# backend.py
from fastapi import FastAPI, Query
from fastapi.middleware.cors import CORSMiddleware
from typing import Optional
import pandas as pd
import geoip2.database
from datetime import datetime

# ----------------------------
# 1. Load Access Logs
# ----------------------------
logs = []
with open("access.log") as f:
    for line in f:
        # Example log format: "2025-08-28T12:34:56Z 192.0.2.1 GET /api/service1"
        parts = line.strip().split(" ", 3)
        if len(parts) != 4:
            continue  # skip malformed lines
        timestamp, ip, method, path = parts
        logs.append({
            "timestamp": timestamp,
            "ip": ip,
            "method": method,
            "path": path
        })
df = pd.DataFrame(logs)
df["timestamp"] = pd.to_datetime(df["timestamp"])
# ----------------------------
# 2. GeoIP Lookup
# ----------------------------
reader = geoip2.database.Reader("GeoLite2-City.mmdb")

def ip_to_geo(ip):
    try:
        response = reader.city(ip)
        return response.location.latitude, response.location.longitude
    except Exception as e:
        print(f"GeoIP lookup failed for {ip}: {e}")
        return None, None
df["lat"], df["lon"] = zip(*df["ip"].apply(ip_to_geo))
print(df)
df = df.dropna(subset=["lat", "lon"])



# ----------------------------
# 3. FastAPI Setup
# ----------------------------
app = FastAPI(title="Reverse Proxy Connections Map API")

# Allow frontend to query API from any origin
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_methods=["*"],
    allow_headers=["*"]
)

# ----------------------------
# 4. API Endpoint
# ----------------------------
@app.get("/connections")
def get_connections(
    service: Optional[str] = Query(None, description="Filter by service path"),
    start: Optional[str] = Query(None, description="Start datetime in ISO format"),
    end: Optional[str] = Query(None, description="End datetime in ISO format")
):
    data = df.copy()

    if service:
        data = data[data["path"].str.contains(service)]

    if start:
        data = data[data["timestamp"] >= pd.to_datetime(start)]
    if end:
        data = data[data["timestamp"] <= pd.to_datetime(end)]
    return data[["timestamp", "path", "lat", "lon"]].to_dict(orient="records")

# ----------------------------
# 5. Healthcheck Endpoint
# ----------------------------
@app.get("/health")
def health():
    return {"status": "ok", "total_connections": len(df)}

if __name__ == "__main__":
    import uvicorn
    uvicorn.run("backend:app", host="0.0.0.0", port=8000, reload=True)