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watcher_visio/metrics/views.py

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+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")