Delete main.py

main.py

@@ -1,136 +0,0 @@
-from fastapi import FastAPI, HTTPException, Query
-from fastapi.middleware.cors import CORSMiddleware
-import pandas as pd
-import numpy as np
-import os
-
-app = FastAPI(
-    title="Districtmaps.ai API",
-    description="District-level health risk intelligence across 708 Indian districts. Powered by NFHS-5 data and validated ML models.",
-    version="1.0.0"
-)
-
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-# Load data at startup
-DATA_PATH = os.getenv("DATA_PATH", "india_all_districts_risk.csv")
-df = None
-
-@app.on_event("startup")
-def load_data():
-    global df
-    df = pd.read_csv(DATA_PATH)
-    df.columns = [c.strip().lower().replace(" ", "_") for c in df.columns]
-    df["district_lower"] = df["district"].str.lower().str.strip()
-    df["state_lower"]    = df["state"].str.lower().str.strip()
-    print(f"Loaded {len(df)} districts.")
-
-def format_district(row):
-    return {
-        "district":               row.get("district", ""),
-        "state":                  row.get("state", ""),
-        "risk_scores": {
-            "diabetes":           safe_float(row.get("diabetes_risk")),
-            "blood_pressure":     safe_float(row.get("blood_pressure_risk")),
-            "obesity":            safe_float(row.get("obesity_risk")),
-            "anaemia":            safe_float(row.get("anaemia_risk")),
-        },
-        "composite_risk":         safe_float(row.get("composite_risk")),
-        "risk_percentile":        safe_float(row.get("diabetes_risk_norm")),
-    }
-
-def safe_float(val):
-    try:
-        f = float(val)
-        return round(f, 4) if not np.isnan(f) else None
-    except:
-        return None
-
-@app.get("/", tags=["Info"])
-def root():
-    return {
-        "product":     "Districtmaps.ai",
-        "description": "District-level NCD risk intelligence for India",
-        "districts":   len(df) if df is not None else 0,
-        "conditions":  ["diabetes", "blood_pressure", "obesity", "anaemia"],
-        "validation": {
-            "cross_sectional_r2": 0.7477,
-            "temporal_r2":        0.6279,
-            "temporal_gap":       "4 years (NFHS-4 2015-16 → NFHS-5 2019-21)",
-            "districts_covered":  708
-        },
-        "endpoints": {
-            "GET /risk":       "Risk scores for a specific district",
-            "GET /districts":  "Full ranked list of all districts",
-            "GET /top":        "Top N highest risk districts",
-            "GET /state/{state}": "All districts within a state",
-        }
-    }
-
-@app.get("/risk", tags=["Risk Scores"])
-def get_district_risk(
-    district: str = Query(..., description="District name e.g. Mumbai"),
-    state:    str = Query(None, description="Optional state filter to disambiguate")
-):
-    mask = df["district_lower"] == district.lower().strip()
-    if state:
-        mask &= df["state_lower"] == state.lower().strip()
-    results = df[mask]
-    if results.empty:
-        # Fuzzy fallback — partial match
-        mask2 = df["district_lower"].str.contains(district.lower().strip(), na=False)
-        if state:
-            mask2 &= df["state_lower"].str.contains(state.lower().strip(), na=False)
-        results = df[mask2]
-    if results.empty:
-        raise HTTPException(status_code=404, detail=f"District '{district}' not found.")
-    return {
-        "query":   district,
-        "matches": [format_district(row) for _, row in results.iterrows()]
-    }
-
-@app.get("/districts", tags=["Rankings"])
-def get_all_districts(
-    sort_by: str = Query("composite_risk", description="Field to sort by"),
-    order:   str = Query("desc", description="asc or desc"),
-    limit:   int = Query(708, ge=1, le=708)
-):
-    ascending = order == "asc"
-    col = sort_by if sort_by in df.columns else "composite_risk"
-    sorted_df = df.sort_values(col, ascending=ascending).head(limit)
-    return {
-        "total":     len(sorted_df),
-        "sorted_by": col,
-        "order":     order,
-        "districts": [format_district(row) for _, row in sorted_df.iterrows()]
-    }
-
-@app.get("/top", tags=["Rankings"])
-def get_top_districts(
-    n:         int = Query(10, ge=1, le=100, description="Number of districts"),
-    condition: str = Query("composite_risk", description="diabetes_risk | blood_pressure_risk | obesity_risk | anaemia_risk | composite_risk")
-):
-    col = condition if condition in df.columns else "composite_risk"
-    top = df.nlargest(n, col)
-    return {
-        "condition": col,
-        "top_n":     n,
-        "districts": [format_district(row) for _, row in top.iterrows()]
-    }
-
-@app.get("/state/{state}", tags=["State"])
-def get_state_districts(state: str):
-    mask    = df["state_lower"].str.contains(state.lower().strip(), na=False)
-    results = df[mask].sort_values("composite_risk", ascending=False)
-    if results.empty:
-        raise HTTPException(status_code=404, detail=f"State '{state}' not found.")
-    return {
-        "state":     state,
-        "districts": len(results),
-        "ranked":    [format_district(row) for _, row in results.iterrows()]
-    }