Is Python easy to learn?

Python is considered one of the easiest programming languages to learn because of its simple and readable syntax. To many, Python reads a lot like the English language, greatly reducing the cognitive load involved with understanding other people's code. Unlike other languages, Python code requires fewer lines, making it a great choice for beginners. Many universities and coding bootcamps use Python as an introduction to programming because of its logical structure and extensive documentation. But in the end, it's also important to mention that "easy" is relative, and everyone learns in their own way, and what might be considered simple or easy for the majority of developers doesn't automatically make it easy for the rest. If you still have doubts about what it takes to learn Python? We have covered this question in detail in our guide [Is Python Hard to Learn?](https://roadmap.sh/python/is-python-hard-to-learn)

Why do beginners use Python?

Beginners choose Python because, generally speaking, it tends to be easier to read, write, and understand than many other programming languages. Python removes the need for complex syntax rules found in languages like C++ or Java (like the use of squirrely braces, or "&&" and "||" to represent a logical AND or a logical OR operator), allowing developers to focus on solving problems rather than debugging syntax errors. On top of that, Python has a vast ecosystem of libraries and frameworks that simplify tasks in web development, data science, and automation, making it very "beginner-friendly" from that POV. Finally, the very active and large community around the language (which helps answer questions and provide learning resources to newcomers) is a very appealing characteristic that attracts beginners to Python.

Is Python easier than C++?

Python is easier than C++ because of its simplified syntax and dynamic typing, making it a more appealing option for new developers. Looking at both languages, C++ can be considered to be "lower level" when compared to Python because the former provides an interface that is closer to the actual hardware than the API provided by Python. A classic example that shows how C++ is closer to the machine is the language requiring manual memory management. That allows developers to directly interact with hardware components by letting them fine-tune CPU records and more. On the other hand, Python handles memory allocation automatically and has a more flexible approach to programming. This higher level of abstraction is what allows Python developers to focus on building software rather than on learning how the machine works so they can build the software on top of it. Of course, there are downsides to this approach as well, but when considering ease of adoption, especially for new developers, abstraction helps keep problems at bay.

How is Python different from Java?

Python is different from Java in many ways. Looking at the syntax alone, Python has a simpler syntax and is dynamically typed, whereas Java is more verbose (and much more similar to that of C or C++) and statically typed. In terms of execution, Java requires its code to be compiled so it can be executed inside its virtual machine (known as JVM or Java Virtual Machine), while Python is interpreted, which makes Python a more flexible but often slower option. Finally, when considering the best use cases for each language, Python is widely used in data science, automation, and backend development, while Java is more common in enterprise applications, Android development, and large-scale system architectures. In the end, there is no best choice between both languages, it's all about your use case and project needs.

How long does it take to learn Python?

The time it takes to learn Python depends on several things, including your past programming experience, how much you want to learn about the language, and the field in which you want to use Python. Generally, most developers going through the learning process can pick up basic Python skills in a few weeks, while mastering the language for professional development could take several months or even years. If, on the other hand, you have no prior experience with programming, it can take somewhere between 6 to 8 weeks to learn the basics of Python and programming, as long as you keep the learning consistent. Finally, if you're hoping to work as a Python developer, chances are you'll need 6 months to a year of consistent learning and practice on top of having all the programming basics covered.

How do I prepare for a Python interview?

If you’re looking to prepare for a Python interview, make sure you’ve tackled the fundamentals of the language, including data types and structures, control flow statements, functions, classes, and so on. You may be asked for technical questions during the interview. To get hands-on Python experience, you should check technical tutorials and work on your own Python project. To get an idea of the types of questions you may be asked during the interview, we recommend that you read our dedicated guide with the [Top 20 Python Interview Questions and Answers.](https://roadmap.sh/questions/python)

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Python Developer

Step by step guide to becoming a Python developer in 2025

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What is a Python developer?

A Python developer is a software developer tasked with building web services, automating tasks, performing data analysis, and everything in between using Python.

In terms of responsibilities, they will vary based on their project, company, and seniority. However, they usually include writing efficient code, managing data structures (especially when doing data science with Python), optimizing algorithms, and working with frameworks such as Pandas, TensorFlow, Django, and others.

How to become a Python developer?

To become a Python developer, the first step is learning the basics of Python, including data types, functions, and object-oriented programming (you can get away without learning OOP as well since Python allows for a hybrid programming model).

Understanding how to work with Python libraries like NumPy, Pandas, and Requests is also essential. Since Python can be used in many different ways, picking the right library and framework to focus on depends on you and your intentions with the language.

Beyond coding skills, to become a great Python developer, you should also spend some time looking into data structures like linked lists, trees, and hash maps. While they're not critical to building applications, they're great tools to show you how to solve problems in different ways.

Python developers should also learn about version control systems like Git, and completing projects that involve APIs, automation, or data processing helps in building a strong portfolio. One way to do this is by contributing to open-source projects to get hands-on experience and improve your problem-solving skills.

Is Python a frontend or backend language?

Python is a backend language, as the only language natively supported by browsers is JavaScript. On the backend, it is used to build the server-side logic that handles data processing, authentication, and even database management.

While it can be used on the frontend through the addition of extra libraries such as PyScript, this is not a normal practice as it adds dependencies and extra logic to already complex applications.

In web development, Python is often used alongside Django or Flask to build robust backend services. It is also used for API development, data processing, and automation.

What is Python used for?

Python is used for many different things and across multiple domains, given how versatile it is.

In web development, for example, Python can be used with frameworks like Django and Flask to help developers create scalable applications. In data science, it is the de facto language for data analysis, machine learning, and artificial intelligence (thanks to libraries like Pandas, NumPy, and TensorFlow).

In the field of automation, this language is also very popular, allowing developers to streamline repetitive tasks through Python code.

Finally, even though it's not as popular in these industries, Python can be used in cybersecurity, embedded systems, and even game development. Many companies use Python for cloud computing and backend services because of its simplicity and extensive support for integration with external systems.

Frequently Asked Questions

The skills that a Python developer needs are highly dependent on the industry they'd like to focus on.

For example, developers interested in backend web development should be familiar with web frameworks such as Django and Flask. They should also spend some time learning about RESTful design, API management, system architecture, and most likely, some SQL for database querying.

On the other hand, for a Python developer who's more interested in data science (also known as a data scientist), expertise in NumPy, Pandas, and machine learning tools becomes necessary.

If automation is their focus, developers should look into IaC (Infrastructure as Code) tools and configuration management and delve a bit deeper into cloud platforms and deployment strategies.

Universally speaking (now outside the domains of Python alone), writing efficient and clean code along with strong problem-solving skills are essential for any development-related role. And you can boost that up with knowledge of data structures and algorithms and understanding object-oriented programming (or functional programming) to top it all up.