Skip to main content

Python bindings for Yrs

Project description

Build Status Code style: black

pycrdt

CRDTs based on Yrs.

Install

pip install pycrdt

Usage

pycrdt offers the following shared data types:

  • Text: a type similar to a str.
  • Array: a type similar to a list.
  • Map: a type similar to a dict.

You can initialize them with their Python built-in counterparts:

from pycrdt import Text, Array, Map

text0 = Text("Hello")
array0 = Array([0, "foo"])
map0 = Map({"key0": "value0"})

But they are pretty useless on their own. They are just placeholders waiting to be inserted in a shared document. Only then do they really become useful:

from pycrdt import Doc

doc = Doc()
doc["text0"] = text0
doc["array0"] = array0
doc["map0"] = map0

Now you can operate on them as you would expect, for instance:

text0 += ", World!"
array0.append("bar")
map0["key1"] = "value1"

Note that an Array and a Map can hold other shared data types:

map1 = Map({"foo": 1})
array1 = Array([5, 6, 7])

array0.append(map1)
map0["key2"] = array1

Every change to doc (a modified/added/deleted value) will generate an update in the form of some encoded binary data. You can listen to these updates and send them on the wire, so that they can be applied to a remote document.

We say that text0, array0 and map0 are root types of doc. When they got inserted into doc, we gave them a name. For instance, text0 was inserted under "text0". This is how a remote document will retrieve the root types of the document, after applying the received updates:

from pycrdt import Doc, Text, Array, Map

remote_doc = Doc()
remote_doc.apply_updates(updates)

text0 = Text()
array0 = Array()
map0 = Map()
remote_doc["text0"] = text0
remote_doc["array0"] = array0
remote_doc["map0"] = map0

You could say that there is nothing fancy here, it's just about encoding data changes so that they can be applied on another object. But this is where the magic of CRDTs comes into play. Their algorithm ensures that if some changes are done concurrently on different objects representing the same data (for instance on different machines), applying the changes will lead to the same data on all objects. Without such algorithms, this property doesn't hold due to the fact that changes depend on the order in which they are applied, and that they take time to travel on the wire.

The most common example is inserting a different character on a text editor on two machines. Say we start with a blank page on both editors, and the user on machine A inserts "a" at the same time the user on machine B inserts "b". After receiving the other user's update, if no special care is taken, machine A will show "ba" and machine B will show "ab". In other words, their document states will diverge, and thus users won't collaborate on the same document anymore. CRDTs ensure that documents don't diverge, their shared documents will eventually have the same state. It will arbitrary be "ab" or "ba", but it will be the same on both machines.

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

pycrdt-0.3.4.tar.gz (21.2 kB view details)

Uploaded Source

Built Distributions

pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.9 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ s390x

pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.7 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ppc64le

pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl (1.6 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARMv7l

pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl (1.6 MB view details)

Uploaded PyPy manylinux: glibc 2.5+ i686

pycrdt-0.3.4-pp39-pypy39_pp73-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl (1.3 MB view details)

Uploaded PyPy macOS 10.9+ universal2 (ARM64, x86-64) macOS 10.9+ x86-64 macOS 11.0+ ARM64

pycrdt-0.3.4-pp39-pypy39_pp73-macosx_10_7_x86_64.whl (662.0 kB view details)

Uploaded PyPy macOS 10.7+ x86-64

pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.9 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ s390x

pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.7 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ppc64le

pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl (1.6 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARMv7l

pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ ARM64

pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.whl (1.6 MB view details)

Uploaded PyPy manylinux: glibc 2.5+ i686

pycrdt-0.3.4-pp38-pypy38_pp73-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl (1.3 MB view details)

Uploaded PyPy macOS 10.9+ universal2 (ARM64, x86-64) macOS 10.9+ x86-64 macOS 11.0+ ARM64

pycrdt-0.3.4-pp38-pypy38_pp73-macosx_10_7_x86_64.whl (662.2 kB view details)

Uploaded PyPy macOS 10.7+ x86-64

pycrdt-0.3.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64

pycrdt-0.3.4-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.8 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ s390x

pycrdt-0.3.4-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.7 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ ppc64le

pycrdt-0.3.4-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl (1.6 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ ARMv7l

pycrdt-0.3.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ ARM64

pycrdt-0.3.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl (1.6 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.5+ i686

pycrdt-0.3.4-cp312-cp312-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl (1.3 MB view details)

Uploaded CPython 3.12 macOS 10.9+ universal2 (ARM64, x86-64) macOS 10.9+ x86-64 macOS 11.0+ ARM64

pycrdt-0.3.4-cp312-cp312-macosx_10_7_x86_64.whl (659.8 kB view details)

Uploaded CPython 3.12 macOS 10.7+ x86-64

pycrdt-0.3.4-cp311-none-win_amd64.whl (464.1 kB view details)

Uploaded CPython 3.11 Windows x86-64

pycrdt-0.3.4-cp311-none-win32.whl (440.5 kB view details)

Uploaded CPython 3.11 Windows x86

pycrdt-0.3.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

pycrdt-0.3.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.9 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ s390x

pycrdt-0.3.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.7 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ppc64le

pycrdt-0.3.4-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl (1.6 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ARMv7l

pycrdt-0.3.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ARM64

pycrdt-0.3.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl (1.6 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.5+ i686

pycrdt-0.3.4-cp311-cp311-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl (1.3 MB view details)

Uploaded CPython 3.11 macOS 10.9+ universal2 (ARM64, x86-64) macOS 10.9+ x86-64 macOS 11.0+ ARM64

pycrdt-0.3.4-cp311-cp311-macosx_10_7_x86_64.whl (662.6 kB view details)

Uploaded CPython 3.11 macOS 10.7+ x86-64

pycrdt-0.3.4-cp310-none-win_amd64.whl (464.4 kB view details)

Uploaded CPython 3.10 Windows x86-64

pycrdt-0.3.4-cp310-none-win32.whl (440.5 kB view details)

Uploaded CPython 3.10 Windows x86

pycrdt-0.3.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

pycrdt-0.3.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.9 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ s390x

pycrdt-0.3.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.7 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ppc64le

pycrdt-0.3.4-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl (1.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARMv7l

pycrdt-0.3.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

pycrdt-0.3.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl (1.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.5+ i686

pycrdt-0.3.4-cp310-cp310-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl (1.3 MB view details)

Uploaded CPython 3.10 macOS 10.9+ universal2 (ARM64, x86-64) macOS 10.9+ x86-64 macOS 11.0+ ARM64

pycrdt-0.3.4-cp310-cp310-macosx_10_7_x86_64.whl (662.6 kB view details)

Uploaded CPython 3.10 macOS 10.7+ x86-64

pycrdt-0.3.4-cp39-none-win_amd64.whl (465.0 kB view details)

Uploaded CPython 3.9 Windows x86-64

pycrdt-0.3.4-cp39-none-win32.whl (440.4 kB view details)

Uploaded CPython 3.9 Windows x86

pycrdt-0.3.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

pycrdt-0.3.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.9 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ s390x

pycrdt-0.3.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.7 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ppc64le

pycrdt-0.3.4-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl (1.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARMv7l

pycrdt-0.3.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

pycrdt-0.3.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl (1.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.5+ i686

pycrdt-0.3.4-cp39-cp39-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl (1.3 MB view details)

Uploaded CPython 3.9 macOS 10.9+ universal2 (ARM64, x86-64) macOS 10.9+ x86-64 macOS 11.0+ ARM64

pycrdt-0.3.4-cp39-cp39-macosx_10_7_x86_64.whl (662.2 kB view details)

Uploaded CPython 3.9 macOS 10.7+ x86-64

pycrdt-0.3.4-cp38-none-win_amd64.whl (464.0 kB view details)

Uploaded CPython 3.8 Windows x86-64

pycrdt-0.3.4-cp38-none-win32.whl (440.3 kB view details)

Uploaded CPython 3.8 Windows x86

pycrdt-0.3.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

pycrdt-0.3.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.9 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ s390x

pycrdt-0.3.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.7 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ppc64le

pycrdt-0.3.4-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl (1.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARMv7l

pycrdt-0.3.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

pycrdt-0.3.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl (1.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.5+ i686

pycrdt-0.3.4-cp38-cp38-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl (1.3 MB view details)

Uploaded CPython 3.8 macOS 10.9+ universal2 (ARM64, x86-64) macOS 10.9+ x86-64 macOS 11.0+ ARM64

pycrdt-0.3.4-cp38-cp38-macosx_10_7_x86_64.whl (663.4 kB view details)

Uploaded CPython 3.8 macOS 10.7+ x86-64

pycrdt-0.3.4-cp37-none-win_amd64.whl (463.9 kB view details)

Uploaded CPython 3.7 Windows x86-64

pycrdt-0.3.4-cp37-none-win32.whl (440.3 kB view details)

Uploaded CPython 3.7 Windows x86

pycrdt-0.3.4-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

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

pycrdt-0.3.4-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.9 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ s390x

pycrdt-0.3.4-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.7 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ppc64le

pycrdt-0.3.4-cp37-cp37m-manylinux_2_17_armv7l.manylinux2014_armv7l.whl (1.6 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ARMv7l

pycrdt-0.3.4-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ARM64

pycrdt-0.3.4-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl (1.6 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.5+ i686

pycrdt-0.3.4-cp37-cp37m-macosx_10_7_x86_64.whl (663.5 kB view details)

Uploaded CPython 3.7m macOS 10.7+ x86-64

File details

Details for the file pycrdt-0.3.4.tar.gz.

File metadata

  • Download URL: pycrdt-0.3.4.tar.gz
  • Upload date:
  • Size: 21.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for pycrdt-0.3.4.tar.gz
Algorithm Hash digest
SHA256 02503edda929196046c12cd64c58e437f3674f2eaa46072df8220e56980c2d4c
MD5 745e330eeea40f55cf73f5e2430d3cf0
BLAKE2b-256 60deeba5491ce89d3e73463022d4bf66fe465d014a3c3bdaa5d857ff16b5784f

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a68bf7e543e10ffa763b8ec0623f10562b80ba502be09648944b2138e28a2c55
MD5 89d31d26e1d5e8490995145b153424dc
BLAKE2b-256 064af7fd111616858a6a3d709f4f423ed7f6aa8929fd431cf9d77d012ccf5237

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 0af8127bbf20f96e9e33850aa5d308e0b492dad67f459bb0eb1b7e72750c8a9e
MD5 16cefccc4373729e86bbfeb4cdd00aec
BLAKE2b-256 1e54e809b3fb087a83f4e1fcfe732a1205870d5185d6a27400aef32856c85d34

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 75f9ffc83d61ef5292fb8090020dad9ced0da1a656a41fbfe62383f9ac0b81bc
MD5 ef2c088a3a8d275091cf493ede71b5e8
BLAKE2b-256 fe97c803d3ae930ca303ecb8b2c8a21e206c16e928ee0deb90d85b0afdba10df

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Algorithm Hash digest
SHA256 5d3665ccfed2eb5c3c61872df07b22994e651b74a4a1bc3e745ef0779926671e
MD5 7f34117b7762783b5c94152e5f938e3b
BLAKE2b-256 9e522ef70828b5e961224693117e88e60c4bf6599f1662aa938825e9a89c4b32

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 cf81bee56a191bb5c66ec0e057f986a836b22676313f6954fdb55e614c026d1f
MD5 22e5876ac26e4dab968e9df8763c3b9c
BLAKE2b-256 871bbd7061116a8b9badb66e7e7b9da0aab7971e2f19853b73530ea158fa4134

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 5a345fed2c38d30c5ef06e552338f456b7b67f34c9d4cec44f40519bfa671891
MD5 6d15ca9317f4b2569ee8df2049565975
BLAKE2b-256 5cd830353a2580a05f3dcadade8d5dd930f806c093b07464b0a05e6bbf522a5c

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-pp39-pypy39_pp73-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-pp39-pypy39_pp73-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 db0e7440f7140c6dbc8603b4e4c18caff141f49768a49f6f3fcad0e6ab426cc7
MD5 97867612657c734c47657337be765931
BLAKE2b-256 120c27314dd4bd369dceba822e118fc560dd9a6168f3f10e627f5ba8d7ecd7df

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-pp39-pypy39_pp73-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-pp39-pypy39_pp73-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 a4cb4c3018a898eacda4477b6974445b2d6afc464ad62b233612a94e21184534
MD5 c08fceaa48d084cbeecd6a6e3b788866
BLAKE2b-256 94467cdbb9f1a0f0ef961e3f1ed9ee1ecf26b26fb9269578d83dd0baf8822a89

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 98ec508735e591fa25cb82035b72a6d13f041e46e08f8f11e1cc021af029e3cb
MD5 4820bf0d84c54967444c101fbe7d8f66
BLAKE2b-256 8c8dc9c4172fbe8543b7dcc094f12a62070d057b6b7cfb4b0671beaa67534d40

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 589857d3598b073837d027cb98c2bd37064988279709afc2cfebee072ac2c226
MD5 c5a5c38acf7b9d87b39da1f964db7eef
BLAKE2b-256 d829dfd631456a45c4fec5fec07aab02e8a613a22352d7b4d719c822b4664157

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 24f71afbd96169c4e791157fe303cc8d7ba9614eabf2ba8aa6ab7a5e67b980c2
MD5 bdc789d8a3d113e0814fa3d5a70b158e
BLAKE2b-256 19ff6922df1d7cd409e05cc4c702f799d20e61bcd11ff3eefeae171eb0c50dcd

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Algorithm Hash digest
SHA256 7040e7229651bd2a15504c3464c6a86347f216b89b80169f1ff89144b9321216
MD5 d64922c25976c128f295a6365302910a
BLAKE2b-256 6703babc036dd06eb053e829d04dcd3b48f00feb36f421aebb23b5a3e73f4014

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 559fbe2d299d0c43eddadce7917f30ac04209659eadddc298e01fa7e34b13103
MD5 aca508b6f62b213869b9321f56ea15ab
BLAKE2b-256 5b6a946e7cf189a881daad0acac2c1b320fdb7303e42b7a53356ebd00d64c2f7

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 7f15b8fb636a30f52a7aac87cdfa025a76361b5bf474ee28aa6a5f9ca67d0aef
MD5 68294fcc199994ff748b7bda87a7e91d
BLAKE2b-256 d520d64c51c003d68de3aed7d1c94b5cea8267b617bc31e0a15ebbc84653089c

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-pp38-pypy38_pp73-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-pp38-pypy38_pp73-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 70fc5c5417a374bf3a701fbbb1396f0c8bcca9997d4f0d638c96e6661a86222a
MD5 9b6daa9d50cf04ae04636991e9391e02
BLAKE2b-256 edf0e026d77d2011a331dd1b2f25114b40799fd6bb962cf9501766df04c3e94f

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-pp38-pypy38_pp73-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-pp38-pypy38_pp73-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 9bfd5c1e196ea02a7d1c84340dcae640916c01189aff69f0d6d0458d60d179f9
MD5 3886f0c09936bdbf0b5081fbbe3d9c6f
BLAKE2b-256 d7e03925caac7b11e313e3d5662d341a6e89eaad418e2af4ea25c2ecc49269e4

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4d4b37e218e32288b3e7c997e6c93743e14f8fa4d268a66e3f78300dbd27d176
MD5 84b47fb8e29a28d83a5e91d315caa669
BLAKE2b-256 ecb5cfb8ad5b31c09ef0c8012fc8d171468025112c8e0ac0f79c1695c9407b2b

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 6fa46769ded01ec16a1845f21af125b0ea8838e0ab0a4c70b68d7ff18b49fa7a
MD5 463e5b06f91cbb2c7e551aa9050c62e8
BLAKE2b-256 cc37f809f93e4ebb67ca9c83886b2fe61d19705ddb271536045383ba83509160

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 17b302bb7aefaf00b740b2b42c9c6150edf5dd464ea9f197384988c26aa86cc1
MD5 32f5f5c0c6c95e59b73fad2f74815ef1
BLAKE2b-256 7e5c930a54c5cb057235fa3e57c6fef33c708d8dbcf714a40bbb78be9d437f62

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Algorithm Hash digest
SHA256 a5fb5ba77f2585f09a0952420e90ccee9692d25ad0e5619cb6041190d3702257
MD5 203a119680dbbff7ddb9d9b3c654d07b
BLAKE2b-256 904681ae4332e1de924aed9aea0e9a8d260b54006258b56aeaf2eea457736e9d

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 fae982c1c7b0515c4cbdb89d98c2c4e6a680a3780049d34be8bdec29d63054f7
MD5 35c02397c6abe7c37590e644de4c1c10
BLAKE2b-256 f695e6cce03f74d0b97eb3cd4ed05cbbaaa03f210c50039b7e2d0363d3097cac

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 8c34c4ce44ae51f5f6a0c9616de47c1e5c2b255b64635ec48becd5705593b74c
MD5 e5acc6bc070087923155fa21430b2d6b
BLAKE2b-256 abd7916beaeb55213a2f63c94ecee368f358b2ebd477e2edcc526a284a73b631

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp312-cp312-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp312-cp312-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 fe2611a0fdaba044f1d39bdc18694aeb48f8493e503692f168e293eecc31b025
MD5 f8e45ba7f1c54e24dfa61f57a8693991
BLAKE2b-256 47563baf63f5b8a6751f05423eebb05145c075bfb82704f4e3bd9efa644567bb

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp312-cp312-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp312-cp312-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 49001dfae6cac39e59fe28cc08f829820c0937e11ad527f4f6586501696e9959
MD5 5fdd507bdfb01397a447c105a5cd92b1
BLAKE2b-256 6af515978facdfb9b913dd1a8fbecdc8809b1d5c1dd7012a78e7c17473055756

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp311-none-win_amd64.whl.

File metadata

  • Download URL: pycrdt-0.3.4-cp311-none-win_amd64.whl
  • Upload date:
  • Size: 464.1 kB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for pycrdt-0.3.4-cp311-none-win_amd64.whl
Algorithm Hash digest
SHA256 8d1ee67fd3eed1aa4fbec7457f820e5bc2d8df93ea54c611d73d38aeb0c60892
MD5 5b4f5fe5d5e7369732ad26c289f139a8
BLAKE2b-256 c6718ea47aa7573e93694022faf6fc9e99d5d519fe4b3811cc99ea1e6adf088e

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp311-none-win32.whl.

File metadata

  • Download URL: pycrdt-0.3.4-cp311-none-win32.whl
  • Upload date:
  • Size: 440.5 kB
  • Tags: CPython 3.11, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for pycrdt-0.3.4-cp311-none-win32.whl
Algorithm Hash digest
SHA256 c8b1b10bd5717aa4a22b74026d06cf1559ef77c5a9ff7c47b287660f605fcd0e
MD5 4b0a47fa7320ec4e05f47fcc5cb06d1c
BLAKE2b-256 1fda30cef629827979c921b845b52abd48393b2626ef00c090c39092be5b6367

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 40368106d27e39d82c8856af8ffb18e16c3fd96a58c24d43e33f23ef47e0ce02
MD5 23d1d98dc680f677901330fc0fa021a9
BLAKE2b-256 ca142c6a2cce917d4e85548a45b4b77d2143d10bc378458ee7f54d8e61ce590d

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 5605ef610067199c8930945d05b64fc5bd56f0f5d1668c4cf965d1584578c382
MD5 ce9b1276924dfcd1fdd9d6486ae94de3
BLAKE2b-256 ccc5664a8b26645584c26f2245bae8826b4443233bcf7ba1286054f6bdef754c

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 300a1559776815f9cb4f1c67f333b037dc5e30f313dc21616586772f9fb8f7fb
MD5 92663ee3b06e2c30f0f0239e4a86d18f
BLAKE2b-256 c4a3b438d75889a379f50b38cdadc2f6a1f0d5b89de8d396b68e7a0686d444e5

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Algorithm Hash digest
SHA256 e21ab4402041d1feff92990eb79a661720d72bcdcd207cc3ba5abca893a1363e
MD5 e8dd326bad092fb5642c567506fc82d5
BLAKE2b-256 f6fb289a97c2eeef4eb393bef9c9b84b6a9d4e4fea7523b37900fd06b7f7acc8

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 4c9edc54a231db15e0392ed8bfb2a2e17ccab8f21d7314dff3178d36c7754820
MD5 bbf8e102c285764fd3fa0524acaf36a8
BLAKE2b-256 76a40a5f68ff277d2f834e177590b9aa3f434f9f9bccb64aaec6410ca79e43d0

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 12920c5c66ed279de59e8a8126eada307167dff57558e160566951a511de0ecd
MD5 0b224423f959d4e303bd09d272d6cb34
BLAKE2b-256 5c092e517b9f53ab503dd6cc591fccb47ddb9d5878ab80c3322e1e58f7471bd5

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp311-cp311-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp311-cp311-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 d8f14a4421004454d45872547fdf86e07036863e2bce17f2d1c7f98de06d3b38
MD5 1b596abf7f51a9ae04fcef463d6b6585
BLAKE2b-256 293bdd2d8eda5885c7d4145eb58a65ad6b58a127b38ef9ae6d01a073c7108a40

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp311-cp311-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp311-cp311-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 5cdfcbb3ed865259b098178a07552937ff51c5a2922782a7ff5d7e63f7ecfab1
MD5 94c64aa7d9a161a82aff59310c19cef8
BLAKE2b-256 bed58fd6124fedf38ad29b39635268fccc03662125c869e4a5d715976311c4c3

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp310-none-win_amd64.whl.

File metadata

  • Download URL: pycrdt-0.3.4-cp310-none-win_amd64.whl
  • Upload date:
  • Size: 464.4 kB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for pycrdt-0.3.4-cp310-none-win_amd64.whl
Algorithm Hash digest
SHA256 302ba8ff4385e14a50ae405610dde36e0a4fdca898456b3e72ef4bfcc180a2e2
MD5 6ef05bd207b8df426e4ea2bc95b8e432
BLAKE2b-256 e917c93c687d6b2fb7d0301fdcd2ab9a79f02c33305d618031c648a73e8312f7

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp310-none-win32.whl.

File metadata

  • Download URL: pycrdt-0.3.4-cp310-none-win32.whl
  • Upload date:
  • Size: 440.5 kB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for pycrdt-0.3.4-cp310-none-win32.whl
Algorithm Hash digest
SHA256 1c3df4008c1b089af8265088414e896aeb7e11497a8fab74e53e07a87b796a92
MD5 c2c87dd24869a0d49bb3905cb7ef4a7f
BLAKE2b-256 6946cf21ef9115012ca40d78f1f6cfdc364f95f2964ac2f5e2dcf0bc618dc631

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ce888bedcec4f88f450ac4a907c1da3dc3d41cd9eaa2c8f5ae1ffe9b31ea6178
MD5 d8a9913ec2ab24917d18ea9d1cb22275
BLAKE2b-256 067603893dd3a69e5b3bcb87898e0058890ffe76c4b558bc81c426670bffdd1e

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 641b5b5caba7612e880c2b1a65f58577479f1ba0d89b906cec3dd86bf132c181
MD5 5cea3954a86f7dbae87ef8547c6fb837
BLAKE2b-256 e704f82d6b7c53a2070741da2563ccd4ab606c83f396fbec8f6eb897e2289838

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 834b0357cf464e09b1adc5d3217ff176bdd11d2afeda6d5d58229844c99ba1ae
MD5 c532a351292d26745c9678a1e00e1b4c
BLAKE2b-256 c6702a46785c7af992ce36c58023f802972cb33c64dbca6fb035697974169469

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Algorithm Hash digest
SHA256 cb45d99036110b074058f1c8708df531322cf0c793ff7d0a5c02bb78fb6c3b3e
MD5 09d44182d8ece6043e602dd5db616720
BLAKE2b-256 7725ccbfa7b66ec37c7de3123005392491d4b5906775ed61e98b6b6ab61cd1f7

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 cee8f11a4761355467cd87a4eb0efd7cc5660324bc484684f0ea4425e608ef46
MD5 bd863d8c14a69af1ba9e031aea40cb49
BLAKE2b-256 a1afde585ff3fe4ff2be7513e7e2890a6321bf4e008691431a791e306df4ab12

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 836f4045241e9f41695772cb551395acece6f5c6042d445e617b1bd51d9c5d91
MD5 d7eaa4e3c7050088589a0c2f7a4a597b
BLAKE2b-256 ebbc845870d2c578ca0bf8a4bb1e7f7ca13a21774c760991ee0d6b8a6462ad98

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp310-cp310-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp310-cp310-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 9d58e039e428006262a84a031b30de2dedb3b3ba62e7c87d77186d2730fcc3f6
MD5 c046f459a3e90eac071c99f16c87381c
BLAKE2b-256 b82efa362a07b7ced3b643a419cb37a366ca7680e514dd7d00c212aa18464ca0

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp310-cp310-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp310-cp310-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 446d6823b858e48b43e80e5a272f6d8d40b8d6d1245ac9562635cad587e3cb01
MD5 0dc989f5ee6994662c76a2deafefce58
BLAKE2b-256 ff4ed0ce0897db4549a6d9285d12bd40664b43863888ace5b866918590569da7

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp39-none-win_amd64.whl.

File metadata

  • Download URL: pycrdt-0.3.4-cp39-none-win_amd64.whl
  • Upload date:
  • Size: 465.0 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for pycrdt-0.3.4-cp39-none-win_amd64.whl
Algorithm Hash digest
SHA256 928fd5410b508a8b59a413cc286be14cd95d411190f6c2c0c41aeb2215215d09
MD5 da03f922bdca97ce6547e393990f85e7
BLAKE2b-256 e52856963970081a27ae507775bbd2be99857d2c9565cafaa6560018377ba6f5

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp39-none-win32.whl.

File metadata

  • Download URL: pycrdt-0.3.4-cp39-none-win32.whl
  • Upload date:
  • Size: 440.4 kB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for pycrdt-0.3.4-cp39-none-win32.whl
Algorithm Hash digest
SHA256 fc6882e4c45256d7ed85af30a0337de37b5bd010d943263f413f69df17023fa7
MD5 2d24d837035c1b4d10114c97dd5ade83
BLAKE2b-256 11d1873057e506daf20c098468d3287117f2f52e673b2c4ce57025bb40ea95a8

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a8fd564951072f85c563812ab8a76904706647538cda3de8b116ff62a9cd711f
MD5 f7f143f3ee0027361422ef3fa98372e4
BLAKE2b-256 bda50cfece01a36de7101065fd4b6161b945af9a6d259009abbba018c56e98cb

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 93f586593ca471421e6e8f0e9ae29c9260be145f3844699f7af848664bb7571a
MD5 537d5de6cfc7263920a1283bd374dc49
BLAKE2b-256 7ea009878bcc227539ec4b369499e8150a079909612b43cbb33ef0bfda90e547

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 8a6073cd6efe2c32a8894242531f2ec364bf0613d28d98c4fdc183fd0d5a1c6f
MD5 0df6ef019eb28f7940d3a5ba6f8ee313
BLAKE2b-256 64f70642ca2d36711dae6df36fdaa0e349b875ad1f7ae0ac8de17732cd27893b

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Algorithm Hash digest
SHA256 847882821ff1b1ea0a55ddf342b6608bed382ee3ebf6762a2848838891e535a7
MD5 6dbe31dbd0212219a97998fbbb42389c
BLAKE2b-256 337c981b8de1784eb9025fd23a0b2f33986427b406095f249eae4aa415c29827

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 1715f89fa55a2656edfdd07606d54aaf1fd08cdf9ee6a7e53755f0404a6c4a31
MD5 035bcf80c86abbedc926010190f9ff8d
BLAKE2b-256 45a5fba48dcf51e56347250c7fbb8d232f82c6f4f03ac230b10aebe0d407b89d

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 de866913d79743a907f6d9c812e90296486c2a56c49ae814e9d4c89864fecff1
MD5 cb78b2c3e8825c1ac8eb3a7093d384c8
BLAKE2b-256 2db10de2b03a41277b4741099b94f92ed6bafaaa81a3c3e92f3d8a5ca7fbda0a

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp39-cp39-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp39-cp39-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 eaf4d65a1785869b85818129cb344752aa0f0f0669e2735013245901c927e0cc
MD5 b7cee5e7e1357d1287e567bf1db243e9
BLAKE2b-256 37e8093e33710296c7ae1082d3cea8ab6be07c345fa02f44258dd1ca3c7a8fca

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp39-cp39-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp39-cp39-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 7905eda8919e3110717a50b60640e3cf65df83295ec913ef58288ea3d0762de3
MD5 86fb9a201c05677f7e96333228871fef
BLAKE2b-256 8b184863867b7ce77fabee1fa1f1e720d75f8868b8c0b8258808914b580463ff

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp38-none-win_amd64.whl.

File metadata

  • Download URL: pycrdt-0.3.4-cp38-none-win_amd64.whl
  • Upload date:
  • Size: 464.0 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for pycrdt-0.3.4-cp38-none-win_amd64.whl
Algorithm Hash digest
SHA256 e47604efafb4c7cc48d4afb5fd674087004c8f4a108073f1b455d73ad095d693
MD5 e5c7137eb9326aa0ffa3b699928cbb53
BLAKE2b-256 40a1765f946b5a673cdd29a8b277a95de7481de07abe96ed7db3bfcb8f9938f7

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp38-none-win32.whl.

File metadata

  • Download URL: pycrdt-0.3.4-cp38-none-win32.whl
  • Upload date:
  • Size: 440.3 kB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for pycrdt-0.3.4-cp38-none-win32.whl
Algorithm Hash digest
SHA256 7bbcb86cdeab6b4dd982c65f12fa9192e8bd641923807d7427658b6f4f927b12
MD5 34f49dcdd668823f600b30bb9e5287bc
BLAKE2b-256 774c322938d3da84086cc7063ef5a3beee205cea06fa29149e4a38ba0cf8793a

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 7ba418f90dbbbf56682e5bb629c874a8b829bebba32f72c63469e5ecd0e7a2ce
MD5 db88db06134dc88b818e564d3432291a
BLAKE2b-256 43170ca17c5e2a0e7b17461162e9cebeae631fa4d21c7e7deaa1a315c0a373db

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 bbfaac4413eab5506354cde5cdc3dd19c0915e58f69b3ad4d650a86e79bf50e3
MD5 1ac207751a0b6294a48beedb1f2b812c
BLAKE2b-256 6c5774ec453738c7705c5c5499590c6aee2e196563e81779194c296161200d4b

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 9c1e292beaf4f348956880cc0be04a0473a471523b9811600e8bdfa89155f284
MD5 4e22ce4bf8ef1f0ab0b7758505c71acd
BLAKE2b-256 c2b3a192b0e827627e2fb3073027c41368384cd084cc24de88e84d867a3c2ea7

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Algorithm Hash digest
SHA256 f5928178d01ed1146b79d68d5d05e566a977a4f924a20336d3179f9203fc7ddb
MD5 3b0a737b4f68b155f489881cb6767dee
BLAKE2b-256 f344c7c75a6e29da46d25e1d48bed5f42d74be640a63fc928135206679ebff10

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 9dddd5704ad4cfd75eb69a74a8065c88d392c69c198a13c1a8d2431a227a1dc9
MD5 71d5500ed85735db90b6c1b6a26d4cca
BLAKE2b-256 ddf5702b911665993303c64f1896d413306e970a940787e33c8e75b60131ed1a

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 986cb89f38e0f45692d9bf7ba493d48e9a4001312394fdd38494e0e8883a354c
MD5 3657080624116c8817c3173cd55bb12c
BLAKE2b-256 21594b0ef0820c00e7dd5a8e4089f10fe2111f78a94656d561ea0c10e2a91227

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp38-cp38-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp38-cp38-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 f0776a4b5cae864e290599b143c12697c185014e794b4d953536a4a63b2235cd
MD5 3b6ba7df25807a27b2aac08771c8cf02
BLAKE2b-256 8c5b941e75ffe31c421e4238cb9f165265eec30d553e90477941dcb3f8b053f8

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp38-cp38-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp38-cp38-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 4ea7f4c92228b9c254df65cf1d4bb2898d36705c922492d899082f827cd3ca6e
MD5 ae0c8150a0f8529ad6b3f360599399ee
BLAKE2b-256 7e90346a7298b3bece57d0f04720d4fb3c62ad9f919a496d0c5a6b1376c9e840

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp37-none-win_amd64.whl.

File metadata

  • Download URL: pycrdt-0.3.4-cp37-none-win_amd64.whl
  • Upload date:
  • Size: 463.9 kB
  • Tags: CPython 3.7, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for pycrdt-0.3.4-cp37-none-win_amd64.whl
Algorithm Hash digest
SHA256 f1bde5e6397848f7b82c381da8754e198e37e51c5645709b19d9477dc0dcfc61
MD5 d78dc595eca97293cd00773967c98b53
BLAKE2b-256 e98a19ce68cb0da95f12848fb15dc727c4f0bb84f1102ba4f3430d3e41e7572a

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp37-none-win32.whl.

File metadata

  • Download URL: pycrdt-0.3.4-cp37-none-win32.whl
  • Upload date:
  • Size: 440.3 kB
  • Tags: CPython 3.7, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for pycrdt-0.3.4-cp37-none-win32.whl
Algorithm Hash digest
SHA256 b85d28329a89400caad44ef6a41a82faffe7d274bfd3c53e2691fcbe3e92c93f
MD5 dbb15b39cf301381924519181af3dbe2
BLAKE2b-256 3fb22cc7e6a9edb95acc3de1e1be10b00a1dc3857a7d6904212ac4bf6c579fe6

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3cd65faba50dd5b77c9ce94e50b89a4eea5d9f7b39e2e22e6a3ed484e16b4689
MD5 9bf8065d0f267e75dc661246094b930a
BLAKE2b-256 1f729f6b5b859c3b23c784e4d083dc271ba8f76ad24205262f16c68f4fd5011d

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 411697ebb082dde3d4f73646bec61fede59675c18f62a15ed66f3927c1470b72
MD5 cfd185a0945850c9326fc0b8e6f6f74a
BLAKE2b-256 53ea2442e8c60ea2f23400f7b67fb54adcc1d8497ccf58fc9af9f288ce33d951

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 4dde4c629d264d87e0141f8ed04857467cab1fbf3f114042c80757d859911703
MD5 6364eb3e8c19cdf32d8be70dac202adc
BLAKE2b-256 53c746c4866803c6a68e9a86f92411292104f2fcab79e8b025c1fa5521901b8d

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp37-cp37m-manylinux_2_17_armv7l.manylinux2014_armv7l.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp37-cp37m-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Algorithm Hash digest
SHA256 04e46cfe4d7c690d179301b4400947681734b3eddc0f912aced006930f82e38d
MD5 8abdfdb0bbfffaf61265a026759f1f9e
BLAKE2b-256 3522c3ddd1a4362d61f69b5153f1ca2d52c0610326fa0acc50a46564a7be74d7

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 cf6485392e2a9e4408a9f3b4953db030bbd2769039d8cd1b706652930be75282
MD5 7ad3e10aaa9d8379eb5e6331ec45fcea
BLAKE2b-256 89ad10dc965569b257eeb528d5480d269e50b489bc2509dba0b9f8240d934c2a

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 7957cad649f39eef77dc4f859a4a4cc51fd78ebbd50832f149be4bd2fe046273
MD5 40f73339e661211589d0c6b934d51377
BLAKE2b-256 1e02e99705113fd8f69ad6c39df36429b9b1bb2254bc931eb00e5d8360a076d6

See more details on using hashes here.

File details

Details for the file pycrdt-0.3.4-cp37-cp37m-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for pycrdt-0.3.4-cp37-cp37m-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 67f090a600c2b6599550bb540f4d618eb1ea933a94956a0d05df42293ffde4bc
MD5 f32cdd2e79cd5ab0f5be795134de6c86
BLAKE2b-256 02d454a9d98679a8e8018c554d8a62c1225f1dbef080f212047fbbbd029eaedf

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