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Written in C++ and published under an MIT license, HiGHS provides programming interfaces to C, Python, Julia, Rust, JavaScript, Fortran, and C#. It has no external dependencies. A convenient thin wrapper to Python is available via the highspy PyPI package. Although generally single-threaded, some solver components can utilize multi-core ...
It adds information (page title, work/website, author and publication date, if metadata is included) to bare URL references, and does additional fixes as well (e.g. combining duplicated references). The tool is written in Python and licensed under Simplified BSD License. The tool is an open-source replacement of Dispenser's Reflinks.
GEKKO works on all platforms and with Python 2.7 and 3+. By default, the problem is sent to a public server where the solution is computed and returned to Python. There are Windows, MacOS, Linux, and ARM (Raspberry Pi) processor options to solve without an Internet connection.
tox is a command-line driven automated testing tool for Python, based on the use of virtualenv. It can be used for both manually-invoked testing from the desktop, or continuous testing within continuous integration frameworks such as Jenkins or Travis CI. [1] [2] Its use began to become popular in the Python community from around 2015. [3]
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These tools look for a very specific set of known problems, some common and some rare, within the source code, concentrating more on the semantics (e.g. data flow) rather than the syntax, as compilers and interpreters do. Both commercial and free tools exist for various languages; some claim to be able to detect hundreds of different problems.
The definition of the term varies depending upon the community using it. In Ruby, [2] Python, [3] and many other dynamic programming languages, the term monkey patch only refers to dynamic modifications of a class or module at runtime, motivated by the intent to patch existing third-party code as a workaround to a bug or feature which does not act as desired.
For each combinatorial optimization problem, there is a corresponding decision problem that asks whether there is a feasible solution for some particular measure m 0. For example, if there is a graph G which contains vertices u and v , an optimization problem might be "find a path from u to v that uses the fewest edges".