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QuantLib-SWIG: language bindings for QuantLib

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QuantLib-SWIG provides the means to use QuantLib from a number of languages including Python, Ruby, Perl, C# and Java.

The QuantLib project (https://www.quantlib.org) is aimed at providing a comprehensive software framework for quantitative finance. QuantLib is a free/open-source library for modeling, trading, and risk management in real-life.

QuantLib is Non-Copylefted Free Software and OSI Certified Open Source Software.

Download and usage

QuantLib-SWIG can be downloaded from https://www.quantlib.org/download.shtml.

On Linux/Unix, you can run:

./configure
make
make check
sudo make install

to build, test and install al modules. If you're only interested in a specific language, you can tell make to only work in its subdirectory, as in:

make -C Python

Alternatively, you can cd to a specific subdirectory and follow the instructions in its README file. This is also the procedure for Windows users.

Questions and feedback

Bugs can be reported as a GitHub issue at https://github.com/lballabio/QuantLib-SWIG/issues; if you have a patch available, you can open a pull request instead (see "Contributing" below).

You can also use the quantlib-users and quantlib-dev mailing lists for feedback, questions, etc. More information and instructions for subscribing are at https://www.quantlib.org/mailinglists.shtml.

Contributing

The easiest way to contribute is through pull requests on GitHub. Get a GitHub account if you don't have it already and clone the repository at https://github.com/lballabio/QuantLib-SWIG with the "Fork" button in the top right corner of the page. Check out your clone to your machine, code away, push your changes to your clone and submit a pull request; instructions are available at https://help.github.com/articles/fork-a-repo. (In case you need them, more detailed instructions for creating pull requests are at https://help.github.com/articles/using-pull-requests, and a basic guide to GitHub is at https://guides.github.com/activities/hello-world/.

It's likely that we won't merge your code right away, and we'll ask for some changes instead. Don't be discouraged! That's normal; the library is complex, and thus it might take some time to become familiar with it and to use it in an idiomatic way.

We're looking forward to your contributions.

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QuantLib wrappers to other languages

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  • SWIG 51.9%
  • Python 33.8%
  • Java 5.7%
  • C# 3.0%
  • Scala 2.8%
  • R 1.6%
  • Other 1.2%