Update web/core/views.py

web/core/views.py

@@ -458,3 +458,107 @@ def normalize_scripture(request):
             "limit": limit,
         },
     )
+    @login_required
+def stats_page(request):
+    total = Entry.objects.count()
+    today = date.today()
+    last30 = Entry.objects.filter(date_added__gte=today - timedelta(days=30)).count()
+    last365 = Entry.objects.filter(date_added__gte=today - timedelta(days=365)).count()
+
+    # ---- Adds per month (existing logic) ----
+    months = []
+    y = today.year
+    m = today.month
+    for i in range(12):
+        mm = m - i
+        yy = y
+        while mm <= 0:
+            mm += 12
+            yy -= 1
+        from datetime import date as _d
+        start = _d(yy, mm, 1)
+        end = _d(yy + 1, 1, 1) if mm == 12 else _d(yy, mm + 1, 1)
+        label = f"{yy}-{mm:02d}"
+        months.append((label, start, end))
+    months = list(reversed(months))
+
+    series = [
+        (label, Entry.objects.filter(date_added__gte=start, date_added__lt=end).count())
+        for label, start, end in months
+    ]
+    peak = max((v for _, v in series), default=1)
+    heights = [(label, value, 8 + int((value / peak) * 100) if peak else 8)
+               for label, value in series]
+
+    # ---- Top subjects (existing logic) ----
+    counts = Counter()
+    for subj in Entry.objects.exclude(subject="").values_list("subject", flat=True):
+        for tag in [t.strip() for t in subj.split(",") if t.strip()]:
+            counts[tag.lower()] += 1
+    top_subjects = [{"name": n.title(), "count": c} for n, c in counts.most_common(10)]
+
+    # ---- Scripture analytics (NEW) ----
+    # Expect canonical like: "Matt. 5:14; Ps. 1:1,2; 1 Cor. 13:4-7"
+    # Split on semicolons; capture book and chap/verses if present.
+    BOOK_RE = re.compile(
+        r"^\s*(?P<book>(?:[1-3]\s+)?[A-Za-z\.]+(?:\s+[A-Za-z\.]+){0,2})"
+        r"(?:\s+(?P<cv>\d+(?::[\d,\-\u2013\u2014]+)?))?\s*$"
+    )
+
+    books_counter = Counter()
+    refs_counter = Counter()
+    ref_per_entry_counts = []
+    entries_with_scripture = 0
+
+    scriptures = Entry.objects.exclude(scripture_raw="") \
+                              .values_list("scripture_raw", flat=True)
+
+    for raw in scriptures:
+        pieces = [p for p in re.split(r"\s*;\s*", raw or "") if p.strip()]
+        if not pieces:
+            continue
+        entries_with_scripture += 1
+        refs_this_entry = 0
+
+        for p in pieces:
+            m = BOOK_RE.match(p)
+            if not m:
+                continue
+            book = (m.group("book") or "").strip()
+            cv = (m.group("cv") or "").strip()
+            if not book:
+                continue
+            books_counter[book] += 1
+            if cv:
+                refs_counter[f"{book} {cv}"] += 1
+                refs_this_entry += 1
+
+        ref_per_entry_counts.append(refs_this_entry)
+
+    top_books = books_counter.most_common(10)
+    top_refs = refs_counter.most_common(10)
+    avg_refs_per_entry = round(
+        (sum(ref_per_entry_counts) / len(ref_per_entry_counts))
+        if ref_per_entry_counts else 0.0, 2
+    )
+    book_distribution = books_counter.most_common(30)  # handy for future charts
+
+    return render(
+        request,
+        "stats.html",
+        {
+            "total": total,
+            "last30": last30,
+            "last365": last365,
+            "series": series,
+            "heights": heights,
+            "top_subjects": top_subjects,
+
+            # NEW context for the template
+            "entries_with_scripture": entries_with_scripture,
+            "avg_refs_per_entry": avg_refs_per_entry,
+            "top_books": top_books,
+            "top_refs": top_refs,
+            "book_distribution": book_distribution,
+        },
+    )