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argszero merged 1 commit into from
Sep 13, 2026
Merged

fix(wallet): filter, sort and export the 点数 column by the value it renders #196

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152 changes: 137 additions & 15 deletions src/routes/wallet.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,36 @@ use crate::routes::{internal, ApiErr, AppState, AuthUser};
/// 两者概念不同，勿混用（`withdraw` 受理但尚无 writer：受理集合与方向集合本就不是同一件事）。
pub const TX_FILTER_TYPES: [&str; 6] = ["consume", "earn", "topup", "gift", "expire", "withdraw"];

/// 交易**方向**的唯一真源 —— 收入类型（点数入账）。
///
/// 与 [`TX_FILTER_TYPES`] 是两件事：那是「**受理哪些值**」的集合，这是「值算收入还是支出」。
/// 每个 writer 都把 `pts` 存成**非负数**，方向由 `type` 决定、不由 `pts` 的符号决定
/// （C2045/C2047/C2050）。凡需要「有符号点数」的地方一律用 [`signed_pts_expr`]，勿再写内联字面量。
const TX_INCOME_TYPES: &str = "'earn','topup','gift'";

/// 交易方向：支出类型（离开账户）—— 消费 / 赠送过期 / 提现。见 [`TX_INCOME_TYPES`]。
const TX_EXPENSE_TYPES: &str = "'consume','expire','withdraw'";

/// 「点数」列在 UI 上**渲染/展示**的有符号值：收入为正、支出为负
/// （前端 `signedPts()`，`ui/js/app.js`）。
///
/// 该列的一切消费方 —— 区间筛选、排序、CSV 导出 —— 都必须与此同口径：筛选/排序是对
/// 「用户看到的数字」的主张，不是对库内原始值的主张。C2054：区间筛选曾直接比较库内 `pts`，
/// 而每个 writer 都存正数 ⇒ 用户按表里看到的负数（如 `-3.7`）筛选会得到 **0 行**。
///
/// `prefix` 是表别名（如 `"t"`；无别名时传 `""`），与 [`tx_where`] 的 `col()` 同一约定。
fn signed_pts_expr(prefix: &str) -> String {
let col = |c: &str| {
if prefix.is_empty() {
c.to_string()
} else {
format!("{prefix}.{c}")
}
};
let (ty, pts) = (col("type"), col("pts"));
format!("(CASE WHEN {ty} IN ({TX_INCOME_TYPES}) THEN {pts} ELSE -{pts} END)")
}

/// 解析 `type` 查询参数：`""` / `"all"` → `None`（不筛），[`TX_FILTER_TYPES`] 成员 → `Some(成员)`，
/// 其余 → 400（文案由 [`TX_FILTER_TYPES`] **派生**，因此不可能再与集合分叉）。
/// `/api/transactions` 与 `/api/transactions/trend` 共用此函数。
Expand Down Expand Up @@ -90,9 +120,9 @@ pub struct TxColFilters {
pub key_name: Option<String>,
/// 状态精确匹配（库内中文值：成功/入账/处理中）
pub status: Option<String>,
/// 点数下限（>=）
/// 点数下限（>=，按列**渲染的有符号值**：收入正 / 支出负 —— 与 `signedPts()` 同口径）
pub pts_min: Option<String>,
/// 点数上限（<=）
/// 点数上限（<=，同上：有符号值）
pub pts_max: Option<String>,
}

Expand Down Expand Up @@ -186,9 +216,12 @@ fn tx_where(
conds.push(format!("{} = ?{}", col("status"), binds.len() + 1));
binds.push(rusqlite::types::Value::Text(s.to_string()));
}
// pts 区间：按**渲染的有符号值**比较（收入正 / 支出负），与列渲染、summary/trend 同口径。
// C2054：原先直接比较库内 `pts`，而每个 writer 都存正数 ⇒ 用户按表里看到的负数筛选得 0 行。
let signed_pts = signed_pts_expr(prefix);
for (v, op) in [(f.pts_min.as_deref(), ">="), (f.pts_max.as_deref(), "<=")] {
if let Some(n) = v.and_then(|s| s.trim().parse::<f64>().ok()) {
conds.push(format!("{} {op} ?{}", col("pts"), binds.len() + 1));
conds.push(format!("{signed_pts} {op} ?{}", binds.len() + 1));
binds.push(rusqlite::types::Value::Real(n));
}
}
Expand Down Expand Up @@ -246,11 +279,12 @@ pub async fn transactions(
// 方向由 `type` 决定，不是 `pts` 的符号（每个 writer 都存正数，C2045/C2050）。
let (where_sql, where_binds) =
tx_where("t", auth.user_id, &type_filter, &start, &end, &q.filters);
let signed_pts = signed_pts_expr("t");
let summary_sql = format!(
"SELECT \
COALESCE(SUM(CASE WHEN t.type IN ('earn','topup','gift') THEN t.pts ELSE 0 END), 0), \
COALESCE(SUM(CASE WHEN t.type IN ('consume','expire','withdraw') THEN t.pts ELSE 0 END), 0), \
COALESCE(SUM(CASE WHEN t.type IN ('earn','topup','gift') THEN t.pts ELSE -t.pts END), 0), \
COALESCE(SUM(CASE WHEN t.type IN ({TX_INCOME_TYPES}) THEN t.pts ELSE 0 END), 0), \
COALESCE(SUM(CASE WHEN t.type IN ({TX_EXPENSE_TYPES}) THEN t.pts ELSE 0 END), 0), \
COALESCE(SUM({signed_pts}), 0), \
COALESCE(SUM(t.tokens), 0), \
COALESCE(SUM(t.tokens - t.cached_tokens - t.output_tokens), 0), \
COALESCE(SUM(t.cached_tokens), 0), \
Expand Down Expand Up @@ -411,11 +445,12 @@ pub async fn transactions_trend(
} else {
""
};
let signed_pts = signed_pts_expr("t");
let trend_sql = format!(
"SELECT strftime('{expr}', t.time{mods}) AS b, \
COALESCE(SUM(CASE WHEN t.type IN ('earn','topup','gift') THEN t.pts ELSE 0 END), 0), \
COALESCE(SUM(CASE WHEN t.type IN ('consume','expire','withdraw') THEN t.pts ELSE 0 END), 0), \
COALESCE(SUM(CASE WHEN t.type IN ('earn','topup','gift') THEN t.pts ELSE -t.pts END), 0), \
COALESCE(SUM(CASE WHEN t.type IN ({TX_INCOME_TYPES}) THEN t.pts ELSE 0 END), 0), \
COALESCE(SUM(CASE WHEN t.type IN ({TX_EXPENSE_TYPES}) THEN t.pts ELSE 0 END), 0), \
COALESCE(SUM({signed_pts}), 0), \
COALESCE(SUM(t.tokens), 0), \
COALESCE(SUM(t.tokens - t.cached_tokens - t.output_tokens), 0), \
COALESCE(SUM(t.cached_tokens), 0), \
Expand Down Expand Up @@ -486,12 +521,13 @@ pub async fn dashboard(
// 近 7 天净额序列（earn/topup/gift 为正、consume 为负；rant 2026-08-22T06:34:37：
// 原先只把 earn 当正数 → topup 充值被误算为负）
let mut stmt = conn
.prepare(
"SELECT date(time), COALESCE(SUM(CASE WHEN type IN ('earn','topup','gift') THEN pts ELSE -pts END), 0) \
.prepare(&format!(
"SELECT date(time), COALESCE(SUM({}), 0) \
FROM transactions \
WHERE user_id = ?1 AND date(time) >= date('now', '-6 days') \
GROUP BY date(time) ORDER BY date(time)",
)
signed_pts_expr("")
))
.map_err(internal)?;
let series = stmt
.query_map([auth.user_id], |r| {
Expand Down Expand Up @@ -953,12 +989,30 @@ mod tests {
let v: serde_json::Value = serde_json::from_str(&body).unwrap();
assert_eq!(v["total"], 1, "status 精确过滤: {body}");
assert_eq!(v["items"].as_array().unwrap()[0]["type"], "earn");
// pts 区间 [15, 25] → 1 条（20）
let (s, body) = get(st.clone(), "/api/transactions?pts_min=15&pts_max=25", &key).await;
// pts 区间：**按列渲染的有符号值**比较（C2054）——三条行的呈现值是
// consume -10.0 / consume -20.0 / earn +30.0，故区间 [-25,-15] → 1 条（-20.0）
let (s, body) = get(
st.clone(),
"/api/transactions?pts_min=-25&pts_max=-15",
&key,
)
.await;
assert_eq!(s, axum::http::StatusCode::OK, "body: {body}");
let v: serde_json::Value = serde_json::from_str(&body).unwrap();
assert_eq!(v["total"], 1, "pts 区间过滤: {body}");
assert_eq!(v["total"], 1, "pts 区间按渲染值过滤: {body}");
assert!((v["items"].as_array().unwrap()[0]["pts"].as_f64().unwrap() - 20.0).abs() < 1e-9);
// 阴性对照：库里存的正数 20.0 不再命中 [15,25]（修复前正是它命中）——
// 若此断言失败，说明筛选又退回了「比较库内原始 pts」
let (s, body) = get(st.clone(), "/api/transactions?pts_min=15&pts_max=25", &key).await;
assert_eq!(s, axum::http::StatusCode::OK, "body: {body}");
let v: serde_json::Value = serde_json::from_str(&body).unwrap();
assert_eq!(v["total"], 0, "库内正数不得再命中（渲染值是负数）: {body}");
// 阳性对照：收入行的渲染值 +30.0 仍落在 [+25,+35]（筛选没有把收入也一起翻掉）
let (s, body) = get(st.clone(), "/api/transactions?pts_min=25&pts_max=35", &key).await;
assert_eq!(s, axum::http::StatusCode::OK, "body: {body}");
let v: serde_json::Value = serde_json::from_str(&body).unwrap();
assert_eq!(v["total"], 1, "收入行按渲染值命中: {body}");
assert_eq!(v["items"].as_array().unwrap()[0]["type"], "earn");
// user_name LIKE（demo，全部 3 条命中）
let (s, body) = get(st.clone(), "/api/transactions?user_name=dem", &key).await;
assert_eq!(s, axum::http::StatusCode::OK, "body: {body}");
Expand Down Expand Up @@ -1002,6 +1056,74 @@ mod tests {
);
}

#[tokio::test]
async fn pts_range_filter_matches_the_rendered_signed_value() {
// C2054：交易页「点数」列**渲染**的是有符号值（income 正 / expense 负，`signedPts()`），
// 但区间筛选曾比较库内原始 `pts`（每个 writer 都存正数）⇒ 用户按表里看到的数字筛选
// （例如「点数 ≤ 0」想看支出）会得到 0 行。规格：**筛选命中的行 = 渲染值落在区间内的行**。
let st = test_state("ptsrange");
let key = login(st.clone()).await;
{
let conn = st.db.lock().unwrap();
// 与 billing.rs 存的完全一样：两行都存正数，方向在 type
conn.execute(
"INSERT INTO transactions (user_id, counterpart, key_id, model, tokens, pts, type, status) \
VALUES (1, '2', 1, 'm', 150, 3.7, 'consume', '成功')",
[],
)
.unwrap();
conn.execute(
"INSERT INTO transactions (user_id, counterpart, key_id, model, tokens, pts, type, status) \
VALUES (1, '3', 2, 'm', 150, 0.5, 'earn', '成功')",
[],
)
.unwrap();
}
// 渲染值：consume → -3.7、earn → +0.5
let cases: [(&str, usize, &str); 4] = [
// 「点数 ≤ 0」＝用户眼里所有支出行
("pts_max=0", 1, "consume"),
// 直接框住单元格里的 -3.7
("pts_min=-4&pts_max=-3", 1, "consume"),
// 没有单元格落在这个区间（-3.7/+0.5 都不在）——修复前返回那条存了 3.7 的消费行
("pts_min=3&pts_max=4", 0, ""),
// 阳性对照：收入行的渲染值 +0.5 仍被命中（证明筛选不是把一切都翻成负数）
("pts_min=0&pts_max=1", 1, "earn"),
];
for (qs, want_total, want_type) in cases {
let (s, body) = get(st.clone(), &format!("/api/transactions?{qs}"), &key).await;
assert_eq!(s, axum::http::StatusCode::OK, "q={qs} body: {body}");
let v: serde_json::Value = serde_json::from_str(&body).unwrap();
assert_eq!(v["total"], want_total, "q={qs} 按渲染值命中数: {body}");
if want_total > 0 {
assert_eq!(
v["items"].as_array().unwrap()[0]["type"],
want_type,
"q={qs}: {body}"
);
}
}
// trend 与列表同口径（同一 where 片段）：pts_max=0 只留消费腿 → expense=3.7、income=0
let (s, body) = get(
st.clone(),
"/api/transactions/trend?bucket=day&pts_max=0",
&key,
)
.await;
assert_eq!(s, axum::http::StatusCode::OK, "body: {body}");
let v: serde_json::Value = serde_json::from_str(&body).unwrap();
let buckets = v["buckets"].as_array().unwrap();
assert_eq!(buckets.len(), 1, "trend 同口径: {body}");
assert!(
(buckets[0]["expense"].as_f64().unwrap() - 3.7).abs() < 1e-9,
"{body}"
);
assert!(
(buckets[0]["income"].as_f64().unwrap()).abs() < 1e-9,
"{body}"
);
}

#[tokio::test]
async fn transactions_trend_buckets() {
// rant 2026-08-23T16:01:07：/api/transactions/trend 按时间桶聚合趋势
Expand Down
2 changes: 1 addition & 1 deletion ui/index.html
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Original file line number Diff line number Diff line change
Expand Up @@ -845,6 +845,6 @@ <h3 id="chat-title">使用模型</h3>
<script src="js/api.js?v=20260912-5"></script>
<script src="js/data.js?v=20260912-5"></script>
<script src="js/i18n.js?v=20260912-5"></script>
<script src="js/app.js?v=20260913-1"></script>
<script src="js/app.js?v=20260913-2"></script>
</body>
</html>
16 changes: 13 additions & 3 deletions ui/js/app.js
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1342,7 +1342,12 @@
render: (t) => {
const v = signedPts(t.type, t.pts);
return '<span style="color:' + (v > 0 ? "var(--ok)" : v < 0 ? "var(--danger)" : "var(--text)") + ';font-weight:600">' + (v > 0 ? "+" : "") + D.fmt(v) + "</span>";
} },
},
// C2054：筛选/排序必须与**渲染值**同口径 —— 用户是按单元格里看到的数字筛选与排序的。
// 少了这两行，`filterRows`/排序会退回 `row.pts`（库内正数）⇒ 按 -3.7 筛选得 0 行、
// 按 3 到 4 反而命中那条「-3.7」的行。
filterVal: (t) => signedPts(t.type, t.pts),
sortVal: (t) => signedPts(t.type, t.pts) },
{ key: "status", title: () => T("tx.col.status"), sort: "string", filter: "select",
// C2031：同 type —— value 是库内值（成功/入账/处理中，语言无关），label 随语言变
options: () => ["成功", "入账", "处理中"].map((s) => ({ value: s, label: txStatus(s) })),
Expand Down Expand Up @@ -1631,7 +1636,9 @@
if (!list.length) { toast(T("tx.export.none"), "info"); return; }
const cell = (v) => { const s = String(v == null ? "" : v); return /[",\n]/.test(s) ? '"' + s.replace(/"/g, '""') + '"' : s; };
const headers = [T("tx.col.time"), T("tx.col.type"), T("tx.col.user"), T("tx.col.model"), T("tx.col.apiKeyName"), T("tx.col.input"), T("tx.col.cached"), T("tx.col.output"), T("tx.col.tokens"), T("tx.col.pts"), T("tx.col.status")];
const lines = list.map((t) => [t.time, txType(t.type), t.user, t.model, t.key, t.inputTokens, t.cachedTokens, t.outputTokens, t.tokens, t.pts, txStatus(t.status)].map(cell).join(","));
// C2054：导出的是「当前筛选可见行」，故「点数」列与表格单元格同口径（有符号：收入正/支出负），
// 否则屏幕上写着 -3.7、导出的文件里却是 3.7。
const lines = list.map((t) => [t.time, txType(t.type), t.user, t.model, t.key, t.inputTokens, t.cachedTokens, t.outputTokens, t.tokens, signedPts(t.type, t.pts), txStatus(t.status)].map(cell).join(","));
const csv = "\uFEFF" + [headers.join(","), ...lines].join("\r\n"); // UTF-8 BOM，Excel 中文不乱码
const blob = new Blob([csv], { type: "text/csv;charset=utf-8" });
const url = URL.createObjectURL(blob);
Expand Down Expand Up @@ -1800,7 +1807,10 @@
data = data.slice().sort((a, b) => {
for (const sk of state.sort) {
const col = columns.find((c) => c.key === sk.key);
const av = a[sk.key], bv = b[sk.key];
// C2054：列的**渲染值**可能与行里存的原始值不同（如 pts 的有符号值）——
// 列可用 `sortVal` 声明「排序按哪个值」，缺省仍是 row[key]（其余 6 张表行为不变）。
const av = col && col.sortVal ? col.sortVal(a) : a[sk.key];
const bv = col && col.sortVal ? col.sortVal(b) : b[sk.key];
let cmp;
if (col && col.sort === "number") cmp = Number(av) - Number(bv);
else cmp = String(av).localeCompare(String(bv), "zh-CN");
Expand Down
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