causal-productivity-intelligence/pyproject.toml at main · nayanekaa/causal-productivity-intelligence · 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
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
[build-system]
requires = ["setuptools>=68.0", "wheel"]
build-backend = "setuptools.backends.legacy:build"

[project]
name = "causal-productivity-intelligence"
version = "1.0.0"
description = "End-to-end causal inference system for knowledge-worker productivity using statistical modelling, Bayesian methods, and LLM integration"
readme = "README.md"
license = { file = "LICENSE" }
requires-python = ">=3.10"
keywords = [
    "causal inference", "productivity", "bayesian statistics",
    "double machine learning", "behavioral science", "streamlit",
]
classifiers = [
    "Development Status :: 4 - Beta",
    "Intended Audience :: Science/Research",
    "License :: OSI Approved :: MIT License",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
    "Topic :: Scientific/Engineering :: Information Analysis",
]

dependencies = [
    "numpy>=1.26.0",
    "pandas>=2.1.0",
    "scipy>=1.11.0",
    "statsmodels>=0.14.0",
    "scikit-learn>=1.3.0",
    "matplotlib>=3.8.0",
    "seaborn>=0.13.0",
    "plotly>=5.18.0",
    "streamlit>=1.31.0",
    "anthropic>=0.18.0",
    "python-dotenv>=1.0.0",
    "joblib>=1.3.0",
    "tqdm>=4.66.0",
]

[project.optional-dependencies]
bayesian = [
    "pymc>=5.9.0",
    "arviz>=0.17.0",
    "pytensor>=2.18.0",
]
notebook = [
    "jupyter>=1.0.0",
    "ipykernel>=6.27.0",
    "nbformat>=5.9.0",
    "nbconvert>=7.14.0",
]
dev = [
    "pytest>=7.4.0",
    "pytest-cov>=4.1.0",
    "black>=24.0.0",
    "isort>=5.13.0",
    "flake8>=7.0.0",
    "mypy>=1.8.0",
    "pre-commit>=3.6.0",
]
all = [
    "causal-productivity-intelligence[bayesian,notebook,dev]",
]

[project.scripts]
cpis-run    = "run_all:run_pipeline"

[project.urls]
Homepage      = "https://github.com/your-username/causal-productivity-intelligence"
Repository    = "https://github.com/your-username/causal-productivity-intelligence"
Issues        = "https://github.com/your-username/causal-productivity-intelligence/issues"
Documentation = "https://github.com/your-username/causal-productivity-intelligence#readme"

# ─────────────────────────────────────────────────────────────────────────────
# Tool configuration
# ─────────────────────────────────────────────────────────────────────────────

[tool.black]
line-length    = 99
target-version = ["py310", "py311", "py312"]
include        = '\.pyi?$'
exclude        = '''
/(
    \.git
  | \.venv
  | build
  | dist
  | notebooks
)/
'''

[tool.isort]
profile                   = "black"
line_length               = 99
known_first_party         = ["src"]
skip_glob                 = ["notebooks/*", ".venv/*"]
force_sort_within_sections = true

[tool.pytest.ini_options]
testpaths     = ["tests"]
python_files  = ["test_*.py"]
python_classes= ["Test*"]
python_functions = ["test_*"]
addopts       = "-v --tb=short --cov=src --cov-report=term-missing"
filterwarnings = [
    "ignore::DeprecationWarning",
    "ignore::FutureWarning",
]

[tool.mypy]
python_version         = "3.10"
warn_return_any        = true
warn_unused_configs    = true
disallow_untyped_defs  = false
ignore_missing_imports = true
exclude                = ["notebooks/", ".venv/"]

[tool.coverage.run]
source  = ["src"]
omit    = ["*/test_*", "*/conftest.py"]

[tool.coverage.report]
show_missing   = true
skip_covered   = false
fail_under     = 50