Skip to main content

Efficient rigid body dynamics (python bindings)

Project description

Pinocchio Logo

License Build Status Coverage Report Conda Downloads Conda Version Anaconda-Server Badge

Pinocchio instantiates the state-of-the-art Rigid Body Algorithms for poly-articulated systems based on revisited Roy Featherstone's algorithms. Besides, Pinocchio provides the analytical derivatives of the main Rigid-Body Algorithms like the Recursive Newton-Euler Algorithm or the Articulated-Body Algorithm.

Pinocchio is first tailored for robotics applications, but it can be used in extra contexts (biomechanics, computer graphics, vision, etc.). It is built upon Eigen for linear algebra and FCL for collision detection. Pinocchio comes with a Python interface for fast code prototyping, directly accessible through Conda.

Pinocchio is now at the heart of various robotics softwares as Crocoddyl, an open-source and efficient Differential Dynamic Programming solver for robotics, the Stack-of-Tasks, an open-source and versatile hierarchical controller framework or the Humanoid Path Planner, an open-source software for Motion and Manipulation Planning.

If you want to learn more on Pinocchio internal behaviors and main features, we invite you to read the related paper.

If you want to directly dive into Pinocchio, only one single line is sufficient (assuming you have Conda):

conda install pinocchio -c conda-forge

News

August 2020: We are hiring! We are looking for a talented C++/Python software developer to enhance and promote Pinocchio inside the robotics community and beyond. Please contact @jcarpent for further details.

Pinocchio main features

Pinocchio is fast:

  • C++ template library,
  • cache friendly,
  • automatic code generation support via CppADCodeGen.

Pinocchio is versatile, implementing basic and more advanced rigid body dynamics algorithms:

  • forward kinematics and its analytical derivatives,
  • forward/inverse dynamics and their analytical derivatives,
  • centroidal dynamics and its analytical derivatives,
  • support of multiple precision arithmetic via Boost.Multiprecision or any similar framework,
  • computations of kinematic and dynamic regressors for system identification and more,
  • and much more with the support of modern and open source Automatic Differentiation frameworks like CppAD or CasADi.

Pinocchio is flexible:

  • header only,
  • C++ 98/03/11/14/17/20 compliant.

Pinocchio is extensible.
Pinocchio is multi-thread friendly.
Pinocchio is reliable and extensively tested (unit-tests, simulations and real world robotics applications).
Pinocchio is supported and tested on Windows, Mac OS X, Unix and Linux (see build status here).

Performances

Pinocchio exploits at best the sparsity induced by the kinematic tree of robotics systems. Thanks to modern programming language paradigms, Pinocchio is able to unroll most of the computations directly at compile time, allowing to achieve impressive performances for a large range of robots, as illustrated by the plot below, obtained on a standard laptop equipped with an Intel Core i7 CPU @ 2.4 GHz.

Pinocchio Logo

For other benchmarks, and mainly the capacity of Pinocchio to exploit at best your CPU capacities using advanced code generation techniques, we refer to the technical paper. In addition, the introspection done here may also help you to understand and compare the performances of the modern rigid body dynamics librairies.

Ongoing developments

If you want to follow the current developments, you can directly refer to the devel branch. The master branch only contains latest release. Any new Pull Request should then be submitted on the devel branch.

Installation

Pinocchio can be easily installed on various Linux (Ubuntu, Fedora, etc.) and Unix distributions (Mac OS X, BSD, etc.). Please refer to the installation procedure.

If you only need the Python bindings of Pinocchio, you may prefer to install it through Conda. Please follow the procedure described here.

Pinocchio is also deployed on ROS, you may follow its deployment status on Melodic or Kinetic.

Documentation

The online Pinocchio documentation of the last release is available here.

Examples

We provide some basic examples on how to use Pinocchio in Python in the examples/python directory. Additional examples introducing Pinocchio are also available in the documentation

Tutorials

Pinocchio comes with a large bunch of tutorials aiming at introducing the basic tools for robotics control. The content of the tutorials is described here.

Visualization

Pinocchio provides support for many open-source and free visualizers:

  • Gepetto Viewer: a C++ viewer based on OpenSceneGraph with Python bindings and Blender export. See here for a C++ example on mixing Pinocchio and Gepetto Viewer.
  • Meshcat: supporting visualization in Python and which can be embeded inside any browser.
  • Panda3d: supporting visualization in Python and which can be embeded inside any browser.

Many external viewers can also be integrated. See example here for more information.

Citing Pinocchio

To cite Pinocchio in your academic research, please use the following bibtex lines:

@misc{pinocchioweb,
   author = {Justin Carpentier and Florian Valenza and Nicolas Mansard and others},
   title = {Pinocchio: fast forward and inverse dynamics for poly-articulated systems},
   howpublished = {https://stack-of-tasks.github.io/pinocchio},
   year = {2015--2021}
}

and the following one for the reference to the paper introducing Pinocchio:

@inproceedings{carpentier2019pinocchio,
   title={The Pinocchio C++ library -- A fast and flexible implementation of rigid body dynamics algorithms and their analytical derivatives},
   author={Carpentier, Justin and Saurel, Guilhem and Buondonno, Gabriele and Mirabel, Joseph and Lamiraux, Florent and Stasse, Olivier and Mansard, Nicolas},
   booktitle={IEEE International Symposium on System Integrations (SII)},
   year={2019}
}

The algorithms for the analytical derivatives of rigid-body dynamics algorithms are detailed here:

@inproceedings{carpentier2018analytical,
  title = {Analytical Derivatives of Rigid Body Dynamics Algorithms},
  author = {Carpentier, Justin and Mansard, Nicolas},
  booktitle = {Robotics: Science and Systems},
  year = {2018}
}

Questions and Issues

You have a question or an issue? You may either directly open a new issue or use the mailing list pinocchio@laas.fr.

Credits

The following people have been involved in the development of Pinocchio and are warmly thanked for their contributions:

If you have taken part to the development of Pinocchio, feel free to add your name and contribution in this list.

Acknowledgments

The development of Pinocchio is actively supported by the Gepetto team @LAAS-CNRS and the Willow team @INRIA.

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.

pin-2.6.0-cp39-cp39-manylinux_2_24_x86_64.whl (13.0 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.24+ x86-64

pin-2.6.0-cp38-cp38-manylinux_2_24_x86_64.whl (13.0 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.24+ x86-64

pin-2.6.0-cp37-cp37m-manylinux_2_24_x86_64.whl (13.0 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.24+ x86-64

pin-2.6.0-cp36-cp36m-manylinux_2_24_x86_64.whl (13.0 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.24+ x86-64

pin-2.6.0-cp35-cp35m-manylinux_2_24_x86_64.whl (13.0 MB view details)

Uploaded CPython 3.5mmanylinux: glibc 2.24+ x86-64

pin-2.6.0-cp27-cp27mu-manylinux_2_24_x86_64.whl (13.0 MB view details)

Uploaded CPython 2.7mumanylinux: glibc 2.24+ x86-64

pin-2.6.0-2-cp39-cp39-manylinux_2_24_x86_64.whl (5.3 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.24+ x86-64

pin-2.6.0-2-cp38-cp38-manylinux_2_24_x86_64.whl (5.3 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.24+ x86-64

pin-2.6.0-2-cp37-cp37m-manylinux_2_24_x86_64.whl (5.3 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.24+ x86-64

pin-2.6.0-2-cp36-cp36m-manylinux_2_24_x86_64.whl (5.3 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.24+ x86-64

pin-2.6.0-2-cp27-cp27mu-manylinux_2_24_x86_64.whl (5.3 MB view details)

Uploaded CPython 2.7mumanylinux: glibc 2.24+ x86-64

pin-2.6.0-1-cp39-cp39-manylinux_2_24_x86_64.whl (5.3 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.24+ x86-64

pin-2.6.0-1-cp38-cp38-manylinux_2_24_x86_64.whl (5.3 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.24+ x86-64

pin-2.6.0-1-cp37-cp37m-manylinux_2_24_x86_64.whl (5.3 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.24+ x86-64

pin-2.6.0-1-cp36-cp36m-manylinux_2_24_x86_64.whl (5.3 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.24+ x86-64

pin-2.6.0-1-cp35-cp35m-manylinux_2_24_x86_64.whl (5.3 MB view details)

Uploaded CPython 3.5mmanylinux: glibc 2.24+ x86-64

pin-2.6.0-1-cp27-cp27mu-manylinux_2_24_x86_64.whl (5.3 MB view details)

Uploaded CPython 2.7mumanylinux: glibc 2.24+ x86-64

File details

Details for the file pin-2.6.0-cp39-cp39-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-cp39-cp39-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 13.0 MB
  • Tags: CPython 3.9, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.3

File hashes

Hashes for pin-2.6.0-cp39-cp39-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 deb2b5539693a719ee97d548c14ffea7e387223aa3846304993cf2e5d5751dc6
MD5 f32ea9885b4e125c69313ceb7eacecf4
BLAKE2b-256 f553c008e58e63c3ffb8264f71b2ddd36ec92217b07cb3a99dc494d3171de42a

See more details on using hashes here.

File details

Details for the file pin-2.6.0-cp38-cp38-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-cp38-cp38-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 13.0 MB
  • Tags: CPython 3.8, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.3

File hashes

Hashes for pin-2.6.0-cp38-cp38-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 9668faf3a8bdf0a5a59581ad72c6be0f6972a3c3f0c2b74f05c9d93b3bb966ac
MD5 c150a8fd5aea7ff44368b7b6934915ca
BLAKE2b-256 6479caeae5a5f0f836ae155236796e22ab351e899e71924bb245690abf782f47

See more details on using hashes here.

File details

Details for the file pin-2.6.0-cp37-cp37m-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-cp37-cp37m-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 13.0 MB
  • Tags: CPython 3.7m, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.3

File hashes

Hashes for pin-2.6.0-cp37-cp37m-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 ae4d633c383c0ebe2dd66414424eb48533969bc540fd15408fbf0f11a647f00f
MD5 58df9b3144e13e290665f4f2d4dcafb0
BLAKE2b-256 58c4968d67bc27777779f0d6c4c3c0e4a697d231270c62ad92275210535aa64b

See more details on using hashes here.

File details

Details for the file pin-2.6.0-cp36-cp36m-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-cp36-cp36m-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 13.0 MB
  • Tags: CPython 3.6m, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.3

File hashes

Hashes for pin-2.6.0-cp36-cp36m-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 561f08983d8b869962781eb97d4f0322fcd3b118d6d925dc15c75bfee320a090
MD5 3096b64050680786fc3f2ab842db8806
BLAKE2b-256 1da84da4aadfe5297bcda4593570bb4a7a1c086a7d1b2ac8262dc3564c3e434d

See more details on using hashes here.

File details

Details for the file pin-2.6.0-cp35-cp35m-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-cp35-cp35m-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 13.0 MB
  • Tags: CPython 3.5m, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.3

File hashes

Hashes for pin-2.6.0-cp35-cp35m-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 4fb6ec354f43cf37ddb848eaab911d7806d7fc92574a4649175fed3ebb18fd91
MD5 1ef33b0278ea1f3faec3e915be78965f
BLAKE2b-256 60db3ae8eead0bdea0aea9993a79aafecbbe41e92d71a191013d30656c28a435

See more details on using hashes here.

File details

Details for the file pin-2.6.0-cp27-cp27mu-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-cp27-cp27mu-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 13.0 MB
  • Tags: CPython 2.7mu, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.3

File hashes

Hashes for pin-2.6.0-cp27-cp27mu-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 38b9e36a40f685f589e6e51a3eee1341bdef1870cbad7011008a405222f64a15
MD5 d82a0b6da1dd266e3ba19c18ca893ba9
BLAKE2b-256 aaff962a547f708bcfe8fdd8f82e29ef9f87990ab61d4fb290043e36661cab86

See more details on using hashes here.

File details

Details for the file pin-2.6.0-2-cp39-cp39-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-2-cp39-cp39-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 5.3 MB
  • Tags: CPython 3.9, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.5

File hashes

Hashes for pin-2.6.0-2-cp39-cp39-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 990ba1307c55de36eb5f5de011aef1b47cd7b5a6ba39e7805a8b51fb21c74597
MD5 07c2cc7515fc734f8056f6b5476529ed
BLAKE2b-256 26c9a9fff7ae3411511820bda597647d3d6b428a844e360fbe95be041b677784

See more details on using hashes here.

File details

Details for the file pin-2.6.0-2-cp38-cp38-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-2-cp38-cp38-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 5.3 MB
  • Tags: CPython 3.8, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.5

File hashes

Hashes for pin-2.6.0-2-cp38-cp38-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 aed85acb311c96df6a58b22b3a52011796c9a6fcdd33c822162558d1b62ed15d
MD5 1c5f1962f55ae20892e3788a6ce37aff
BLAKE2b-256 f6dfeafad91e3d7a92cd01fb73c5c9344042720dedac01fefe7b522d05281ace

See more details on using hashes here.

File details

Details for the file pin-2.6.0-2-cp37-cp37m-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-2-cp37-cp37m-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 5.3 MB
  • Tags: CPython 3.7m, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.5

File hashes

Hashes for pin-2.6.0-2-cp37-cp37m-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 bffecee8d3b6b53763a7a1a17004e5bda3390493fcb29ebb303be74a338ccc58
MD5 86500a5997a0bf2b827fbcba772a547a
BLAKE2b-256 3369699f519aede0400f772d96b070fb2ba9fe433c81be4121e32d457489eeeb

See more details on using hashes here.

File details

Details for the file pin-2.6.0-2-cp36-cp36m-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-2-cp36-cp36m-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 5.3 MB
  • Tags: CPython 3.6m, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.5

File hashes

Hashes for pin-2.6.0-2-cp36-cp36m-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 52ec1f457a4aeb3742d87274be7b7487ff0f931be7b11288b3ed2fce89057253
MD5 42f6fe152fec151e82c1f87bd7dcc2af
BLAKE2b-256 3a5a370fe1efcf0de02f69cd53fc423bcb630dd43a860acb7487f93dc522393f

See more details on using hashes here.

File details

Details for the file pin-2.6.0-2-cp27-cp27mu-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-2-cp27-cp27mu-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 5.3 MB
  • Tags: CPython 2.7mu, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.5

File hashes

Hashes for pin-2.6.0-2-cp27-cp27mu-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 a57027ed30c8d874aa0102ea7f14da0a19060b0d97c5354fccedb2454069c69e
MD5 563b0d67ae887c1e4176f5b0cb9159b3
BLAKE2b-256 75582b22e1cf59c8d9707493462bfe6cc9ea0cd34fcf252ee9090380bcbe6716

See more details on using hashes here.

File details

Details for the file pin-2.6.0-1-cp39-cp39-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-1-cp39-cp39-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 5.3 MB
  • Tags: CPython 3.9, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.3

File hashes

Hashes for pin-2.6.0-1-cp39-cp39-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 116af89dffa8d4415bdb588b987320b44910a371afaa0be8b6737e448996a30a
MD5 5685142a88481d52fdbd5b8d5cbe42d8
BLAKE2b-256 61dfaa820a7221a400763d455bf2c7c5047e17fa93e1c8339b0f9e35db7922e0

See more details on using hashes here.

File details

Details for the file pin-2.6.0-1-cp38-cp38-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-1-cp38-cp38-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 5.3 MB
  • Tags: CPython 3.8, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.3

File hashes

Hashes for pin-2.6.0-1-cp38-cp38-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 f9fa4083a55465567988b0c776a72121e36e239380572c0804322f90e053f7c3
MD5 5f0539693f1248c1882ded28e8ee7519
BLAKE2b-256 2091dc891aa27fdded6be3ed7f7c33573a8e1a1f3fb9ea1ed83133e9e1327afb

See more details on using hashes here.

File details

Details for the file pin-2.6.0-1-cp37-cp37m-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-1-cp37-cp37m-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 5.3 MB
  • Tags: CPython 3.7m, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.3

File hashes

Hashes for pin-2.6.0-1-cp37-cp37m-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 9b5f7d8d8cff94f66d9f2ed936d0a47fc0d881b8431a67c1ce1d34ec59b47c5a
MD5 52dd3b4f4d496110822ad12d580bab1a
BLAKE2b-256 df9c62a74997b0280b6d723818074894e38b8c5a9ebeb6b77a7032cecd64c55f

See more details on using hashes here.

File details

Details for the file pin-2.6.0-1-cp36-cp36m-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-1-cp36-cp36m-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 5.3 MB
  • Tags: CPython 3.6m, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.3

File hashes

Hashes for pin-2.6.0-1-cp36-cp36m-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 a6800c11dadbc68fb04ed5676b6e0aed786fa467b4cee306cb06e763d2b3de0f
MD5 f22f6013c75dec67a49ae46bc8cdb08e
BLAKE2b-256 413d32e925d4c1d0198abbfb33a64cc3757a97c030a32848b2da61b737d35156

See more details on using hashes here.

File details

Details for the file pin-2.6.0-1-cp35-cp35m-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-1-cp35-cp35m-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 5.3 MB
  • Tags: CPython 3.5m, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.3

File hashes

Hashes for pin-2.6.0-1-cp35-cp35m-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 cdd0dd3acf6511a89915d131c1d2582ccb3df178928b992c3789e018ca8e9945
MD5 51f35853c1fda508cf65d15b60284149
BLAKE2b-256 fa37c124e94ee30d67defc9de98e02f3cf55dff094375578c258167b51dbb6bc

See more details on using hashes here.

File details

Details for the file pin-2.6.0-1-cp27-cp27mu-manylinux_2_24_x86_64.whl.

File metadata

  • Download URL: pin-2.6.0-1-cp27-cp27mu-manylinux_2_24_x86_64.whl
  • Upload date:
  • Size: 5.3 MB
  • Tags: CPython 2.7mu, manylinux: glibc 2.24+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.54.0 CPython/3.9.3

File hashes

Hashes for pin-2.6.0-1-cp27-cp27mu-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 7d7d48088bf38dcd3925e3a27bc503c615cb16bf2248dc9e74c3cabec25fec62
MD5 0f4cc082c05c765bb94019186db7000a
BLAKE2b-256 71cb243f40323c31c451bf91f218e67b24dbbbbe9dee53db38873e00f0ddb7b0

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