Skip to main content

PLATE RECognition In PYthon

Project description

logo

platerecipy: a package for PLATE RECognition In PYthon

platerecipy is a tool for detecting candidate plates on global geophysical datasets. It analyzes the surface to identify diffuse and non-conforming regions, as well as regions with low confidence in plate assignment.

Supported platforms

Though platerecipy is fundamentally a Python package, it also relies on backend functionalities that are implemented in C. Linux is the main operating system for platerecipy. However, expect for a number of optimizations (e.g., multithreaded C functions), platerecipy is now available via pip on Windows systems.

Installation

Version releases are made available on PyPI so that platerecipy can be installed using pip on the shell as follows:

pip install platerecipy

User guide

platerecipy's documentation is moved to platerecipy.readthedocs.io!

For a detailed explanation and illustration of platerecipy's core functionalities, please refer to:

Javaheri, P., & Lowman, J. P. (2026). A random walker algorithm for plate boundary detection in spherical mantle convection models and global geophysical data sets: Application to Euler vector determination. Journal of Geophysical Research: Solid Earth, 131, e2025JB032259. https://doi.org/10.1029/2025JB032259

As a demonstration, assuming a given input_xs, input_ys, input_zs, and
input_field (all numpy arrays), using platerecipy is as simple as follows:

from platerecipy.model import PlateModel
from platerecipy.grid import SphericalGrid

input_xs    = # to be specified ...
input_ys    = # to be specified ...
input_zs    = # to be specified ...
input_field = # to be specified ...

# generating a consistent grid for interpolation
grid = SphericalGrid(input_xs, input_ys, input_zs)

# interpolating an input field
field = grid.interpolate_field(input_field)

# initializing a plate model
m = PlateModel(grid)

# stacking the interpolated field
m.stack_field(field, take_log=True)

# finding plates on the stacked field
m.find_plates(
    boundary_quantile     = 0.9,            # threshold for the boundaries 
    separation_tolerance  = 4*3.1416/180.,  # 4 degrees for separation tolerance
    RW_beta               = 200,            # RW beta (for feature sharpness)
    min_marker_size       = 100             # to filter out micro plates
)

# outputting as a ParaView readable .vtk file
from platerecipy import io
io.save_as_vtk(m)

Citing platerecipy

If this package has been useful to your research, please cite the original paper:

Javaheri, P., & Lowman, J. P. (2026). A random walker algorithm for plate boundary detection in spherical mantle convection models and global geophysical data sets: Application to Euler vector determination. Journal of Geophysical Research: Solid Earth, 131, e2025JB032259. https://doi.org/10.1029/2025JB032259

@article{platerecipy,
author = {Javaheri, P. and Lowman, J. P.},
title = {{A random walker algorithm for plate boundary detection in spherical mantle convection models and global geophysical data sets: Application to Euler vector determination}},
journal = {Journal of Geophysical Research: Solid Earth},
volume = {131},
number = {3},
pages = {e2025JB032259},
keywords = {plate tectonics, plate modeling, Euler vector, diffuse zones, mantle convection, strain-rate},
doi = {https://doi.org/10.1029/2025JB032259},
url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2025JB032259},
eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2025JB032259},
note = {e2025JB032259 2025JB032259},
year = {2026}
}

as well as the software version:

P. Javaheri. (2025). pjavaheri/platerecipy: Release of version 1.0.0 (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.15625716

@software{p_javaheri_2025_15625716,
  author       = {P. Javaheri},
  title        = {pjavaheri/platerecipy: Release of version 1.0.0},
  month        = jun,
  year         = 2025,
  publisher    = {Zenodo},
  version      = {v1.0.0},
  doi          = {10.5281/zenodo.15625716},
  url          = {https://doi.org/10.5281/zenodo.15625716},
}

Please note that platerecipy is a platform under development. Depending on your installed version, the software version citation should point to the most recent prior release on Zenodo.


Developed by Pejvak Javaheri, pejvak.javaheri@mail.utoronto.ca.

Project details


Download files

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

Source Distribution

platerecipy-2.0.2.tar.gz (34.9 kB view details)

Uploaded Source

Built Distributions

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

platerecipy-2.0.2-cp314-cp314t-win_amd64.whl (51.7 kB view details)

Uploaded CPython 3.14tWindows x86-64

platerecipy-2.0.2-cp314-cp314t-win32.whl (46.8 kB view details)

Uploaded CPython 3.14tWindows x86

platerecipy-2.0.2-cp314-cp314t-musllinux_1_2_x86_64.whl (75.1 kB view details)

Uploaded CPython 3.14tmusllinux: musl 1.2+ x86-64

platerecipy-2.0.2-cp314-cp314t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl (76.0 kB view details)

Uploaded CPython 3.14tmanylinux: glibc 2.28+ x86-64manylinux: glibc 2.5+ x86-64

platerecipy-2.0.2-cp314-cp314t-macosx_11_0_arm64.whl (46.4 kB view details)

Uploaded CPython 3.14tmacOS 11.0+ ARM64

platerecipy-2.0.2-cp314-cp314-win_amd64.whl (51.7 kB view details)

Uploaded CPython 3.14Windows x86-64

platerecipy-2.0.2-cp314-cp314-win32.whl (46.8 kB view details)

Uploaded CPython 3.14Windows x86

platerecipy-2.0.2-cp314-cp314-musllinux_1_2_x86_64.whl (75.1 kB view details)

Uploaded CPython 3.14musllinux: musl 1.2+ x86-64

platerecipy-2.0.2-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl (76.0 kB view details)

Uploaded CPython 3.14manylinux: glibc 2.28+ x86-64manylinux: glibc 2.5+ x86-64

platerecipy-2.0.2-cp314-cp314-macosx_11_0_arm64.whl (46.4 kB view details)

Uploaded CPython 3.14macOS 11.0+ ARM64

platerecipy-2.0.2-cp313-cp313-win_amd64.whl (50.9 kB view details)

Uploaded CPython 3.13Windows x86-64

platerecipy-2.0.2-cp313-cp313-win32.whl (46.1 kB view details)

Uploaded CPython 3.13Windows x86

platerecipy-2.0.2-cp313-cp313-musllinux_1_2_x86_64.whl (75.1 kB view details)

Uploaded CPython 3.13musllinux: musl 1.2+ x86-64

platerecipy-2.0.2-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl (76.0 kB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ x86-64manylinux: glibc 2.5+ x86-64

platerecipy-2.0.2-cp313-cp313-macosx_11_0_arm64.whl (46.4 kB view details)

Uploaded CPython 3.13macOS 11.0+ ARM64

platerecipy-2.0.2-cp312-cp312-win_amd64.whl (50.9 kB view details)

Uploaded CPython 3.12Windows x86-64

platerecipy-2.0.2-cp312-cp312-win32.whl (46.1 kB view details)

Uploaded CPython 3.12Windows x86

platerecipy-2.0.2-cp312-cp312-musllinux_1_2_x86_64.whl (75.1 kB view details)

Uploaded CPython 3.12musllinux: musl 1.2+ x86-64

platerecipy-2.0.2-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl (76.0 kB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ x86-64manylinux: glibc 2.5+ x86-64

platerecipy-2.0.2-cp312-cp312-macosx_11_0_arm64.whl (46.4 kB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

platerecipy-2.0.2-cp311-cp311-win_amd64.whl (50.9 kB view details)

Uploaded CPython 3.11Windows x86-64

platerecipy-2.0.2-cp311-cp311-win32.whl (46.1 kB view details)

Uploaded CPython 3.11Windows x86

platerecipy-2.0.2-cp311-cp311-musllinux_1_2_x86_64.whl (75.1 kB view details)

Uploaded CPython 3.11musllinux: musl 1.2+ x86-64

platerecipy-2.0.2-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl (75.9 kB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ x86-64manylinux: glibc 2.5+ x86-64

platerecipy-2.0.2-cp311-cp311-macosx_11_0_arm64.whl (46.4 kB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

platerecipy-2.0.2-cp310-cp310-win_amd64.whl (50.9 kB view details)

Uploaded CPython 3.10Windows x86-64

platerecipy-2.0.2-cp310-cp310-win32.whl (46.1 kB view details)

Uploaded CPython 3.10Windows x86

platerecipy-2.0.2-cp310-cp310-musllinux_1_2_x86_64.whl (75.0 kB view details)

Uploaded CPython 3.10musllinux: musl 1.2+ x86-64

platerecipy-2.0.2-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl (75.9 kB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ x86-64manylinux: glibc 2.5+ x86-64

platerecipy-2.0.2-cp310-cp310-macosx_11_0_arm64.whl (46.4 kB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

platerecipy-2.0.2-cp39-cp39-win_amd64.whl (50.8 kB view details)

Uploaded CPython 3.9Windows x86-64

platerecipy-2.0.2-cp39-cp39-win32.whl (46.1 kB view details)

Uploaded CPython 3.9Windows x86

platerecipy-2.0.2-cp39-cp39-musllinux_1_2_x86_64.whl (75.0 kB view details)

Uploaded CPython 3.9musllinux: musl 1.2+ x86-64

platerecipy-2.0.2-cp39-cp39-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl (75.9 kB view details)

Uploaded CPython 3.9manylinux: glibc 2.28+ x86-64manylinux: glibc 2.5+ x86-64

platerecipy-2.0.2-cp39-cp39-macosx_11_0_arm64.whl (46.4 kB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

platerecipy-2.0.2-cp38-cp38-win_amd64.whl (50.8 kB view details)

Uploaded CPython 3.8Windows x86-64

platerecipy-2.0.2-cp38-cp38-win32.whl (46.0 kB view details)

Uploaded CPython 3.8Windows x86

platerecipy-2.0.2-cp38-cp38-musllinux_1_2_x86_64.whl (74.8 kB view details)

Uploaded CPython 3.8musllinux: musl 1.2+ x86-64

platerecipy-2.0.2-cp38-cp38-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl (75.7 kB view details)

Uploaded CPython 3.8manylinux: glibc 2.28+ x86-64manylinux: glibc 2.5+ x86-64

platerecipy-2.0.2-cp38-cp38-macosx_11_0_arm64.whl (46.1 kB view details)

Uploaded CPython 3.8macOS 11.0+ ARM64

File details

Details for the file platerecipy-2.0.2.tar.gz.

File metadata

  • Download URL: platerecipy-2.0.2.tar.gz
  • Upload date:
  • Size: 34.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for platerecipy-2.0.2.tar.gz
Algorithm Hash digest
SHA256 2258f7cd201bdd9f6537f600403d25ee85e30bea173b05a97c0ba4ea63e65eb9
MD5 d599ef49424aab52b2a6d3940acd8177
BLAKE2b-256 ed2dab2f0d264a4675d15a5791bb9358ee1c936f96344f0ac384c55037202e5f

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp314-cp314t-win_amd64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp314-cp314t-win_amd64.whl
Algorithm Hash digest
SHA256 61787c4e6dadeb79ecbbec4603a53f25b9c453f4c75991629d69ceed75519d49
MD5 2cc1d2e7d52a031e635de83a30d9c834
BLAKE2b-256 fce471172f53444493a578e26bc83b1c251bca0fa8345ddffe289510c2acc656

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp314-cp314t-win32.whl.

File metadata

  • Download URL: platerecipy-2.0.2-cp314-cp314t-win32.whl
  • Upload date:
  • Size: 46.8 kB
  • Tags: CPython 3.14t, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for platerecipy-2.0.2-cp314-cp314t-win32.whl
Algorithm Hash digest
SHA256 d56437f1ca0a6e949bd45aa917ffdea3df0c5787a0f1b16c25aea970fad06e92
MD5 877fc484e97f2702040142c645f16279
BLAKE2b-256 3d8680a2f7ad1d29e4f029e65be03181e79a2b57460297c232291207e48b94e9

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp314-cp314t-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp314-cp314t-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 24e3e3e61899bcd66d78e416af85d931cb9bbe17b099fbc7b08f62dadc339e20
MD5 39b1bc28564b731906dc72fd2a98a1c6
BLAKE2b-256 09ed1a61bd226193b8bac10c96a14dacbfd53ac6f83ff2d99656cd9907236e50

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp314-cp314t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp314-cp314t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl
Algorithm Hash digest
SHA256 6142b9062fc27f2027197564f47b0fde57fe98244a393ffd510dfca9af629374
MD5 0bd59776dc20d009caeda8c397cf6e8d
BLAKE2b-256 362eb078d7637ed6065a2d43cd5e9b5b67f7bb7c84c19584238cf6f70e959a7c

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp314-cp314t-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp314-cp314t-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 df4e027aec20c4ec582647005eacd429e86b7e5d1e0eef2b27fff2cb768cf255
MD5 579593d4357ac26b0eb6976d6dcc6f2f
BLAKE2b-256 9b424776f2f17e68c638f23d0b6b2501f38f08d4cb1f1cf516dafde580333871

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp314-cp314-win_amd64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp314-cp314-win_amd64.whl
Algorithm Hash digest
SHA256 30d02868e019ba51d7d7e98caa5cf0d8004be1132f2109d420f06e9336b2c5c2
MD5 da70d536cfcf0f65b8c615e9c9bf9c56
BLAKE2b-256 48bcf9890d62df9d96e10a446a0f7479dc43a7db4ae7c843566b0227fa72c7c9

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp314-cp314-win32.whl.

File metadata

  • Download URL: platerecipy-2.0.2-cp314-cp314-win32.whl
  • Upload date:
  • Size: 46.8 kB
  • Tags: CPython 3.14, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for platerecipy-2.0.2-cp314-cp314-win32.whl
Algorithm Hash digest
SHA256 29302d77fdde3498496055b96c896dea0686ecc8be13d7189e0478599f660d6a
MD5 a5a5ad42f4c37db4bacda7923df57ea8
BLAKE2b-256 817e8c0f6f4ff9c348f107408711c13fd2334d56a273e689ce5db5a7c4244730

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp314-cp314-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp314-cp314-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 726bd0b82d37d23bf97ea1d6c67bfa5fbc993f3f016567e8e62d63b38051fcb5
MD5 1960251ebc0367fd5ef43e86e02b2324
BLAKE2b-256 6e7065052248231da0472caad7288358cb5c53608bc36e6ae56caaf5b8adffba

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl
Algorithm Hash digest
SHA256 5ef079e029810a999a4d0918c1b158a3275a6e49b9dc3daef676ce1a90bd7455
MD5 61f5ded65fdc072c6866228795052aaa
BLAKE2b-256 fad8755e59172ecc3339baa89b74c35a4e03f9301940272a61bdef4b90b005fb

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp314-cp314-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp314-cp314-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 9cf9e2a6e0c693557eff14d58c93501fd007868c659a8a0b27b34a00a041ef1a
MD5 76672b9643eb192652ecfa0ae5437153
BLAKE2b-256 326038152535ea06216e052e551de250cb687031fb6548d548187c0a06b46f14

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp313-cp313-win_amd64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 234d9ebe47f09547134df8ee245703f86e5d9a3e0902620308f03a2eee5732e1
MD5 d4afe9a07a3c402f0c87e484558e2f4d
BLAKE2b-256 b3f81b7a75ff5328ad1caf438d1764fe7a467891b40f23d4fd16e1a26ae1790e

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp313-cp313-win32.whl.

File metadata

  • Download URL: platerecipy-2.0.2-cp313-cp313-win32.whl
  • Upload date:
  • Size: 46.1 kB
  • Tags: CPython 3.13, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for platerecipy-2.0.2-cp313-cp313-win32.whl
Algorithm Hash digest
SHA256 a7c61bd81f97beffb87e2acf10ce520108c718b2638e666f8a76388ada17841a
MD5 680afc297087189b085517ba58a679c4
BLAKE2b-256 15404bb65f452c7c2719f8d94e48580e9f8b6014b4c92247682f27c1cfe3dd67

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp313-cp313-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp313-cp313-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 fdfdb91798a38a7d778598ddea31553d1c935b63b8dff8b8d480ebb0c6a84f9b
MD5 9231a89dd1ec2aae4726d9502de59bd1
BLAKE2b-256 453c34b70c49be840a8d8c399666e98c767401e4ef2d35111e19e248d0fa7c45

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl
Algorithm Hash digest
SHA256 5dc9e4f0c9e2027a42b5f0ef5e4580c346795e6f17a6014e4acee221801e03bd
MD5 8f97beec0bf4c84ab5abcdda9ef0c4ef
BLAKE2b-256 98cef9b70d63fd55447cd903ae87b6cbff4234b5dd70dc95c8fe701596e31c11

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 9deb6ec5ef72135b175108706c05da383e40859e4e25f5ae81a37e9c59848a03
MD5 ef8b898d9f77cd5ef992fdb1d82ed0f9
BLAKE2b-256 649f579c19485d74865412a3c6d6cf350f0194c52c7f214583f3d65e0ab0a9e3

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 c5fcd416bac5acc3d0f90c67204f430d5e530d79d55cc83450a6452b573a0f9a
MD5 0cfbde74b1fab98c48f97e87f3160929
BLAKE2b-256 ef353065eef24f3995cd5ce05a25dc01270055d2add1b28c65332f221d4e82c0

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp312-cp312-win32.whl.

File metadata

  • Download URL: platerecipy-2.0.2-cp312-cp312-win32.whl
  • Upload date:
  • Size: 46.1 kB
  • Tags: CPython 3.12, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for platerecipy-2.0.2-cp312-cp312-win32.whl
Algorithm Hash digest
SHA256 381aa58088afe2472bcc6f12228454b7bcf3450c32f913319391e12ac46bcbf3
MD5 b5bfbd547eaecbe2ff0dd227570f0d66
BLAKE2b-256 187a950434304ba37ec062025810633f0c8c3db3c9b1905dc7feea68d2aa2f6c

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp312-cp312-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp312-cp312-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 27f69a4845324ba7b9c5ae9b4525c2f791538abebc823ac9a9559570ce899461
MD5 8ba65c3171eeed66bcd93608fc80b568
BLAKE2b-256 17ebf2a6d2d28012af995b6668d3680a3e5addffaf525e5df94101fa0628c595

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl
Algorithm Hash digest
SHA256 1576c48670d64f923b4bd1341aaea0e28dfaa2b99cae66664bb51ce13cb49fe4
MD5 7e63b9dff001741c5e4d1337a0be86d3
BLAKE2b-256 0542d5a375f732460aedbb7f234226f2e412bee1280d0bc1273ea650aac37260

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7901a48c6981f45789d504b6b0093b9da3213b946bd4c0cb81598095cab8afa9
MD5 5e1e5224e12670451795fe68287519e2
BLAKE2b-256 1964c24a191a60bec0d548b612d8e20ac0e7291084106028d08fe9bc16fccf9b

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 816e29be95f15b1861d60c277b20e837db9e734c1949e70f00bfe1bd3bf1a137
MD5 ad524322a2f589c68adb4f53f5f77174
BLAKE2b-256 5e3b790507511f01e1210b0d73f44be327ff9059e9c763366745cbda4aa7e4c2

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp311-cp311-win32.whl.

File metadata

  • Download URL: platerecipy-2.0.2-cp311-cp311-win32.whl
  • Upload date:
  • Size: 46.1 kB
  • Tags: CPython 3.11, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for platerecipy-2.0.2-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 2ab6d6828fe7f02b5e1c3cecd0862c26cc7be6be75d10a738b37c6501af7aed7
MD5 352fd4f4a1eea3b7829bf442ab960709
BLAKE2b-256 f7c59f3c761b3e9b0c6bbd3bb2efd54ed5947e14770a09dc5a892aeba1a49693

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp311-cp311-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp311-cp311-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 e1ee269dbf996292d060586337baefc870c67b62d6f7fb2a70046da0162dbcce
MD5 783cbd477f91869255853dce7af4e911
BLAKE2b-256 55e3a9c117d8b494b42e03768b1e550cba70926e6f6ac8097f96ee99dfb7abd3

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl
Algorithm Hash digest
SHA256 83b4842dbb21e9bd5c268c28a19294c24a732f178732f9ad7cd5ad4bdeb2c8d3
MD5 b79b58fa0a31c66de2940e2b1b0281f1
BLAKE2b-256 6c877c8975e1bb9583d5294e050dc53700827a7ecf05c1fffc5ef9d156f83ab1

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 d4f4f69d4df93806f83a2311864e7265a964cb74222b67e0f8f3f4e367164ef7
MD5 ebaffc69644a4c0c9973edede86a9a0f
BLAKE2b-256 df16204a0b6cfab40e1635b6c76d7a22252d9633468853fcc725626deeaf5d95

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 30f663c8a7c5444ba119838ce4df722aa9b64f0edb152b6e1d37cf7c097f94f4
MD5 2e75a6abb415be793fa38e16fd650848
BLAKE2b-256 1b20601e9acf6a5becb98a567a85afaeb9656e16b42397f12e4b43fe3324fd51

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp310-cp310-win32.whl.

File metadata

  • Download URL: platerecipy-2.0.2-cp310-cp310-win32.whl
  • Upload date:
  • Size: 46.1 kB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for platerecipy-2.0.2-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 606d8cc423bdda79a0a00bbf31c8498bd190bc6fd0b0844c4d27a0662361b5e7
MD5 9f4c3d171ad430d52092eb2509e4c377
BLAKE2b-256 ed2e686c97c3528914292445f8df1929089fabf497ff7b94b0b93a8b6efa7500

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp310-cp310-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp310-cp310-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 6513ca3b77c32654da92c338a5c690e3660202e20eab515dd2f5dbafad660d36
MD5 cdc354294fdb384b736d4333181f35a3
BLAKE2b-256 5db500253813900bb3af3c43da4415eca91359170f69ff48bd17f10ce70ba978

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl
Algorithm Hash digest
SHA256 c1f21dad9ca0283af484a09b70c4ed90ceb61b54910ae11db24d5b48e86b29d5
MD5 e419e7cf3870674ef6e22f1c52570161
BLAKE2b-256 05d22a451d1269445cf3976d00e4620cae736dfd47b54ec63e53e75622eda5a0

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 4cd6a430755298ed82bcbd7cbd158a3de7572dc175905d4cf72a587ff8c79b6e
MD5 29d62fb95d26c1da8bfc2573e11582ff
BLAKE2b-256 c629f8d5b03d537e846017d9008bab3a65fd6f1ee6b90e3f26c0ada69f46078b

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: platerecipy-2.0.2-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 50.8 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for platerecipy-2.0.2-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 ec62ea2d3778a677780d6c5dc9360fa3e9e85f2ba40175fee95e60e07b4709ce
MD5 7775f938203ee6d12d1df64056a0a36b
BLAKE2b-256 d37cdf49a919f381ab6df1db1b127ff729a7c511a00e913bb6b8bb7b806d3c30

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp39-cp39-win32.whl.

File metadata

  • Download URL: platerecipy-2.0.2-cp39-cp39-win32.whl
  • Upload date:
  • Size: 46.1 kB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for platerecipy-2.0.2-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 015b58e429b2036904df0e839cb1188ab7ee676f8a593835e492c25c95bf0bb1
MD5 8f5368aa394e57e86e0d548a20994072
BLAKE2b-256 1e6d02e9e8151d0cc40fc28c2660e2c3ad8cc9ac22004edc72aa2b9af41d66eb

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp39-cp39-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp39-cp39-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 42ddfca7b1fac8f668babc216f23e053aecbc4d2e4ac843b2fc9747ed1690d08
MD5 7775201aca225b4fb413b9a1ea8655fc
BLAKE2b-256 9fcf6ec87ea9e5c922021e6ca1bcfc6b38e1d9eddf2fb4a46fc0ad4ddbfd0a1d

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp39-cp39-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp39-cp39-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl
Algorithm Hash digest
SHA256 3c896de890ba992a06768b23aeffb2c3542577443ab0c7a119e635483e1d825a
MD5 b10de34511a14ac3a7f69975dd3585d7
BLAKE2b-256 aa16ebcad9d60277735182c8d32a12cbd1f44caa01a3540ea3bf54a11e2e585a

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 e5f2efa11f723b886192792d15c8644c0038a348659188dba0624ea02e7235e2
MD5 0b862d35279a4e17f64455fa88b1e9bd
BLAKE2b-256 f418721d3a5f211d378ffde5782191ee513d0254a6fbd5528733dc4af6d4b5d1

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: platerecipy-2.0.2-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 50.8 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for platerecipy-2.0.2-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 58f0de81772135e8d27ebd0775d6305768710b0a34d943002204c111b8f4bd63
MD5 fee51a982e5b6ab82bd8015a1162ac06
BLAKE2b-256 3db59c32ebd146ebea1f884301095038de06154c46aa5607b7fff08362aac8b7

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp38-cp38-win32.whl.

File metadata

  • Download URL: platerecipy-2.0.2-cp38-cp38-win32.whl
  • Upload date:
  • Size: 46.0 kB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for platerecipy-2.0.2-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 b4ba13f6ef76b4a774f53a69668bd65ec249d24634741afe754d1c9a22857003
MD5 6f2dc09db70bf5772527a8c8a2c8beee
BLAKE2b-256 d46855ead59e7cd90b562362cdc50a776fbbe62d1132b9af124a598b5a3fb3c6

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp38-cp38-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp38-cp38-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 bc46260f824bf6fdcf9c5e7feb882f6cc6fed98e095071481b908ed2b63b72d2
MD5 bcbd80f19be8709d07cbecf8f5e4d4e3
BLAKE2b-256 12d95c18bc18b5aecc96a621e7065559e87c4b92391b6b469301388f2add9709

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp38-cp38-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp38-cp38-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl
Algorithm Hash digest
SHA256 6202bb4b3318f233d68c3cdac0ae79ce182ef6952d093f7d9caded4af62b7a5b
MD5 f8684ea61e89bbe73f16463bcc4609a2
BLAKE2b-256 6ee1f11fe58493de0f537c060c6ee6264bb7642a84c572b337f922b03cb8f063

See more details on using hashes here.

File details

Details for the file platerecipy-2.0.2-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for platerecipy-2.0.2-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 2d1678c30ca9e875efc3985e850b7cf88a7a2b27146b4c938cf79080f4edfcb1
MD5 f30143f34376b4bf5f18465a32bb6d8a
BLAKE2b-256 a475e4c582d4ad96889ea8e8baaeb7e3478684ff958916b6786a2754bb3d9708

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