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Whether a difference list is more efficient than other list representations depends on usage patterns. If an algorithm builds a list by concatenating smaller lists, which are themselves built by concatenating still smaller lists, then the usage of difference lists can improve performance by effectively "flattening" the list building computations.
Statement separator – demarcates the boundary between two statements; need needed for the last statement; Line continuation – escapes a newline to continue a statement on the next line; Some languages define a special character as a terminator while some, called line-oriented, rely on the newline.
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[52] [53] While Python 2.7 and older versions are officially unsupported, a different unofficial Python implementation, PyPy, continues to support Python 2, i.e. "2.7.18+" (plus 3.10), with the plus meaning (at least some) "backported security updates". [54] Python 3.0 was released on 3 December 2008, with some new semantics and changed syntax.
Python: Application, general, web, scripting, artificial intelligence, scientific computing Yes Yes Yes Yes Yes Yes Aspect-oriented De facto standard via Python Enhancement Proposals (PEPs) R: Application, statistics Yes Yes Yes Yes No Yes No Racket: Education, general, scripting Yes Yes Yes Yes No Yes Modular, logic, meta No Raku
Displaying the differences between two or more sets of data, file comparison tools can make computing simpler, and more efficient by focusing on new data and ignoring what did not change. Generically known as a diff [ 18 ] after the Unix diff utility , there are a range of ways to compare data sources and display the results.
Displaying the differences between two or more sets of data, file comparison tools can make computing simpler, and more efficient by focusing on new data and ignoring what did not change. Generically known as a diff [ 1 ] after the Unix diff utility , there are a range of ways to compare data sources and display the results.
Introduced in Python 2.2 as an optional feature and finalized in version 2.3, generators are Python's mechanism for lazy evaluation of a function that would otherwise return a space-prohibitive or computationally intensive list. This is an example to lazily generate the prime numbers: