"""孕妈悄悄话置顶笔记的 100 条模拟祝福评论(11-07 用户:「评论里按正常评论放上 100 个」)。 lines.txt 一行一条,「||」后面是楼中楼回复(其他孕妈/宝妈)。人设从 cm.json 的 1000 人里挑:主评论用孕期人设、回复混宝妈; 尽量挑在别的帖子下出现少的人。确定性(固定种子),重跑结果不变;只追加/覆盖 c[TARGET],不动其他帖子。""" import json, random from collections import Counter TARGET = 'wh-20260928' P = 'guangchang/cm.json' d = json.load(open(P, encoding='utf-8')) used = Counter(c[0] for k, L in d['c'].items() if k != TARGET for c in L) rnd = random.Random(20261107) import re def wk(p): m = re.match(r'孕 ?(\d+)', p[2]); return int(m.group(1)) if m else 0 # 内容多是胎动、产检、待产(孕中晚期的事)→ 主评论只用孕 24 周以上的人设,免得「孕 6 周」说「头朝下了」 preg = sorted([i for i, p in enumerate(d['p']) if wk(p) >= 24], key=lambda i: (used[i], i)) anyp = sorted(range(len(d['p'])), key=lambda i: (used[i], i)) # 11-07 用户看评论:名字套路太像(4 个「在挑名字」、4 个「今天也开心」、3 个「水獭」、虎虎的老母亲/虎虎妈妈…)→ 同一帖里前两个字、后两个字都不撞 SIG = set() def fresh(i): n = d['p'][i][0]; ks = {'h:' + n[:2], 't:' + n[-2:]} return not (ks & SIG) def take(pool, k): out = [] for i in pool: if len(out) >= k: break if fresh(i): n = d['p'][i][0]; SIG.update({'h:' + n[:2], 't:' + n[-2:]}); out.append(i) for i in pool: # 不够就只要求后两个字不撞 if len(out) >= k: break n = d['p'][i][0] if i not in out and 't:' + n[-2:] not in SIG: SIG.add('t:' + n[-2:]); out.append(i) for i in pool: # 还不够就随它 if len(out) >= k: break if i not in out: out.append(i) return out preg = take(preg, 160) mains = preg[:200]; rnd.shuffle(mains) anyp = [i for i in anyp if i not in set(preg) and not re.match(r'准爸爸', d['p'][i][2])] # 回复里不放「准爸爸」(还没娃,说不了打针) reps = take(anyp, 31); rnd.shuffle(reps) lines = [l.strip() for l in open('tools/whcm/lines.txt', encoding='utf-8') if l.strip()] assert len(lines) == 100, len(lines) out, ri = [], 0 # 内容要和孕周对得上:按关键词给每条定孕周范围,从打乱后的人设里挑第一个落在范围内的 RULES = [(r'糖耐', 24, 28), (r'预产期在月底', 37, 39), (r'待产包|入盆|无痛|胎位|头朝下|小床|产假|月子餐|育儿嫂|报纸|满月|儿科医生|插座|剪了标签|绘本', 32, 39), (r'踢的位置越来越低|孕妇照|羊水|吸奶器|数胎动|数你|产褥垫|剪指甲|洗了第一批衣服|婴儿车', 28, 39), (r'四维', 24, 30)] def rng(t): for pat, lo, hi in RULES: if re.search(pat, t): return lo, hi return 24, 39 left = list(mains) def pick(t): lo, hi = rng(t) for i in left: if lo <= wk(d['p'][i]) <= hi: left.remove(i); return i raise SystemExit('没有合适人设:' + t) for k, l in enumerate(lines): parts = l.split('||') likes = max(3, int(520 * (0.965 ** k)) + rnd.randint(-18, 18)) rr = [] for t in parts[1:]: rr.append([reps[ri], t]); ri += 1 out.append([pick(parts[0]), parts[0], likes, rr]) # 11-07 用户:「评论里也加一些孕早期的孕妈,看到别人有胎动也有期待,也有自己的话对孩子说;都要真人感」 # early.txt = 孕 6~13 周人设的留言(回复用孕中晚期/宝妈人设,像过来人);均匀插进前 100 条中间,不全堆在后面 # early_rep.txt = 「原留言开头|早孕妈妈的回复」,挂在已有留言楼里(「看你们说胎动好羡慕」这类) early_p = take(sorted([i for i, p in enumerate(d['p']) if 6 <= wk(p) <= 13 and i not in set(reps) and not re.search(r'待产|宝妈|老母亲|养娃|学抱娃|拼尿布|麻麻|大宝', p[0])], key=lambda i: (used[i], i)), 51) er = random.Random(20261108); er.shuffle(early_p) ei = 0 for t in [l.strip() for l in open('tools/whcm/early_rep.txt', encoding='utf-8') if l.strip()]: head, txt = t.split('|', 1) hit = [c for c in out if c[1].startswith(head)] assert len(hit) == 1, head hit[0][3].append([early_p[ei], txt]); ei += 1 early = [l.strip() for l in open('tools/whcm/early.txt', encoding='utf-8') if l.strip()] eo = [] for k, l in enumerate(early): parts = l.split('||') rr = [] for t in parts[1:]: rr.append([reps[ri], t]); ri += 1 eo.append([early_p[ei], parts[0], 0, rr]); ei += 1 # 定赞数:从第 3 条起每隔约 2~3 条放一条早孕的,赞数取前后两条之间 merged = [] step = len(out) / len(eo) j = 0 for k, c in enumerate(out): merged.append(c) while j < len(eo) and k >= 2 + j * step * .96: e = eo[j]; nxt = out[k + 1][2] if k + 1 < len(out) else 3 e[2] = max(3, (c[2] + nxt) // 2 + rnd.randint(-4, 4)); merged.append(e); j += 1 for e in eo[j:]: e[2] = 3 # 追加在最后(模拟留言的 key 是「帖子#下标」,插在中间会让原来那 100 条下标错位,真实回复/本机点赞挂错楼); # 赞数已按插入位置取好,「最热」排序时自然穿插在中间 out = out + eo d['c'][TARGET] = out json.dump(d, open(P, 'w', encoding='utf-8'), ensure_ascii=False, separators=(',', ':')) print('ok', len(out), 'replies', ri, 'early', len(eo), 'early-replies', ei - len(eo))