex language syntax or many lines of code written, Python offers syntax similar to everyday English. Therefore, the commands can be easier to understand and remember.

Developer communities also contribute to making learning this programming language more accessible and approachable. On the official website, even a stranger to programming and software development can find many learning resources and downloadable items like libraries or source code. At the same time, the active community provides additional help to kick off the development process. Numerous other resources and repositories for learning Python across the Internet exist.

Since developers can apply Python to major systems like Windows, macOS or Android, this general-purpose language has its ever-growing community that keeps extending the boundaries of using Python for business.

As mentioned earlier, Python is a great language, and beginners learn Python to have more considerable versatility with their projects. As it’s not a complicated language with fewer lines of code, programmers can utilize it for data science and web applications (for which the Django framework can be advantageous).

Our developers also consider Python a valuable and easy-to-learn language for various purposes. Here are some key reasons:

  • Low entry threshold: it’s easy to start learning Python due to its simple syntax and vast community of developers. Learners can find many tutorials and courses they can explore further with Python communities.
  • Clean and understandable syntax: syntax is easy to understand and write; thus, compared to other languages, programming in Python can be less taxing and result in shorter code.
  • Available resources: there’s a wide range of resources and pre-made libraries, up to ready environments (for example, a multipurpose environment Conda that can also work with other programming languages). Python learners and developers can easily find code fragments or libraries useful for their projects (for example, creating image collages).
  • Great potential for testing ideas and theories: it can be an ideal tool to quickly write and test ideas to see if they can work in further development due to its scrip nature and potential in coding quickly. Python can be helpful when creating an MVP.

As general advice for beginner Python developers, the key conclusion to be drawn from this is to make the most of the wide range of available resources and pre-made elements to learn and develop their solutions.

Python is easy to learn

How is Python used in business?


Python is great for performing a wide range of calculations. Python can make a formidable competition for complex and expensive mathematical environments, from creating simple calculators to more complex math operations, like functions and trigonometric values.

Calculations are one of the essential parts of Python, and they can find their application in scientific computing, science projects, financial applications, data science and more. It can find its place in working with statistics, finances, astronomy, etc. Calculations lie at the core of the use of Python.


Due to its scripting nature, Python can be ideal for automating repetitive tasks. It can save a lot of tedious manual work. Since it’s a cross-platform language with a wide range of pre-existing libraries, creating a script to run some tasks repeatedly is relatively easy.

Since Python has a simple syntax and a wide range of resources, creating a script to automate a tedious task doesn’t require much work and can take some work off human shoulders. It can make an ideal solution for some simple tasks like sending out automated emails, performing quick math equations, converting image files (for example, with the use of the Pillow module), calculating exchange rates (best with the Forex Python module) and scraping data from web pages and then saving it on a hard drive (with the use of BeautifulSoup library).

Selenium with Python can be ideal for automating tests carried out in web browsers. These, in turn, can test websites for bugs, site crashes, and similar issues. It can save you from being in the dark about the website going offline.

Data science and data visualization

Python gained recognition as one of data scientists’ most popular languages. Thanks to its commonly available packages and libraries and the simple, readable syntax, Python can cover most of the tasks required in data science and data analysis.

The key reasons behind the popularity of Python in that field are that this programming language is accessible, easier to learn than other languages, and can handle many tasks. It is also helpful because it is a well-supported language. There are pre-existing data manipulation libraries and fragments of code for many tasks that can save development hours.

Built-in data analytics tools allow Python to process complex data. It can also penetrate patterns, correlate information in extensive sets, and provide better insights and other critical matrices in evaluating performance.

Python also has an extensive base of libraries that anyone can use for data visualisation. Thus, it can help present data and the results of its manipulation in a clean, coherent way, whether allowing the delivery and presentation to a client or a manager.

Web development

Python, used for web development, usually involves developing the backend of a website or application. It can include sending data to and from servers, processing data and communicating with databases, URL routing, and ensuring security. Python offers some frameworks for network programming and web application development. However, the most notable one is the Django framework.

Game development

Python can be used to develop games with 3D graphics, as it comes with a built-in game dev library, “pygame”. Game developers can use this language for creating functionalities and add-ons in larger games as one of many tools.

This multipurpose language boasts flexible object orientation that works by assigning attributes or features (properties) to a class or type of object. Any other categories derived from them can then inherit these functions. It allows programmers to create new or modify already existing objects easily. And dynamic typing makes Python ideal for faster prototyping and testing. Thus making Python lucrative for game development.

Machine learning and Artificial Intelligence

These two areas of use hit particularly close to home for our developers, as it’s one of many areas of expertise in

Machine learning and artificial intelligence are at the heart of driving innovation and developing emerging technologies. Python suits these purposes because of its approachability, low learning curve and huge developers’ community and support. Thanks to its flexibility, startups use Python in earlier stages of development for testing their ideas.

Python’s ability to analyse big data and find patterns, trends and associations makes it helpful for machine learning and artificial intelligence. The larger the data set, the better chance for the learning algorithms to process the data and provide the results quicker. Many libraries are also already available, like NumPy, SciPy and Scikit-learn.

Python in machine learning

Embedded systems

This use of Python is also highly valued by our developers. External programs can quickly test embedded systems. For example, an embedded system can be connected to a computer with a different operating system and write a program in Python to interact with that system for a range of purposes, including testing, control and extraction of the parameters.

In embedded systems, developers face multidimensional problems combining mathematics and physics, like models or abstract occurrences. It might be hard to run a testing environment on the embedded system. Thus, writing an algorithm on a separate device can simulate the algorithm on the embedded system.

See how we applied Python in a ball trajectory-tracking app.

View the case study


Due to its script nature and relatively slow operation, Python might not be an ideal target language for software. However, a development team can use Python for testing. And that covers some already developed functions and trying out new ideas, processes or algorithms.

Python development is ideal for this, as it is easy to learn, has a simple syntax, and an active community that already provides many libraries and other helpful resources. Its open-source nature also allows starting quickly without investing money in complex programs or environments. Thus, when the idea is not yet wholly feasible, Python may be a cheap solution for testing it.

Python programming language for business: pros and cons

As we already established, businesses can use Python for various applications. However, like any other programming language, businesses Python has its assets and drawbacks. Python developers discuss a range of universal pros and cons of Python language. Still, a liability for one can mean an advantage for another type of business. We will look at various aspects of the Python language that need consideration when choosing it.

Python is a beginner-friendly language

As stated earlier, Python has a simple syntax, compared to other languages, that is easy to learn, which makes it so popular. Writing code in Python can be faster and easier in comparison. A lower learning curve makes it one of the best startup programming languages. It can be a significant company asset, as many adepts learn Python. On the other hand, many potential developers might make it hard to find the right candidate for the business needs—especially when dealing with more complex designs.

Python has a large community

The approachability and low learning curve help build a large community of coders, developers, students, software engineers and professionals. The combined effort resulted in building a base of libraries and powerful packages intended for different purposes, including documentation generation, regular expressions, web browsers, unit-testing, web applications, CGI and more. Consequently, the developers can save time they’d need to write the code from scratch.

Python is flexible, extensible, embeddable and highly scalable

Users can extend Python to other languages, including C and C++. They can write and build new features in this dynamically typed language. It also allows for adding scripting capabilities to the code in another language.

Python code is also scalable. Some prominent examples to prove this are Instagram, Facebook, and Pinterest. All of them use versatile Python in their web development endeavours.

Python in embedded systems

Python is a dynamically typed and interpreted language

Although developers can use this versatile language on most major platforms, it requires significant computational power. Thus, it runs visibly slower compared to compilable languages. This programming language might not be ideal for rapid application development when the project is tight on the clock. However, this general-purpose programming language might be preferred if the project is not on a tight deadline. Being script language, it may require more power and resources to run. Thus, it may not be a target programming language on small battery-powered devices.

Python is a portable language

Developers can run this multipurpose language on different platforms and major operating systems. Among other programming languages (like Java), Python is a WORA (Write Once, Run Anywhere) language. It makes it a great programming language for designing software on multiple platforms.

Python’s security may need extra attention

Programming in Python requires extra steps to ensure the code is secure. This drawback, however, can be fixed by performing thorough QA tests.

Python’s memory consumption, garbage collection, and multithreading may cause concern

Python development requires considering some things. It comes with high memory consumption, which needs to be carefully addressed by the development team. Its garbage collection employs reference counting, which may result in memory losses. Thus, it may make it inefficient on small, battery-powered devices, requiring resources that might turn out too draining.

How can you make your business grow with Python?

Tabular data is one of the most popular data types used in a business. It includes order records, personnel information, sales contracts, and more, such as structural data. Python is one of the most popular languages for handling tabular data, requiring fewer lines of code written for basic operations or accessing Excel files with gathered records. Thus, it can be considered one of the top programming languages for analyzing data.

Since the language places itself near the top of popularity rankings, many beginners and advanced developers on the market use Python in their everyday work. Many users may make finding the required talent for the business easier.

Python is a versatile programming language that allows for speedy business app development. It can be advantageous for creating an MVP to release for the market-fit review and testing by the project’s audience. It can also help to acquire revenue for the future development process while the product is already live.

Another argument for using it for business is that it has an extensive and mature community that keeps improving and creating new libraries and functions. In turn, it might help to speed up the development. Thus, a startup can have a working product significantly faster, saving resources.

Grow with Python

Python vs other programming languages

Let’s have a quick look at Python in comparison to other languages. You can find more extensive insights on the official website, so we’ll highlight some key differences.

  • Python vs Java: Python programs run slower than those written in Java but take less time to develop. On average, Python programs are 3-5 times shorter than equivalent Java programs. However, developers can effectively combine these two languages, as the components can be developed in Java and combined to form applications in Python. Python can be helpful in prototyping components for their later implementation In Java.
  • Python vs JavaScript: both languages share the object-based subset and support a style that implements simple functions and variables without engaging in class definitions. That’s about what JavaScript can do, while Python can help write more extensive programs and better code reuse through a true object-oriented programming style.
  • Python vs Perl: these two languages share a similar background (Unix scripting, which both have long outgrown). Similar features of both come with a different philosophy in mind. Perl focuses on everyday application-oriented tasks like built-in regular expressions, file scanning, and report-generating features. On the other hand, Python is oriented on standard programming methodologies such as data structure design and object-oriented programming, encouraging users to write readable (and thus maintainable) code by providing an elegant but not overly cryptic notation.
  • Python vs Tcl: both are usable as an application extension language and a stand-alone programming language. Tcl, however, shows a particular weakness in data structures, as it traditionally stores the data as strings. It also takes longer to execute typical code in comparison.
  • Python vs C++: the first of these two languages can take 5-10 times longer to develop an app or a program. Python can act as a glue language to combine components written in C++. Therefore, the two of them can neatly work together.
  • Python vs R: R may be harder to learn than Python due to its more complex coding. Although Python seems to be used more by the general public, R can find its niche in the academia and research industry due to its prowess in data manipulation. Both languages offer thousands of ready packages and libraries. Those in R are more specialized and science-oriented than a mix-and-match provided by Python. Neither language is fast in comparison with, for example, C++.

The most recent developments

Here are some of the most important developments in Python this year:

  • PEP 703 and the Global Interpreter Lock (GIL): A significant step towards a version of Python without the GIL has been made with the acceptance of PEP 703. The GIL in Python ensures that only one thread accesses the interpreter at a time, making parallel processing more challenging. The removal of the GIL (a move towards “free-threading”) is expected to enhance Python’s performance in multi-threaded environments. This change will be implemented gradually and in phases to minimize disruption to the Python ecosystem.
  • Microsoft Excel Integration with Python: Microsoft has introduced an experimental Python code editor for Excel, developed as part of a partnership with Anaconda. This add-in provides advanced formula editing features like syntax highlighting, auto-completion, and inline error reporting. It is built on the Monaco Editor, a component of Visual Studio Code, allowing it to run in web browsers. This integration is particularly beneficial for data scientists, as it brings the power of Python to Excel for data manipulation and analysis.
  • Mojo Programming Language by Modular: a startup company, has released the Mojo Software Development Kit (SDK) for Linux. Mojo is a new programming language based on Python, designed to leverage modern multi-core hardware architectures for performance gains. It’s compatible with existing Python libraries and frameworks, making it an attractive option for AI and machine learning applications. Mojo aims to combine the ease of Python with the speed of compiled languages like C and C++.

See how Java compares to Kotlin to make the right choice for your project.

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Do you know how we can help your business with Python?

Our developers use Python in their everyday work to create great projects. The areas of work include mainly, but not exclusively, embedded systems, machine learning and AI, big data, and testing all new and good ideas. We have already created successful projects, and our customers are happy with the solutions.

Among others, we worked with Sports Computing on a solution allowing tracking the ball’s trajectory and speed while shooting on goal, thus improving the player’s accuracy. The project was a success, and the customer was satisfied. And for collecting the data for the project, our team also used Python as one of the critical technologies. Our team of experts delivered, as you can read in the following testimonial:

“Most important is that you cover our professional needs, which are extensive and different from more traditional projects. We couldn’t get an ideal partner with extraordinary skills within AI and application development.”

If you think you could use this language well in your projects and need experts to aid with that, you can reach out to us, and we’ll be happy to provide a free estimate for the development process.

Python - a universal business solution

Python for business purposes: A universal solution

Summing up, Python can make a highly versatile programming language. Its open-source nature and easy syntax combine well with a large, active community. The number of existing libraries and even entire environments makes it an easy language to start with and ideal for multiple and rapid developments or testing needs. Thus, it can be an ideal programming language for businesses with different experiences and backgrounds.

Don’t hesitate to contact us for more help and expertise; we will listen to your professional needs.

Get in touch to see how our solutions can address your needs.

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Katarzyna Świątek

Junior Content Specialist at


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