The Julia programming language can be considered the successor to Scientific Python (SciPy). The language is designed for scientific computing by having built-in multi-dimensional arrays and parallel processing features. Yet, it can also be used as a general-purpose programming language like Python. Unlike Python, Julia solves the two-language problem by using just-in-time (JIT) compilation to generate machine code from high level expressions. In most cases, Julia is as fast as C, and in some cases faster. Julia is also a composable language, so independent libraries or packages usually work well together without any modification. These important features make Julia a very productive language for scientific software development by reducing the number of lines of code.