RandomGen
This package contains additional bit generators for NumPy's
Generator and an ExtendedGenerator exposing methods not in Generator.
Continuous Integration
Coverage
Latest Release
License
This is a library and generic interface for alternative random generators in Python and NumPy.
New Features
See the development documentation for the latest features, or the stable documentation for the latest released features.
WARNINGS
Changes in v1.24
Generator and RandomState were removed in 1.23.0.
Changes from 1.18 to 1.19
Generator and RandomState have been officially deprecated in 1.19, and will
warn with a FutureWarning about their removal. They will also receive virtually
no maintenance. It is now time to move to NumPy's np.random.Generator which has
features not in randomstate.Generator and is maintained more actively.
A few distributions that are not present in np.random.Generator have been moved
to randomstate.ExtendedGenerator:
multivariate_normal: which supports broadcastinguintegers: fast 32 and 64-bit uniform integerscomplex_normal: scalar complex normals
There are no plans to remove any of the bit generators, e.g., AESCounter,
ThreeFry, or PCG64.
Changes from 1.16 to 1.18
There are many changes between v1.16.x and v1.18.x. These reflect API
decision taken in conjunction with NumPy in preparation of the core
of randomgen being used as the preferred random number generator in
NumPy. These all issue DeprecationWarnings except for BasicRNG.generator
which raises NotImplementedError. The C-API has also changed to reflect
the preferred naming the underlying Pseudo-RNGs, which are now known as
bit generators (or BitGenerators).
Future Plans
- Add some distributions that are not supported in NumPy. Ongoing
- Add any interesting bit generators I come across. Recent additions include the DXSM and CM-DXSM variants of PCG64 and the LXM generator.
Included Pseudo Random Number Generators
This module includes a number of alternative random number generators in addition to the MT19937 that is included in NumPy. The RNGs include:
- Cryptographic cipher-based random number generator based on AES, ChaCha20, HC128 and Speck128.
- MT19937, the NumPy rng
- dSFMT a SSE2-aware version of the MT19937 generator that is especially fast at generating doubles
- xoroshiro128+, xorshift1024*φ, xoshiro256**, and xoshiro512**
- PCG64
- ThreeFry and Philox from Random123
- Other cryptographic-based generators:
AESCounter,SPECK128,ChaCha, andHC128. - Hardware (non-reproducible) random number generator on AMD64 using
RDRAND. - Chaotic PRNGS: Small-Fast Chaotic (
SFC64) and Jenkin's Small-Fast (JSF).
Status
- Builds and passes all tests on:
- Linux 64-bit (x86-64), Python 3.10, 3.11, 3.12, 3.13, 3.14, 3.15
- Linux ARM64, current Python
- macOS, Python 3.10, 3.11, 3.12, 3.15
- Windows 64-bit, Python 3.10, 3.11, 3.12, 3.13, 3.14, 3.15
- Windows ARM64, Python 3.11, 3.15 and 3.14t
- Free-threaded Python 3.14t and 3.15t on Linux, macOS and Windows
Version
The package version matches the latest version of NumPy when the package is released.
Documentation
Documentation for the latest release is available on my GitHub pages. Documentation for the latest commit (unreleased) is available under devel.
Requirements
Building requires:
- Python (3.10, 3.11, 3.12, 3.13, 3.14, 3.15)
- NumPy (1.26+ except 2.4.0, runtime; 2.0.0+, building)
- Cython (3.1.0+)
Testing requires pytest (9+).
The development dependencies are dependency groups in pyproject.toml.
With pip 25.1 or later, install everything needed to build, test and lint
randomgen, and then randomgen itself, with
python -m pip install --group dev
python -m pip install -e . --no-build-isolation
The groups are build, test, lint, doc (for the documentation) and
dev (build, test and lint together).
Note: it might work with other versions but only tested with these versions.
Development and Testing
All development has been on 64-bit Linux, and it is regularly tested on Azure (Linux-AMD64, Windows, and macOS) and GitHub Actions (Linux-ARM64, Windows-ARM64 and free-threaded Python).
Tests are in place for all RNGs. The MT19937 is tested against NumPy's implementation for identical results. It also passes NumPy's test suite where still relevant.
Installing
Either install from PyPi using
python -m pip install randomgen
or, if you want the latest version,
python -m pip install git+https://github.com/bashtage/randomgen.git
or from a cloned repo,
python -m pip install .
If you use conda, you can install using conda forge
conda install -c conda-forge randomgen
SSE2
dSFMT and SFMT make use of SSE2 by default. If you have a very old
computer or are building on non-x86, you can install using:
python -m pip install . -Csetup-args=-Ddisable-sse2=true
Windows
Either use a binary wheel, or if building from scratch, use the Visual Studio
Build Tools (MSVC). Builds with clang-cl are also tested.
License
Dual: BSD 3-Clause and NCSA, plus sub licenses for components.
1 maintainer
Metadata
1 maintainer
Release files for randomgen 2.5.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| randomgen-2.5.1.tar.gz | 1.5 MB | Without provenance | Details for randomgen-2.5.1.tar.gz |
Built distributions (wheels)
Total release size: 174.0 MB
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twine/7.0.0 CPython/3.14.10
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Release files / randomgen-2.5.1-cp314-cp314-win_arm64.whl
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Release files / randomgen-2.5.1-cp314-cp314-win_amd64.whl
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| Size | 2.9 MB |
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Release files / randomgen-2.5.1-cp314-cp314-musllinux_1_2_x86_64.whl
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| Size | 3.4 MB |
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Release files / randomgen-2.5.1-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
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twine/7.0.0 CPython/3.15.2
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Release files / randomgen-2.5.1-cp314-cp314-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl
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| Size | 3.3 MB |
| Tags | CPython 3.14 Linux glibc 2.27+ ARM64 Linux glibc 2.28+ ARM64 |
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Release files / randomgen-2.5.1-cp314-cp314-macosx_11_0_arm64.whl
| Download URL | randomgen-2.5.1-cp314-cp314-macosx_11_0_arm64.whl |
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twine/7.0.0 CPython/3.14.10
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Release files / randomgen-2.5.1-cp314-cp314-macosx_10_15_x86_64.whl
| Download URL | randomgen-2.5.1-cp314-cp314-macosx_10_15_x86_64.whl |
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No |
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twine/7.0.0 CPython/3.14.7
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Release files / randomgen-2.5.1-cp313-cp313-win_arm64.whl
| Download URL | randomgen-2.5.1-cp313-cp313-win_arm64.whl |
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No |
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twine/7.0.0 CPython/3.15.2
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Release files / randomgen-2.5.1-cp313-cp313-win_amd64.whl
| Download URL | randomgen-2.5.1-cp313-cp313-win_amd64.whl |
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| Size | 2.9 MB |
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No |
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twine/7.0.0 CPython/3.15.2
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Release files / randomgen-2.5.1-cp313-cp313-musllinux_1_2_x86_64.whl
| Download URL | randomgen-2.5.1-cp313-cp313-musllinux_1_2_x86_64.whl |
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twine/7.0.0 CPython/3.15.2
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Release files / randomgen-2.5.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
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No |
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twine/7.0.0 CPython/3.15.2
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Release files / randomgen-2.5.1-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl
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| Size | 3.2 MB |
| Tags | CPython 3.13 Linux glibc 2.27+ ARM64 Linux glibc 2.28+ ARM64 |
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No |
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twine/7.0.0 CPython/3.15.2
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Release files / randomgen-2.5.1-cp313-cp313-macosx_11_0_arm64.whl
| Download URL | randomgen-2.5.1-cp313-cp313-macosx_11_0_arm64.whl |
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| Size | 3.0 MB |
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No |
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twine/7.0.0 CPython/3.14.10
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Release files / randomgen-2.5.1-cp313-cp313-macosx_10_13_x86_64.whl
| Download URL | randomgen-2.5.1-cp313-cp313-macosx_10_13_x86_64.whl |
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No |
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twine/7.0.0 CPython/3.14.7
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Release files / randomgen-2.5.1-cp312-cp312-win_arm64.whl
| Download URL | randomgen-2.5.1-cp312-cp312-win_arm64.whl |
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No |
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twine/7.0.0 CPython/3.15.2
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Release files / randomgen-2.5.1-cp312-cp312-win_amd64.whl
| Download URL | randomgen-2.5.1-cp312-cp312-win_amd64.whl |
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No |
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twine/7.0.0 CPython/3.15.2
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Release files / randomgen-2.5.1-cp312-cp312-musllinux_1_2_x86_64.whl
| Download URL | randomgen-2.5.1-cp312-cp312-musllinux_1_2_x86_64.whl |
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twine/7.0.0 CPython/3.15.1
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Release files / randomgen-2.5.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
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No |
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twine/7.0.0 CPython/3.15.1
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Release files / randomgen-2.5.1-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl
| Download URL | randomgen-2.5.1-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl |
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| Size | 3.3 MB |
| Tags | CPython 3.12 Linux glibc 2.27+ ARM64 Linux glibc 2.28+ ARM64 |
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No |
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twine/7.0.0 CPython/3.15.1
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Release files / randomgen-2.5.1-cp312-cp312-macosx_11_0_arm64.whl
| Download URL | randomgen-2.5.1-cp312-cp312-macosx_11_0_arm64.whl |
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| Size | 3.0 MB |
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No |
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twine/7.0.0 CPython/3.14.10
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Release files / randomgen-2.5.1-cp312-cp312-macosx_10_13_x86_64.whl
| Download URL | randomgen-2.5.1-cp312-cp312-macosx_10_13_x86_64.whl |
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| Size | 3.1 MB |
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No |
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twine/7.0.0 CPython/3.14.7
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Release files / randomgen-2.5.1-cp311-cp311-win_arm64.whl
| Download URL | randomgen-2.5.1-cp311-cp311-win_arm64.whl |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.15.1
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Release files / randomgen-2.5.1-cp311-cp311-win_amd64.whl
| Download URL | randomgen-2.5.1-cp311-cp311-win_amd64.whl |
|---|---|
| Size | 2.9 MB |
| Tags | CPython 3.11 Windows x86-64 |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.15.2
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Release files / randomgen-2.5.1-cp311-cp311-musllinux_1_2_x86_64.whl
| Download URL | randomgen-2.5.1-cp311-cp311-musllinux_1_2_x86_64.whl |
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| Size | 3.4 MB |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.15.2
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Release files / randomgen-2.5.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
| Download URL | randomgen-2.5.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl |
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| Size | 3.4 MB |
| Tags | CPython 3.11 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64 |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.15.2
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Release files / randomgen-2.5.1-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl
| Download URL | randomgen-2.5.1-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl |
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| Size | 3.3 MB |
| Tags | CPython 3.11 Linux glibc 2.27+ ARM64 Linux glibc 2.28+ ARM64 |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.15.2
|
Release files / randomgen-2.5.1-cp311-cp311-macosx_11_0_arm64.whl
| Download URL | randomgen-2.5.1-cp311-cp311-macosx_11_0_arm64.whl |
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| Size | 3.0 MB |
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No |
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twine/7.0.0 CPython/3.14.10
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Release files / randomgen-2.5.1-cp311-cp311-macosx_10_9_x86_64.whl
| Download URL | randomgen-2.5.1-cp311-cp311-macosx_10_9_x86_64.whl |
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| Size | 3.1 MB |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.14.7
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Release files / randomgen-2.5.1-cp310-cp310-win_amd64.whl
| Download URL | randomgen-2.5.1-cp310-cp310-win_amd64.whl |
|---|---|
| Size | 2.9 MB |
| Tags | CPython 3.10 Windows x86-64 |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.15.2
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Release files / randomgen-2.5.1-cp310-cp310-musllinux_1_2_x86_64.whl
| Download URL | randomgen-2.5.1-cp310-cp310-musllinux_1_2_x86_64.whl |
|---|---|
| Size | 3.4 MB |
| Tags | CPython 3.10 Linux musl 1.2+ x86-64 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.15.1
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Release files / randomgen-2.5.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
| Download URL | randomgen-2.5.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl |
|---|---|
| Size | 3.4 MB |
| Tags | CPython 3.10 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64 |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.15.1
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Release files / randomgen-2.5.1-cp310-cp310-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl
| Download URL | randomgen-2.5.1-cp310-cp310-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl |
|---|---|
| Size | 3.3 MB |
| Tags | CPython 3.10 Linux glibc 2.27+ ARM64 Linux glibc 2.28+ ARM64 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.15.1
|
Release files / randomgen-2.5.1-cp310-cp310-macosx_11_0_arm64.whl
| Download URL | randomgen-2.5.1-cp310-cp310-macosx_11_0_arm64.whl |
|---|---|
| Size | 3.1 MB |
| Tags | CPython 3.10 macOS 11.0+ ARM64 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.10
|
Release files / randomgen-2.5.1-cp310-cp310-macosx_10_9_x86_64.whl
| Download URL | randomgen-2.5.1-cp310-cp310-macosx_10_9_x86_64.whl |
|---|---|
| Size | 3.1 MB |
| Tags | CPython 3.10 macOS 10.9+ x86-64 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
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Security for randomgen 2.5.1
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