Java vs Python — What do developers do?

Skills Bootcamps candidates often ask us about the differences between Java and Python developers.

While specialists use their respective programming language to develop software applications, there are interesting differences.

Here's a quick look at what Java and Python developers do.

Java

Java is a popular and versatile language widely used in a variety of applications, including:

• web development
• mobile app development
• enterprise software development
• game development

Java developers are responsible for designing, developing, testing, and deploying software applications that meet the needs of businesses and users.

Common Java development tasks include:

• Designing, coding, testing, and deploying software applications using Java
• Using web frameworks such as Spring, Struts, and JavaServer Faces to build web applications and web services
• Working with databases such as MySQL, Oracle, and SQL Server to store and manage data for their applications
• Developing mobile applications for Android devices
• Using Java Enterprise Edition (Java EE) to develop enterprise applications that can run on large-scale systems
• Finding and fixing bugs in code and troubleshooting issues that arise during the development process
• Collaborating with other developers to create software applications
  
  

Python

Python is a high-level, interpreted language that is widely used in many areas, including:

• web development
• scientific computing
• data analysis
• Artificial Intelligence (AI)
• Machine Learning (ML)
• automation

Common Python development tasks include:

• Designing, coding, testing, and deploying software applications
• Building web applications and web services with web frameworks such as Django, Flask, Pyramid, and Bottle
• Working with databases such as MySQL, PostgreSQL, and MongoDB to store and manage data for their applications
• Using Python scripts to automate repetitive tasks, such as data entry, file processing, and system administration
• Using libraries such as NumPy, Pandas, and SciPy to analyse and manipulate data for scientific research, data analysis, and Machine Learning
• Using libraries such as TensorFlow, Keras, and Scikit-learn to build Machine Learning models for data analysis, prediction, and classification
• Finding and fixing bugs in code and troubleshooting issues that arise during the development process
• Collaborating with other developers to create software applications
  
  

Interested in Java or Python?

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