cit-sci-traits/pyproject.toml at main · GeoSense-Freiburg/cit-sci-traits · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
[tool.poetry]
name = "cit-sci-traits"
version = "0.1.0"
description = ""
authors = ["Daniel Lusk <daniel.lusk@geosense.uni-freiburg.de>"]
readme = "README.md"
packages = [{include = "src"}]

[tool.poetry.dependencies]
python = ">3.11.0,<3.12"
python-dotenv = "^1.0.1"
ipykernel = "^6.29.3"
pandas = "^2.2.1"
rioxarray = "^0.15.1"
rasterio = "^1.3.9"
pyogrio = "^0.7.2"
pyyaml = "^6.0.1"
numpy = "^1.26.4"
matplotlib = "^3.8.3"
ipywidgets = "^8.1.2"
python-box = "~7"
seaborn = "^0.13.2"
cartopy = "^0.23.0"
geopandas = "^0.14.3"
pyarrow = "^16.0.0"
dask-geopandas = "^0.3.1"
dask = {extras = ["dataframe"], version = "^2024.4.2"}
joblib = "^1.4.2"
tqdm = "^4.66.4"
h3 = "^3.7.7"
pykrige = "^1.7.1"
utm = "^0.7.0"
bokeh = "^3.4.1"
setuptools = "^69.5.1"
wheel = "^0.43.0"
autogluon-tabular = {extras = ["all"], version = "^1.1.0"}
statsmodels = "^0.14.2"
tabulate = "^0.9.0"
scikit-learn = "~1.4"
rio-cogeo = "^5.3.6"
ease-grid = "^0.2"
verstack = "^4.1.4"

[tool.poetry.group.cuda.dependencies]
cudf-cu11 = { version = "24.10.*", source = "nvidia" }
cuml-cu11 = { version = "24.10.*", source = "nvidia" }
cupy-cuda11x = "^13.3.0"

[tool.poetry.group.r.dependencies]
rpy2 = "^3.5.16"

[tool.poetry.group.dev.dependencies]
pre-commit = "^3.6.2"
pytest = "^8.1.1"
pylint = "^3.1.0"
pylint-pytest = "^1.1.7"
pytest-mock = "^3.12.0"
paramiko = "^3.4.0"
earthengine-api = "^1.4.5"

[tool.poetry.group.profiling.dependencies]
line_profiler = "^4"
scalene = "^1.5.51"

[tool.poetry.group.analysis.dependencies]
adjusttext = "^1.3.0"

python-docx = "^1.1.2"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"

[[tool.poetry.source]]
name = "nvidia"
url = "https://pypi.nvidia.com"
priority = "supplemental"