It is actually much easier to answer the opposite question – what is Python not used for? Well, it’s not the best pick for mobile development or applications with huge memory consumption. Neither of these options is entirely off the table for Python, but many other technologies are better suited for the job. Other than that, Python can easily be considered a go-to language for numerous and diverse business purposes:
- Web Development
- Data Science and Data Analytics
- Data Visualization
- Natural Language Processing
- Artificial Intelligence and Machine Learning
- Financial Analysis
- Fintech Platforms
- Blockchain Technology Development
- Internet of Things (IoT)
Developers value Python language for its unmatched versatility. In web development, Python can be employed for both front-end and back-end development services. No general-purpose programming language excels at everything, of course, but Python ranks very close to perfection in that regard.
Python isn’t difficult to learn – that’s a known fact. It has a readable and simple syntax that is easy to grasp, even for people without coding experience. But the low entry threshold mustn’t be considered the sole reason for Python’s status as the most popular language in the software development world. Python code comprises features that make it an excellent choice for any business today and for years to come.
Whatever your next project requirements are, chances are Python has you covered. This high-level programming language can be successfully utilized for almost every business case. Python offers unmatched applicability to various business and data science scenarios thanks to its numerous open-source libraries, frameworks, and modules available with a simple line of code. Furthermore, it is highly scalable and can be used for medium- and large-sized projects.
The efficient task automation capability is one of Python’s strongest suits. Python comes packed with libraries and modules that can help you accomplish any imaginable automation goal – from Excel file creation and web scraping to data analysis and operating system administration – you name it. It is also often considered a primary language for software testers, as it allows for the rapid and efficient development of automated test scripts for applications. There’s no automation task too complex or too heavy for Python.
For many data scientists and data analysts, picking Python over other languages is virtually a no-brainer. With a vast selection of data science libraries and frameworks, such as NumPy, pandas, TensorFlow, SciPy, or Matplotlib, Python established itself as the most popular programming language for data analysis and visualization purposes. It is worth noting that some data science frameworks support other languages, but none can match Python in terms of sheer productivity and flexibility.
With simplicity often comes efficiency. Python is not a complicated language, making it an excellent choice for projects where app development time is of the essence. Its readable and dynamically typed code allows developers to focus on the program’s functionality and new features rather than its cryptic meaning. Furthermore, any given Python script is usually shorter and less time-consuming to write when compared to other languages. Less coding means fewer mistakes and faster product deployment.
Python is sometimes described as a “glue language“, meaning it can functionally connect applications coded in different technologies. It uses REST API or Foreign Function Interface (FFI) to make them talk to each other directly. One of the biggest advantages of Python’s integration capabilities is that it allows different teams to work on the same project while using their own set of languages and technologies. And the effects can then be neatly “glued” together with Python.
In terms of scale, the Python community is considered one of the biggest. Suffice it to say that no other programming language tutorials are searched on Google as often as Python’s. Many expert programmers contribute their time and effort to develop this open-source code further and help fellow Pythonistas. Unrestricted access to the knowledge base and a helpful attitude in a vibrant community with such a large user base is practically a given.
Code’s simplicity, readability, and conciseness play a significant role when discussing the cost-effectiveness of a software project. Compared to other programming languages (e.g., Java), Python offers a much more streamlined and time-effective development process. With Python, it is easier to read (and comprehend) someone else’s scripts, explain your code to others, or find bugs. Coding in Python is faster, so fewer working hours are needed to get the job done. And the same applies to the maintenance stage once the product is released.
Now that we’ve learned about the main benefits of Python business and data science applications, it’s time to check some real-life use cases. We already know that Python can be used for widely different software projects. But the sheer scale of Python’s applicability and flexibility is nothing short of impressive.
With its ability to process giant datasets with machine learning algorithms and a rich ecosystem of libraries and data analytics tools, Python makes an excellent choice for banks and Fintech companies. Venmo, a massively popular US social payment app, has been built with Python. Another example of a Python-based finance solution is Stripe, a global platform for processing online payments. Python is also widely used for building data mining and blockchain solutions.
The significance of using Python-driven Artificial Intelligence in healthcare has grown exponentially in recent years. For example, healthcare professionals now use machine learning for image analysis of x-rays, Computed Tomography (CT), and Magnetic Resonance Imaging (MRI) scans. During the pandemic, Python’s scientific computing capabilities were used for the analysis and classification of COVID-19 pneumonia detection. Python is also commonly utilized for analyzing data in drug discovery research and disease prediction projects.
Machine learning and data science play a pivotal role in the manufacturing industry nowadays. Examples of implementing Python code in manufacturing companies’ day-to-day operations are aplenty:
- predictive maintenance and predictive quality
- safety and warranty analytics
- plant facilities monitoring
- 3D vision inspection for safety and quality control
- sales and KPI forecasting
- and many more
With Python’s knack for task automation and versatility, no wonder it’s the programming language of choice for many manufacturing businesses.
“Ok Google, find me the nearest gas station” – search engines, smart assistants, and voice bots utilize Python-powered natural language processing to make our lives easier. Google Assistant and Apple’s Siri are prime examples of Python’s contribution to the rapid development of natural language processing technology.
In web development, open-source Python gained a firm footing thanks to its competent web frameworks and libraries like Django or Flask. Quora, the popular global platform for sharing knowledge, is built with Python. Facebook, Instagram, Pinterest, and Reddit also utilize Python programs to varying degrees.
Global streaming services, like Netflix, use Python libraries primarily for data analysis and server-side services. Spotify also utilizes Python frameworks to drive playlist discovery and smart radio channels. Google’s YouTube makes use of the language for the integration of streaming videos into their internet pages. Python also has its role in game development. Creators of EVE Online, a wildly popular MMO set in space, incorporated Python into the game’s codebase for, e.g., handling user interface and management of graphic libraries. Python is usually not the first choice for game development companies, but they often use it to implement AI and machine learning features into their products.
Why do companies outsource their Python development services? The most obvious answer is – because it’s cheaper. And while cost-effectiveness is always of utmost importance, it’s neither a whole nor only factor making development outsourcing a sensible choice.
Every business today primarily looks for value, whether a startup or an established corporation. Finding a contractor overseas, where labor costs are relatively lower, is often the only way to keep the project’s profitability within desired margins. But it’s not only about the developers’ wages. Overhead expenses, like employment fees (health insurance, taxes, etc.) and office expenditures, can quickly stack up to the point where having the in-house Python development team becomes a liability from a financial perspective.
Due to its relative simplicity and flexibility, Python is one of the best programming languages to use when fast project completion is at stake. Outsourcing the development process to a team of Python experts versed in the Agile approach guarantees that the expected time to market will be as short as possible. And finding an equally skilled team to work in-house is not always feasible or financially viable for the reasons we’ve mentioned earlier.
Outsourcing development services allow companies to focus steadily on what they do best – their core business operations. All the issues pertaining to team management, recruitment, or administration are not a concern, as these aspects are handled solely by the contractor.
By outsourcing your project to a firm skilled in Python development, you can be sure it will be built with all the latest tools and technologies available. It’s only natural for such a company to keep pace with technological progress to maintain a competitive edge in the market. This is vital, especially for Python, as its library of modules, frameworks, and machine-learning applications grows rapidly every day.
This is another advantage directly linked with a high level of expertise held by a trusted Python software partner. Experienced development companies keep established procedures in place for identifying, monitoring, and minimizing potential risks to the project. Comprehensive and efficient quality control is also guaranteed as a fundamental part of the development process.
Even though the benefits of outsourcing Python development services are many, finding the right software partner can be challenging. To avoid the common pitfalls of the vetting process, make sure to follow the checklist below:
- Understand and define what you’re looking for – create a comprehensive list of your project’s requirements to ensure the company you’re considering has the proper skill set and resources.
- Check the portfolio and study the customer’s reviews – you don’t want to entrust the fate of your important project to a company that has just started to use Python.
- Test their knowledge – there’s nothing wrong with asking the developers about their experience with the most recent features or frameworks. It will give you valuable insight into the range of technologies they’re most adept at.
- Consider their approach – if you expect the developers to come up with their suggestions for new features or functionalities, discuss this before making any commitments. Some development teams are superb at translating clients’ visions into code but are not too keen on coming up with their own ideas.
- Ascertain the communication style – whether you expect frequent updates on the progress or only want to hear about completed milestones, make sure it’s discussed and agreed upon beforehand. Ineffective communication can make even the simplest of projects challenging.
- Focus on value, not the price – albeit price is always deemed a vital factor, often “cheaper” means “more expensive” at the end of the day. Read the fine print, determine the level of support after the building stage (when applicable), and consider all development and maintenance costs to figure out the actual value of the partnership.
The good news is that with Scalo software development company, you can rest assured that you’re getting real value. We are always happy to provide our potential partners with clear and comprehensive information about what can be expected of us and what we can do to make the cooperation as efficient as possible.
With its wide range of applications, unmatched flexibility, and robustness, Python is the general-purpose programming language of today and tomorrow. The importance of Python programming for global business cannot be understated. And that is why at Scalo, we feel incredibly fortunate to have the opportunity to develop high-value services for our partners and use Python every day.