shenleiandClaude Opus 5
6b42b7abc3
## 独立词库 理解词原先只能跟着课程单元走，学完 A0 十课词汇量只增加约 22 个实词， 不足以解决"记不住单词"。新增一份独立词库 assets/words/wordbank.json （2748 词，A1–B1），挂进 receptiveWordRegistry 的合成单元 bank-A1/A2/B1， 完全复用理解词已有的状态机，不依赖课程进度，第一天就能用。 数据来源、许可与合成规则记在 tool/words/DATA-NOTE.md：CEFR-J 定等级、 公开词书提供音标、AI 重写全部释义并生成例句、OpenSubtitles 提供口语词频。 词书部分为 CC BY-NC-SA 4.0 且上游权利不明，仅供个人非商用； 若要分发或上架，须替换音标那一列。 ## 背单词机制 - 间隔阶梯 1/3/7/15/30/60/120 天，连续答对上一级，答错回第一级。 原先首次答对后要等 7 天才复习，正是"第二天就忘"的成因。 - 每日新词上限（10 分钟 8 个 / 20 分钟 15 个 / 30 分钟 20 个）。 阶梯第一级是次日，今天引入的新词就是明天的工作量。 - 新词按口语频率发放，不再按字母序 —— A1 从 a.m./ability 变成 no/not/know/just。 - 三个方向按层级轮转：看词（英→中）→ 听词（音→中）→ 想词（中→英）。 想词题仍是选择题，不要求产出，理解词定位不变，不进升级分母。 - 单词页独立成 tab，首页今日任务卡下方给一张认词入口卡。 ## 用法对照 课程 JSON 增加 usage 字段（when/reply/swap/confuse）：一个句型用在什么场合、 对方通常怎么答、还能怎么说、跟哪个学过的句型容易混。 知道 How are you? 的意思，不等于知道它不是用来问名字的。 ## 复习流 - 当日快闪（recap）独立成队列，不占复习预算，也不计入积压。 - 只发放当日预算内的量，其余保持到期状态等下次，不悄悄丢弃或改期。 - 答错的项隔几题后回来，而不是立刻重问。 测试 296 通过，flutter analyze 干净。 Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
70 lines
2.1 KiB
Python
70 lines
2.1 KiB
Python
"""Writes a frequency rank onto every bank word.
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Without this the bank is handed out in alphabetical order, so the first two
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weeks are nothing but words starting with `a`. Rank 0 is the most common word.
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A multi-word entry (`bus stop`, `air conditioning`) is not in a word frequency
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list at all, so it takes the rank of its rarest part: a phrase is no easier
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than the hardest word in it.
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"""
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import json
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import os
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import re
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import sys
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ROOT = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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BANK = os.path.join(ROOT, 'assets/words/wordbank.json')
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# Words the list does not have at all go last, but stay in their level.
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UNRANKED = 99999
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def load_ranks(path):
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ranks = {}
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with open(path) as handle:
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for position, line in enumerate(handle):
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parts = line.split()
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if len(parts) == 2:
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ranks.setdefault(parts[0], position)
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return ranks
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def rank_of(word, ranks):
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direct = ranks.get(word.lower())
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if direct is not None:
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return direct
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parts = [re.sub(r"[^a-z']", '', part) for part in word.lower().split()]
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parts = [part for part in parts if part]
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found = [ranks[part] for part in parts if part in ranks]
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if len(found) == len(parts) and found:
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return max(found)
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return UNRANKED
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def main():
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frequency = sys.argv[1]
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ranks = load_ranks(frequency)
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with open(BANK) as handle:
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bank = json.load(handle)
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unranked = 0
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for word in bank['words']:
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rank = rank_of(word['en'], ranks)
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word['rank'] = rank
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if rank == UNRANKED:
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unranked += 1
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with open(BANK, 'w') as handle:
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json.dump(bank, handle, ensure_ascii=False, separators=(',', ':'))
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handle.write('\n')
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print('ranked %d, unranked %d' % (len(bank['words']) - unranked, unranked))
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for level in ('A1', 'A2', 'B1'):
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words = sorted(
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(w for w in bank['words'] if w['level'] == level),
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key=lambda w: w['rank'],
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)
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print('%s first 12: %s' % (level, ' '.join(w['en'] for w in words[:12])))
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if __name__ == '__main__':
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main()
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