Adding poetry.lock, pyproject.toml

museum_analytics/museum_api.py

@@ -26,13 +26,10 @@ from fastapi import FastAPI, HTTPException, Query
 from pydantic import BaseModel, Field
 from sklearn.linear_model import LinearRegression
 from sklearn.model_selection import KFold, cross_val_score
-
-
 from dotenv import load_dotenv
 
 load_dotenv()
 
-
 REQUIRED_COLUMNS = ["Name", "Visitors", "City", "Country", "Population"]
 
 
@@ -245,6 +242,14 @@ def create_app(
         return [Prediction(population=p, predicted_visitors=float(v))
                 for p, v in zip(req.populations, preds)]
 
+    @app.get("/data")
+    def data():
+        """Every row the model was fitted on, with its prediction."""
+        m = get_model()
+        d = m.data.copy()
+        d["Predicted"] = m.predictions
+        return d.to_dict(orient="records")
+
     @app.get("/residuals")
     def residuals(
         top: int = Query(10, ge=1, le=500),

pyproject.toml

@@ -0,0 +1,29 @@
+[project]
+name = "museum-analytics"
+version = "0.1.0"
+description = ""
+authors = [
+    {name = "hansp",email = "hanspayer@gmail.com"}
+]
+readme = "README.md"
+requires-python = "^3.12"
+dependencies = [
+    "requests (>=2.34.2,<3.0.0)",
+    "pandas (>=3.0.6,<4.0.0)",
+    "python-dotenv (>=1.2.4,<2.0.0)",
+    "wikipedia-api (>=0.16.0,<0.17.0)",
+    "lxml (>=6.1.3,<7.0.0)",
+    "html5lib (>=1.1,<2.0)",
+    "beautifulsoup4 (>=4.15.0,<5.0.0)",
+    "numpy (>=2.5.3,<3.0.0)",
+    "fastapi (>=0.142.3,<0.143.0)",
+    "scikit-learn (>=1.9.1,<2.0.0)",
+    "uvicorn (>=0.54.0,<0.55.0)",
+    "jupyterlab (>=4.6.4,<5.0.0)",
+    "matplotlib (>=3.11.2,<4.0.0)",
+]
+
+
+[build-system]
+requires = ["poetry-core>=2.0.0,<3.0.0"]
+build-backend = "poetry.core.masonry.api"