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-2.11.5-cp310-cp310-win_amd64.whl (3.7 MB view details)

Uploaded CPython 3.10Windows x86-64

pySPlisHSPlasH-2.11.5-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-2.11.5-cp39-cp39-win_amd64.whl (3.7 MB view details)

Uploaded CPython 3.9Windows x86-64

pySPlisHSPlasH-2.11.5-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-2.11.5-cp38-cp38-win_amd64.whl (3.7 MB view details)

Uploaded CPython 3.8Windows x86-64

pySPlisHSPlasH-2.11.5-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-2.11.5-cp37-cp37m-win_amd64.whl (3.7 MB view details)

Uploaded CPython 3.7mWindows x86-64

pySPlisHSPlasH-2.11.5-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-2.11.5-cp36-cp36m-win_amd64.whl (3.7 MB view details)

Uploaded CPython 3.6mWindows x86-64

pySPlisHSPlasH-2.11.5-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-2.11.5-cp35-cp35m-win_amd64.whl (3.7 MB view details)

Uploaded CPython 3.5mWindows x86-64

pySPlisHSPlasH-2.11.5-cp27-cp27m-win_amd64.whl (3.7 MB view details)

Uploaded CPython 2.7mWindows x86-64

File details

Details for the file pySPlisHSPlasH-2.11.5-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.5-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 825918775bf17c3b9a75c2aea2a536465156160a873b45a7698e0e79b5b7227a
MD5 735631e4bf9a4698054f280081d4484e
BLAKE2b-256 5e6c5fdc01199725e0b956da57268eb8410ca671a6d7158305721482b7956835

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.5-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.5-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 41e4ab81b0426fef1a5f3e4edeb045b81e533deac3436ababa0004531a7c1878
MD5 0ff9ab62b91300e5ac3b89ce70bd9ead
BLAKE2b-256 325cbf13782448726987daa2a4228afa27d8f8c3a9211d6a232012e9e4025888

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.5-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.5-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 335014209c3e88e432f6311e1a8bb529d8a04a87e51795c5868b3d29799d761a
MD5 5dc862b2d9158fca5dd81d244cbf9f1a
BLAKE2b-256 622084771100f72a0ed7536e9628e671fa8cfbf55bb0c3a9373e86487979fa6d

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.5-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.5-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 05194c8adfb49ef1bfceb3c27eb846a634498712a4389d141dd0a501c4a93184
MD5 32c6b03e228972f2439cbec027d35534
BLAKE2b-256 e0b7ab538ea38e0a8997b0cea56bd6f18f31ad2621664c0bc7fad4e7cd0935fd

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.5-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.5-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 3c1b199078312229fd11ef82483c627552a6c00d9fc7eee68e5f48e3a1fa6c9e
MD5 86b569bd0882b842d4a025feee4d4894
BLAKE2b-256 44ff184f6cac9990cc77dc88eb777ef91ef31626bc2dee1dafe6b736039f6897

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.5-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.5-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 26fd7a1dfdce4f0438ea8cda3a2dce515e55771c2d2e144b5f5931d379b4b928
MD5 274a6ae0b2c0e94128b90ed287fcca2e
BLAKE2b-256 8ee2189208d8afe92f9475c43c7a3f4f36572a0dcb6aa61decfdcc38cca61f52

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.5-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.5-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 7e1eedc29311dfb8ea9d42ae7a110f2e5aa7a2568e5b002f216166e5c686f0cf
MD5 3cfe43cb117385ac46166f1acdebb107
BLAKE2b-256 f9162cfce6528f44522de78076935e7cd41d16d8ac7052d1f6f46130aabf9857

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.5-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.5-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 c61c096dcabd575af606f7c5c6edf44cc2778fccbe03e86bd4e94c6adf907b8a
MD5 75620e51414cae1b6d5d0776091e2963
BLAKE2b-256 15f3079db043c065f4726c55886e34b2b5ddd1ef2278217eff0266a8b4682b5f

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.5-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: pySPlisHSPlasH-2.11.5-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/0.10.1 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-2.11.5-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 fc5be39ff2b7ec4af7b98a7ce4d8f8c8557f33c20efefb97ba18c5bf2fa08a7e
MD5 3b0a0bb131e47c74b0846a5a91fef545
BLAKE2b-256 66fc1b4f638ac72fd03d5e06439d9327239935e044e45ebea98de0e69479ce21

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.5-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for pySPlisHSPlasH-2.11.5-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 1c2d44c8e61f6487501014aac5239884934133506dc8047839c05eb5b5a0dc60
MD5 33e4885d1b25b05ac5bfd3630f0f062d
BLAKE2b-256 0f51ac2a8746302febab32fcfb7101fa32c32d029a2d2bd2d7085046a5c77a05

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.5-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: pySPlisHSPlasH-2.11.5-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/0.10.1 tqdm/4.64.1 CPython/3.5.4

File hashes

Hashes for pySPlisHSPlasH-2.11.5-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 13c4333f802248779e5a3f263ee3332f1f2ef8f79c9edbb88a35ee6f5f142762
MD5 29c1d4054b9a5421369eb9903899398d
BLAKE2b-256 5145627a7e5bc190d7e2fa09beb278ed626d27318f6d333526f15697cd702930

See more details on using hashes here.

File details

Details for the file pySPlisHSPlasH-2.11.5-cp27-cp27m-win_amd64.whl.

File metadata

  • Download URL: pySPlisHSPlasH-2.11.5-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/0.10.1 tqdm/4.64.1 CPython/2.7.18

File hashes

Hashes for pySPlisHSPlasH-2.11.5-cp27-cp27m-win_amd64.whl
Algorithm Hash digest
SHA256 8ba47f7a8974c88f1f76c14639c3bee7f5399a48bf144df6bd2b85766f650fe8
MD5 86af09b198c092a4fc50fc5f18c89ddf
BLAKE2b-256 d1c9d0ba39645744e0b8b1a8455613d29f8694226566f75f65076a7626d0f1da

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