-
Notifications
You must be signed in to change notification settings - Fork 610
/
pyproject.toml
145 lines (132 loc) · 3.49 KB
/
pyproject.toml
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
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
[tool.black]
line-length = 120
include = '\.pyi?$'
exclude = '''
(
/(
\.eggs # exclude a few common directories in the
| \.git # root of the project
| \.hg
| \.mypy_cache
| \.tox
| \.venv
| _build
| buck-out
| build
| dist
)/
| docs/build/
| node_modules/
| venve/
| .venv/
)
'''
[tool.nbqa.mutate]
isort = 1
black = 1
[project]
name = "pytorch-forecasting"
readme = "README.md" # Markdown files are supported
version = "1.1.1" # is being replaced automatically
authors = [
{name = "Jan Beitner"},
]
requires-python = ">=3.8,<3.13"
classifiers = [
"Intended Audience :: Developers",
"Intended Audience :: Science/Research",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Mathematics",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Topic :: Software Development",
"Topic :: Software Development :: Libraries",
"Topic :: Software Development :: Libraries :: Python Modules",
"License :: OSI Approved :: MIT License",
]
description = "Forecasting timeseries with PyTorch - dataloaders, normalizers, metrics and models"
dependencies = [
"numpy<2.0.0",
"torch >=2.0.0,!=2.0.1,<3.0.0",
"lightning >=2.0.0,<3.0.0",
"scipy >=1.8,<2.0",
"pandas >=1.3.0,<3.0.0",
"scikit-learn >=1.2,<2.0",
]
[project.optional-dependencies]
# there are the following dependency sets:
# - all_extras - all soft dependencies
# - granular dependency sets:
# - tuning - dependencies for tuning hyperparameters via optuna
# - mqf2 - dependencies for multivariate quantile loss
# - graph - dependencies for graph based forecasting
# - dev - the developer dependency set, for contributors to pytorch-forecasting
# - CI related: e.g., dev, github-actions. Not for users of sktime.
#
# soft dependencies are not required for the core functionality of sktime
# but are required by popular estimators, e.g., prophet, tbats, etc.
# all soft dependencies
#
# users can install via "pip install pytorch-forecasting[all_extras]"
#
all_extras = [
"cpflows",
"matplotlib",
"optuna >=3.1.0,<4.0.0",
"optuna-integration",
"pytorch_optimizer >=2.5.1,<4.0.0",
"statsmodels",
]
tuning = [
"optuna >=3.1.0,<4.0.0",
"optuna-integration",
"statsmodels",
]
mqf2 = ["cpflows"]
# the graph set is not currently used within pytorch-forecasting
# but is kept for future development, as it has already been released
graph = ["networkx"]
# dev - the developer dependency set, for contributors to pytorch-forecasting
dev = [
"pydocstyle >=6.1.1,<7.0.0",
# checks and make tools
"pre-commit >=3.2.0,<4.0.0",
"invoke",
"flake8",
"mypy",
"pylint",
"isort",
# pytest
"pytest",
"pytest-xdist",
"pytest-cov",
"pytest-sugar",
"coverage",
"pyarrow",
# jupyter notebook
"ipykernel",
"nbconvert",
"black[extras]",
# documentatation
"sphinx",
"pydata-sphinx-theme",
"nbsphinx",
"recommonmark",
"ipywidgets>=8.0.1,<9.0.0",
"pytest-dotenv>=0.5.2,<1.0.0",
"tensorboard>=2.12.1,<3.0.0",
"pandoc>=2.3,<3.0.0",
]
github-actions = ["pytest-github-actions-annotate-failures"]
[tool.setuptools.packages.find]
exclude = ["build_tools"]
[build-system]
build-backend = "setuptools.build_meta"
requires = [
"setuptools>=70.0.0",
]