feat(统计): 统计接口补上每人每道题的每一次提交、流程图每人最好的一次，流程图也能一次查几道题
- 新增 GET /submissions/statistics/grid：范围内每个学生的每次提交（只含普通学生，最多 5000 条）， 没选班级时附带各班花名册人数，统计页按「人 × 题」画方块串、按班级汇总 - /flowcharts/statistics 题号可以一次填几道，多返回 people（每人分数最高的那张） Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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@@ -358,21 +358,30 @@ flowchartRoutes.get("/flowcharts/statistics", requireTeacher, async (c) => {
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]
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if (start) filters.push(sql`${schema.flowchartSubmission.createTime} >= ${start}`)
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const displayId = c.req.query("problemDisplayId")?.trim()
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if (displayId) {
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const [problem] = await db
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.select({ id: schema.problem.id })
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// 可以一次查几道（统计页的题号框和代码统计同一个），有一道找不到就整体报错，
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// 不退化成「全部题目」—— 否则打错一个字看到的是全站数据
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const displayIds = parseDisplayIds(c.req.query("problemDisplayId") ?? "")
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if (displayIds.length) {
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const lowered = displayIds.map((id) => id.toLowerCase())
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const problems = await db
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.select({ id: schema.problem.id, displayId: schema.problem.displayId })
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.from(schema.problem)
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.where(
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and(
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sql`lower(${schema.problem.displayId}) = lower(${displayId})`,
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inArray(sql`lower(${schema.problem.displayId})`, lowered),
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isNull(schema.problem.contestId),
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eq(schema.problem.visible, true),
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),
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)
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.limit(1)
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if (!problem) return failure(c, 404, "problem-not-found", "Problem does not exist")
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filters.push(eq(schema.flowchartSubmission.problemId, problem.id))
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const found = new Set(problems.map((row) => row.displayId.toLowerCase()))
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const missing = displayIds.find((id) => !found.has(id.toLowerCase()))
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if (missing) return failure(c, 404, "problem-not-found", `Problem ${missing} does not exist`)
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filters.push(
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inArray(
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schema.flowchartSubmission.problemId,
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problems.map((row) => row.id),
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),
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)
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}
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const username = c.req.query("username")?.trim()
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@@ -400,49 +409,52 @@ flowchartRoutes.get("/flowcharts/statistics", requireTeacher, async (c) => {
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* （criteria 255 + suggestions 64 + feedback 47），现在 2134 条无感，5 万条就是一次
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* 点击 18MB，而老师是开着面板反复切时段、切班的。
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*/
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const [[totals], gradeRows, criteriaRows, textRows, submittedRows] = await Promise.all([
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db
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.select({
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total: count(),
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/**
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* 均分拆成 sum / count 两项，不直接用 `avg()`：分母是**有分数的条数**而不是
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* 总条数（对齐 Django 的 Avg()，它跳过 NULL），拆开之后这个口径在代码里是
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* 写明的，也省掉 avg() 在空集上回 NULL 还要兜底。
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*/
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scoreSum: sql<number>`coalesce(sum(${schema.flowchartSubmission.aiScore}), 0)`.mapWith(
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Number,
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),
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scoreCount: sql<number>`count(${schema.flowchartSubmission.aiScore})::int`.mapWith(Number),
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// 完成人数。user_id 和 username 一一对应，按哪个 distinct 都一样，
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// 按 user_id 就不必 join user
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completedCount:
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sql<number>`count(distinct ${schema.flowchartSubmission.userId})::int`.mapWith(Number),
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})
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.from(schema.flowchartSubmission)
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.where(where),
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db
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.select({ grade: schema.flowchartSubmission.aiGrade, n: count() })
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.from(schema.flowchartSubmission)
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.where(where)
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.groupBy(schema.flowchartSubmission.aiGrade),
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/**
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* 各项**平均分**。`ai_criteria_details` 是 `{ 项名: { score, max, comment } }`，
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* 用 jsonb_each 展开之后按项名分组。分数不是数字的项整项跳过，和原来 JS 那句
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* `typeof detail.score !== "number"` 的 continue 一致。
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*
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* **那道 `jsonb_typeof(...) = 'object'` 的闸不能省，而且要写在 jsonb_each 的参数里。**
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* 不能省：撞上标量（历史脏数据）jsonb_each 直接抛错，整个面板 500 ——
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* 拿 `'5'::jsonb` 和 `'[1,2]'::jsonb` 各插一行验过。
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*
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* 写在哪儿则纯是规划器的脸色：挪进 where 当基表过滤条件时，53350 行的探针上
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* 实测 180ms → 360ms，因为计划从「并行 Partial HashAggregate」换成了「串行
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* GroupAggregate + 21 万行外部归并排序、落盘 26MB」。两种写法都正确，选快的那个。
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*
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* 每项的**满分**不在这里取，见下面 criteriaMax 的注释：在这条 SQL 里按
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* create_time 取「最新那条」要给 21 万行（4 项 × 5 万条）排序，同一个探针上
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* 实测 254ms → 842ms，而满分本来就是几个常数。
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*/
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db.execute<{ key: string; avg: number }>(sql`
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const [[totals], gradeRows, criteriaRows, textRows, submittedRows, peopleRows] =
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await Promise.all([
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db
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.select({
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total: count(),
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/**
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* 均分拆成 sum / count 两项，不直接用 `avg()`：分母是**有分数的条数**而不是
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* 总条数（对齐 Django 的 Avg()，它跳过 NULL），拆开之后这个口径在代码里是
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* 写明的，也省掉 avg() 在空集上回 NULL 还要兜底。
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*/
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scoreSum: sql<number>`coalesce(sum(${schema.flowchartSubmission.aiScore}), 0)`.mapWith(
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Number,
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),
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scoreCount: sql<number>`count(${schema.flowchartSubmission.aiScore})::int`.mapWith(
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Number,
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),
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// 完成人数。user_id 和 username 一一对应，按哪个 distinct 都一样，
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// 按 user_id 就不必 join user
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completedCount:
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sql<number>`count(distinct ${schema.flowchartSubmission.userId})::int`.mapWith(Number),
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})
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.from(schema.flowchartSubmission)
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.where(where),
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db
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.select({ grade: schema.flowchartSubmission.aiGrade, n: count() })
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.from(schema.flowchartSubmission)
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.where(where)
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.groupBy(schema.flowchartSubmission.aiGrade),
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/**
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* 各项**平均分**。`ai_criteria_details` 是 `{ 项名: { score, max, comment } }`，
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* 用 jsonb_each 展开之后按项名分组。分数不是数字的项整项跳过，和原来 JS 那句
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* `typeof detail.score !== "number"` 的 continue 一致。
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*
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* **那道 `jsonb_typeof(...) = 'object'` 的闸不能省，而且要写在 jsonb_each 的参数里。**
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* 不能省：撞上标量（历史脏数据）jsonb_each 直接抛错，整个面板 500 ——
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* 拿 `'5'::jsonb` 和 `'[1,2]'::jsonb` 各插一行验过。
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*
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* 写在哪儿则纯是规划器的脸色：挪进 where 当基表过滤条件时，53350 行的探针上
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* 实测 180ms → 360ms，因为计划从「并行 Partial HashAggregate」换成了「串行
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* GroupAggregate + 21 万行外部归并排序、落盘 26MB」。两种写法都正确，选快的那个。
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*
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* 每项的**满分**不在这里取，见下面 criteriaMax 的注释：在这条 SQL 里按
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* create_time 取「最新那条」要给 21 万行（4 项 × 5 万条）排序，同一个探针上
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* 实测 254ms → 842ms，而满分本来就是几个常数。
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*/
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db.execute<{ key: string; avg: number }>(sql`
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select e.key as key, avg((e.value->>'score')::double precision) as avg
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from ${schema.flowchartSubmission}
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cross join lateral jsonb_each(
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@@ -453,25 +465,51 @@ flowchartRoutes.get("/flowcharts/statistics", requireTeacher, async (c) => {
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where ${where} and jsonb_typeof(e.value->'score') = 'number'
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group by e.key
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`),
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// 词云的原料。只有这条要读大列，所以只有它按时间倒序取最近的 N 条
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db
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.select({
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criteria: schema.flowchartSubmission.aiCriteriaDetails,
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feedback: schema.flowchartSubmission.aiFeedback,
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suggestions: schema.flowchartSubmission.aiSuggestions,
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})
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.from(schema.flowchartSubmission)
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.where(where)
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.orderBy(desc(schema.flowchartSubmission.createTime))
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.limit(WORDCLOUD_TEXT_LIMIT),
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// 「谁没做」只在有花名册时算得出来，行数也就一个班
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roster.length
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? db
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.selectDistinct({ userId: schema.flowchartSubmission.userId })
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.from(schema.flowchartSubmission)
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.where(where)
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: [],
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])
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// 词云的原料。只有这条要读大列，所以只有它按时间倒序取最近的 N 条
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db
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.select({
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criteria: schema.flowchartSubmission.aiCriteriaDetails,
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feedback: schema.flowchartSubmission.aiFeedback,
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suggestions: schema.flowchartSubmission.aiSuggestions,
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})
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.from(schema.flowchartSubmission)
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.where(where)
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.orderBy(desc(schema.flowchartSubmission.createTime))
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.limit(WORDCLOUD_TEXT_LIMIT),
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// 「谁没做」只在有花名册时算得出来，行数也就一个班
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roster.length
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? db
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.selectDistinct({ userId: schema.flowchartSubmission.userId })
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.from(schema.flowchartSubmission)
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.where(where)
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: [],
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// 每人最好的一次。等级取分数最高那张的等级（同分取最近的），只算普通学生
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db
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.select({
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username: schema.user.username,
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className: schema.user.className,
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bestScore: sql<number | null>`max(${schema.flowchartSubmission.aiScore})`,
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bestGrade: sql<string | null>`(array_agg(${schema.flowchartSubmission.aiGrade}
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order by ${schema.flowchartSubmission.aiScore} desc nulls last, ${schema.flowchartSubmission.createTime} desc))[1]`,
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count: count(),
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})
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.from(schema.flowchartSubmission)
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.innerJoin(schema.user, eq(schema.user.id, schema.flowchartSubmission.userId))
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.where(
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and(where, eq(schema.user.adminType, "Regular User"), eq(schema.user.isDisabled, false)),
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)
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.groupBy(schema.user.id, schema.user.username, schema.user.className)
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.orderBy(sql`max(${schema.flowchartSubmission.aiScore}) asc nulls first`)
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.limit(500),
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])
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const people = peopleRows.map((row) => ({
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username: row.username,
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realName: stripClassPrefix(row.username, row.className),
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bestScore: row.bestScore === null ? null : Number(row.bestScore),
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bestGrade: row.bestGrade,
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count: row.count,
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}))
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if (!totals || totals.total === 0) {
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return success(c, {
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@@ -488,6 +526,7 @@ flowchartRoutes.get("/flowcharts/statistics", requireTeacher, async (c) => {
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username: row.username,
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realName: stripClassPrefix(row.username, row.className),
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})),
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people: [],
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} satisfies FlowchartStatistics)
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}
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@@ -551,6 +590,7 @@ flowchartRoutes.get("/flowcharts/statistics", requireTeacher, async (c) => {
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username: row.username,
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realName: stripClassPrefix(row.username, row.className),
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})),
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people,
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} satisfies FlowchartStatistics)
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})
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