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Python uses the following syntax to express list comprehensions over finite lists: S = [ 2 * x for x in range ( 100 ) if x ** 2 > 3 ] A generator expression may be used in Python versions >= 2.4 which gives lazy evaluation over its input, and can be used with generators to iterate over 'infinite' input such as the count generator function which ...
Strings in Python are immutable, so a string operation such as a substitution of characters, that in other programming languages might alter the string in place, returns a new string in Python. Performance considerations sometimes push for using special techniques in programs that modify strings intensively, such as joining character arrays ...
Here, the list [0..] represents , x^2>3 represents the predicate, and 2*x represents the output expression.. List comprehensions give results in a defined order (unlike the members of sets); and list comprehensions may generate the members of a list in order, rather than produce the entirety of the list thus allowing, for example, the previous Haskell definition of the members of an infinite list.
Methods on objects are functions attached to the object's class; the syntax instance. method (argument) is, for normal methods and functions, syntactic sugar for Class. method (instance, argument). Python methods have an explicit self parameter to access instance data, in contrast to the implicit self (or this) in some other object-oriented ...
Lazy evaluation is difficult to combine with imperative features such as exception handling and input/output, because the order of operations becomes indeterminate. The opposite of lazy evaluation is eager evaluation, sometimes known as strict evaluation. Eager evaluation is the evaluation strategy employed in most [quantify] programming languages.
With evaluation is meant the level of achieving the target for a particular evaluation item. There are general "methods" respectively approaches as well as IT-supported "software tools" that enable an effective and efficient work. The following is a list of notable methods and benchmarking software tools.
PyCharm – Cross-platform Python IDE with code inspections available for analyzing code on-the-fly in the editor and bulk analysis of the whole project. PyDev – Eclipse-based Python IDE with code analysis available on-the-fly in the editor or at save time. Pylint – Static code analyzer. Quite stringent; includes many stylistic warnings as ...
In applied mathematics, test functions, known as artificial landscapes, are useful to evaluate characteristics of optimization algorithms, such as convergence rate, precision, robustness and general performance.