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Example one shows how narrative text can be interspersed with testable examples in a docstring. In the second example, more features of doctest are shown, together with their explanation. Example three is set up to run all doctests in a file when the file is run, but when imported as a module, the tests will not be run.
Download as PDF; Printable version; In other projects ... to a file or on the screen in order to determine the error's location in code. ... This example function in ...
Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})
After a function's value is computed for that parameter or set of parameters, the result is stored in a lookup table that is indexed by the values of those parameters; the next time the function is called, the table is consulted to determine whether the result for that combination of parameter values is already available. If so, the stored ...
They can cause loss of information and resources that might result severely harmful for users, the general public, or employers. Therefore, software developers should minimize the risk of harming others due to coding errors, or security issues, by following standards to design and test systems (Code of Ethics and Professional Conduct). [3]
Magic numbers become particularly confusing when the same number is used for different purposes in one section of code. It is easier to alter the value of the number, as it is not duplicated. Changing the value of a magic number is error-prone, because the same value is often used several times in different places within a program. [6]
Convolutional code with any code rate can be designed based on polynomial selection; [15] however, in practice, a puncturing procedure is often used to achieve the required code rate. Puncturing is a technique used to make a m / n rate code from a "basic" low-rate (e.g., 1/ n ) code.
In cryptography, learning with errors (LWE) is a mathematical problem that is widely used to create secure encryption algorithms. [1] It is based on the idea of representing secret information as a set of equations with errors. In other words, LWE is a way to hide the value of a secret by introducing noise to it. [2]