import os
import json
import time
import requests
from django.conf import settings
from django.shortcuts import render
from django.http import JsonResponse, HttpResponse
from django.template.loader import render_to_string

# Helper: query Prometheus HTTP API (query_range)
def query_prometheus_range(query, start, end, step="60s"):
    url = settings.PROMETHEUS_URL.rstrip("/") + "/api/v1/query_range"
    params = {"query": query, "start": start, "end": end, "step": step}
    r = requests.get(url, params=params, timeout=10)
    r.raise_for_status()
    return r.json()

# API endpoint used by Chart.js frontend
def metrics_api(request):
    # get parameters or default (last 1 hour)
    metric = request.GET.get("metric", settings.PROMETHEUS_DEFAULT_METRIC)
    now = int(time.time())
    start = request.GET.get("start", str(now - 3600))  # unix epoch seconds
    end = request.GET.get("end", str(now))
    step = request.GET.get("step", "60s")

    # Example: if the metric is a gauge giving bytes, we may want to convert ... keep raw for now
    q = metric
    data = query_prometheus_range(q, start, end, step)
    # Prometheus returns JSON; keep it minimal for Chart.js: {labels: [...], datasets: [{label,...,data:[...]}]}
    series = []
    labels = []
    datasets = []

    if data.get("status") != "success":
        return JsonResponse({"error": "prometheus error", "detail": data})

    result = data["data"]["result"]  # list of time series
    # if no series, return empty
    if not result:
        return JsonResponse({"labels": [], "datasets": []})

    # Build labels from first series timestamps
    # Prometheus returns values as [[ts, value], ...]
    first_values = result[0]["values"]
    labels = [int(float(t[0])) * 1000 for t in first_values]  # JS prefers ms
    for s in result:
        # create dataset for each timeseries (label from metric labels)
        metric_labels = s.get("metric", {})
        label = metric_labels.get("instance") or metric_labels.get("domain") or json.dumps(metric_labels)
        values = [float(v[1]) if v[1] != "NaN" else None for v in s["values"]]
        datasets.append({
            "label": label,
            "data": values,
        })

    return JsonResponse({"labels": labels, "datasets": datasets})

# Dashboard page (Jinja template)
def dashboard(request):
    # let template ask API for data with JS.
    return render(request, "dashboard.html", {
        "default_metric": settings.PROMETHEUS_DEFAULT_METRIC,
    })

# Render page to PDF using WeasyPrint
def report_pdf(request):
    # optionally accept ?metric=...&start=...&end=...
    metric = request.GET.get("metric", settings.PROMETHEUS_DEFAULT_METRIC)
    now = int(time.time())
    start = int(request.GET.get("start", now - 3600))
    end = int(request.GET.get("end", now))

    # fetch data server-side to include in report
    try:
        resp = query_prometheus_range(metric, start, end, step="60s")
    except Exception as e:
        return HttpResponse(f"Error fetching metrics: {e}", status=500)

    context = {
        "metric": metric,
        "prom_data": resp.get("data", {}),
        "generated_at": time.strftime("%Y-%m-%d %H:%M:%S", time.gmtime()),
    }
    html = render_to_string("report.html", context)

    # Generate PDF via WeasyPrint
    from weasyprint import HTML
    pdf = HTML(string=html, base_url=request.build_absolute_uri("/")).write_pdf()
    return HttpResponse(pdf, content_type="application/pdf")