self-hosted/immich
1
0
Fork 0
mirror of https://github.com/immich-app/immich.git synced 2024-11-24 08:52:28 +02:00
Code Issues Releases Activity

pin python (#5272)

Browse Source
This commit is contained in:
Mert 2023-11-22 19:42:17 -05:00 committed by GitHub
parent 6eadca330b
commit 6e10d15f2c
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 4 additions and 124 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

126
machine-learning/poetry.lock generated
View File

@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
[[package]]
name = "aiocache"
@ -585,68 +585,6 @@ files = [
test = ["PyYAML", "mock", "pytest"]
yaml = ["PyYAML"]
[[package]]
name = "contourpy"
version = "1.1.0"
description = "Python library for calculating contours of 2D quadrilateral grids"
optional = false
python-versions = ">=3.8"
files = [
{file = "contourpy-1.1.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:89f06eff3ce2f4b3eb24c1055a26981bffe4e7264acd86f15b97e40530b794bc"},
{file = "contourpy-1.1.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:dffcc2ddec1782dd2f2ce1ef16f070861af4fb78c69862ce0aab801495dda6a3"},
{file = "contourpy-1.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:25ae46595e22f93592d39a7eac3d638cda552c3e1160255258b695f7b58e5655"},
{file = "contourpy-1.1.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:17cfaf5ec9862bc93af1ec1f302457371c34e688fbd381f4035a06cd47324f48"},
{file = "contourpy-1.1.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:18a64814ae7bce73925131381603fff0116e2df25230dfc80d6d690aa6e20b37"},
{file = "contourpy-1.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:90c81f22b4f572f8a2110b0b741bb64e5a6427e0a198b2cdc1fbaf85f352a3aa"},
{file = "contourpy-1.1.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:53cc3a40635abedbec7f1bde60f8c189c49e84ac180c665f2cd7c162cc454baa"},
{file = "contourpy-1.1.0-cp310-cp310-win32.whl", hash = "sha256:9b2dd2ca3ac561aceef4c7c13ba654aaa404cf885b187427760d7f7d4c57cff8"},
{file = "contourpy-1.1.0-cp310-cp310-win_amd64.whl", hash = "sha256:1f795597073b09d631782e7245016a4323cf1cf0b4e06eef7ea6627e06a37ff2"},
{file = "contourpy-1.1.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:0b7b04ed0961647691cfe5d82115dd072af7ce8846d31a5fac6c142dcce8b882"},
{file = "contourpy-1.1.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:27bc79200c742f9746d7dd51a734ee326a292d77e7d94c8af6e08d1e6c15d545"},
{file = "contourpy-1.1.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:052cc634bf903c604ef1a00a5aa093c54f81a2612faedaa43295809ffdde885e"},
{file = "contourpy-1.1.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9382a1c0bc46230fb881c36229bfa23d8c303b889b788b939365578d762b5c18"},
{file = "contourpy-1.1.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e5cec36c5090e75a9ac9dbd0ff4a8cf7cecd60f1b6dc23a374c7d980a1cd710e"},
{file = "contourpy-1.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1f0cbd657e9bde94cd0e33aa7df94fb73c1ab7799378d3b3f902eb8eb2e04a3a"},
{file = "contourpy-1.1.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:181cbace49874f4358e2929aaf7ba84006acb76694102e88dd15af861996c16e"},
{file = "contourpy-1.1.0-cp311-cp311-win32.whl", hash = "sha256:edb989d31065b1acef3828a3688f88b2abb799a7db891c9e282df5ec7e46221b"},
{file = "contourpy-1.1.0-cp311-cp311-win_amd64.whl", hash = "sha256:fb3b7d9e6243bfa1efb93ccfe64ec610d85cfe5aec2c25f97fbbd2e58b531256"},
{file = "contourpy-1.1.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:bcb41692aa09aeb19c7c213411854402f29f6613845ad2453d30bf421fe68fed"},
{file = "contourpy-1.1.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:5d123a5bc63cd34c27ff9c7ac1cd978909e9c71da12e05be0231c608048bb2ae"},
{file = "contourpy-1.1.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:62013a2cf68abc80dadfd2307299bfa8f5aa0dcaec5b2954caeb5fa094171103"},
{file = "contourpy-1.1.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0b6616375d7de55797d7a66ee7d087efe27f03d336c27cf1f32c02b8c1a5ac70"},
{file = "contourpy-1.1.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:317267d915490d1e84577924bd61ba71bf8681a30e0d6c545f577363157e5e94"},
{file = "contourpy-1.1.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d551f3a442655f3dcc1285723f9acd646ca5858834efeab4598d706206b09c9f"},
{file = "contourpy-1.1.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:e7a117ce7df5a938fe035cad481b0189049e8d92433b4b33aa7fc609344aafa1"},
{file = "contourpy-1.1.0-cp38-cp38-win32.whl", hash = "sha256:108dfb5b3e731046a96c60bdc46a1a0ebee0760418951abecbe0fc07b5b93b27"},
{file = "contourpy-1.1.0-cp38-cp38-win_amd64.whl", hash = "sha256:d4f26b25b4f86087e7d75e63212756c38546e70f2a92d2be44f80114826e1cd4"},
{file = "contourpy-1.1.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:bc00bb4225d57bff7ebb634646c0ee2a1298402ec10a5fe7af79df9a51c1bfd9"},
{file = "contourpy-1.1.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:189ceb1525eb0655ab8487a9a9c41f42a73ba52d6789754788d1883fb06b2d8a"},
{file = "contourpy-1.1.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9f2931ed4741f98f74b410b16e5213f71dcccee67518970c42f64153ea9313b9"},
{file = "contourpy-1.1.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:30f511c05fab7f12e0b1b7730ebdc2ec8deedcfb505bc27eb570ff47c51a8f15"},
{file = "contourpy-1.1.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:143dde50520a9f90e4a2703f367cf8ec96a73042b72e68fcd184e1279962eb6f"},
{file = "contourpy-1.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e94bef2580e25b5fdb183bf98a2faa2adc5b638736b2c0a4da98691da641316a"},
{file = "contourpy-1.1.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:ed614aea8462735e7d70141374bd7650afd1c3f3cb0c2dbbcbe44e14331bf002"},
{file = "contourpy-1.1.0-cp39-cp39-win32.whl", hash = "sha256:71551f9520f008b2950bef5f16b0e3587506ef4f23c734b71ffb7b89f8721999"},
{file = "contourpy-1.1.0-cp39-cp39-win_amd64.whl", hash = "sha256:438ba416d02f82b692e371858143970ed2eb6337d9cdbbede0d8ad9f3d7dd17d"},
{file = "contourpy-1.1.0-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:a698c6a7a432789e587168573a864a7ea374c6be8d4f31f9d87c001d5a843493"},
{file = "contourpy-1.1.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:397b0ac8a12880412da3551a8cb5a187d3298a72802b45a3bd1805e204ad8439"},
{file = "contourpy-1.1.0-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:a67259c2b493b00e5a4d0f7bfae51fb4b3371395e47d079a4446e9b0f4d70e76"},
{file = "contourpy-1.1.0-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:2b836d22bd2c7bb2700348e4521b25e077255ebb6ab68e351ab5aa91ca27e027"},
{file = "contourpy-1.1.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:084eaa568400cfaf7179b847ac871582199b1b44d5699198e9602ecbbb5f6104"},
{file = "contourpy-1.1.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:911ff4fd53e26b019f898f32db0d4956c9d227d51338fb3b03ec72ff0084ee5f"},
{file = "contourpy-1.1.0.tar.gz", hash = "sha256:e53046c3863828d21d531cc3b53786e6580eb1ba02477e8681009b6aa0870b21"},
]
[package.dependencies]
numpy = ">=1.16"
[package.extras]
bokeh = ["bokeh", "selenium"]
docs = ["furo", "sphinx-copybutton"]
mypy = ["contourpy[bokeh,docs]", "docutils-stubs", "mypy (==1.2.0)", "types-Pillow"]
test = ["Pillow", "contourpy[test-no-images]", "matplotlib"]
test-no-images = ["pytest", "pytest-cov", "wurlitzer"]
[[package]]
name = "contourpy"
version = "1.1.1"
@ -2578,64 +2516,6 @@ files = [
{file = "packaging-23.2.tar.gz", hash = "sha256:048fb0e9405036518eaaf48a55953c750c11e1a1b68e0dd1a9d62ed0c092cfc5"},
]
[[package]]
name = "pandas"
version = "2.1.0"
description = "Powerful data structures for data analysis, time series, and statistics"
optional = false
python-versions = ">=3.9"
files = [
{file = "pandas-2.1.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:40dd20439ff94f1b2ed55b393ecee9cb6f3b08104c2c40b0cb7186a2f0046242"},
{file = "pandas-2.1.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:d4f38e4fedeba580285eaac7ede4f686c6701a9e618d8a857b138a126d067f2f"},
{file = "pandas-2.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6e6a0fe052cf27ceb29be9429428b4918f3740e37ff185658f40d8702f0b3e09"},
{file = "pandas-2.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9d81e1813191070440d4c7a413cb673052b3b4a984ffd86b8dd468c45742d3cc"},
{file = "pandas-2.1.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:eb20252720b1cc1b7d0b2879ffc7e0542dd568f24d7c4b2347cb035206936421"},
{file = "pandas-2.1.0-cp310-cp310-win_amd64.whl", hash = "sha256:38f74ef7ebc0ffb43b3d633e23d74882bce7e27bfa09607f3c5d3e03ffd9a4a5"},
{file = "pandas-2.1.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:cda72cc8c4761c8f1d97b169661f23a86b16fdb240bdc341173aee17e4d6cedd"},
{file = "pandas-2.1.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:d97daeac0db8c993420b10da4f5f5b39b01fc9ca689a17844e07c0a35ac96b4b"},
{file = "pandas-2.1.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d8c58b1113892e0c8078f006a167cc210a92bdae23322bb4614f2f0b7a4b510f"},
{file = "pandas-2.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:629124923bcf798965b054a540f9ccdfd60f71361255c81fa1ecd94a904b9dd3"},
{file = "pandas-2.1.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:70cf866af3ab346a10debba8ea78077cf3a8cd14bd5e4bed3d41555a3280041c"},
{file = "pandas-2.1.0-cp311-cp311-win_amd64.whl", hash = "sha256:d53c8c1001f6a192ff1de1efe03b31a423d0eee2e9e855e69d004308e046e694"},
{file = "pandas-2.1.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:86f100b3876b8c6d1a2c66207288ead435dc71041ee4aea789e55ef0e06408cb"},
{file = "pandas-2.1.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:28f330845ad21c11db51e02d8d69acc9035edfd1116926ff7245c7215db57957"},
{file = "pandas-2.1.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b9a6ccf0963db88f9b12df6720e55f337447aea217f426a22d71f4213a3099a6"},
{file = "pandas-2.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d99e678180bc59b0c9443314297bddce4ad35727a1a2656dbe585fd78710b3b9"},
{file = "pandas-2.1.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:b31da36d376d50a1a492efb18097b9101bdbd8b3fbb3f49006e02d4495d4c644"},
{file = "pandas-2.1.0-cp39-cp39-win_amd64.whl", hash = "sha256:0164b85937707ec7f70b34a6c3a578dbf0f50787f910f21ca3b26a7fd3363437"},
{file = "pandas-2.1.0.tar.gz", hash = "sha256:62c24c7fc59e42b775ce0679cfa7b14a5f9bfb7643cfbe708c960699e05fb918"},
]
[package.dependencies]
numpy = {version = ">=1.23.2", markers = "python_version >= \"3.11\""}
python-dateutil = ">=2.8.2"
pytz = ">=2020.1"
tzdata = ">=2022.1"
[package.extras]
all = ["PyQt5 (>=5.15.6)", "SQLAlchemy (>=1.4.36)", "beautifulsoup4 (>=4.11.1)", "bottleneck (>=1.3.4)", "dataframe-api-compat (>=0.1.7)", "fastparquet (>=0.8.1)", "fsspec (>=2022.05.0)", "gcsfs (>=2022.05.0)", "html5lib (>=1.1)", "hypothesis (>=6.46.1)", "jinja2 (>=3.1.2)", "lxml (>=4.8.0)", "matplotlib (>=3.6.1)", "numba (>=0.55.2)", "numexpr (>=2.8.0)", "odfpy (>=1.4.1)", "openpyxl (>=3.0.10)", "pandas-gbq (>=0.17.5)", "psycopg2 (>=2.9.3)", "pyarrow (>=7.0.0)", "pymysql (>=1.0.2)", "pyreadstat (>=1.1.5)", "pytest (>=7.3.2)", "pytest-asyncio (>=0.17.0)", "pytest-xdist (>=2.2.0)", "pyxlsb (>=1.0.9)", "qtpy (>=2.2.0)", "s3fs (>=2022.05.0)", "scipy (>=1.8.1)", "tables (>=3.7.0)", "tabulate (>=0.8.10)", "xarray (>=2022.03.0)", "xlrd (>=2.0.1)", "xlsxwriter (>=3.0.3)", "zstandard (>=0.17.0)"]
aws = ["s3fs (>=2022.05.0)"]
clipboard = ["PyQt5 (>=5.15.6)", "qtpy (>=2.2.0)"]
compression = ["zstandard (>=0.17.0)"]
computation = ["scipy (>=1.8.1)", "xarray (>=2022.03.0)"]
consortium-standard = ["dataframe-api-compat (>=0.1.7)"]
excel = ["odfpy (>=1.4.1)", "openpyxl (>=3.0.10)", "pyxlsb (>=1.0.9)", "xlrd (>=2.0.1)", "xlsxwriter (>=3.0.3)"]
feather = ["pyarrow (>=7.0.0)"]
fss = ["fsspec (>=2022.05.0)"]
gcp = ["gcsfs (>=2022.05.0)", "pandas-gbq (>=0.17.5)"]
hdf5 = ["tables (>=3.7.0)"]
html = ["beautifulsoup4 (>=4.11.1)", "html5lib (>=1.1)", "lxml (>=4.8.0)"]
mysql = ["SQLAlchemy (>=1.4.36)", "pymysql (>=1.0.2)"]
output-formatting = ["jinja2 (>=3.1.2)", "tabulate (>=0.8.10)"]
parquet = ["pyarrow (>=7.0.0)"]
performance = ["bottleneck (>=1.3.4)", "numba (>=0.55.2)", "numexpr (>=2.8.0)"]
plot = ["matplotlib (>=3.6.1)"]
postgresql = ["SQLAlchemy (>=1.4.36)", "psycopg2 (>=2.9.3)"]
spss = ["pyreadstat (>=1.1.5)"]
sql-other = ["SQLAlchemy (>=1.4.36)"]
test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-asyncio (>=0.17.0)", "pytest-xdist (>=2.2.0)"]
xml = ["lxml (>=4.8.0)"]
[[package]]
name = "pandas"
version = "2.1.2"
@ -4771,5 +4651,5 @@ testing = ["coverage (>=5.0.3)", "zope.event", "zope.testing"]
[metadata]
lock-version = "2.0"
python-versions = "^3.11"
content-hash = "bba5f87aa67bc1d2283a9f4b471ef78e572337f22413870d324e908014410d53"
python-versions = "~3.11"
content-hash = "a4c9b3550bb2a67a54b9ab70e700b24fb9eb0b652e90d7dd8ec92abd121ca6e3"

2
machine-learning/pyproject.toml
View File

@ -7,7 +7,7 @@ readme = "README.md"
packages = [{include = "app"}]
[tool.poetry.dependencies]
python = "^3.11"
python = "~3.11"
torch = [
{markers = "platform_machine == 'arm64' or platform_machine == 'aarch64'", version = "=2.1.0", source = "pypi"},
{markers = "platform_machine == 'amd64' or platform_machine == 'x86_64'", version = "=2.1.0", source = "pytorch-cpu"}