Science Score: 49.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 3 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (18.7%) to scientific vocabulary
Repository
Forked from lballabio/QuantLib-SWIG
Basic Info
Statistics
- Stars: 0
- Watchers: 1
- Forks: 2
- Open Issues: 0
- Releases: 4
Metadata Files
README.md
QuantLib-SWIG: language bindings for QuantLib
QuantLib-SWIG provides the means to use QuantLib from a number of languages; currently their list includes Python, C#, Java and R.
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.
Owner
- Name: OpenSourceRisk
- Login: OpenSourceRisk
- Kind: organization
- Website: www.opensourcerisk.org
- Repositories: 4
- Profile: https://github.com/OpenSourceRisk
GitHub Events
Total
- Watch event: 1
- Delete event: 1
- Push event: 5
- Pull request event: 4
- Fork event: 1
- Create event: 4
Last Year
- Watch event: 1
- Delete event: 1
- Push event: 5
- Pull request event: 4
- Fork event: 1
- Create event: 4
Dependencies
- actions/checkout v3 composite
- peter-evans/create-pull-request v4 composite
- actions/checkout v3 composite
- actions/checkout v3 composite
- peter-evans/create-pull-request v4 composite
- sobolevn/misspell-fixer-action master composite
- actions/checkout v3 composite
- peter-evans/create-pull-request v4 composite
- actions/stale v6 composite
- methods * depends
- QuantLib *
- jupyter *
- jupytext *
- matplotlib *
- numpy *
- pandas *