No project description provided

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for yojeep from gravatar.com yojeep

Unverified details

These details have not been verified by PyPI
Meta
  • Requires: Python >=3.8
Report project as malware

Project description

The author of this package has not provided a project description

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for yojeep from gravatar.com yojeep

Unverified details

These details have not been verified by PyPI
Meta
  • Requires: Python >=3.8

Release history Release notifications | RSS feed

0.0.33

0.0.32

0.0.24

0.0.23

0.0.20

0.0.18

0.0.17

This version

0.0.16

0.0.15

0.0.14

0.0.13

0.0.12

0.0.11

0.0.10

0.0.9

0.0.8

0.0.7

0.0.6

0.0.5

0.0.4

0.0.3

0.0.2

0.0.1

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.

pypne-0.0.16-pp311-pypy311_pp73-win_amd64.whl (1.0 MB view details)

Uploaded PyPyWindows x86-64

pypne-0.0.16-pp311-pypy311_pp73-manylinux_2_28_x86_64.whl (610.4 kB view details)

Uploaded PyPymanylinux: glibc 2.28+ x86-64

pypne-0.0.16-pp310-pypy310_pp73-win_amd64.whl (1.0 MB view details)

Uploaded PyPyWindows x86-64

pypne-0.0.16-pp310-pypy310_pp73-manylinux_2_28_x86_64.whl (608.7 kB view details)

Uploaded PyPymanylinux: glibc 2.28+ x86-64

pypne-0.0.16-pp39-pypy39_pp73-win_amd64.whl (1.0 MB view details)

Uploaded PyPyWindows x86-64

pypne-0.0.16-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl (608.4 kB view details)

Uploaded PyPymanylinux: glibc 2.28+ x86-64

pypne-0.0.16-pp38-pypy38_pp73-win_amd64.whl (1.0 MB view details)

Uploaded PyPyWindows x86-64

pypne-0.0.16-pp38-pypy38_pp73-manylinux_2_28_x86_64.whl (608.6 kB view details)

Uploaded PyPymanylinux: glibc 2.28+ x86-64

pypne-0.0.16-cp313-cp313-win_amd64.whl (1.0 MB view details)

Uploaded CPython 3.13Windows x86-64

pypne-0.0.16-cp313-cp313-musllinux_1_2_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.13musllinux: musl 1.2+ x86-64

pypne-0.0.16-cp313-cp313-manylinux_2_28_x86_64.whl (610.1 kB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ x86-64

pypne-0.0.16-cp312-cp312-win_amd64.whl (1.0 MB view details)

Uploaded CPython 3.12Windows x86-64

pypne-0.0.16-cp312-cp312-musllinux_1_2_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.12musllinux: musl 1.2+ x86-64

pypne-0.0.16-cp312-cp312-manylinux_2_28_x86_64.whl (610.2 kB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ x86-64

pypne-0.0.16-cp311-cp311-win_amd64.whl (1.0 MB view details)

Uploaded CPython 3.11Windows x86-64

pypne-0.0.16-cp311-cp311-musllinux_1_2_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.11musllinux: musl 1.2+ x86-64

pypne-0.0.16-cp311-cp311-manylinux_2_28_x86_64.whl (609.4 kB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ x86-64

pypne-0.0.16-cp310-cp310-win_amd64.whl (1.0 MB view details)

Uploaded CPython 3.10Windows x86-64

pypne-0.0.16-cp310-cp310-musllinux_1_2_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.10musllinux: musl 1.2+ x86-64

pypne-0.0.16-cp310-cp310-manylinux_2_28_x86_64.whl (607.3 kB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ x86-64

pypne-0.0.16-cp39-cp39-win_amd64.whl (1.0 MB view details)

Uploaded CPython 3.9Windows x86-64

pypne-0.0.16-cp39-cp39-musllinux_1_2_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.9musllinux: musl 1.2+ x86-64

pypne-0.0.16-cp39-cp39-manylinux_2_28_x86_64.whl (608.8 kB view details)

Uploaded CPython 3.9manylinux: glibc 2.28+ x86-64

pypne-0.0.16-cp38-cp38-win_amd64.whl (1.0 MB view details)

Uploaded CPython 3.8Windows x86-64

pypne-0.0.16-cp38-cp38-musllinux_1_2_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.8musllinux: musl 1.2+ x86-64

pypne-0.0.16-cp38-cp38-manylinux_2_28_x86_64.whl (608.7 kB view details)

Uploaded CPython 3.8manylinux: glibc 2.28+ x86-64

File details

Details for the file pypne-0.0.16-pp311-pypy311_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-pp311-pypy311_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 91775a5954d26fe951938cea7c47b6642ab953ed34c1d84dc4706deac1cf5410
MD5 e3fc286d24d154c98e3360bb048e13db
BLAKE2b-256 303aeb8b4fa6322f2ada2096c42cd310b770886d96545e81ff4fb3e125c4b825

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-pp311-pypy311_pp73-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-pp311-pypy311_pp73-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 407306829f94f4125da9d8bd8b85bfcdcfcdec20caa93fbab5c085c5a94b08fd
MD5 29d5e796797210e4b9c50475fe9c25f8
BLAKE2b-256 553fa433adfec34947394884dc20e1ca94082e01428659a0244eace0fd8ae184

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-pp310-pypy310_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-pp310-pypy310_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 94e7b9abbb26acfdb1a706ef0111144e6c7f8ba276feb579b2f89e1646f48a24
MD5 83a5767b967eb152a20bd02c4a672be2
BLAKE2b-256 cfbe9fdf01d65d66e9eef57d5a9825c44cdf0345b08a9fb9ddbf72e5a90f5d04

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-pp310-pypy310_pp73-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-pp310-pypy310_pp73-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 af06ec9c6d4d9c7245814d6832a60ded4a606580a4350605d541cc5fa0ea193e
MD5 4eb0910519b0f82f1437cdcd160dcee1
BLAKE2b-256 9753359ffa9dba29efdefe012991fe1c01aa120167954ffe7b522b11f2d8a05c

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 49c812486b8c0b1358380af945913bfeb7dfdecfd1288dd5ff954977fc563305
MD5 8f9b9de48565305c94e8dd112692e1a0
BLAKE2b-256 adf4c6eddeb92e333ea6a8961ea5270118062fef71c0f3557efffb03cbe0187f

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 96808aff0b418d50575bc26b1bbd7b505731e00324dc0c21be4c262fb7d20573
MD5 e6921bab3da08c04c1b515adc0f5a892
BLAKE2b-256 1bce91e11f7c3e946e9eef3874f8976121882d13016fabe4afd6f1b500526617

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-pp38-pypy38_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-pp38-pypy38_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 e6bc5dde58aacd720644143d8848972e715382f5b7506d4ed6f36f8c87d212ac
MD5 1654c3ebe4dcf1a465c0eaff99a1068d
BLAKE2b-256 d63a064ca6c9e57171ad17bf080448c55d9279bf092f8b67bd8fa8cd8c3c55a1

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-pp38-pypy38_pp73-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-pp38-pypy38_pp73-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 5497f44ac696a73b478ec1281289a5eb763422158001b667ad33c4e171b22029
MD5 3b3c6dd8aa768550901e1a35ebcb810d
BLAKE2b-256 ba51db65d036547fc020f2030bdb7f54ac14b53cd92a06c1690c80faf98bc185

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: pypne-0.0.16-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 1.0 MB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.11

File hashes

Hashes for pypne-0.0.16-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 749d240c86f3d48a8e260a30d3662ea3562dcaaeeaf88e53f36b04bb39efad22
MD5 4831652b0a6b2f26c02d1b21a0df26cb
BLAKE2b-256 0d48a0670d2af4ada61a414d152c1d75f0ff3ebd2968d29095229b38f46889a0

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp313-cp313-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-cp313-cp313-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 301075da767341db282f7e5174d4fd1111dfe43373857d7a059eb3f56f75b149
MD5 f2012812ebcf678a8f4c410c797d85fc
BLAKE2b-256 f8a1af2b3f62cf121d93604207e29ba020159753c4ca5c71052faa697924e68d

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp313-cp313-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-cp313-cp313-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 a5e26dcc0fb0c5912a95d27401a3f873cbdee53861995f8effb154075f0d1d2e
MD5 36e3d234d602e2a4dc6c66fa8ee2ab29
BLAKE2b-256 0aae46f29d7cfab2166186302df8af9dced06114eff8a00036cc1a473b21ae48

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: pypne-0.0.16-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 1.0 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.11

File hashes

Hashes for pypne-0.0.16-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 72200a85f20eef0bc6440874c116faf3f15ee6e6db7dea33b3d735ae6e085191
MD5 95db8d2dcf42bbe539f5ee1a2b2de3fe
BLAKE2b-256 709fa7525013b60ee408ac883163bc40202c5c4feebd91cea900841129d2257e

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp312-cp312-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-cp312-cp312-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 0a3e687afebd7566c3d9e77a72ba52f4fe17b060a19026fb93de3f5ae8ae2c6d
MD5 4a28ef097b1dbd9a99972ae495c06057
BLAKE2b-256 36b2b869d51b20ca9ce2d6780fdac899bfdcd1c8d961bc9bace710dd241eaaa9

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 67d0f13c1308ac33f56e05f1605fd6f2b2c1c3eadbd5b743058850d145ec7314
MD5 4f49dc3e1c8525367119bd7afbc58ae2
BLAKE2b-256 9dd03d3eced02d83ecac00c6c419bacb319873a9c8b6dde07288a437cbb3a6c2

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: pypne-0.0.16-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 1.0 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.11

File hashes

Hashes for pypne-0.0.16-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 201deacf9da909ce065799b9cf83f89bde74f34e51e5ed6a8282006a5f01c724
MD5 a43285e0d36a4963dff5f3a58b5a31da
BLAKE2b-256 5bab8566c6727e1a17efe2153f7515c1860efc51b933ccf4be1d7797e48822e2

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp311-cp311-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-cp311-cp311-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 293389c8e413f38e20cf63446d0d870ad4d627c2057547f390f5b55ddf31a206
MD5 199460cd5d4f699661720088a52d615a
BLAKE2b-256 228a0524b2a49d23274dce122631165b69a8a4f433d4caadd9f159165aacdd1c

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 6c1838da59d7db92fb6367b59f5edadbfdfce187126492cabd63cace97cb317b
MD5 cb929a94dfff68f287385074f69e90c0
BLAKE2b-256 79a169e98d3c0bae2b7177c066e375917ce5b4badc8a52eec75661d778f738aa

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: pypne-0.0.16-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 1.0 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.11

File hashes

Hashes for pypne-0.0.16-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 b49852ee48636cbb31f0f7aa13f6017f776924293f72f1edd8ca1c2533d67538
MD5 e6a6b7953eaabe5d17aa5f94592d08a8
BLAKE2b-256 e219ab576cc959bb4f65cb9b790631dd7544c583256f21e131b57ff56d2742c6

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp310-cp310-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-cp310-cp310-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 e9071cc2e4fa8f29eda830f905899f6214a626b8ad098502a0436083fda4b2d1
MD5 46bcb1ec7becc5614d61785b1ea73e93
BLAKE2b-256 f9e8afec8b934030e50d103048db1c75ce6940096f7d180d649105d48d3e24f6

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 6a0ac188270c37cd9263ec3abf536b603efa27b3b38977c0e432fab919025b9a
MD5 19b1347cfdae84d91b2af820f6d7593a
BLAKE2b-256 38e6099e106fef562c0d03000f5577900a1b24be180b6784f670852b12556667

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: pypne-0.0.16-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 1.0 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.11

File hashes

Hashes for pypne-0.0.16-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 ab1456419be2656fa08fff9a98a23feffa66b59057546f945453533b48744c61
MD5 8e8fc93e793155202128ac1d709ad1cb
BLAKE2b-256 25cc6d25d83da6974e3cf326e45e9fc65cf62a5499c6e67c57f7836f1c82b275

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp39-cp39-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-cp39-cp39-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 c1e40f6b9cd547ba4a6b4883e795ffe0ce6ec1d58f398464ef31e45e977a3da7
MD5 f6197226615b754700e7b5fa98fa9c48
BLAKE2b-256 abde342caad4bf8decc115f72921fa2cd9d6980900afc031f81b2bb5a9fffee3

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp39-cp39-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-cp39-cp39-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 c73b092020c3780dbe2ce35ad113b3fde8be2ff701e9181923dff2e65dd2b764
MD5 73ccd76632e8fae7acc595c4a0305ae2
BLAKE2b-256 976ddd176f3cad078142253c3825dcb463279f91e14a82364f8eaad14f02a9e3

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: pypne-0.0.16-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 1.0 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.11

File hashes

Hashes for pypne-0.0.16-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 506623ed05dfafd50f4247e7d481d2ea69a43a12a1552d131c60a0a2713ff87f
MD5 a7940963d2c009f28a9703ff8009ec31
BLAKE2b-256 71ff330bf093d8b8aba32e55c3ab4264ce1b6c3b569f4f8e3b1d9d19b4236b7f

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp38-cp38-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-cp38-cp38-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 948dbcfd104fae486fdfa4736e0a0e9b8fdcff71314616df0fdcc123d699bed0
MD5 82d08616f627d7a8dcafba967450d30f
BLAKE2b-256 e3ec9be1992d48a02bf897305d5f9f06387922a80b450eaae8c0101e61bde3fa

See more details on using hashes here.

File details

Details for the file pypne-0.0.16-cp38-cp38-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pypne-0.0.16-cp38-cp38-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 943af83a7939f3b46886cdbf26bb60d55325d741ffa19d40f848a939c6f444a2
MD5 29cf0e59e0922f31fd8df58a43bf0850
BLAKE2b-256 e871c096f978ee3922fdcacd35fcc2e147b420538c5629efbc6866a0eb41f1f0

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