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Functions declared as pytest fixtures are marked by the @pytest.fixture decorator, whose names can then be passed into test functions as parameters. [12] When pytest finds the fixtures' names in test functions' parameters, it first searches in the same module for such fixtures, and if not found, it searches for such fixtures in the conftest.py ...
An output parameter, also known as an out parameter or return parameter, is a parameter used for output, rather than the more usual use for input. Using call by reference parameters, or call by value parameters where the value is a reference, as output parameters is an idiom in some languages, notably C and C++, [ b ] while other languages have ...
Some people (including Guido van Rossum himself) have called this parameter-passing scheme "call by object reference". An object reference means a name, and the passed reference is an "alias", i.e. a copy of the reference to the same object, just as in C/C++. The object's value may be changed in the called function with the "alias", for example:
Without named parameters, optional parameters can only appear at the end of the parameter list, since there is no other way to determine which values have been omitted. In languages that support named optional parameters, however, programs may supply any subset of the available parameters, and the names are used to determine which values have ...
Test-driven development (TDD) is a way of writing code that involves writing an automated unit-level test case that fails, then writing just enough code to make the test pass, then refactoring both the test code and the production code, then repeating with another new test case.
Languages without a return statement, such as standard Pascal don't have this problem. Some languages, such as C++ and Python, employ concepts which allow actions to be performed automatically upon return (or exception throw) which mitigates some of these issues – these are often known as "try/finally" or similar.
mod_python, an Apache module allowing direct integration of Python scripts with the Apache web server PyObjC , a Python to Objective-C bridge that allows writing OS X software in Python Robot Framework , a generic test automation framework for acceptance testing and acceptance test-driven development (ATDD)
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]