Create main.py

main.py

@@ -0,0 +1,60 @@
+from fastapi import FastAPI, Query, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+import pandas as pd
+import requests
+from io import StringIO
+
+app = FastAPI(title="IAPI", version="1.0.0")
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+DATA_URL = "https://raw.githubusercontent.com/live-by-unix/iapi-csv/refs/heads/main/iapi_data.csv"
+
+def load_database():
+    try:
+        response = requests.get(DATA_URL)
+        response.raise_for_status()
+        return pd.read_csv(StringIO(response.text))
+    except Exception:
+        return pd.DataFrame(columns=["category", "title", "content"])
+
+df = load_database()
+
+@app.get("/")
+async def root():
+    return {
+        "name": "IAPI",
+        "records": len(df),
+        "license": "CC BY-SA 4.0",
+        "attribution": "Data sourced from Wikipedia editors",
+        "status": "Online"
+    }
+
+@app.get("/category/{category_name}")
+async def get_category(category_name: str):
+    subset = df[df['category'].str.lower() == category_name.lower()]
+    if subset.empty:
+        raise HTTPException(status_code=404, detail="Category not found")
+    return subset.to_dict(orient="records")
+
+@app.get("/search")
+async def search(q: str = Query(..., min_length=2)):
+    mask = df['title'].str.contains(q, case=False, na=False) | \
+           df['content'].str.contains(q, case=False, na=False)
+    results = df[mask]
+    return results.to_dict(orient="records")
+
+@app.get("/article/random")
+async def get_random():
+    if df.empty:
+        raise HTTPException(status_code=503, detail="Database unavailable")
+    return df.sample(1).to_dict(orient="records")[0]
+
+@app.get("/meta/stats")
+async def get_stats():
+    return df['category'].value_counts().to_dict()