Update web/core/views.py
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commit
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@ -457,4 +457,108 @@ def normalize_scripture(request):
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"preview": preview,
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"preview": preview,
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"limit": limit,
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"limit": limit,
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},
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},
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)
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@login_required
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def stats_page(request):
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total = Entry.objects.count()
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today = date.today()
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last30 = Entry.objects.filter(date_added__gte=today - timedelta(days=30)).count()
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last365 = Entry.objects.filter(date_added__gte=today - timedelta(days=365)).count()
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# ---- Adds per month (existing logic) ----
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months = []
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y = today.year
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m = today.month
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for i in range(12):
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mm = m - i
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yy = y
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while mm <= 0:
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mm += 12
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yy -= 1
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from datetime import date as _d
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start = _d(yy, mm, 1)
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end = _d(yy + 1, 1, 1) if mm == 12 else _d(yy, mm + 1, 1)
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label = f"{yy}-{mm:02d}"
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months.append((label, start, end))
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months = list(reversed(months))
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series = [
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(label, Entry.objects.filter(date_added__gte=start, date_added__lt=end).count())
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for label, start, end in months
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]
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peak = max((v for _, v in series), default=1)
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heights = [(label, value, 8 + int((value / peak) * 100) if peak else 8)
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for label, value in series]
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# ---- Top subjects (existing logic) ----
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counts = Counter()
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for subj in Entry.objects.exclude(subject="").values_list("subject", flat=True):
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for tag in [t.strip() for t in subj.split(",") if t.strip()]:
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counts[tag.lower()] += 1
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top_subjects = [{"name": n.title(), "count": c} for n, c in counts.most_common(10)]
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# ---- Scripture analytics (NEW) ----
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# Expect canonical like: "Matt. 5:14; Ps. 1:1,2; 1 Cor. 13:4-7"
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# Split on semicolons; capture book and chap/verses if present.
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BOOK_RE = re.compile(
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r"^\s*(?P<book>(?:[1-3]\s+)?[A-Za-z\.]+(?:\s+[A-Za-z\.]+){0,2})"
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r"(?:\s+(?P<cv>\d+(?::[\d,\-\u2013\u2014]+)?))?\s*$"
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)
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books_counter = Counter()
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refs_counter = Counter()
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ref_per_entry_counts = []
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entries_with_scripture = 0
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scriptures = Entry.objects.exclude(scripture_raw="") \
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.values_list("scripture_raw", flat=True)
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for raw in scriptures:
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pieces = [p for p in re.split(r"\s*;\s*", raw or "") if p.strip()]
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if not pieces:
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continue
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entries_with_scripture += 1
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refs_this_entry = 0
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for p in pieces:
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m = BOOK_RE.match(p)
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if not m:
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continue
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book = (m.group("book") or "").strip()
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cv = (m.group("cv") or "").strip()
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if not book:
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continue
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books_counter[book] += 1
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if cv:
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refs_counter[f"{book} {cv}"] += 1
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refs_this_entry += 1
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ref_per_entry_counts.append(refs_this_entry)
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top_books = books_counter.most_common(10)
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top_refs = refs_counter.most_common(10)
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avg_refs_per_entry = round(
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(sum(ref_per_entry_counts) / len(ref_per_entry_counts))
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if ref_per_entry_counts else 0.0, 2
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)
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book_distribution = books_counter.most_common(30) # handy for future charts
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return render(
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request,
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"stats.html",
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{
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"total": total,
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"last30": last30,
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"last365": last365,
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"series": series,
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"heights": heights,
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"top_subjects": top_subjects,
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# NEW context for the template
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"entries_with_scripture": entries_with_scripture,
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"avg_refs_per_entry": avg_refs_per_entry,
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"top_books": top_books,
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"top_refs": top_refs,
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"book_distribution": book_distribution,
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},
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)
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)
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