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v3.1: support py3.12, update formatting, replace pkg_resources with locate

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Elia Robyn Lake 2023-11-21 18:07:04 -05:00
parent 6fc77b4b29
commit 2be781fd1a
19 changed files with 766 additions and 419 deletions
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2
.gitignore vendored
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@ -11,3 +11,5 @@ wordfreq-data.tar.gz
build.dot
.pytest_cache
.tox
.vscode
prof

1
mypy.ini
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@ -1,5 +1,6 @@
[mypy]
python_version = 3.7
files = wordfreq
[mypy-ipadic]
ignore_missing_imports = True

658
poetry.lock generated
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@ -1,3 +1,5 @@
# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
[[package]]
name = "appnope"
version = "0.1.3"
@ -5,6 +7,10 @@ description = "Disable App Nap on macOS >= 10.9"
category = "dev"
optional = false
python-versions = "*"
files = [
{file = "appnope-0.1.3-py2.py3-none-any.whl", hash = "sha256:265a455292d0bd8a72453494fa24df5a11eb18373a60c7c0430889f22548605e"},
{file = "appnope-0.1.3.tar.gz", hash = "sha256:02bd91c4de869fbb1e1c50aafc4098827a7a54ab2f39d9dcba6c9547ed920e24"},
]
[[package]]
name = "attrs"
@ -13,12 +19,16 @@ description = "Classes Without Boilerplate"
category = "dev"
optional = false
python-versions = ">=3.5"
files = [
{file = "attrs-22.1.0-py2.py3-none-any.whl", hash = "sha256:86efa402f67bf2df34f51a335487cf46b1ec130d02b8d39fd248abfd30da551c"},
{file = "attrs-22.1.0.tar.gz", hash = "sha256:29adc2665447e5191d0e7c568fde78b21f9672d344281d0c6e1ab085429b22b6"},
]
[package.extras]
dev = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "mypy (>=0.900,!=0.940)", "pytest-mypy-plugins", "zope.interface", "furo", "sphinx", "sphinx-notfound-page", "pre-commit", "cloudpickle"]
docs = ["furo", "sphinx", "zope.interface", "sphinx-notfound-page"]
tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "mypy (>=0.900,!=0.940)", "pytest-mypy-plugins", "zope.interface", "cloudpickle"]
tests_no_zope = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "mypy (>=0.900,!=0.940)", "pytest-mypy-plugins", "cloudpickle"]
dev = ["cloudpickle", "coverage[toml] (>=5.0.2)", "furo", "hypothesis", "mypy (>=0.900,!=0.940)", "pre-commit", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "sphinx", "sphinx-notfound-page", "zope.interface"]
docs = ["furo", "sphinx", "sphinx-notfound-page", "zope.interface"]
tests = ["cloudpickle", "coverage[toml] (>=5.0.2)", "hypothesis", "mypy (>=0.900,!=0.940)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "zope.interface"]
tests-no-zope = ["cloudpickle", "coverage[toml] (>=5.0.2)", "hypothesis", "mypy (>=0.900,!=0.940)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins"]
[[package]]
name = "backcall"
@ -27,41 +37,10 @@ description = "Specifications for callback functions passed in to an API"
category = "dev"
optional = false
python-versions = "*"
[[package]]
name = "black"
version = "22.10.0"
description = "The uncompromising code formatter."
category = "dev"
optional = false
python-versions = ">=3.7"
[package.dependencies]
click = ">=8.0.0"
mypy-extensions = ">=0.4.3"
pathspec = ">=0.9.0"
platformdirs = ">=2"
tomli = {version = ">=1.1.0", markers = "python_full_version < \"3.11.0a7\""}
typed-ast = {version = ">=1.4.2", markers = "python_version < \"3.8\" and implementation_name == \"cpython\""}
typing-extensions = {version = ">=3.10.0.0", markers = "python_version < \"3.10\""}
[package.extras]
colorama = ["colorama (>=0.4.3)"]
d = ["aiohttp (>=3.7.4)"]
jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
uvloop = ["uvloop (>=0.15.2)"]
[[package]]
name = "click"
version = "8.1.3"
description = "Composable command line interface toolkit"
category = "dev"
optional = false
python-versions = ">=3.7"
[package.dependencies]
colorama = {version = "*", markers = "platform_system == \"Windows\""}
importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
files = [
{file = "backcall-0.2.0-py2.py3-none-any.whl", hash = "sha256:fbbce6a29f263178a1f7915c1940bde0ec2b2a967566fe1c65c1dfb7422bd255"},
{file = "backcall-0.2.0.tar.gz", hash = "sha256:5cbdbf27be5e7cfadb448baf0aa95508f91f2bbc6c6437cd9cd06e2a4c215e1e"},
]
[[package]]
name = "colorama"
@ -70,6 +49,10 @@ description = "Cross-platform colored terminal text."
category = "dev"
optional = false
python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
files = [
{file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"},
{file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
]
[[package]]
name = "decorator"
@ -78,6 +61,10 @@ description = "Decorators for Humans"
category = "dev"
optional = false
python-versions = ">=3.5"
files = [
{file = "decorator-5.1.1-py3-none-any.whl", hash = "sha256:b8c3f85900b9dc423225913c5aace94729fe1fa9763b38939a95226f02d37186"},
{file = "decorator-5.1.1.tar.gz", hash = "sha256:637996211036b6385ef91435e4fae22989472f9d571faba8927ba8253acbc330"},
]
[[package]]
name = "exceptiongroup"
@ -86,24 +73,14 @@ description = "Backport of PEP 654 (exception groups)"
category = "dev"
optional = false
python-versions = ">=3.7"
files = [
{file = "exceptiongroup-1.0.0rc9-py3-none-any.whl", hash = "sha256:2e3c3fc1538a094aab74fad52d6c33fc94de3dfee3ee01f187c0e0c72aec5337"},
{file = "exceptiongroup-1.0.0rc9.tar.gz", hash = "sha256:9086a4a21ef9b31c72181c77c040a074ba0889ee56a7b289ff0afb0d97655f96"},
]
[package.extras]
test = ["pytest (>=6)"]
[[package]]
name = "flake8"
version = "4.0.1"
description = "the modular source code checker: pep8 pyflakes and co"
category = "dev"
optional = false
python-versions = ">=3.6"
[package.dependencies]
importlib-metadata = {version = "<4.3", markers = "python_version < \"3.8\""}
mccabe = ">=0.6.0,<0.7.0"
pycodestyle = ">=2.8.0,<2.9.0"
pyflakes = ">=2.4.0,<2.5.0"
[[package]]
name = "ftfy"
version = "6.1.1"
@ -111,25 +88,25 @@ description = "Fixes mojibake and other problems with Unicode, after the fact"
category = "main"
optional = false
python-versions = ">=3.7,<4"
files = [
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]
[package.dependencies]
wcwidth = ">=0.2.5"
[[package]]
name = "importlib-metadata"
version = "4.2.0"
description = "Read metadata from Python packages"
name = "gprof2dot"
version = "2022.7.29"
description = "Generate a dot graph from the output of several profilers."
category = "dev"
optional = false
python-versions = ">=3.6"
[package.dependencies]
typing-extensions = {version = ">=3.6.4", markers = "python_version < \"3.8\""}
zipp = ">=0.5"
[package.extras]
docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)"]
testing = ["pytest (>=4.6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "packaging", "pep517", "pyfakefs", "flufl.flake8", "pytest-black (>=0.3.7)", "pytest-mypy", "importlib-resources (>=1.3)"]
python-versions = ">=2.7"
files = [
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]
[[package]]
name = "iniconfig"
@ -138,6 +115,10 @@ description = "iniconfig: brain-dead simple config-ini parsing"
category = "dev"
optional = false
python-versions = "*"
files = [
{file = "iniconfig-1.1.1-py2.py3-none-any.whl", hash = "sha256:011e24c64b7f47f6ebd835bb12a743f2fbe9a26d4cecaa7f53bc4f35ee9da8b3"},
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]
[[package]]
name = "ipadic"
@ -146,6 +127,9 @@ description = "IPAdic packaged for Python"
category = "main"
optional = false
python-versions = "*"
files = [
{file = "ipadic-1.0.0.tar.gz", hash = "sha256:f5923d31eca6131acaaf18ed28d8998665b1347b640d3a6476f64650e9a71c07"},
]
[[package]]
name = "ipython"
@ -154,6 +138,10 @@ description = "IPython: Productive Interactive Computing"
category = "dev"
optional = false
python-versions = ">=3.7"
files = [
{file = "ipython-7.34.0-py3-none-any.whl", hash = "sha256:c175d2440a1caff76116eb719d40538fbb316e214eda85c5515c303aacbfb23e"},
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]
[package.dependencies]
appnope = {version = "*", markers = "sys_platform == \"darwin\""}
@ -166,6 +154,7 @@ pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""}
pickleshare = "*"
prompt-toolkit = ">=2.0.0,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.1.0"
pygments = "*"
setuptools = ">=18.5"
traitlets = ">=4.2"
[package.extras]
@ -174,10 +163,10 @@ doc = ["Sphinx (>=1.3)"]
kernel = ["ipykernel"]
nbconvert = ["nbconvert"]
nbformat = ["nbformat"]
notebook = ["notebook", "ipywidgets"]
notebook = ["ipywidgets", "notebook"]
parallel = ["ipyparallel"]
qtconsole = ["qtconsole"]
test = ["nose (>=0.10.1)", "requests", "testpath", "pygments", "nbformat", "ipykernel", "numpy (>=1.17)"]
test = ["ipykernel", "nbformat", "nose (>=0.10.1)", "numpy (>=1.17)", "pygments", "requests", "testpath"]
[[package]]
name = "jedi"
@ -186,6 +175,10 @@ description = "An autocompletion tool for Python that can be used for text edito
category = "dev"
optional = false
python-versions = ">=3.6"
files = [
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{file = "jedi-0.18.1.tar.gz", hash = "sha256:74137626a64a99c8eb6ae5832d99b3bdd7d29a3850fe2aa80a4126b2a7d949ab"},
]
[package.dependencies]
parso = ">=0.8.0,<0.9.0"
@ -201,6 +194,9 @@ description = "Chinese Words Segmentation Utilities"
category = "main"
optional = false
python-versions = "*"
files = [
{file = "jieba-0.42.1.tar.gz", hash = "sha256:055ca12f62674fafed09427f176506079bc135638a14e23e25be909131928db2"},
]
[[package]]
name = "langcodes"
@ -209,10 +205,26 @@ description = "Tools for labeling human languages with IETF language tags"
category = "main"
optional = false
python-versions = ">=3.6"
files = [
{file = "langcodes-3.3.0-py3-none-any.whl", hash = "sha256:4d89fc9acb6e9c8fdef70bcdf376113a3db09b67285d9e1d534de6d8818e7e69"},
{file = "langcodes-3.3.0.tar.gz", hash = "sha256:794d07d5a28781231ac335a1561b8442f8648ca07cd518310aeb45d6f0807ef6"},
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data = ["language-data (>=1.1,<2.0)"]
[[package]]
name = "locate"
version = "1.1.1"
description = "Locate the file location of your current running script."
category = "main"
optional = false
python-versions = ">=3.4"
files = [
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[[package]]
name = "matplotlib-inline"
version = "0.1.6"
@ -220,18 +232,14 @@ description = "Inline Matplotlib backend for Jupyter"
category = "dev"
optional = false
python-versions = ">=3.5"
files = [
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]
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traitlets = "*"
[[package]]
name = "mccabe"
version = "0.6.1"
description = "McCabe checker, plugin for flake8"
category = "dev"
optional = false
python-versions = "*"
[[package]]
name = "mecab-ko-dic"
version = "1.0.0"
@ -239,6 +247,9 @@ description = "mecab-ko-dic packaged for Python"
category = "main"
optional = false
python-versions = "*"
files = [
{file = "mecab-ko-dic-1.0.0.tar.gz", hash = "sha256:3ba22858736e02e8a0e92f2a7f099528c733ae47701b29d12c75e982a85d1f11"},
]
[[package]]
name = "mecab-python3"
@ -247,6 +258,29 @@ description = "Python wrapper for the MeCab morphological analyzer for Japanese"
category = "main"
optional = false
python-versions = "*"
files = [
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[package.extras]
unidic = ["unidic"]
@ -254,37 +288,129 @@ unidic-lite = ["unidic-lite"]
[[package]]
name = "msgpack"
version = "1.0.4"
version = "1.0.7"
description = "MessagePack serializer"
category = "main"
optional = false
python-versions = "*"
python-versions = ">=3.8"
files = [
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@ -370,6 +493,10 @@ description = "Library for building powerful interactive command lines in Python
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optional = false
python-versions = ">=3.7"
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[[package]]
name = "setuptools"
version = "69.0.2"
description = "Easily download, build, install, upgrade, and uninstall Python packages"
category = "dev"
optional = false
python-versions = ">=3.8"
files = [
{file = "setuptools-69.0.2-py3-none-any.whl", hash = "sha256:1e8fdff6797d3865f37397be788a4e3cba233608e9b509382a2777d25ebde7f2"},
{file = "setuptools-69.0.2.tar.gz", hash = "sha256:735896e78a4742605974de002ac60562d286fa8051a7e2299445e8e8fbb01aa6"},
]
[package.extras]
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "packaging (>=23.1)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
[[package]]
name = "six"
version = "1.16.0"
description = "Python 2 and 3 compatibility utilities"
category = "dev"
optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
files = [
{file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
{file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
]
[[package]]
name = "tomli"
@ -456,6 +748,10 @@ description = "A lil' TOML parser"
category = "dev"
optional = false
python-versions = ">=3.7"
files = [
{file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"},
{file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
]
[[package]]
name = "traitlets"
@ -464,27 +760,15 @@ description = ""
category = "dev"
optional = false
python-versions = ">=3.7"
files = [
{file = "traitlets-5.5.0-py3-none-any.whl", hash = "sha256:1201b2c9f76097195989cdf7f65db9897593b0dfd69e4ac96016661bb6f0d30f"},
{file = "traitlets-5.5.0.tar.gz", hash = "sha256:b122f9ff2f2f6c1709dab289a05555be011c87828e911c0cf4074b85cb780a79"},
]
[package.extras]
docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
test = ["pre-commit", "pytest"]
[[package]]
name = "typed-ast"
version = "1.5.4"
description = "a fork of Python 2 and 3 ast modules with type comment support"
category = "dev"
optional = false
python-versions = ">=3.6"
[[package]]
name = "types-setuptools"
version = "57.4.18"
description = "Typing stubs for setuptools"
category = "dev"
optional = false
python-versions = "*"
[[package]]
name = "typing-extensions"
version = "4.4.0"
@ -492,6 +776,10 @@ description = "Backported and Experimental Type Hints for Python 3.7+"
category = "dev"
optional = false
python-versions = ">=3.7"
files = [
{file = "typing_extensions-4.4.0-py3-none-any.whl", hash = "sha256:16fa4864408f655d35ec496218b85f79b3437c829e93320c7c9215ccfd92489e"},
{file = "typing_extensions-4.4.0.tar.gz", hash = "sha256:1511434bb92bf8dd198c12b1cc812e800d4181cfcb867674e0f8279cc93087aa"},
]
[[package]]
name = "wcwidth"
@ -500,73 +788,17 @@ description = "Measures the displayed width of unicode strings in a terminal"
category = "main"
optional = false
python-versions = "*"
[[package]]
name = "zipp"
version = "3.10.0"
description = "Backport of pathlib-compatible object wrapper for zip files"
category = "dev"
optional = false
python-versions = ">=3.7"
[package.extras]
docs = ["sphinx (>=3.5)", "jaraco.packaging (>=9)", "rst.linker (>=1.9)", "furo", "jaraco.tidelift (>=1.4)"]
testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "flake8 (<5)", "pytest-cov", "pytest-enabler (>=1.3)", "jaraco.itertools", "func-timeout", "jaraco.functools", "more-itertools", "pytest-black (>=0.3.7)", "pytest-mypy (>=0.9.1)"]
files = [
{file = "wcwidth-0.2.5-py2.py3-none-any.whl", hash = "sha256:beb4802a9cebb9144e99086eff703a642a13d6a0052920003a230f3294bbe784"},
{file = "wcwidth-0.2.5.tar.gz", hash = "sha256:c4d647b99872929fdb7bdcaa4fbe7f01413ed3d98077df798530e5b04f116c83"},
]
[extras]
cjk = ["mecab-python3", "ipadic", "mecab-ko-dic", "jieba"]
cjk = ["ipadic", "jieba", "mecab-ko-dic", "mecab-python3"]
jieba = ["jieba"]
mecab = ["mecab-python3", "ipadic", "mecab-ko-dic"]
mecab = ["ipadic", "mecab-ko-dic", "mecab-python3"]
[metadata]
lock-version = "1.1"
python-versions = "^3.7"
content-hash = "3701c1761f9f8e16cefafdfdf04e64cb436dc96cda64fc524ed9c8b8204046a6"
[metadata.files]
appnope = []
attrs = []
backcall = []
black = []
click = []
colorama = []
decorator = []
exceptiongroup = []
flake8 = []
ftfy = []
importlib-metadata = []
iniconfig = []
ipadic = []
ipython = []
jedi = []
jieba = []
langcodes = []
matplotlib-inline = []
mccabe = []
mecab-ko-dic = []
mecab-python3 = []
msgpack = []
mypy = []
mypy-extensions = []
packaging = []
parso = []
pathspec = []
pexpect = []
pickleshare = []
platformdirs = []
pluggy = []
prompt-toolkit = []
ptyprocess = []
pycodestyle = []
pyflakes = []
pygments = []
pyparsing = []
pytest = []
regex = []
tomli = []
traitlets = []
typed-ast = []
types-setuptools = []
typing-extensions = []
wcwidth = []
zipp = []
lock-version = "2.0"
python-versions = ">= 3.8, < 4"
content-hash = "c3aecf3636c5f6b3aa9472843a96a57b2fc0b3f2f36e683046eedfdf42839e32"

72
pyproject.toml
View File

@ -1,6 +1,6 @@
[tool.poetry]
name = "wordfreq"
version = "3.0.3"
version = "3.1.0"
description = "Look up the frequencies of words in many languages, based on many sources of data."
authors = ["Robyn Speer <rspeer@arborelia.net>"]
license = "Apache-2.0"
@ -8,33 +8,75 @@ readme = "README.md"
homepage = "https://github.com/rspeer/wordfreq/"
[tool.poetry.dependencies]
python = "^3.7"
msgpack = ">= 1.0"
python = ">= 3.8, < 4"
msgpack = "^1.0.7"
langcodes = ">= 3.0"
regex = ">= 2021.7.6"
regex = ">= 2023.10.3"
ftfy = ">= 6.1"
mecab-python3 = {version = "^1.0.5", optional = true}
ipadic = {version = "^1.0.0", optional = true}
mecab-ko-dic = {version = "^1.0.0", optional = true}
jieba = {version = ">=0.42", optional = true}
mecab-python3 = { version = "^1.0.5", optional = true }
ipadic = { version = "^1.0.0", optional = true }
mecab-ko-dic = { version = "^1.0.0", optional = true }
jieba = { version = ">=0.42", optional = true }
locate = "^1.1.1"
[tool.poetry.dev-dependencies]
[tool.poetry.group.dev.dependencies]
pytest = "^7.2.0"
mecab-python3 = "^1.0.4"
jieba = ">= 0.42"
mecab-python3 = "^1.0.5"
jieba = "^0.42.1"
ipadic = "^1.0.0"
mecab-ko-dic = "^1.0.0"
ipython = ">=7"
black = "^22.1.0"
flake8 = "^4.0.1"
types-setuptools = "^57.4.9"
mypy = "^0.931"
mypy = "^1.7.0"
ruff = "^0.1.6"
setuptools = "^69.0.2" # implicit dependency in jieba
pytest-profiling = "^1.7.0"
[tool.poetry.extras]
cjk = ["mecab-python3", "ipadic", "mecab-ko-dic", "jieba"]
mecab = ["mecab-python3", "ipadic", "mecab-ko-dic"]
jieba = ["jieba"]
[tool.ruff]
# ruff is a Python linter and formatter, which reimplements black, flake8, pylint, and more
line-length = 99
show-fixes = true
src = ["src"]
target-version = "py38"
[tool.ruff.lint]
extend-select = [
"D", # docstring style
"I", # isort
"UP", # pyupgrade -- catches obsolete code patterns
"ANN", # type annotations
"ASYNC", # async code checks
"B", # flake8-bugbear -- catches bug-prone usage
"C4", # list comprehensions
"FA", # correct use of `from __future__ import annotations`
"INP", # checks for presence of __init__.py
"T20", # print statements
"TID", # tidy imports
"PTH", # use pathlib instead of os.path
"PLE", # pylint errors
]
ignore = [
"D100", # modules without top-of-module docstrings are okay
"D104", # __init__.py doesn't need a docstring
"D107", # __init__ method doesn't need a docstring
"D2", # don't check whitespace in docstrings
"D4", # don't check grammar and style in docstrings
"E501", # long lines after auto-formatting, such as long strings, are okay
"ANN002", # we don't demand a type on *args, particularly because it's difficult to specify
"ANN003", # we don't demand a type on **kwargs, particularly because it's difficult to specify
"ANN101", # self does not need a type
"ANN102", # `cls` in classmethod does not need a type
"PTH123", # we don't need to construct a Path just to open a file by filename
]
[tool.ruff.lint.per-file-ignores]
# We are less strict about test code
"tests/**" = ["D", "ANN", "T20", "INP"]
[build-system]
requires = ["poetry-core>=1.0.0"]
build-backend = "poetry.core.masonry.api"

2
tests/test_apostrophes.py
View File

@ -1,4 +1,4 @@
from wordfreq import tokenize, word_frequency
from wordfreq import tokenize
def test_apostrophes():

2
tests/test_at_sign.py
View File

@ -1,4 +1,4 @@
from wordfreq import tokenize, lossy_tokenize, word_frequency
from wordfreq import lossy_tokenize, tokenize, word_frequency
def test_gender_neutral_at():

2
tests/test_chinese.py
View File

@ -1,5 +1,5 @@
from wordfreq import tokenize, word_frequency, zipf_frequency
import pytest
from wordfreq import tokenize, word_frequency, zipf_frequency
def test_tokens():

45
tests/test_general.py
View File

@ -1,14 +1,14 @@
import pytest
from wordfreq import (
word_frequency,
available_languages,
cB_to_freq,
top_n_list,
random_words,
random_ascii_words,
tokenize,
lossy_tokenize,
random_ascii_words,
random_words,
tokenize,
top_n_list,
word_frequency,
)
import pytest
def test_freq_examples():
@ -142,9 +142,17 @@ def test_tokenization():
"see",
]
assert tokenize(
"I don't split at apostrophes, you see.", "en", include_punctuation=True
) == ["i", "don't", "split", "at", "apostrophes", ",", "you", "see", "."]
assert tokenize("I don't split at apostrophes, you see.", "en", include_punctuation=True) == [
"i",
"don't",
"split",
"at",
"apostrophes",
",",
"you",
"see",
".",
]
# Certain punctuation does not inherently split a word.
assert tokenize("Anything is possible at zombo.com", "en") == [
@ -158,17 +166,20 @@ def test_tokenization():
# Splits occur after symbols, and at splitting punctuation such as hyphens.
assert tokenize("😂test", "en") == ["😂", "test"]
assert tokenize("flip-flop", "en") == ["flip", "flop"]
assert tokenize(
"this text has... punctuation :)", "en", include_punctuation=True
) == ["this", "text", "has", "...", "punctuation", ":)"]
assert tokenize("this text has... punctuation :)", "en", include_punctuation=True) == [
"this",
"text",
"has",
"...",
"punctuation",
":)",
]
# Multi-codepoint emoji sequences such as 'medium-skinned woman with headscarf'
# and 'David Bowie' stay together, because our Unicode segmentation algorithm
# is up to date
assert tokenize("emoji test 🧕🏽", "en") == ["emoji", "test", "🧕🏽"]
assert tokenize(
"👨‍🎤 Planet Earth is blue, and there's nothing I can do 🌎🚀", "en"
) == [
assert tokenize("👨‍🎤 Planet Earth is blue, and there's nothing I can do 🌎🚀", "en") == [
"👨‍🎤",
"planet",
"earth",
@ -221,9 +232,7 @@ def test_uncurl_quotes():
def test_phrase_freq():
ff = word_frequency("flip-flop", "en")
assert ff > 0
phrase_freq = 1.0 / word_frequency("flip", "en") + 1.0 / word_frequency(
"flop", "en"
)
phrase_freq = 1.0 / word_frequency("flip", "en") + 1.0 / word_frequency("flop", "en")
assert 1.0 / ff == pytest.approx(phrase_freq, rel=0.01)

2
tests/test_japanese.py
View File

@ -1,5 +1,5 @@
from wordfreq import tokenize, simple_tokenize, word_frequency
import pytest
from wordfreq import simple_tokenize, tokenize, word_frequency
def test_tokens():

2
tests/test_korean.py
View File

@ -1,5 +1,5 @@
from wordfreq import tokenize, word_frequency
import pytest
from wordfreq import tokenize, word_frequency
def test_tokens():

2
tests/test_numbers.py
View File

@ -1,6 +1,6 @@
from pytest import approx
from wordfreq import word_frequency
from wordfreq.numbers import digit_freq, smash_numbers
from pytest import approx
def test_number_smashing():

61
wordfreq/__init__.py
View File

@ -1,25 +1,28 @@
from pkg_resources import resource_filename
from functools import lru_cache
from typing import List, Dict, Iterator, Tuple
import langcodes
import msgpack
from __future__ import annotations
import gzip
import itertools
import pathlib
import random
import logging
import math
import random
import warnings
from functools import lru_cache
from typing import Iterator
import langcodes
import msgpack
from wordfreq.tokens import tokenize, simple_tokenize, lossy_tokenize
from wordfreq.language_info import get_language_info
from wordfreq.numbers import digit_freq, has_digit_sequence, smash_numbers
from wordfreq.tokens import lossy_tokenize, simple_tokenize, tokenize
from .util import data_path
logger = logging.getLogger(__name__)
CACHE_SIZE = 100000
DATA_PATH = pathlib.Path(resource_filename("wordfreq", "data"))
DATA_PATH = data_path()
# We'll divide the frequency by 10 for each token boundary that was inferred.
# (We determined the factor of 10 empirically by looking at words in the
@ -35,7 +38,7 @@ tokenize = tokenize
simple_tokenize = simple_tokenize
def read_cBpack(filename: str) -> List[List[str]]:
def read_cBpack(filename: str) -> list[list[str]]:
"""
Read a file from an idiosyncratic format that we use for storing
approximate word frequencies, called "cBpack".
@ -79,16 +82,12 @@ def read_cBpack(filename: str) -> List[List[str]]:
with gzip.open(filename, "rb") as infile:
data = msgpack.load(infile, raw=False)
header = data[0]
if (
not isinstance(header, dict)
or header.get("format") != "cB"
or header.get("version") != 1
):
if not isinstance(header, dict) or header.get("format") != "cB" or header.get("version") != 1:
raise ValueError("Unexpected header: %r" % header)
return data[1:]
def available_languages(wordlist: str = "best") -> Dict[str, str]:
def available_languages(wordlist: str = "best") -> dict[str, str]:
"""
Given a wordlist name, return a dictionary of language codes to filenames,
representing all the languages in which that wordlist is available.
@ -114,7 +113,7 @@ def available_languages(wordlist: str = "best") -> Dict[str, str]:
@lru_cache(maxsize=None)
def get_frequency_list(
lang: str, wordlist: str = "best", match_cutoff: None = None
) -> List[List[str]]:
) -> list[list[str]]:
"""
Read the raw data from a wordlist file, returning it as a list of
lists. (See `read_cBpack` for what this represents.)
@ -125,19 +124,21 @@ def get_frequency_list(
Looking up the alternate code 'por' will also get the same list.
"""
if match_cutoff is not None:
warnings.warn("The `match_cutoff` parameter is deprecated", DeprecationWarning)
warnings.warn(
"The `match_cutoff` parameter is deprecated", DeprecationWarning, stacklevel=2
)
available = available_languages(wordlist)
# the max_distance is high because we unify scripts, such as Traditional
# vs. Simplified Chinese, in one wordlist
best, _distance = langcodes.closest_match(lang, list(available), max_distance=60)
if best == "und":
raise LookupError("No wordlist %r available for language %r" % (wordlist, lang))
raise LookupError(f"No wordlist {wordlist!r} available for language {lang!r}")
if best != lang:
logger.warning(
"You asked for word frequencies in language %r. Using the "
"nearest match, which is %r." % (lang, best)
f"You asked for word frequencies in language {lang!r}. Using the "
f"nearest match, which is {best!r}."
)
return read_cBpack(available[best])
@ -198,13 +199,15 @@ def freq_to_zipf(freq: float) -> float:
@lru_cache(maxsize=None)
def get_frequency_dict(
lang: str, wordlist: str = "best", match_cutoff: None = None
) -> Dict[str, float]:
) -> dict[str, float]:
"""
Get a word frequency list as a dictionary, mapping tokens to
frequencies as floating-point probabilities.
"""
if match_cutoff is not None:
warnings.warn("The `match_cutoff` parameter is deprecated", DeprecationWarning)
warnings.warn(
"The `match_cutoff` parameter is deprecated", DeprecationWarning, stacklevel=2
)
freqs = {}
pack = get_frequency_list(lang, wordlist)
for index, bucket in enumerate(pack):
@ -229,7 +232,7 @@ def iter_wordlist(lang: str, wordlist: str = "best") -> Iterator[str]:
# This dict and inner function are used to implement a "drop everything" cache
# for word_frequency(); the overheads of lru_cache() are comparable to the time
# it takes to look up frequencies from scratch, so something faster is needed.
_wf_cache: Dict[Tuple[str, str, str, float], float] = {}
_wf_cache: dict[tuple[str, str, str, float], float] = {}
def _word_frequency(word: str, lang: str, wordlist: str, minimum: float) -> float:
@ -277,9 +280,7 @@ def _word_frequency(word: str, lang: str, wordlist: str, minimum: float) -> floa
return round(unrounded, leading_zeroes + 3)
def word_frequency(
word: str, lang: str, wordlist: str = "best", minimum: float = 0.0
) -> float:
def word_frequency(word: str, lang: str, wordlist: str = "best", minimum: float = 0.0) -> float:
"""
Get the frequency of `word` in the language with code `lang`, from the
specified `wordlist`.
@ -306,7 +307,7 @@ def word_frequency(
return _wf_cache[args]
def zipf_frequency(word: str, lang: str, wordlist: str = "best", minimum: float = 0.0):
def zipf_frequency(word: str, lang: str, wordlist: str = "best", minimum: float = 0.0) -> float:
"""
Get the frequency of `word`, in the language with code `lang`, on the Zipf
scale.
@ -334,9 +335,7 @@ def zipf_frequency(word: str, lang: str, wordlist: str = "best", minimum: float
@lru_cache(maxsize=100)
def top_n_list(
lang: str, n: int, wordlist: str = "best", ascii_only: bool = False
) -> List[str]:
def top_n_list(lang: str, n: int, wordlist: str = "best", ascii_only: bool = False) -> list[str]:
"""
Return a frequency list of length `n` in descending order of frequency.
This list contains words from `wordlist`, of the given language.

31
wordfreq/chinese.py
View File

@ -1,21 +1,22 @@
from pkg_resources import resource_filename
from typing import List
import jieba
import msgpack
from __future__ import annotations
import gzip
DICT_FILENAME = resource_filename("wordfreq", "data/jieba_zh.txt")
ORIG_DICT_FILENAME = resource_filename("wordfreq", "data/jieba_zh_orig.txt")
SIMP_MAP_FILENAME = resource_filename("wordfreq", "data/_chinese_mapping.msgpack.gz")
import jieba
import msgpack
from .util import data_path
DICT_FILENAME = data_path("jieba_zh.txt")
ORIG_DICT_FILENAME = data_path("jieba_zh_orig.txt")
SIMP_MAP_FILENAME = data_path("_chinese_mapping.msgpack.gz")
try:
SIMPLIFIED_MAP = msgpack.load(
gzip.open(SIMP_MAP_FILENAME), raw=False, strict_map_key=False
)
SIMPLIFIED_MAP = msgpack.load(gzip.open(SIMP_MAP_FILENAME), raw=False, strict_map_key=False)
except TypeError:
# work around incompatibility between pure-Python msgpack and C msgpack
SIMPLIFIED_MAP = msgpack.load(gzip.open(SIMP_MAP_FILENAME), raw=False)
jieba_tokenizer = None
jieba_orig_tokenizer = None
jieba_tokenizer: jieba.Tokenizer | None = None
jieba_orig_tokenizer: jieba.Tokenizer | None = None
def simplify_chinese(text: str) -> str:
@ -32,7 +33,7 @@ def simplify_chinese(text: str) -> str:
return text.translate(SIMPLIFIED_MAP).casefold()
def jieba_tokenize(text: str, external_wordlist: bool = False) -> List[str]:
def jieba_tokenize(text: str, external_wordlist: bool = False) -> list[str]:
"""
Tokenize the given text into tokens whose word frequencies can probably
be looked up. This uses Jieba, a word-frequency-based tokenizer.
@ -61,8 +62,6 @@ def jieba_tokenize(text: str, external_wordlist: bool = False) -> List[str]:
# those spans from the original text, even if it's in Traditional
# Chinese
tokens = []
for _token, start, end in jieba_tokenizer.tokenize(
simplify_chinese(text), HMM=False
):
for _token, start, end in jieba_tokenizer.tokenize(simplify_chinese(text), HMM=False):
tokens.append(text[start:end])
return tokens

10
wordfreq/language_info.py
View File

@ -1,6 +1,8 @@
from __future__ import annotations
from functools import lru_cache
from langcodes import Language, closest_match
from typing import List, Union
# Text in scripts written without spaces has to be handled specially in our
# tokenization regex (see TOKEN_RE in tokens.py). Also, when one of these is
@ -44,9 +46,7 @@ EXTRA_JAPANESE_CHARACTERS = "ー々〻〆"
# happens in ConceptNet.
def _language_in_list(
language: Language, targets: List[str], max_distance: int = 10
) -> bool:
def _language_in_list(language: Language, targets: list[str], max_distance: int = 10) -> bool:
"""
A helper function to determine whether this language matches one of the
target languages, with a match score above a certain threshold.
@ -59,7 +59,7 @@ def _language_in_list(
@lru_cache(maxsize=None)
def get_language_info(language: Union[str, Language]) -> dict:
def get_language_info(language: str | Language) -> dict:
"""
Looks up the things we need to know about how to handle text in a given
language. This will return a dictionary with the following fields:

15
wordfreq/mecab.py
View File

@ -1,7 +1,8 @@
import MeCab
from __future__ import annotations
import unicodedata
from typing import Dict, List
import MeCab
def make_mecab_analyzer(lang: str) -> MeCab.Tagger:
@ -22,10 +23,10 @@ def make_mecab_analyzer(lang: str) -> MeCab.Tagger:
# The constructed analyzers will go in this dictionary.
MECAB_ANALYZERS: Dict[str, MeCab.Tagger] = {}
MECAB_ANALYZERS: dict[str, MeCab.Tagger] = {}
def mecab_tokenize(text: str, lang: str) -> List[str]:
def mecab_tokenize(text: str, lang: str) -> list[str]:
"""
Use the mecab-python3 package to tokenize the given text. The `lang`
must be 'ja' for Japanese or 'ko' for Korean.
@ -42,8 +43,4 @@ def mecab_tokenize(text: str, lang: str) -> List[str]:
analyzed = analyzer.parse(text)
if not analyzed:
return []
return [
line.split("\t")[0]
for line in analyzed.split("\n")
if line != "" and line != "EOS"
]
return [line.split("\t")[0] for line in analyzed.split("\n") if line != "" and line != "EOS"]

5
wordfreq/preprocess.py
View File

@ -1,9 +1,10 @@
import regex
import unicodedata
import regex
from langcodes import Language
from .language_info import get_language_info
from .transliterate import transliterate
from langcodes import Language
MARK_RE = regex.compile(r"[\p{Mn}\N{ARABIC TATWEEL}]", regex.V1)

46
wordfreq/tokens.py
View File

@ -1,31 +1,31 @@
import regex
import unicodedata
from __future__ import annotations
import logging
import unicodedata
import langcodes
from typing import List
import regex
from ftfy.fixes import uncurl_quotes
from .language_info import (
get_language_info,
SPACELESS_SCRIPTS,
EXTRA_JAPANESE_CHARACTERS,
SPACELESS_SCRIPTS,
get_language_info,
)
from .preprocess import preprocess_text
# Placeholders for CJK functions that we'll import on demand
_mecab_tokenize = None
_jieba_tokenize = None
_simplify_chinese = None
_mecab_tokenize = None # type: ignore
_jieba_tokenize = None # type: ignore
_simplify_chinese = None # type: ignore
_WARNED_LANGUAGES = set()
_WARNED_LANGUAGES: set[str] = set()
logger = logging.getLogger(__name__)
def _make_spaceless_expr() -> str:
scripts = sorted(SPACELESS_SCRIPTS)
pieces = [r"\p{IsIdeo}"] + [
r"\p{Script=%s}" % script_code for script_code in scripts
]
pieces = [r"\p{IsIdeo}"] + [r"\p{Script=%s}" % script_code for script_code in scripts]
return "".join(pieces) + EXTRA_JAPANESE_CHARACTERS
@ -148,11 +148,7 @@ TOKEN_RE = regex.compile(
# part of the token in Case 3.
\w\w?'
""".replace(
"<SPACELESS>", SPACELESS_EXPR
).replace(
"<VOWEL>", INITIAL_VOWEL_EXPR
),
""".replace("<SPACELESS>", SPACELESS_EXPR).replace("<VOWEL>", INITIAL_VOWEL_EXPR),
regex.V1 | regex.WORD | regex.VERBOSE,
)
@ -167,11 +163,7 @@ TOKEN_RE_WITH_PUNCTUATION = regex.compile(
(?=[\w\p{So}]) (?!\w\w?'<VOWEL>)
\X+? (?: @s? (?!w) | \b) | # Case 3
\w\w?' # Case 4
""".replace(
"<SPACELESS>", SPACELESS_EXPR
).replace(
"<VOWEL>", INITIAL_VOWEL_EXPR
),
""".replace("<SPACELESS>", SPACELESS_EXPR).replace("<VOWEL>", INITIAL_VOWEL_EXPR),
regex.V1 | regex.WORD | regex.VERBOSE,
)
@ -180,7 +172,7 @@ TOKEN_RE_WITH_PUNCTUATION = regex.compile(
PUNCT_RE = regex.compile(r"[\p{punct}]+")
def simple_tokenize(text: str, include_punctuation: bool = False) -> List[str]:
def simple_tokenize(text: str, include_punctuation: bool = False) -> list[str]:
"""
Tokenize the given text using a straightforward, Unicode-aware token
expression.
@ -220,7 +212,7 @@ def tokenize(
lang: str,
include_punctuation: bool = False,
external_wordlist: bool = False,
) -> List[str]:
) -> list[str]:
"""
Tokenize this text in a way that's relatively simple but appropriate for
the language. Strings that are looked up in wordfreq will be run through
@ -286,9 +278,7 @@ def tokenize(
if info["tokenizer"] != "regex" and lang not in _WARNED_LANGUAGES:
logger.warning(
"The language '{}' is in the '{}' script, which we don't "
"have a tokenizer for. The results will be bad.".format(
lang, info["script"]
)
"have a tokenizer for. The results will be bad.".format(lang, info["script"])
)
_WARNED_LANGUAGES.add(lang)
tokens = simple_tokenize(text, include_punctuation=include_punctuation)
@ -301,7 +291,7 @@ def lossy_tokenize(
lang: str,
include_punctuation: bool = False,
external_wordlist: bool = False,
) -> List[str]:
) -> list[str]:
"""
Get a list of tokens for this text, with largely the same results and
options as `tokenize`, but aggressively normalize some text in a lossy way

212
wordfreq/transliterate.py
View File

@ -1,96 +1,156 @@
from __future__ import annotations
# This table comes from
# https://github.com/opendatakosovo/cyrillic-transliteration/blob/master/cyrtranslit/mapping.py,
# from the 'cyrtranslit' module. We originally had to reimplement it because
# 'cyrtranslit' didn't work in Python 3; now it does, but we've made the table
# more robust than the one in cyrtranslit.
SR_LATN_TABLE = {
ord('А'): 'A', ord('а'): 'a',
ord('Б'): 'B', ord('б'): 'b',
ord('В'): 'V', ord('в'): 'v',
ord('Г'): 'G', ord('г'): 'g',
ord('Д'): 'D', ord('д'): 'd',
ord('Ђ'): 'Đ', ord('ђ'): 'đ',
ord('Е'): 'E', ord('е'): 'e',
ord('Ж'): 'Ž', ord('ж'): 'ž',
ord('З'): 'Z', ord('з'): 'z',
ord('И'): 'I', ord('и'): 'i',
ord('Ј'): 'J', ord('ј'): 'j',
ord('К'): 'K', ord('к'): 'k',
ord('Л'): 'L', ord('л'): 'l',
ord('Љ'): 'Lj', ord('љ'): 'lj',
ord('М'): 'M', ord('м'): 'm',
ord('Н'): 'N', ord('н'): 'n',
ord('Њ'): 'Nj', ord('њ'): 'nj',
ord('О'): 'O', ord('о'): 'o',
ord('П'): 'P', ord('п'): 'p',
ord('Р'): 'R', ord('р'): 'r',
ord('С'): 'S', ord('с'): 's',
ord('Т'): 'T', ord('т'): 't',
ord('Ћ'): 'Ć', ord('ћ'): 'ć',
ord('У'): 'U', ord('у'): 'u',
ord('Ф'): 'F', ord('ф'): 'f',
ord('Х'): 'H', ord('х'): 'h',
ord('Ц'): 'C', ord('ц'): 'c',
ord('Ч'): 'Č', ord('ч'): 'č',
ord('Џ'): 'Dž', ord('џ'): 'dž',
ord('Ш'): 'Š', ord('ш'): 'š',
ord("А"): "A",
ord("а"): "a",
ord("Б"): "B",
ord("б"): "b",
ord("В"): "V",
ord("в"): "v",
ord("Г"): "G",
ord("г"): "g",
ord("Д"): "D",
ord("д"): "d",
ord("Ђ"): "Đ",
ord("ђ"): "đ",
ord("Е"): "E",
ord("е"): "e",
ord("Ж"): "Ž",
ord("ж"): "ž",
ord("З"): "Z",
ord("з"): "z",
ord("И"): "I",
ord("и"): "i",
ord("Ј"): "J",
ord("ј"): "j",
ord("К"): "K",
ord("к"): "k",
ord("Л"): "L",
ord("л"): "l",
ord("Љ"): "Lj",
ord("љ"): "lj",
ord("М"): "M",
ord("м"): "m",
ord("Н"): "N",
ord("н"): "n",
ord("Њ"): "Nj",
ord("њ"): "nj",
ord("О"): "O",
ord("о"): "o",
ord("П"): "P",
ord("п"): "p",
ord("Р"): "R",
ord("р"): "r",
ord("С"): "S",
ord("с"): "s",
ord("Т"): "T",
ord("т"): "t",
ord("Ћ"): "Ć",
ord("ћ"): "ć",
ord("У"): "U",
ord("у"): "u",
ord("Ф"): "F",
ord("ф"): "f",
ord("Х"): "H",
ord("х"): "h",
ord("Ц"): "C",
ord("ц"): "c",
ord("Ч"): "Č",
ord("ч"): "č",
ord("Џ"): "Dž",
ord("џ"): "dž",
ord("Ш"): "Š",
ord("ш"): "š",
# Handle Cyrillic letters from other languages. We hope these cases don't
# come up often when we're trying to transliterate Serbian, but if these
# letters show up in loan-words or code-switching text, we can at least
# transliterate them approximately instead of leaving them as Cyrillic
# letters surrounded by Latin.
# Russian letters
ord('Ё'): 'Jo', ord('ё'): 'jo',
ord('Й'): 'J', ord('й'): 'j',
ord('Щ'): 'Šč', ord('щ'): 'šč',
ord('Ъ'): '', ord('ъ'): '',
ord('Ы'): 'Y', ord('ы'): 'y',
ord('Ь'): "'", ord('ь'): "'",
ord('Э'): 'E', ord('э'): 'e',
ord('Ю'): 'Ju', ord('ю'): 'ju',
ord('Я'): 'Ja', ord('я'): 'ja',
ord("Ё"): "Jo",
ord("ё"): "jo",
ord("Й"): "J",
ord("й"): "j",
ord("Щ"): "Šč",
ord("щ"): "šč",
ord("Ъ"): "",
ord("ъ"): "",
ord("Ы"): "Y",
ord("ы"): "y",
ord("Ь"): "'",
ord("ь"): "'",
ord("Э"): "E",
ord("э"): "e",
ord("Ю"): "Ju",
ord("ю"): "ju",
ord("Я"): "Ja",
ord("я"): "ja",
# Belarusian letter
ord('Ў'): 'Ŭ', ord('ў'): 'ŭ',
ord("Ў"): "Ŭ",
ord("ў"): "ŭ",
# Ukrainian letters
ord('Є'): 'Je', ord('є'): 'je',
ord('І'): 'I', ord('і'): 'i',
ord('Ї'): 'Ï', ord('ї'): 'ï',
ord('Ґ'): 'G', ord('ґ'): 'g',
ord("Є"): "Je",
ord("є"): "je",
ord("І"): "I",
ord("і"): "i",
ord("Ї"): "Ï",
ord("ї"): "ï",
ord("Ґ"): "G",
ord("ґ"): "g",
# Macedonian letters
ord('Ѕ'): 'Dz', ord('ѕ'): 'dz',
ord('Ѓ'): 'Ǵ', ord('ѓ'): 'ǵ',
ord('Ќ'): 'Ḱ', ord('ќ'): 'ḱ',
ord("Ѕ"): "Dz",
ord("ѕ"): "dz",
ord("Ѓ"): "Ǵ",
ord("ѓ"): "ǵ",
ord("Ќ"): "Ḱ",
ord("ќ"): "ḱ",
}
AZ_LATN_TABLE = SR_LATN_TABLE.copy()
AZ_LATN_TABLE.update({
# Distinct Azerbaijani letters
ord('Ҹ'): 'C', ord('ҹ'): 'c',
ord('Ә'): 'Ə', ord('ә'): 'ə',
ord('Ғ'): 'Ğ', ord('ғ'): 'ğ',
ord('Һ'): 'H', ord('һ'): 'h',
ord('Ө'): 'Ö', ord('ө'): 'ö',
ord('Ҝ'): 'G', ord('ҝ'): 'g',
ord('Ү'): 'Ü', ord('ү'): 'ü',
# Azerbaijani letters with different transliterations
ord('Ч'): 'Ç', ord('ч'): 'ç',
ord('Х'): 'X', ord('х'): 'x',
ord('Ы'): 'I', ord('ы'): 'ı',
ord('И'): 'İ', ord('и'): 'i',
ord('Ж'): 'J', ord('ж'): 'j',
ord('Ј'): 'Y', ord('ј'): 'y',
ord('Г'): 'Q', ord('г'): 'q',
ord('Ш'): 'Ş', ord('ш'): 'ş',
})
AZ_LATN_TABLE.update(
{
# Distinct Azerbaijani letters
ord("Ҹ"): "C",
ord("ҹ"): "c",
ord("Ә"): "Ə",
ord("ә"): "ə",
ord("Ғ"): "Ğ",
ord("ғ"): "ğ",
ord("Һ"): "H",
ord("һ"): "h",
ord("Ө"): "Ö",
ord("ө"): "ö",
ord("Ҝ"): "G",
ord("ҝ"): "g",
ord("Ү"): "Ü",
ord("ү"): "ü",
# Azerbaijani letters with different transliterations
ord("Ч"): "Ç",
ord("ч"): "ç",
ord("Х"): "X",
ord("х"): "x",
ord("Ы"): "I",
ord("ы"): "ı",
ord("И"): "İ",
ord("и"): "i",
ord("Ж"): "J",
ord("ж"): "j",
ord("Ј"): "Y",
ord("ј"): "y",
ord("Г"): "Q",
ord("г"): "q",
ord("Ш"): "Ş",
ord("ш"): "ş",
}
)
def transliterate(table, text):
def transliterate(table: dict[int, str], text: str) -> str:
"""
Transliterate text according to one of the tables above.
@ -101,9 +161,9 @@ def transliterate(table, text):
Latin alphabet.
- 'az-Latn' means the same for Azerbaijani Cyrillic to Latn.
"""
if table == 'sr-Latn':
if table == "sr-Latn":
return text.translate(SR_LATN_TABLE)
elif table == 'az-Latn':
elif table == "az-Latn":
return text.translate(AZ_LATN_TABLE)
else:
raise ValueError("Unknown transliteration table: {!r}".format(table))
raise ValueError(f"Unknown transliteration table: {table!r}")

15
wordfreq/util.py Normal file
View File

@ -0,0 +1,15 @@
from __future__ import annotations
from pathlib import Path
import locate
def data_path(filename: str | None = None) -> Path:
"""
Get a path to a file in the data directory.
"""
if filename is None:
return Path(locate.this_dir(), "data")
else:
return Path(locate.this_dir(), "data", filename)