egutierrez
ea6678ec23
Añade dos funciones impuras dict-no-throw, deterministas por seed, al dominio datascience (grupo eda): - generate_synthetic_eda_table: una tabla DuckDB de 19 columnas (numéricas correlacionadas + outliers, categóricas desbalanceadas, texto largo multi-idioma es/en/fr, fecha DATE, lat/lon válidas, PII email/iban/phone/uuid, nulos con patrón MCAR/MAR co-ocurrentes). Activa 14 capítulos del motor AutomaticEDA (num_distr, cat_distr, text_distr, calidad, missingness, correlacion, relaciones, modelos, timeseries, geospatial, agregacion, glosario + portada/overview). - generate_synthetic_eda_folder: 3 CSV relacionados (customers/orders/reviews) con FK customer detectable por containment, para el EDA de carpeta multi-tabla. Determinismo via Faker.seed_instance + numpy.default_rng. Tests: 16 passed (incluye determinismo por hash, rangos lat/lon, co-nulos income/spending, mediana palabras review >=20, phone formato internacional, FK containment). Añade faker (40.27.0) a python/pyproject.toml + uv.lock. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
73 lines
1.9 KiB
TOML
73 lines
1.9 KiB
TOML
[project]
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name = "fn-registry-python"
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version = "0.1.0"
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description = "Funciones Python del fn-registry: Metabase API, ML, utilidades"
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readme = "README.md"
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requires-python = ">=3.12"
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dependencies = [
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"chardet>=7.4.3",
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"contextily>=1.7.0",
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"cryptography>=46.0.6",
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"duckdb>=1.5.2",
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"faker>=40.27.0",
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"fpdf2>=2.8.7",
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"geopandas>=1.1.3",
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"google-api-python-client>=2.197.0",
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"google-auth>=2.49.1",
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"google-cloud-bigquery>=3.25",
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"google-cloud-bigquery-datatransfer>=3.22.0",
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"google-cloud-bigquery-storage>=2.27",
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"google-cloud-storage>=3.10.1",
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"httpx",
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"langdetect>=1.0.9",
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"matplotlib>=3.10.9",
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"opencv-contrib-python-headless>=4.13.0.92",
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"openpyxl>=3.1.5",
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"pillow>=12.2.0",
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"polars>=1.40.1",
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"pymeshlab>=2025.7.post1",
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"pymssql>=2.3.13",
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"pymupdf>=1.28.0",
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"pypdf>=6.10.0",
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"pyproj>=3.7.2",
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"python-docx>=1.2.0",
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"python-pptx>=1.0.2",
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"pyyaml>=6.0.3",
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"qrcode[pil]>=8.2",
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"rapidfuzz>=3.14.5",
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"reportlab>=4.5.0",
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"scikit-image>=0.26.0",
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"scikit-learn>=1.8.0",
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"scipy>=1.17.1",
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"seaborn>=0.13.2",
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"shapely>=2.1.2",
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"statsmodels>=0.14.6",
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"textstat>=0.7.13",
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"trimesh>=4.12.2",
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"xlrd>=2.0.2",
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]
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[project.optional-dependencies]
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nlp = [
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"gliner>=0.2.13",
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"glirel>=1.0.0",
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]
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jupyter = [
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"jupyterlab>=4.0",
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"jupyter-collaboration>=2.0",
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"jupyter-mcp-server",
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]
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[dependency-groups]
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dev = [
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"pytest>=9.0.2",
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]
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[tool.pytest.ini_options]
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# Las funciones del registry importan paquetes por su nombre raiz
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# (p.ej. `from obsidian import format_obsidian_note`), por lo que el
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# directorio `functions/` debe estar en sys.path al recolectar tests.
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# `functions/obsidian` permite a los tests importar los modulos hoja por
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# su nombre directo (p.ej. `from format_obsidian_note import ...`).
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pythonpath = ["functions", "functions/obsidian"]
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