Skip to main content

A Interval Tree Library

Project description

iTree - an Interval Tree library

In computer science, an interval tree is a tree data structure to hold intervals. Every node in itree has a start and an end value.

Installation

Install itree by running:

  pip install py-itree

Quick Start

  • Symbol For Node And Tree
  🟢  - normal node; 
  🔵  - zero interval node; 
  🍁  - leaf node, which means no child node
  🌳  - a tree
  • Create Some Nodes
  >>> import itree
  >>> itree.Node('fruit', 0, 40)
  [🍁 n=fruit,s=0.00,e=40.00,x=0,c=0]
  >>> itree.Node('fruit')
  [🔵 n=fruit]
  >>> a=itree.Node('fruit', 0, 200)
  >>> b=itree.Node('apple', 10, 20)
  >>> print(a)
  [🍁 n=fruit,s=0.00,e=40.00,x=0,c=0]
  >>> a.append(b)
  >>> print(a)
  [🟢 n=fruit,s=0.00,e=200.00,x=0,c=1]
  >>> print(b)
  [🍁 n=apple,s=10.00,e=20.00,x=0,c=0]
  >>> print(a.nodes)
  [[🍁 n=apple,s=10.00,e=20.00,x=0,c=0]]
  >>> 
  • Create And Render A Tree
  >>> from itree import Tree
  >>> def demo_tree():
        t = Tree(tid="123", extra={"img": "1241241313.png"})
        t.start("root", 1, {"name": "itree"})
        t.start("math", 2, {"age": 10})
        t.start("music", 3, {"location": [1, 2, 3]})
        t.end("music", 4, {"price": 12.3})
        t.end("math", 16284000, {"memory": (1, 2, 3)})
        t.start("music", 122840057.8713503)
        t.end("music", 1228400500)
        t.start("music", 32840057.8713503)
        t.start("egg", 3284.8713503)
        t.start("icecream", 32843.8713503)
        t.start("pizza", 32843.8713503)
        t.end("pizza", 62845003)
        t.end("icecream", 62845003)
        t.end("egg", 6284500)
        t.end("music", 628400500)
        t.start("piggy", 3284.8713503)
        t.start("unicorn", 32843.8713503)
        t.start("monkey", 32843.8713503)
        t.end("monkey", 62845003)
        t.end("unicorn", 62845003)
        t.end("piggy", 6284500)
        t.end("root", 1628400570.8713503)
        print(f"{t.count},{t.depth}")
        t.consolidate()
        img_path = t.to_img()
        return img_path, t
  >>> img_path, t = demo_tree()
  >>> t
  (🌳 id=123,c=11,x=1,d=6,m=0,o=1)

Run the demo_tree() function, a tree digraph will be generated:

The green circle node is a virtual node. The yellow record box is the node with max interval.

Development

Turn on local build to ON in itree/CMakeLists.txt:

option(LOCAL_BUILD "build locally" OFF)
  • Test
$python -m unittest discover
...............
----------------------------------------------------------------------
Ran 15 tests in 1.209s

OK
  • Format
find itree -iname *.h -o -iname *.cpp | xargs clang-format -i
black -S . --exclude '(gcc|infer|\.history|workspace|vendor|\.vscode|\.git|\.VSCodeCounter|img|venv|.ansible|.cache|.local|.vim)'
  • Build
rm -fr itree/build/ && ./release.sh && yes | cp itree/build/_itree.* itree/
pip install --editable .

License

Tree is licensed under the Apache 2.0 License.

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

py_itree-0.0.8-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (217.7 kB view details)

Uploaded PyPy manylinux: glibc 2.12+ x86-64

py_itree-0.0.8-pp37-pypy37_pp73-manylinux_2_12_i686.manylinux2010_i686.whl (231.1 kB view details)

Uploaded PyPy manylinux: glibc 2.12+ i686

py_itree-0.0.8-pp37-pypy37_pp73-macosx_10_9_x86_64.whl (182.8 kB view details)

Uploaded PyPy macOS 10.9+ x86-64

py_itree-0.0.8-cp310-cp310-musllinux_1_1_x86_64.whl (745.8 kB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ x86-64

py_itree-0.0.8-cp310-cp310-musllinux_1_1_i686.whl (815.2 kB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ i686

py_itree-0.0.8-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (220.6 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.12+ x86-64

py_itree-0.0.8-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.whl (233.6 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.12+ i686

py_itree-0.0.8-cp310-cp310-macosx_10_9_x86_64.whl (184.9 kB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

py_itree-0.0.8-cp39-cp39-musllinux_1_1_x86_64.whl (746.8 kB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ x86-64

py_itree-0.0.8-cp39-cp39-musllinux_1_1_i686.whl (815.7 kB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ i686

py_itree-0.0.8-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (220.8 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.12+ x86-64

py_itree-0.0.8-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl (233.1 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.12+ i686

py_itree-0.0.8-cp39-cp39-macosx_10_9_x86_64.whl (185.0 kB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

py_itree-0.0.8-cp38-cp38-musllinux_1_1_x86_64.whl (746.3 kB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ x86-64

py_itree-0.0.8-cp38-cp38-musllinux_1_1_i686.whl (815.5 kB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ i686

py_itree-0.0.8-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (219.3 kB view details)

Uploaded CPython 3.8 manylinux: glibc 2.12+ x86-64

py_itree-0.0.8-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl (232.4 kB view details)

Uploaded CPython 3.8 manylinux: glibc 2.12+ i686

py_itree-0.0.8-cp38-cp38-macosx_10_9_x86_64.whl (184.9 kB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

py_itree-0.0.8-cp37-cp37m-musllinux_1_1_x86_64.whl (749.1 kB view details)

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

py_itree-0.0.8-cp37-cp37m-musllinux_1_1_i686.whl (818.8 kB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ i686

py_itree-0.0.8-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (221.2 kB view details)

Uploaded CPython 3.7m manylinux: glibc 2.12+ x86-64

py_itree-0.0.8-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.whl (236.1 kB view details)

Uploaded CPython 3.7m manylinux: glibc 2.12+ i686

py_itree-0.0.8-cp37-cp37m-macosx_10_9_x86_64.whl (182.5 kB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

py_itree-0.0.8-cp36-cp36m-musllinux_1_1_x86_64.whl (748.9 kB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ x86-64

py_itree-0.0.8-cp36-cp36m-musllinux_1_1_i686.whl (816.8 kB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ i686

py_itree-0.0.8-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (220.7 kB view details)

Uploaded CPython 3.6m manylinux: glibc 2.12+ x86-64

py_itree-0.0.8-cp36-cp36m-manylinux_2_12_i686.manylinux2010_i686.whl (236.1 kB view details)

Uploaded CPython 3.6m manylinux: glibc 2.12+ i686

py_itree-0.0.8-cp36-cp36m-macosx_10_9_x86_64.whl (182.2 kB view details)

Uploaded CPython 3.6m macOS 10.9+ x86-64

File details

Details for the file py_itree-0.0.8-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for py_itree-0.0.8-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 2613bd32a3076bc52eb8b7c22ae907727ac815785620b49efd68527752110236
MD5 887432dbe6c80bbae380348bf0a417ae
BLAKE2b-256 1c3f6ed5c12123277f289aa36cf6eb6e1efaee90516d6990b0b0f5ce049f593e

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-pp37-pypy37_pp73-manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for py_itree-0.0.8-pp37-pypy37_pp73-manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 ce38e71ba661869db0509f9af007a83192b2a1eca3a9d9ea9ffa8893036f842e
MD5 2229b5c484b99cbdc61949a3f0f79a67
BLAKE2b-256 43123a5f301d128f9fb6727fb5f094db78ee2f46d087e382b741939df1052543

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-pp37-pypy37_pp73-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: py_itree-0.0.8-pp37-pypy37_pp73-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 182.8 kB
  • Tags: PyPy, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for py_itree-0.0.8-pp37-pypy37_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 8de36350f130dff1a1b21145ca96fdaa05b48f977059fcaf79a5f19cdb1da2da
MD5 868e9897c90f700565b0541bfdb53a9a
BLAKE2b-256 51b04eae41e75a89f4c1d2fe6f2fbe50ff316571480dd2ff6ec0281b6ba61106

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp310-cp310-musllinux_1_1_x86_64.whl.

File metadata

  • Download URL: py_itree-0.0.8-cp310-cp310-musllinux_1_1_x86_64.whl
  • Upload date:
  • Size: 745.8 kB
  • Tags: CPython 3.10, musllinux: musl 1.1+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for py_itree-0.0.8-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 cf165b9f10d31faa9c4168343341218b4702af5cc0fe42fa813284cf7cff71a8
MD5 3637de9002933c1260493944fff4ba4e
BLAKE2b-256 c9497b531286a980b2806de9d1a26636ff387c1f178ef673b420ffcf1acdf565

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp310-cp310-musllinux_1_1_i686.whl.

File metadata

  • Download URL: py_itree-0.0.8-cp310-cp310-musllinux_1_1_i686.whl
  • Upload date:
  • Size: 815.2 kB
  • Tags: CPython 3.10, musllinux: musl 1.1+ i686
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for py_itree-0.0.8-cp310-cp310-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 d38d91b8dab6b21113c7badd85c1a3105d1a861ddbf7ef598d7088164204383e
MD5 42688249f2094bc077d88cc26a387536
BLAKE2b-256 640d1898b61a1e17a81e16d1c3e1f99bd777300f2ef0e4351225ada498538435

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for py_itree-0.0.8-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 a9016bd35be2a2a6a46fccfd2fbf7e05cdce1721a08cdabf895866d703f21e54
MD5 50f5f898336b0c8912352127cbb0e286
BLAKE2b-256 1eb55593a392f74371d3660eba7025e1659749c88b9dcfb9b46e066bdef3445e

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for py_itree-0.0.8-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 9ce7cb3cb0903cbc1946a89e20ccac865d4ddf70f87f6fa0a529bb30002e5c4b
MD5 edfe7d9a3a09482d8f8b85d8766c62fe
BLAKE2b-256 e57863e3a392ffdc6d914189852f037f104d2f2bcac97acb8e7454722b487a5c

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: py_itree-0.0.8-cp310-cp310-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 184.9 kB
  • Tags: CPython 3.10, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for py_itree-0.0.8-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 0ce1e06d8dd9363356fb6bda93a13e7d8507a7949a1e4ec3f27541d4a5357d52
MD5 bd6acd370f1dda2a18372b754ca88c87
BLAKE2b-256 acf444ec9408510f570cd63987eabf2897f6389f9a68c8c03a24ac86e4a068e3

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp39-cp39-musllinux_1_1_x86_64.whl.

File metadata

  • Download URL: py_itree-0.0.8-cp39-cp39-musllinux_1_1_x86_64.whl
  • Upload date:
  • Size: 746.8 kB
  • Tags: CPython 3.9, musllinux: musl 1.1+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for py_itree-0.0.8-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 6eca1d36ced7c74b6377c5562805910625fdfe14acc3b09d72bf14303e8619b2
MD5 a4e5d9302f012bc303e21ebbafd0c15d
BLAKE2b-256 acb98154614b932771714de66bff8dd447f33de2eed71deb76992efeb3dfe928

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp39-cp39-musllinux_1_1_i686.whl.

File metadata

  • Download URL: py_itree-0.0.8-cp39-cp39-musllinux_1_1_i686.whl
  • Upload date:
  • Size: 815.7 kB
  • Tags: CPython 3.9, musllinux: musl 1.1+ i686
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for py_itree-0.0.8-cp39-cp39-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 66a801a43bcc9a19f13ea185a81af3fea2eb463f112ae56ff073cfa116b6a5ec
MD5 8217b18ca2f18fb43ad80ca8cbacc874
BLAKE2b-256 4d3c1522451f15d583a4de7bd8ab4795d92826780afc79636a868ffe0d40d3a0

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for py_itree-0.0.8-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 8e86168591c35a3d1de320b4ef1470fbdaa17ea8b8c571de63f25bcd4e817a72
MD5 ae1be3a0355d72cff2549f86b876ea83
BLAKE2b-256 796fc03d963d8cd73ceb170fdbee0182241764dca755eebbad31a69c708f2a9a

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for py_itree-0.0.8-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 eb249833fa2a2ed645c7fb9993f17d560f8baf3ce61d121c2f4c913450ede3c7
MD5 c0d6955c900ef5616de63bb14a0260ad
BLAKE2b-256 6676b378f016186f725522c8c6fdcfef65af6b98db16e437a085f24c969f31ff

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: py_itree-0.0.8-cp39-cp39-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 185.0 kB
  • Tags: CPython 3.9, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for py_itree-0.0.8-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 b75bd681a4c60601353bfb34c3d6b0d3cac2bd0d81c2f586ee714667d5f33d99
MD5 94df5202824dd3b1cb4a1655a1667256
BLAKE2b-256 eceeb84da74def1d3257ec0d454cb08a4f83b257203e1ca8bf413b669d59be09

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp38-cp38-musllinux_1_1_x86_64.whl.

File metadata

  • Download URL: py_itree-0.0.8-cp38-cp38-musllinux_1_1_x86_64.whl
  • Upload date:
  • Size: 746.3 kB
  • Tags: CPython 3.8, musllinux: musl 1.1+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for py_itree-0.0.8-cp38-cp38-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 61c996f6b76444dd3b44a4fc6ca7dfd58d8b2e2ac9c0677674b3b29d7acd57f3
MD5 9d9c33f576ac83273db144713fb63440
BLAKE2b-256 af1676ddf244c33494697e5c3f569802103ddac95098871ca44563a4e4d4d914

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp38-cp38-musllinux_1_1_i686.whl.

File metadata

  • Download URL: py_itree-0.0.8-cp38-cp38-musllinux_1_1_i686.whl
  • Upload date:
  • Size: 815.5 kB
  • Tags: CPython 3.8, musllinux: musl 1.1+ i686
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for py_itree-0.0.8-cp38-cp38-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 87df42e0e67a049b3cdb027cb262754ed8e48b76a03b6e05c6265ae3cbb6a48b
MD5 cb78bb91922969ea7e7d91d056a20ea5
BLAKE2b-256 bc0c17efa097c008155626f68cc4d6dc74c3be7865696f59e5032cb5364868c7

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for py_itree-0.0.8-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 34ba0838fc9209ea2716e1b607b20ba636ddb8e4edbfb832d616e7d81b62edf7
MD5 eafe039ee240939a4617d2df4912a678
BLAKE2b-256 a9beee86bb0ba129d12e72e60e51df0ff81c883e783f007ed874b4e230be1ac0

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for py_itree-0.0.8-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 7c201718465351feb993e33ab4734d665c1d755d6f8356dfadd70d5f9cba282a
MD5 91c3fb9c0c0ccc067b704f9f49cd5362
BLAKE2b-256 ace50501f68f88e0fe53c3c85bb926b5a6dc158b633b5a79548deb488a88ad10

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: py_itree-0.0.8-cp38-cp38-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 184.9 kB
  • Tags: CPython 3.8, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for py_itree-0.0.8-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 069f23d421ccc423c52ec472eccfb2b2871f8458fbaafed69e2fdcf6ce234f44
MD5 38779b083e666ccb396bae2570dd7d73
BLAKE2b-256 76a582ab349492bc86af74b7666999181e276ea31d94fef2f740db08bc833c92

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp37-cp37m-musllinux_1_1_x86_64.whl.

File metadata

  • Download URL: py_itree-0.0.8-cp37-cp37m-musllinux_1_1_x86_64.whl
  • Upload date:
  • Size: 749.1 kB
  • Tags: CPython 3.7m, musllinux: musl 1.1+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for py_itree-0.0.8-cp37-cp37m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 cf854da797d4a107a5b81b06c3e83796431e6e30dd547998bd972c9e56bb9537
MD5 2093fd0a5cdb78218c5d57d1c15bc3fe
BLAKE2b-256 e4bd6542080f469f951dbfe86eac9e621165b1ba4e4dc322cbcdd3cf14fb2427

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp37-cp37m-musllinux_1_1_i686.whl.

File metadata

  • Download URL: py_itree-0.0.8-cp37-cp37m-musllinux_1_1_i686.whl
  • Upload date:
  • Size: 818.8 kB
  • Tags: CPython 3.7m, musllinux: musl 1.1+ i686
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for py_itree-0.0.8-cp37-cp37m-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 67b56e496ee9d49be2c8ad8c07bbd516165110de9c7efcaf6fdfbd09512eff81
MD5 af105448202b0e8c884b0223385586a9
BLAKE2b-256 93a3d5c1785d8180720f4b391e5cf6d008d8df984484d32084367c6d0da316be

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for py_itree-0.0.8-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 28e1925c8dd8e04083b3882627376de529f264ffe83ec3c263e06f866d32fd48
MD5 9f26f56cd4316ad943dade3a8a2b7103
BLAKE2b-256 ff70dfc213294c994274aea7e184613ae3ac7d5a4e594d24cd3e30d9401ddf3e

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for py_itree-0.0.8-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 719697c91e0d7ed535d6a2b92264343b62d0324fffed5dfd27269b6adf76c889
MD5 83fb9f311d4970a7a638415cb037e685
BLAKE2b-256 70a7a369199628ebb5d111e1edf850b76941fdaf2fba1313d0fb4f443a2e35be

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: py_itree-0.0.8-cp37-cp37m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 182.5 kB
  • Tags: CPython 3.7m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for py_itree-0.0.8-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 2656dc618a17659bfdc538d9570c4673cf34604d537330eca344bf64cf8ff6f8
MD5 d124058bae1a9a20bbc28445e8ed6b18
BLAKE2b-256 c77c3b468f386545bf0b9208913d776af0d0be1710825fb8967f151247ecbf71

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp36-cp36m-musllinux_1_1_x86_64.whl.

File metadata

  • Download URL: py_itree-0.0.8-cp36-cp36m-musllinux_1_1_x86_64.whl
  • Upload date:
  • Size: 748.9 kB
  • Tags: CPython 3.6m, musllinux: musl 1.1+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for py_itree-0.0.8-cp36-cp36m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 7de3698dfaa78547cab3d4c7997638e81cf7ff2f474ce6b5e0f14142803b470e
MD5 c1c3760edd88cf6ffce2c668261fa8c9
BLAKE2b-256 d8152e1d639a0858a98abba4d4356d56ab00e88d24c8bafc8d74ba60c8277911

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp36-cp36m-musllinux_1_1_i686.whl.

File metadata

  • Download URL: py_itree-0.0.8-cp36-cp36m-musllinux_1_1_i686.whl
  • Upload date:
  • Size: 816.8 kB
  • Tags: CPython 3.6m, musllinux: musl 1.1+ i686
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for py_itree-0.0.8-cp36-cp36m-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 b3e23ea4a61c29dd511114863f6ad1e53eedebbefd2f00493bac440253ac5410
MD5 d5fe9d0b8ece27409033ea345a589a10
BLAKE2b-256 4daad993c0008e5c9e31f0e1caaff8c028cf67ceac6016bb8eda4e707ddd7cd2

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for py_itree-0.0.8-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 0c4adb5138695076adba38332426f72f02d10e7f7bb29f574b5bff86a9c08d66
MD5 065f6c02db8b4451ffea19ebae6256f9
BLAKE2b-256 2c086bc19cdaf3332aec3ed5662cc62f5db43c35dae2fd4beb3f22142f59489c

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp36-cp36m-manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for py_itree-0.0.8-cp36-cp36m-manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 066fe6999a0b89f511fbdc1dced75dfafc622f8467ea2b26decb171ed49eec36
MD5 ead9075d2e4e36cb679aa2f979a0547c
BLAKE2b-256 3c3ae276c3b946b988236a0f9a1a54e9c536f7a9f4004815fe3b0f15823b6e6f

See more details on using hashes here.

File details

Details for the file py_itree-0.0.8-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: py_itree-0.0.8-cp36-cp36m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 182.2 kB
  • Tags: CPython 3.6m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for py_itree-0.0.8-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 10f487b17d4776f503d1f8f215a34541689fa42683bb11f8352c9c63bc1668af
MD5 259ddd780ea050e97c236d943b0979ed
BLAKE2b-256 9cb006f821298ac774d2b962dd43e0acf8f41fc6b7e4f03bf83f84b8ce045504

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