Skip to main content

Python library for calculating contours of 2D quadrilateral grids

Project description

ContourPy

ContourPy is a Python library for calculating contours of 2D quadrilateral grids. It is written in C++11 and wrapped using pybind11.

It contains the 2005 and 2014 algorithms used in Matplotlib as well as a newer algorithm that includes more features and is available in both serial and multithreaded versions. It provides an easy way for Python libraries to use contouring algorithms without having to include Matplotlib as a dependency.

Latest release PyPI version conda-forge version
Downloads PyPi downloads conda-forge downloads
Python Python versions

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

contourpy-1.0.3.tar.gz (12.2 MB view details)

Uploaded Source

Built Distributions

contourpy-1.0.3-pp39-pypy39_pp73-win_amd64.whl (159.0 kB view details)

Uploaded PyPy Windows x86-64

contourpy-1.0.3-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (243.8 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

contourpy-1.0.3-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (256.2 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

contourpy-1.0.3-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (232.5 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

contourpy-1.0.3-pp39-pypy39_pp73-macosx_10_9_x86_64.whl (227.9 kB view details)

Uploaded PyPy macOS 10.9+ x86-64

contourpy-1.0.3-pp38-pypy38_pp73-win_amd64.whl (158.8 kB view details)

Uploaded PyPy Windows x86-64

contourpy-1.0.3-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (244.4 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

contourpy-1.0.3-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (255.7 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

contourpy-1.0.3-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (233.1 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

contourpy-1.0.3-pp38-pypy38_pp73-macosx_10_9_x86_64.whl (228.1 kB view details)

Uploaded PyPy macOS 10.9+ x86-64

contourpy-1.0.3-pp37-pypy37_pp73-win_amd64.whl (158.7 kB view details)

Uploaded PyPy Windows x86-64

contourpy-1.0.3-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (245.1 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

contourpy-1.0.3-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (256.9 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

contourpy-1.0.3-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (233.7 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

contourpy-1.0.3-pp37-pypy37_pp73-macosx_10_9_x86_64.whl (228.1 kB view details)

Uploaded PyPy macOS 10.9+ x86-64

contourpy-1.0.3-cp310-cp310-win_amd64.whl (160.0 kB view details)

Uploaded CPython 3.10 Windows x86-64

contourpy-1.0.3-cp310-cp310-win32.whl (141.7 kB view details)

Uploaded CPython 3.10 Windows x86

contourpy-1.0.3-cp310-cp310-musllinux_1_1_x86_64.whl (788.8 kB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ x86-64

contourpy-1.0.3-cp310-cp310-musllinux_1_1_i686.whl (849.3 kB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ i686

contourpy-1.0.3-cp310-cp310-musllinux_1_1_aarch64.whl (762.3 kB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ ARM64

contourpy-1.0.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (273.0 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

contourpy-1.0.3-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl (283.6 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ i686

contourpy-1.0.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (258.5 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

contourpy-1.0.3-cp310-cp310-macosx_11_0_arm64.whl (214.2 kB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

contourpy-1.0.3-cp310-cp310-macosx_10_9_x86_64.whl (233.0 kB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

contourpy-1.0.3-cp310-cp310-macosx_10_9_universal2.whl (429.9 kB view details)

Uploaded CPython 3.10 macOS 10.9+ universal2 (ARM64, x86-64)

contourpy-1.0.3-cp39-cp39-win_amd64.whl (157.5 kB view details)

Uploaded CPython 3.9 Windows x86-64

contourpy-1.0.3-cp39-cp39-win32.whl (141.8 kB view details)

Uploaded CPython 3.9 Windows x86

contourpy-1.0.3-cp39-cp39-musllinux_1_1_x86_64.whl (788.9 kB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ x86-64

contourpy-1.0.3-cp39-cp39-musllinux_1_1_i686.whl (849.1 kB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ i686

contourpy-1.0.3-cp39-cp39-musllinux_1_1_aarch64.whl (762.8 kB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ ARM64

contourpy-1.0.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (274.0 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

contourpy-1.0.3-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl (283.8 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ i686

contourpy-1.0.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (258.9 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

contourpy-1.0.3-cp39-cp39-macosx_11_0_arm64.whl (214.3 kB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

contourpy-1.0.3-cp39-cp39-macosx_10_9_x86_64.whl (233.2 kB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

contourpy-1.0.3-cp39-cp39-macosx_10_9_universal2.whl (430.1 kB view details)

Uploaded CPython 3.9 macOS 10.9+ universal2 (ARM64, x86-64)

contourpy-1.0.3-cp38-cp38-win_amd64.whl (159.8 kB view details)

Uploaded CPython 3.8 Windows x86-64

contourpy-1.0.3-cp38-cp38-win32.whl (141.7 kB view details)

Uploaded CPython 3.8 Windows x86

contourpy-1.0.3-cp38-cp38-musllinux_1_1_x86_64.whl (788.6 kB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ x86-64

contourpy-1.0.3-cp38-cp38-musllinux_1_1_i686.whl (848.4 kB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ i686

contourpy-1.0.3-cp38-cp38-musllinux_1_1_aarch64.whl (762.6 kB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ ARM64

contourpy-1.0.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (272.6 kB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

contourpy-1.0.3-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl (283.4 kB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ i686

contourpy-1.0.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (258.2 kB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

contourpy-1.0.3-cp38-cp38-macosx_11_0_arm64.whl (214.2 kB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

contourpy-1.0.3-cp38-cp38-macosx_10_9_x86_64.whl (232.8 kB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

contourpy-1.0.3-cp38-cp38-macosx_10_9_universal2.whl (429.7 kB view details)

Uploaded CPython 3.8 macOS 10.9+ universal2 (ARM64, x86-64)

contourpy-1.0.3-cp37-cp37m-win_amd64.whl (160.2 kB view details)

Uploaded CPython 3.7m Windows x86-64

contourpy-1.0.3-cp37-cp37m-win32.whl (143.0 kB view details)

Uploaded CPython 3.7m Windows x86

contourpy-1.0.3-cp37-cp37m-musllinux_1_1_x86_64.whl (785.8 kB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ x86-64

contourpy-1.0.3-cp37-cp37m-musllinux_1_1_i686.whl (846.7 kB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ i686

contourpy-1.0.3-cp37-cp37m-musllinux_1_1_aarch64.whl (764.8 kB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ ARM64

contourpy-1.0.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (270.1 kB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

contourpy-1.0.3-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl (278.2 kB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ i686

contourpy-1.0.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (257.7 kB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ARM64

contourpy-1.0.3-cp37-cp37m-macosx_10_9_x86_64.whl (228.0 kB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

File details

Details for the file contourpy-1.0.3.tar.gz.

File metadata

  • Download URL: contourpy-1.0.3.tar.gz
  • Upload date:
  • Size: 12.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for contourpy-1.0.3.tar.gz
Algorithm Hash digest
SHA256 5a747ef2ebd994a90de6e5fc53e78bca4d4bc76422307cac15a71ad95028772b
MD5 3221c37d734396004a14f1ae8dfb643f
BLAKE2b-256 1e49004641fdd67641ac9564ca6c14ea9540c66fb4c14d8183ec231629e63b9f

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 67d13952d0da590fcb1c4d88c4ef1a9e36328445cd14bdbf30c678a78affc344
MD5 5121040636f993b018a3ffd9e243b0bf
BLAKE2b-256 d478f8e88c558653403ef3c4584461bd5084814047eca5682d8db332169d2c56

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 443e0258617a852c053175488d3229864f92ca009258cb9ce49e95bbf85a6aa5
MD5 0d3699b0c52d6818697bd6b0fda8a436
BLAKE2b-256 be74603a6df849825d20c7d0394139802549e351a03a84d71e70696d16922ef4

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 97e2a47eb67955690d62ef7a225c2ec8990eddc36e0fe568a2b7230e2a866b3b
MD5 cc367b70cb2677d4d9697128609eb647
BLAKE2b-256 196aaff1e65ced87c24cfa6c1e01084dfe81f4a19a26d23ed571ef8886a05f95

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 7148d8090b21b11e87e01421d2dd4b8f47af527d22d0348ac1d1c4d3d13523ca
MD5 b06041ff9ebff21f6dde59fd88d29b84
BLAKE2b-256 0d4262f2a76388c088804013e7906f23c57aa605aef8972cc04155de2a4bbb0f

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-pp39-pypy39_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-pp39-pypy39_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 158faa423ae93ec926efcc7ed766915278c51f9a57b93e0491222ce13f3b742b
MD5 f6aee81c28d573694b18c9dac367e4a9
BLAKE2b-256 ddcd6e4b17c92e39ed593ecb68d7386e4904a31e38b5d01155ef4911463309ef

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-pp38-pypy38_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-pp38-pypy38_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 bb46d943eb4af03de61a65b1232b25a8ab4cc9f7acad8fb541cdb73876761b65
MD5 f21f1495974c0850f516837b291f0415
BLAKE2b-256 1c3e4f91ddbfb567819920dc7b13fdb49473b817025cf0bc5f432990d4851db7

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 561953c8aac95d8c6800e48bf233ee2827507fc027fd86c37c0b7953e1828939
MD5 6e5d19a387435920bed76484d184fd81
BLAKE2b-256 7db97957b619f9040b7e14503f91577deadc2f1f67e82f109b4282dfd7e1f1c6

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 32b915ed70f7856c5fe1c09a798b3576a1b5646c08c679ac8c33c85de36643df
MD5 13b9910c8eae167773aa4acdc6b30bf8
BLAKE2b-256 89889d1c58e26daeda25464b4ead093d0ebed75f13e470d2241654fb9dc3575b

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 7d746752a364911ddf507a0f5229c46e9dd06b602f048bd1f4ab80a6c461bd04
MD5 63950201ca2d4d9625e6cb72584fb0db
BLAKE2b-256 3abd589518c8415c39553ab0914e85b4b52e2d749082cb1bf845d0c4252cfdab

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-pp38-pypy38_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 0924cf865ed193fd436fc604c0bbbb5412f33ab46d97efe4e9dbe14484130672
MD5 406c145953042a59e4883f5ad9dfced8
BLAKE2b-256 595ce0defb50ef679312dfdc62b4069aa8648ec51881e3928d67761ff1a1cf2f

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-pp37-pypy37_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-pp37-pypy37_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 ca355b92b8a603adda30068537b78f031451bf5112fed760731f5ebb4f513163
MD5 d88f4506096cd7e8e91a1bf113fea138
BLAKE2b-256 cd4e2c0e7869b35ff337291bd286ff2d6b618b5aa3e3c897072791fe7c90c3b7

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 5cfa054c6530d195b49a971ac083f59d2360ea2c550106ffbf69c2512858c01d
MD5 4a390495466220746dbc7ca7c776b3b3
BLAKE2b-256 e1a96c50e23ec7b43b350de41b4874f0ae3c97c0a41f2cf9d02269b1b8c7e102

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 4c4b1cc41a5d84d7ab879a7f5d9b016241125534e763d4823ba09babc60ef5a4
MD5 9c52dbec5c937e14c265699618c2814e
BLAKE2b-256 b67fd857fb224efa53fc9693573359611ee3e33ef236725ca4eb4e5d6def26ef

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 5f6590a3c2d62c965263083d77e8a81a98d86f13e5155baa8ce9aebd06410991
MD5 16a8e3eec2dbc98cc887494d1e01007d
BLAKE2b-256 4af289bb672fc8a32686ef210ba1f80c9ed3a59b436b5759df347c30e9377d1d

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-pp37-pypy37_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-pp37-pypy37_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 8f88e7b52df990f7718fedbf3f4edf910a40e467e5c2f576b6cbe294b8d4d1b8
MD5 5ce31f2209f5a496ba64f4fb2315a01f
BLAKE2b-256 a9031be085dfb58ad1db1ffbdbf72c5b006243acfee8eaa37e06b79817db2889

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 12245a879ea6ef906d547ea5a748498bf7cb912ef35ea17a9a20b565041dc525
MD5 7475c0aa63b91f38e0e4cdfd6d35d12d
BLAKE2b-256 97f2f146cf2db2e1cad1e15cf39f22932e461de2f0b912a998aa7312263629e4

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp310-cp310-win32.whl.

File metadata

  • Download URL: contourpy-1.0.3-cp310-cp310-win32.whl
  • Upload date:
  • Size: 141.7 kB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for contourpy-1.0.3-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 05cb4cc72902cf02cbb00ea20b6826533a6b8c74e2a3fcaef6510660414f508e
MD5 c3bc6bc274a413cb23e2d5497b2b552c
BLAKE2b-256 e00aef0c248385cb5af07240463b7004a1a6b6e1f34c292c4117d044829020c5

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp310-cp310-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 5117c46e7e1b11519531aaae5417b35d20d6e42d2c609cb17d26a295a08788fd
MD5 664aadc9dbce5e738fc03d31a20d314e
BLAKE2b-256 c156fc4e34a9f91760acee2945895bc59c063dd45f935b37480f02d4ee803749

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp310-cp310-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp310-cp310-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 ef396a643ac162b54bf86ea8b813836f384558442efbc9c97fe332f3335d2bab
MD5 ec03daae1fb6b63163bdc2db040a8b75
BLAKE2b-256 d0e64255578de218f497eebeb06c2b3f2fcb50035e533ef506a233d7eda14ccb

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp310-cp310-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp310-cp310-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 6f88c4fddad898e09f850dce7f9f09921b07c835592109a7a444c77817d975dd
MD5 8ac2b4ee075d3e170ed95ac139083064
BLAKE2b-256 784ebc5a962bb0fe77260a9b73872e493618f1a71fb0dc58ddb9035ec5dea629

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d6d14876e2254db147c0ce5c1c30249d7b65f4cfc230d5c4b4556bbfb4ce23d9
MD5 a9bbf128ae9ea0670a94600591a9e1c6
BLAKE2b-256 246bf1d3b7f40f744267cd4a30fd8e7c24175def0a2a74b1dd7c04af7b19abde

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 8899e0d736e8f6b815f5a2b69d509ef0b8caf16cafece3a089e0cdcc3bf0dbe1
MD5 21fbda6e2108973e81a0bf4deb2feb24
BLAKE2b-256 e233e5dd09376c4b3b1c66af070efe013dfac03e0becde8f16f86a3dbbae4fa1

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 8dccc2ae8b878398ac87f92e5d5959ab710cc7f38f250c469f58c78fe29f1216
MD5 ba2fd14a23509935198927198041296d
BLAKE2b-256 96a3804ee2a12de5b250eca970f9e87f4a05b9c0086d384e004dce1d83509699

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 26e27074bf23c225c93ce7b8f58b6f948dbf0eead2c67f9979f280e20880e4cf
MD5 5e6ee149ba5f42981cface4aef5aefb0
BLAKE2b-256 e4977b5a3f408e1aec8d113904eb46f38c00cd76cf20366ae7b135e4d234c3d6

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 332e3b585b10d953d7bd3ca361dc8ef0d9f4bc6f0d5d65897fe6bb26722ba221
MD5 e6e559b049b27588e28b886d0bff4ad5
BLAKE2b-256 d13416ca2e9e3fdf14b883e5f2725f35204a4c67262995e0b957fb6f266d5084

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp310-cp310-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp310-cp310-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 c45d555ae87ddf47d869adfaad63fe78f87d5bdb6cc61d746467912aa4d72d45
MD5 42ef53dd0bda1cbb2ee25ba866b1c026
BLAKE2b-256 696aafd6a68561b9f50700aacd6f7f8f46b8cd77bacb1ffa17cc1d06395434fb

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: contourpy-1.0.3-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 157.5 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for contourpy-1.0.3-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 99aa776937f81421c90efb9fa54d7c92a41076530189958a8daf5f6f7df398d9
MD5 be28f019bf29c0556f234a85f734efb1
BLAKE2b-256 c4b25faf20dc065d598fa13902ad84283dbd3c3b90386a1b45f6f49c898539c9

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp39-cp39-win32.whl.

File metadata

  • Download URL: contourpy-1.0.3-cp39-cp39-win32.whl
  • Upload date:
  • Size: 141.8 kB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for contourpy-1.0.3-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 edd528cbd990fb537c526623960192deaf5ba1a990dbae52b6aa894e0ade059c
MD5 2df57420c437052304900939f4932dce
BLAKE2b-256 db4c39e398e585d7e59573b82536d98bca00da5c7e8dfc9497981860773b5f98

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp39-cp39-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 881f692d61d86fad136b6f61d73a11d115637a42ae17dd9a30cc495afa3565af
MD5 ac0fe5d5c9c8986cf52a37df749c2fe9
BLAKE2b-256 31df4a4c085d12e00e23c35e1af52e3845fed6ede7d06e022607009632d57932

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp39-cp39-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp39-cp39-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 db55e24c328c28b730e233ab27566f2cd897a5bf50455edf0f7be130ce164fb0
MD5 9da6806124dd23545d72fb0b17c44b13
BLAKE2b-256 6aa49d49ac275a0a5e1e055f844942ce4bc1c9fb19f7cc061c806b88c89b06c0

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp39-cp39-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp39-cp39-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 7053b4f7035fcf2c50096ebaa53fc6ded1752ea4e3bab80d057465a39a9219ec
MD5 9853c64901eff83eada47d18ae12a53a
BLAKE2b-256 403c3527350e26038731bf946bf10fbeb97c126f162ff31b90d04f0668c25a4a

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 33e9a21587451db381a6d19f178ad2469855bbe0c054b025e60d417378892ab2
MD5 f466bb3a20e78d63b41961210a34948b
BLAKE2b-256 d3a6f271fda4fa83a252e7c20c06e6426f655a83426d0b707af732d7bcc597ac

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 1def7d1ba144c21e7de025f9f91e99ef2cf3c26ef77cd3c7b521350d4f04d7a9
MD5 d7e3adf2b876f49751820487369bb99f
BLAKE2b-256 20b5edabdf399fef94c5257e8e0bb77a5a053f5b92e926a3c4c42808bcda4d6b

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 c7442800c32564f988ab9ee5adad008c5ac00e02ec1dc39f62d30434e000fa97
MD5 0724286895c4fdf629eed946bd31d33a
BLAKE2b-256 d41e4e9a8f3ec1135fa2a5f3bddebb501f7191c2b15c97c57eca42774d31606d

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 bff4b90838b881624c8c8e9800d48e8e15b38d144b983d16691b08b5bf775492
MD5 60d255ab5c678493856f74b9fe223bb1
BLAKE2b-256 b5783dc93721f7ff8826306b55738690d7347c367475e50ef979204c154d11ab

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 9522b2cc844ebf4fdc1914ff6a0f1668c8256629254848d405b11f8ee88b9ef7
MD5 32965d709a4ecbfc9d889c4bcc950abf
BLAKE2b-256 ec687b810e3f1ee64a37a36796b9535582fa13360d8545d36ca619121d3083ab

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp39-cp39-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp39-cp39-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 2f3260cdc4fc760a903f73c6cb06b2b0612f294ff2955548bc75cd576bdfdf17
MD5 8b4b5aeed2401fe0f7b09d8ace4d6d43
BLAKE2b-256 cd2a92a3c6d60659b3ddf96f6c01e84825ba0252436d478ec75167a000064b30

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: contourpy-1.0.3-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 159.8 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for contourpy-1.0.3-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 2c23814becccfa6aa3e92693f08f301042f0514174ba86153593cb20abe3d150
MD5 298b39de3c60263cc6cd10c591181e6f
BLAKE2b-256 9ee0065a06ee2d62a4246c0bb59db894f37f2d9710e49c24743d036debd3f9bb

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp38-cp38-win32.whl.

File metadata

  • Download URL: contourpy-1.0.3-cp38-cp38-win32.whl
  • Upload date:
  • Size: 141.7 kB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for contourpy-1.0.3-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 4d3e414280097de8017576ec817f3066c077b97972f2fc4cfa9ddf035dc8d8d9
MD5 f98f641315358dc1319e9fd5c7072445
BLAKE2b-256 5660ab327536a3d1259ede6098057ff2310ace89379fa0ae7c2752156554e466

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp38-cp38-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp38-cp38-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 ff72d5c846bc170d9ef025a5b127fb3fa5ce804b485e8dfb80d9cbb428e95dca
MD5 b8581bdb45daabcb24d5267c101b36c2
BLAKE2b-256 eff8a7dcc102fc7fd168899ac8f27a17005c547097af0ff4b2b3b23c9c2a6057

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp38-cp38-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp38-cp38-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 414ca3dfb0427beb974709d3014cfaf920179bb480733953b128e366539177e7
MD5 54d77c6453740021ea11bd3aa7615210
BLAKE2b-256 4b0cb09ac2e5fc12b509b7a5230ace8f1fd93336089db5f1688d4560ef9d5e9e

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp38-cp38-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp38-cp38-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 ebdd40d0a5624346f71c67960bf8b4e1c2ecd0e80b881ddba69ea4f32f7d0810
MD5 3a5ddd50491b34b5fcc6196642ed9b2b
BLAKE2b-256 11ca0773fcd6f0a6aad9df35b1644a78e61fbf89770800f4d7c873bc72f109f2

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 73d3debbb67a2de7362814f46d1cea9a1f764ab0782bc832666ccce0ec105613
MD5 08d65ca570185dacbfe90ae89cfae668
BLAKE2b-256 1ba688a9e5919ba0843f3b6b512ece5ec5f52a39769d678c4605a66d5b230b6d

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 85847f663e3278128e23509fcdd34891a8573c11125f6b617c6c9656143eba77
MD5 acd66dd25c6ea60f233222d1222da729
BLAKE2b-256 0e4bf4bcb4fe110099f81c15b46bca88873dd4f67c7dd02a575e911026c68cae

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 2a661eabeed7c2bea35e8dc789b47da6644edf2b77dea9dc8ca2c64040ed8b25
MD5 6dd787756be4f8772f6096146bdc4007
BLAKE2b-256 7ad2477517d05462ce76286e2f7010a4d03ac8326d7bcdba5b1d6f79cca84291

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 921a68b639f00a0bf89e340a7a59acdcd01826ca5dfa64d8ec435dc62da61f13
MD5 aacaba5144780abe1d9f54d2b1d526fa
BLAKE2b-256 c286ed333e0e65fdb8b08a12ae6d0889e5b1909a8d08a9c46ad32d31abebaa14

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 3eeae8fde14eee7f644c9af3a6ec91c2bcf5bcf22699e164f0e9c524fb4c1e03
MD5 bd9bdeac9205b90fcd9a7f922a201312
BLAKE2b-256 fcb35ad92191963321d9cf4fa5b961bce13a59a76cfa8fff3a0ecb91b34eaa29

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp38-cp38-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp38-cp38-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 d64390acabc5157eb7774df550ac9a47a03849d781007e8e76ced6bb0ff9d592
MD5 c29dde8ae3f183285d1cb327253ab9e4
BLAKE2b-256 1cb171a16c3e83ae39bd8cfdeaab15f4f215e695106e6bbb2268ff148c68edf2

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: contourpy-1.0.3-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 160.2 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for contourpy-1.0.3-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 2b55dc3243b2c46015ded5383e624e405c61c13c9f5543b1fa0ee464dfbbe0aa
MD5 c78a1c57f4708026fd7184dd5c250b10
BLAKE2b-256 a58fc41382d11cce150f41578278ce39a4c49adb121872067e737cae0b91ee1e

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp37-cp37m-win32.whl.

File metadata

  • Download URL: contourpy-1.0.3-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 143.0 kB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for contourpy-1.0.3-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 339cd251556e37915d50a48b3a175d93302d9e8624c4366e37b49c8be38f1320
MD5 daf8e287b1d32a9ef773e0d88fdfd2bb
BLAKE2b-256 42ada8ed26b6d86992524f719a8331444696d20b58537ea6590fb28b611017b8

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp37-cp37m-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp37-cp37m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 d9ba69a35094fb8cdda4e0cab947a7c1ac440d6f9e594060b252e2af44eff5de
MD5 de9ba39972da5e0e93b88799668b2e0b
BLAKE2b-256 de103601a798c751fd0f9c2fc56f65bca3714170498f68fe1035cc0186277e33

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp37-cp37m-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp37-cp37m-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 56888a312983045f414c5812a22dba60d0b408ad033555adf565dd812bbe19b7
MD5 e028e3d132db280ba3c7dbd3a4ce0ab9
BLAKE2b-256 77ddba868b3d0bb1c44381940f7d34b0c71f451f7cce36be8b3fe1a966f6d5c4

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp37-cp37m-musllinux_1_1_aarch64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp37-cp37m-musllinux_1_1_aarch64.whl
Algorithm Hash digest
SHA256 41bcb1ebb998da0054bd905656c5a5bd24403e1b1d92db75744a0b9c66695f67
MD5 3620f6b7bac2a87f915616778846fae1
BLAKE2b-256 f41fb7bd42424c24024911b567a9273752921d245014dcde4da803de61715a5d

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 30bd31227b77e489e1caf08d79921775c6452522004e4e257f1ea99746d5ab90
MD5 9d579b7891699d3285040beede1d1424
BLAKE2b-256 5c8fccfea9371b0ae6a7ed2716157e336c8f73bbac5d08e81abab0f6124c48f4

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 9bc4b388a4ef3ef60628c5aaee72f5b002a2da64e324d2ff370bd67245c99b60
MD5 ae55a0b20ea8f1b33d47ee3a2c3e2fe2
BLAKE2b-256 2d7c26c8aa5ac52732ead9eca0f3654e5415c17f86d0bd3cf3a9a035b03d6950

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 bb14ffddc6319ca5af0f09c963910161b6d33d3245f051185b5cc3d798a927fe
MD5 bba286048731d24b94e91abf14eec3ec
BLAKE2b-256 f1d512cfafe350872ec528105dde5579ae2266cfc0b19c20809a1e8c8305242b

See more details on using hashes here.

File details

Details for the file contourpy-1.0.3-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for contourpy-1.0.3-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 597fe5bcaed69fbe1461ab1e8e7898cba67a2f92add45a4425dd3080b7e14d01
MD5 e7f2195c534376faba1c536d3854a051
BLAKE2b-256 d5164698fa3fa9a5a961354c99081cb79d708be23baeeb5c144dcd7fb6b4eae8

See more details on using hashes here.

Supported by

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