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https://github.com/marcom/dssopt_jll.jl


https://github.com/marcom/dssopt_jll.jl

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# `DssOpt_jll.jl` (v1.0.5+0)

This is an autogenerated package constructed using [`BinaryBuilder.jl`](https://github.com/JuliaPackaging/BinaryBuilder.jl).

## Documentation

For more details about JLL packages and how to use them, see `BinaryBuilder.jl` [documentation](https://docs.binarybuilder.org/stable/jll/).

## Sources

The tarballs for `DssOpt_jll.jl` have been built from these sources:

* git repository: https://github.com/marcom/dss-opt/ (revision: `3058fb040fdcebf901b250b624f7a9e0670ef96f`)

## Platforms

`DssOpt_jll.jl` is available for the following platforms:

* `macOS aarch64` (`aarch64-apple-darwin`)
* `Linux aarch64 {libc=glibc}` (`aarch64-linux-gnu`)
* `Linux aarch64 {libc=musl}` (`aarch64-linux-musl`)
* `Linux armv6l {call_abi=eabihf, libc=glibc}` (`armv6l-linux-gnueabihf`)
* `Linux armv6l {call_abi=eabihf, libc=musl}` (`armv6l-linux-musleabihf`)
* `Linux armv7l {call_abi=eabihf, libc=glibc}` (`armv7l-linux-gnueabihf`)
* `Linux armv7l {call_abi=eabihf, libc=musl}` (`armv7l-linux-musleabihf`)
* `Linux i686 {libc=glibc}` (`i686-linux-gnu`)
* `Linux i686 {libc=musl}` (`i686-linux-musl`)
* `Windows i686` (`i686-w64-mingw32`)
* `Linux powerpc64le {libc=glibc}` (`powerpc64le-linux-gnu`)
* `macOS x86_64` (`x86_64-apple-darwin`)
* `Linux x86_64 {libc=glibc}` (`x86_64-linux-gnu`)
* `Linux x86_64 {libc=musl}` (`x86_64-linux-musl`)
* `FreeBSD x86_64` (`x86_64-unknown-freebsd`)
* `Windows x86_64` (`x86_64-w64-mingw32`)

## Dependencies

The following JLL packages are required by `DssOpt_jll.jl`:

* `GSL_jll`

## Products

The code bindings within this package are autogenerated from the following `Products`:

* `LibraryProduct`: `libdssopt`
* `ExecutableProduct`: `eval_dGdp`
* `ExecutableProduct`: `eval_pseq`
* `ExecutableProduct`: `eval_score`
* `ExecutableProduct`: `eval_useq`
* `ExecutableProduct`: `opt_md`
* `ExecutableProduct`: `opt_sd`
* `ExecutableProduct`: `opt_sd_gsl`
* `ExecutableProduct`: `random_seq`
* `ExecutableProduct`: `random_vienna`
* `ExecutableProduct`: `rna_ensemble_distance`