Skip to main content

SPlisHSPlasH Project Python Bindings

Project description


      Documentation Status

SPlisHSPlasH is an open-source library for the physically-based simulation of fluids. The simulation in this library is based on the Smoothed Particle Hydrodynamics (SPH) method which is a popular meshless Lagrangian approach to simulate complex fluid effects. The SPH formalism allows an efficient computation of a certain quantity of a fluid particle by considering only a finite set of neighboring particles. One of the most important research topics in the field of SPH methods is the simulation of incompressible fluids. SPlisHSPlasH implements current state-of-the-art pressure solvers (WCSPH, PCISPH, PBF, IISPH, DFSPH, PF) to simulate incompressibility. Moreover, the library provides different methods to simulate viscosity, surface tension and vorticity.

The library uses the following external libraries: Eigen, json, partio, zlib, cxxopts, tinyexpr, toojpeg, pybind, glfw, hapPLY, and imgui or AntTweakBar. All external dependencies are included.

Furthermore we use our own libraries:

SPlisHSPlasH can export the particle data in the partio and vtk format. If you want to import partio files in Maya, try out our Maya plugin:

Author: Jan Bender

License

The SPlisHSPlasH library code is licensed under the MIT license. See LICENSE for details.

External dependencies are covered by separate licensing terms. See the extern folder for the code and respective licensing terms of each dependency.

Documentation

Forum

On our GitHub discussions page you can ask questions, discuss about simulation topics, and share ideas.

Build Instructions

This project is based on CMake. Simply generate project, Makefiles, etc. using CMake and compile the project with a compiler of your choice that supports C++11. The code was tested with the following configurations:

  • Windows 10 64-bit, CMake 3.18.3, Visual Studio 2019
  • Debian 9 64-bit, CMake 3.12.3, GCC 6.3.0.

Note: Please use a 64-bit target on a 64-bit operating system. 32-bit builds on a 64-bit OS are not supported.

Python Installation Instruction

For Windows and Linux targets there exists prebuilt python wheel files which can be installed using

pip install pysplishsplash

These are available for Python Versions: 2.7, 3.5, 3.6, 3.7, 3.8. If you do not meet these conditions please refer to the build instructions and to the python binding Getting started guide.

The command line simulator is available by running one of the following

splash
splash --help

Features

SPlisHSPlasH implements:

  • an open-source SPH fluid simulation (2D & 3D)
  • neighborhood search on CPU or GPU
  • supports vectorization using AVX
  • Python binding (thanks to Stefan Jeske)
  • supports embedded Python scripts
  • several implicit pressure solvers (WCSPH, PCISPH, PBF, IISPH, DFSPH, PF)
  • explicit and implicit viscosity methods
  • current surface tension approaches
  • different vorticity methods
  • computation of drag forces
  • support for multi-phase simulations
  • simulation of deformable solids
  • rigid-fluid coupling with static and dynamic bodies
  • two-way coupling with deformable solids
  • fluid emitters
  • scripted animation fields
  • a json-based scene file importer
  • automatic surface sampling
  • a tool for volume sampling of closed geometries
  • a tool to generate spray, foam and bubble particles in a postprocessing step
  • a tool to skin a visual mesh to the moving particles of an elastic solid in a postprocessing step
  • partio file export of all particle data
  • VTK file export of all particle data (enables the data import in ParaView)
  • rigid body export
  • a Maya plugin to model and generate scene files
  • a ParaView plugin to import particle data

Pressure Solvers

The SPlisHSPlasH library implements the following pressure solvers:

  • Weakly compressible SPH for free surface flows (WCSPH)
  • Predictive-corrective incompressible SPH (PCISPH)
  • Position based fluids (PBF)
  • Implicit incompressible SPH (IISPH)
  • Divergence-free smoothed particle hydrodynamics (DFSPH)
  • Projective Fluids (PF)
  • Implicit compressible SPH (ICSPH)

Boundary Handling

The SPlisHSPlasH library implements the following boundary handling methods:

  • Nadir Akinci, Markus Ihmsen, Gizem Akinci, Barbara Solenthaler, and Matthias Teschner, "Versatile rigid-fluid coupling for incompressible SPH", ACM Transactions on Graphics 31(4), 2012

  • Dan Koschier and Jan Bender, "Density Maps for Improved SPH Boundary Handling", In Proceedings of ACM SIGGRAPH / EUROGRAPHICS Symposium on Computer Animation (SCA), 2017

  • Jan Bender, Tassilo Kugelstadt, Marcel Weiler, Dan Koschier, "Volume Maps: An Implicit Boundary Representation for SPH", ACM SIGGRAPH Conference on Motion, Interaction and Games, 2019

Viscosity

The SPlisHSPlasH library implements explicit viscosity methods:

  • Standard SPH formulation of viscosity
  • XSPH

and the implicit methods of the following publications:

  • Jan Bender and Dan Koschier, "Divergence-free SPH for incompressible and viscous fluids", IEEE Transactions on Visualization and Computer Graphics, 2017

  • Andreas Peer, Markus Ihmsen, Jens Cornelis, and Matthias Teschner, "An Implicit Viscosity Formulation for SPH Fluids", ACM Transactions on Graphics, 34(4), 2015

  • Andreas Peer and Matthias Teschner. Prescribed Velocity Gradients for Highly Viscous SPH Fluids with Vorticity Diffusion. IEEE Transactions on Visualization and Computer Graphics, 2016

  • An improved version of: Tetsuya Takahashi, Yoshinori Dobashi, Issei Fujishiro, Tomoyuki Nishita, and Ming C. Lin. Implicit Formulation for SPH-based Viscous Fluids. Computer Graphics Forum, 34, 2015.

  • Marcel Weiler, Dan Koschier, Magnus Brand and Jan Bender. A Physically Consistent Implicit Viscosity Solver for SPH Fluids. Computer Graphics Forum (Eurographics), 37(2), 2018

Surface Tension

The SPlisHSPlasH library implements the surface tension methods of the following publications:

  • Markus Becker and Matthias Teschner. Weakly compressible SPH for free surface flows. In Proceedings of ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 2007. Eurographics Association.
  • Nadir Akinci, Gizem Akinci, and Matthias Teschner. Versatile surface tension and adhesion for SPH fluids. ACM Trans. Graph., 32(6):182:1–182:8, 2013.
  • Xiaowei He, Huamin Wang, Fengjun Zhang, Hongan Wang, Guoping Wang, and Kun Zhou, "Robust simulation of sparsely sampled thin features in SPH-based free surface flows", ACM Transactions on Graphics, 34(1), 2014.
  • F. Zorilla, M. Ritter, J. Sappl, W. Rauch, M. Harders, "Accelerating Surface Tension Calculation in SPH via Particle Classification and Monte Carlo Integration", Computers 9, 23, 2020.

Vorticity

The SPlisHSPlasH library implements the vorticity methods of the following publications:

  • Jan Bender, Dan Koschier, Tassilo Kugelstadt and Marcel Weiler. A Micropolar Material Model for Turbulent SPH Fluids. In Proceedings of ACM SIGGRAPH / EUROGRAPHICS Symposium on Computer Animation, 2017

  • Miles Macklin and Matthias Müller. Position based fluids. ACM Trans. Graph., 32(4):104:1–104:12, July 2013.

Drag Forces

The SPlisHSPlasH library implements the drag force computation of the following publications:

  • Christoph Gissler, Stefan Band, Andreas Peer, Markus Ihmsen and Matthias Teschner. Approximate Air-Fluid Interactions for SPH. In Proceedings of Virtual Reality Interactions and Physical Simulations, 2017

  • Miles Macklin, Matthias Müller, Nuttapong Chentanez and Tae-Yong Kim. Unified Particle Physics for Real-Time Applications. ACM Trans. Graph., 33(4), 2014

Elastic Forces

  • M. Becker, M. Ihmsen, and M. Teschner. Corotated SPH for deformable solids. Proceedings of Eurographics Conference on Natural Phenomena, 2009

  • A. Peer, C. Gissler, S. Band, and M. Teschner. An Implicit SPH Formulation for Incompressible Linearly Elastic Solids. Computer Graphics Forum, 2017

  • Tassilo Kugelstadt, Jan Bender, José Antonio Fernández-Fernández, Stefan Rhys Jeske, Fabian Löschner, and Andreas Longva. Fast Corotated Elastic SPH Solids with Implicit Zero-Energy Mode Control. Proceedings of the ACM on Computer Graphics and Interactive Techniques, 2021

Multi-Phase Fluid Simulation

The SPlisHSPlasH library implements the following publication to realize multi-phase simulations:

  • B. Solenthaler and R. Pajarola. Density Contrast SPH Interfaces. In Proceedings of ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 2008.

Volume Sampling

The SPlisHSPlasH library implements the volume sampling techniques of following publications:

  • M. Jiang, Y. Zhou, R. Wang, R. Southern, J. J. Zhang. Blue noise sampling using an SPH-based method. ACM Transactions on Graphics, 2015
  • Tassilo Kugelstadt, Jan Bender, José Antonio Fernández-Fernández, Stefan Rhys Jeske, Fabian Löschner, and Andreas Longva. Fast Corotated Elastic SPH Solids with Implicit Zero-Energy Mode Control. Proceedings of the ACM on Computer Graphics and Interactive Techniques, 2021

Screenshots

Videos

The following videos were generated using the SPlisHSPlasH library:

A Micropolar Material Model for Turbulent SPH Fluids Density Maps for Improved SPH Boundary Handling
Video Video
Divergence-Free Smoothed Particle Hydrodynamics Divergence-Free SPH for Incompressible and Viscous Fluids
Video Video
A Physically Consistent Implicit Viscosity Solver for SPH Fluids Turbulent Micropolar SPH Fluids with Foam
Video Video
Volume Maps: An Implicit Boundary Representation for SPH Implicit Frictional Boundary Handling for SPH
Video Video
Fast Corotated Elastic SPH Solids with Implicit Zero-Energy Mode Control
Video

References

  • Nadir Akinci, Gizem Akinci, and Matthias Teschner. Versatile surface tension and adhesion for SPH fluids. ACM Trans. Graph., 32(6):182:1–182:8, 2013.
  • Nadir Akinci, Markus Ihmsen, Gizem Akinci, Barbara Solenthaler, and Matthias Teschner, "Versatile rigid-fluid coupling for incompressible SPH", ACM Transactions on Graphics 31(4), 2012
  • Markus Becker and Matthias Teschner. Weakly compressible SPH for free surface flows. In Proceedings of ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 2007. Eurographics Association.
  • M. Becker, M. Ihmsen, and M. Teschner. Corotated SPH for deformable solids. Proceedings of Eurographics Conference on Natural Phenomena, 2009
  • Jan Bender and Dan Koschier. Divergence-free smoothed particle hydrodynamics. In Proceedings of ACM SIGGRAPH / Eurographics Symposium on Computer Animation, 2015. ACM.
  • Jan Bender and Dan Koschier. Divergence-free SPH for incompressible and viscous fluids. IEEE Transactions on Visualization and Computer Graphics, 2017.
  • Jan Bender, Dan Koschier, Tassilo Kugelstadt and Marcel Weiler. A Micropolar Material Model for Turbulent SPH Fluids. In Proceedings of ACM SIGGRAPH / EUROGRAPHICS Symposium on Computer Animation, 2017
  • Jan Bender, Dan Koschier, Tassilo Kugelstadt and Marcel Weiler. Turbulent Micropolar SPH Fluids with Foam. IEEE Transactions on Visualization and Computer Graphics 25(6), 2019
  • Jan Bender, Tassilo Kugelstadt, Marcel Weiler, Dan Koschier, "Volume Maps: An Implicit Boundary Representation for SPH", ACM SIGGRAPH Conference on Motion, Interaction and Games, 2019
  • Jan Bender, Tassilo Kugelstadt, Marcel Weiler, Dan Koschier, "Implicit Frictional Boundary Handling for SPH", IEEE Transactions on Visualization and Computer Graphics, 2020
  • Jan Bender, Matthias Müller, Miguel A. Otaduy, Matthias Teschner, and Miles Macklin. A survey on position-based simulation methods in computer graphics. Computer Graphics Forum, 33(6):228–251, 2014.
  • Jan Bender, Matthias Müller, and Miles Macklin. Position-based simulation methods in computer graphics. In EUROGRAPHICS 2015 Tutorials. Eurographics Association, 2015.
  • Christoph Gissler, Stefan Band, Andreas Peer, Markus Ihmsen and Matthias Teschner. Approximate Air-Fluid Interactions for SPH. In Proceedings of Virtual Reality Interactions and Physical Simulations, 2017
  • C. Gissler, A. Henne, S. Band, A. Peer and M. Teschner. An Implicit Compressible SPH Solver for Snow Simulation, ACM Transactions on Graphics 39(4), 2020.
  • Xiaowei He, Huamin Wang, Fengjun Zhang, Hongan Wang, Guoping Wang, and Kun Zhou. Robust simulation of sparsely sampled thin features in SPH-based free surface flows. ACM Trans. Graph., 34(1):7:1–7:9, December 2014.
  • Markus Ihmsen, Nadir Akinci, Gizem Akinci, Matthias Teschner. Unified spray, foam and air bubbles for particle-based fluids. The Visual Computer 28(6), 2012
  • Markus Ihmsen, Jens Cornelis, Barbara Solenthaler, Christopher Horvath, and Matthias Teschner. Implicit incompressible SPH. IEEE Transactions on Visualization and Computer Graphics, 20(3):426–435, March 2014.
  • Markus Ihmsen, Jens Orthmann, Barbara Solenthaler, Andreas Kolb, and Matthias Teschner. SPH Fluids in Computer Graphics. In Eurographics 2014 - State of the Art Reports. The Eurographics Association, 2014.
  • M. Jiang, Y. Zhou, R. Wang, R. Southern, J. J. Zhang. Blue noise sampling using an SPH-based method. ACM Transactions on Graphics, 2015
  • Dan Koschier and Jan Bender, "Density Maps for Improved SPH Boundary Handling", In Proceedings of ACM SIGGRAPH / EUROGRAPHICS Symposium on Computer Animation (SCA), 2017
  • Tassilo Kugelstadt, Jan Bender, José Antonio Fernández-Fernández, Stefan Rhys Jeske, Fabian Löschner, and Andreas Longva. Fast Corotated Elastic SPH Solids with Implicit Zero-Energy Mode Control. Proceedings of the ACM on Computer Graphics and Interactive Techniques, 2021
  • Miles Macklin and Matthias Müller. Position based fluids. ACM Trans. Graph., 32(4):104:1–104:12, July 2013.
  • Miles Macklin, Matthias Müller, Nuttapong Chentanez and Tae-Yong Kim. Unified Particle Physics for Real-Time Applications. ACM Trans. Graph., 33(4), 2014
  • A. Peer, C. Gissler, S. Band, and M. Teschner. An Implicit SPH Formulation for Incompressible Linearly Elastic Solids. Computer Graphics Forum, 2017
  • Andreas Peer, Markus Ihmsen, Jens Cornelis, and Matthias Teschner. An Implicit Viscosity Formulation for SPH Fluids. ACM Trans. Graph., 34(4), 2015.
  • Andreas Peer and Matthias Teschner. Prescribed Velocity Gradients for Highly Viscous SPH Fluids with Vorticity Diffusion. IEEE Transactions on Visualization and Computer Graphics, 2016.
  • Hagit Schechter and Robert Bridson. Ghost sph for animating water. ACM Trans. Graph., 31(4):61:1–61:8, July 2012.
  • B. Solenthaler and R. Pajarola. Density Contrast SPH Interfaces. In Proceedings of ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 2008.
  • B. Solenthaler and R. Pajarola. Predictive-corrective incompressible SPH. ACM Trans. Graph., 28(3):40:1–40:6, July 2009.
  • Tetsuya Takahashi, Yoshinori Dobashi, Issei Fujishiro, Tomoyuki Nishita, and Ming C. Lin. Implicit Formulation for SPH-based Viscous Fluids. Computer Graphics Forum, 34, 2015.
  • Marcel Weiler, Dan Koschier and Jan Bender. Projective Fluids. Proceedings of the 9th International Conference on Motion in Games, ACM, 2016, 79-84
  • Marcel Weiler, Dan Koschier, Magnus Brand and Jan Bender. A Physically Consistent Implicit Viscosity Solver for SPH Fluids. Computer Graphics Forum (Eurographics), 37(2), 2018
  • F. Zorilla, M. Ritter, J. Sappl, W. Rauch, M. Harders. Accelerating Surface Tension Calculation in SPH via Particle Classification and Monte Carlo Integration. Computers 9, 23, 2020.

Other research projects using SPlisHSPlasH

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

pySPlisHSPlasH-2.11.4-cp310-cp310-win_amd64.whl (3.7 MB view details)

Uploaded CPython 3.10Windows x86-64

pySPlisHSPlasH-2.11.4-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (4.2 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.12+ x86-64

pySPlisHSPlasH-2.11.4-cp39-cp39-win_amd64.whl (3.7 MB view details)

Uploaded CPython 3.9Windows x86-64

pySPlisHSPlasH-2.11.4-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (4.2 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.12+ x86-64

pySPlisHSPlasH-2.11.4-cp38-cp38-win_amd64.whl (3.7 MB view details)

Uploaded CPython 3.8Windows x86-64

pySPlisHSPlasH-2.11.4-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (4.2 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ x86-64

pySPlisHSPlasH-2.11.4-cp37-cp37m-win_amd64.whl (3.7 MB view details)

Uploaded CPython 3.7mWindows x86-64

pySPlisHSPlasH-2.11.4-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (4.2 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64

pySPlisHSPlasH-2.11.4-cp36-cp36m-win_amd64.whl (3.7 MB view details)

Uploaded CPython 3.6mWindows x86-64

pySPlisHSPlasH-2.11.4-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (4.2 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ x86-64

pySPlisHSPlasH-2.11.4-cp35-cp35m-win_amd64.whl (3.7 MB view details)

Uploaded CPython 3.5mWindows x86-64

pySPlisHSPlasH-2.11.4-cp27-cp27m-win_amd64.whl (3.7 MB view details)

Uploaded CPython 2.7mWindows x86-64

File details

Details for the file pySPlisHSPlasH-2.11.4-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.4-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 9104f12645dfb714a43723bf0ef0a74fd892b2d292012ed42127f2b85765f872
MD5 ccc60a5c62bfbc05352e4b5f66e5f6db
BLAKE2b-256 20ed2ec5df2140c41603dec184208fb378856315d4328e56e3e9d979e7703151

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.4-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.4-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 fe4e097fd3a27ff090c524876f766409732f7ba60528af6ce007b40870a267bc
MD5 1a652e68247d987b68eb9ddcd64b7e8a
BLAKE2b-256 31068b5206f6037db81f3b6f7ada49b9c1bf85c8d3a86799f82b18dbc0e5046d

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.4-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.4-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 67e7132d7653b7a58efd54926c0d0793659a43fba10e9f2bef5279331848356e
MD5 1a552debc408cb8586b5626a8705b5a1
BLAKE2b-256 d05b589f5211b7ffbd3713dec51213ffd76d17d4bdd7c48b43270a741bae9b2e

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.4-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.4-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 e03aa757f223a6575cd56e656aa6c01978d0b22a2a4bc43b6a2b9a23c2a95efc
MD5 59453ec203b1997d8ad8b94b009472ea
BLAKE2b-256 6d2e1563b509a0a4813642d44f33add86c41f9285de51f551562d0f846b5d587

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.4-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.4-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 d1e8441a9b4cbce10ee66872971d5e96931ee6089ce8dc80c48b985cc1531b33
MD5 0f7d38d64d63fa8681f5c2ed856112f4
BLAKE2b-256 062cb4e1489dd85a06a9a5edc3ad938af130efa4afc478321644798653a706d9

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.4-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.4-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 16f5c4143c3cf7204e6a53306c8cb2e78d54e4913c3e02b4011a5267f7418562
MD5 64db7221d7c0258fe6c9db93496a84f2
BLAKE2b-256 31431c80747c13acb9e689c473f8f0a18256517718c3d28813a0ae2505534c2a

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.4-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.4-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 e8c3a89cf1f1482630963e85ccd66b1ac87ecdc76b1aa881e2c6e0890e45bcb7
MD5 ca6532679f48b0a6f10947a5e7d5c36f
BLAKE2b-256 59b6b21572f68cdebab7116193daf5f54c37a0eaf604167c6c8bd8f08cf6665c

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.4-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.4-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 d3bd2cd1250634a701fe98206ffb1aeeabfa29ec365694aae39387dcc52c655a
MD5 0c4da4c6c8a142dac1df6f2db0031ec9
BLAKE2b-256 ef479b684fe537a18f861500740a62b2890c97837f06f38c3061bef76c38f3c3

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.4-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: pySPlisHSPlasH-2.11.4-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 3.7 MB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.3 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.10.0 urllib3/1.26.12 tqdm/4.64.1 importlib-metadata/4.8.3 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.5 CPython/3.6.8

File hashes

Hashes for pySPlisHSPlasH-2.11.4-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 280e5b4dc06655a70f066e5d392ce97ad448989e603782f6acebf08ec0ce44d7
MD5 2f700f1fed12acc1d10e53f957c723e7
BLAKE2b-256 81de283342c57ba31408ae692488e695048f970e75ab71d20d9d0827d41253fb

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.4-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.4-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 991a942e489d80a9ee4fc7c769872ad5ede7bee476c87f51b8f2f4ac258a3505
MD5 4e8e0199389b883e65ca0044dbc7b7fa
BLAKE2b-256 54269960c19856692dc3bd27eacf14118f04529e5b0431b4bbae7fa6e9275556

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.4-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: pySPlisHSPlasH-2.11.4-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 3.7 MB
  • Tags: CPython 3.5m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.8.2 requests/2.25.1 setuptools/50.3.2 requests-toolbelt/0.10.0 tqdm/4.64.1 CPython/3.5.4

File hashes

Hashes for pySPlisHSPlasH-2.11.4-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 141b7a0425edcaf17678c8c8653b8373e2c134ee95f50ea06a8652832b166fb9
MD5 32920f2551270f44426d350fde71b5c5
BLAKE2b-256 890952f73456cc75a3d655f9370e31467a867329447f0a63fd190acd515e8048

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.4-cp27-cp27m-win_amd64.whl.

File metadata

  • Download URL: pySPlisHSPlasH-2.11.4-cp27-cp27m-win_amd64.whl
  • Upload date:
  • Size: 3.7 MB
  • Tags: CPython 2.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.8.3 requests/2.27.1 setuptools/44.1.1 requests-toolbelt/0.10.0 tqdm/4.64.1 CPython/2.7.18

File hashes

Hashes for pySPlisHSPlasH-2.11.4-cp27-cp27m-win_amd64.whl
Algorithm Hash digest
SHA256 b870fd18301c3930003b720f53f2fab3b0817765b15adca3b6e1dc68af8db493
MD5 c71ac28b97b1409f3d2e88c3f784df49
BLAKE2b-256 9e46892f762d5f7dfe3334b879d3020657516085fbf7668235d439137ce9c293

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page