Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level inbuilt data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, also as to be used as a scripting or glue language to attach existing components together. Python's simple, easy to find out syntax emphasizes readability and thus reduces the value of program maintenance. Python supports modules and packages, which inspires program modularity and code reuse. The Python interpreter and therefore the extensive standard library are available in source or binary form for free of charge for all major platforms, and may be freely distributed.

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Often, programmers fall crazy with Python due to the increased productivity it provides. Since there's no compilation step, the edit-test-debug cycle is incredibly fast. Debugging Python programs is easy: a bug or bad input will never cause a segmentation fault. Instead, when the interpreter discovers a mistake, it raises an exception. When the program doesn't catch the exception, the interpreter prints a stack trace. A source level debugger allows inspection of local and global variables, evaluation of arbitrary expressions, setting breakpoints, stepping through the code a line at a time, and so on. The debugger is written in Python itself, testifying to Python's introspective power. On the opposite hand, often the quickest thanks to debug a program is to feature a couple of print statements to the source:

Python programs are generally expected to run slower than Java programs, but they also take much less time to develop. Python programs are typically 3-5 times shorter than equivalent Java programs. This difference are often attributed to Python's built-in high-level data types and its dynamic typing. for instance, a Python programmer wastes no time declaring the kinds of arguments or variables, and Python's powerful polymorphic list and dictionary types, that rich syntactic support is made straight into the language, find a use in almost every Python program. due to the run-time typing, Python's run time must work harder than Java's. for instance, when evaluating the expression a + b, it must first inspect the objects a and b to seek out out their type, which isn't known at compile time. It then invokes the acceptable addition operation, which can be an overloaded user-defined method. Java, on the opposite hand, can perform an efficient integer or floating point addition, but requires variable declarations for a and b, and doesn't allow overloading of the + operator for instances of user-defined classes.

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For these reasons, Python is far better suited as a "glue" language, while Java is best characterized as a low-level implementation language. In fact, the 2 together make a superb combination. Components are often developed in Java and combined to make applications in Python; Python also can be wont to prototype components until their design are often "hardened" during a Java implementation. To support this sort of development, a Python implementation written in Java is under development, which allows calling Python code from Java and the other way around. during this implementation, Python ASCII text file is translated to Java bytecode (with help from a run-time library to support Python's dynamic semantics).