https://github.com/diku-dk/sml-random
Standard ML library for generating random numbers
https://github.com/diku-dk/sml-random
sml smlpkg standard-ml
Last synced: 6 months ago
JSON representation
Standard ML library for generating random numbers
- Host: GitHub
- URL: https://github.com/diku-dk/sml-random
- Owner: diku-dk
- License: mit
- Created: 2020-04-06T17:00:49.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2023-10-01T07:56:30.000Z (about 2 years ago)
- Last Synced: 2025-01-31T23:57:56.310Z (8 months ago)
- Topics: sml, smlpkg, standard-ml
- Language: Standard ML
- Size: 7.81 KB
- Stars: 4
- Watchers: 8
- Forks: 2
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# sml-random [](https://github.com/diku-dk/sml-random/actions)
Standard ML library for generating random numbers.
## Overview of MLB files
- `lib/github.com/diku-dk/sml-random/random.mlb`:
- **signature** [`RANDOM`](lib/github.com/diku-dk/sml-random/RANDOM.sig)
- **structure** `Random`
## Use of the package
This library is set up to work well with the SML package manager
[smlpkg](https://github.com/diku-dk/smlpkg). To use the package, in
the root of your project directory, execute the command:
```
$ smlpkg add github.com/diku-dk/sml-random
```
This command will add a _requirement_ (a line) to the `sml.pkg` file in your
project directory (and create the file, if there is no file `sml.pkg`
already).
To download the library into the directory
`lib/github.com/diku-dk/sml-random`, execute the command:
```
$ smlpkg sync
```
You can now reference the `mlb`-file using relative paths from within
your project's `mlb`-files.
Notice that you can choose either to treat the downloaded package as
part of your own project sources (vendoring) or you can add the
`sml.pkg` file to your project sources and make the `smlpkg sync`
command part of your build process.
## Authors
The `Random` structure was originally written by Peter Sestoft for
[Moscow ML](https://mosml.org), based on the implementation of random
numbers found in Lawrence C. Paulson's book _ML for the Working
Programmer, 2nd Edition_, page 201.