Version: 0.9.77.dev.260505
后端:
1.阶段 6 CP4/CP5 目录收口与共享边界纯化
- 将 backend 根目录收口为 services、client、gateway、cmd、shared 五个一级目录
- 收拢 bootstrap、inits、infra/kafka、infra/outbox、conv、respond、pkg、middleware,移除根目录旧实现与空目录
- 将 utils 下沉到 services/userauth/internal/auth,将 logic 下沉到 services/schedule/core/planning
- 将迁移期 runtime 桥接实现统一收拢到 services/runtime/{conv,dao,eventsvc,model},删除 shared/legacy 与未再被 import 的旧 service 实现
- 将 gateway/shared/respond 收口为 HTTP/Gin 错误写回适配,shared/respond 仅保留共享错误语义与状态映射
- 将 HTTP IdempotencyMiddleware 与 RateLimitMiddleware 收口到 gateway/middleware
- 将 GormCachePlugin 下沉到 shared/infra/gormcache,将共享 RateLimiter 下沉到 shared/infra/ratelimit,将 agent token budget 下沉到 services/agent/shared
- 删除 InitEino 兼容壳,收缩 cmd/internal/coreinit 仅保留旧组合壳残留域初始化语义
- 更新微服务迁移计划与桌面 checklist,补齐 CP4/CP5 当前切流点、目录终态与验证结果
- 完成 go test ./...、git diff --check 与最终真实 smoke;health、register/login、task/create+get、schedule/today、task-class/list、memory/items、agent chat/meta/timeline/context-stats 全部 200,SSE 合并结果为 CP5_OK 且 [DONE] 只有 1 个
This commit is contained in:
@@ -8,8 +8,8 @@ import (
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"strconv"
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"strings"
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"github.com/LoveLosita/smartflow/backend/conv"
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"github.com/LoveLosita/smartflow/backend/model"
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"github.com/LoveLosita/smartflow/backend/services/runtime/conv"
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"github.com/LoveLosita/smartflow/backend/services/runtime/model"
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"gorm.io/gorm"
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"gorm.io/gorm/clause"
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)
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823
backend/services/schedule/core/planning/smart_planning.go
Normal file
823
backend/services/schedule/core/planning/smart_planning.go
Normal file
@@ -0,0 +1,823 @@
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package planning
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import (
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"fmt"
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"github.com/LoveLosita/smartflow/backend/services/runtime/conv"
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"github.com/LoveLosita/smartflow/backend/services/runtime/model"
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"github.com/LoveLosita/smartflow/backend/shared/respond"
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)
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type slotStatus int
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const (
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Free slotStatus = iota // 0: 纯空闲
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Occupied // 1: 已有课/任务,不可动
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Blocked // 2: 用户屏蔽时段
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Filler // 3: 水课,允许嵌入
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)
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type slotNode struct {
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Status slotStatus
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EventID uint // 🚀 关键:记录课程 ID,用于识别水课边界
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}
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type grid struct {
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data map[int]map[int][13]slotNode
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startWeek int
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startDay int
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endWeek int
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endDay int
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}
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// getNode 和 setNode 是对 grid 数据结构的封装,确保我们在访问时能正确处理默认值(Free)和边界情况
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func (g *grid) getNode(w, d, s int) slotNode {
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if dayMap, ok := g.data[w]; ok {
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return dayMap[d][s]
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}
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return slotNode{Status: Free, EventID: 0}
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}
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func (g *grid) setNode(w, d, s int, node slotNode) {
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if _, ok := g.data[w]; !ok {
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g.data[w] = make(map[int][13]slotNode)
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}
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dayData := g.data[w][d]
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dayData[s] = node
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g.data[w][d] = dayData
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}
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// 检查是否可用 (Free 或 Filler 且不在 Blocked 时段内)
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func (g *grid) isAvailable(w, d, s int) bool {
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node := g.getNode(w, d, s)
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return node.Status == Free || node.Status == Filler
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}
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// countAvailableSlots 统计指定周次范围内所有可用的原子节次总数
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func (g *grid) countAvailableSlots(currW, currD, currS int) int {
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count := 0
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if currW == 0 && currD == 0 && currS == 0 {
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currW, currD, currS = g.startWeek, g.startDay, 1
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}
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for w := currW; w <= g.endWeek; w++ {
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dayMap, hasData := g.data[w]
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for d := 1; d <= 7; d++ {
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// 🚀 头部裁剪:过滤开始日期前的天数
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if w == currW && d < currD {
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continue
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}
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// 🚀 尾部裁剪:过滤结束日期后的天数
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if w == g.endWeek && d > g.endDay {
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break
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}
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var dayData [13]slotNode
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if hasData {
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dayData = dayMap[d]
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}
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for s := 1; s <= 12; s++ {
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if w == currW && d == currD && s < currS {
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continue
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}
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if dayData[s].Status == Free || dayData[s].Status == Filler {
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count++
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}
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}
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}
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}
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return count
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}
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// FindNextAvailable 从当前时间点开始,按周、天、节次顺序查找下一个可用格子
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func (g *grid) FindNextAvailable(currW, currD, currS int) (int, int, int) {
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// 基础越界检查
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if currW > g.endWeek || (currW == g.endWeek && currD > g.endDay) {
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return -1, -1, -1
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}
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for w := currW; w <= g.endWeek; w++ {
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dayMap, hasData := g.data[w]
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for d := 1; d <= 7; d++ {
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if w == currW && d < currD {
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continue
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}
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if w == g.endWeek && d > g.endDay {
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break
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} // 🚀 守住结束天
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var dayData [13]slotNode
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if hasData {
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dayData = dayMap[d]
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}
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for s := 1; s <= 12; s++ {
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if w == currW && d == currD && s < currS {
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continue
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}
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if dayData[s].Status == Free || dayData[s].Status == Filler {
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return w, d, s
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}
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}
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}
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}
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return -1, -1, -1
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}
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// 辅助函数:向后跳过指定数量的可用坑位
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func (g *grid) skipAvailableSlots(w, d, s, skipCount int) (int, int, int) {
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if skipCount <= 0 {
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// 即使 gap 为 0,也要至少移到下一节
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s++
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if s > 12 {
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s = 1
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d++
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if d > 7 {
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d = 1
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w++
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}
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}
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return w, d, s
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}
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found := 0
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currW, currD, currS := w, d, s+1
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for currW <= g.endWeek {
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if currS > 12 {
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currS = 1
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currD++
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if currD > 7 {
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currD = 1
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currW++
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}
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continue
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}
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// 如果已经跳到了最后一天,不要再跳了,直接返回终点坐标
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if currW == g.endWeek && currD > g.endDay {
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return g.endWeek, g.endDay, 12
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}
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if g.isAvailable(currW, currD, currS) {
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found++
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if found > skipCount {
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return currW, currD, currS
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}
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}
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currS++
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}
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return currW, currD, currS
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}
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func SmartPlanningMainLogic(schedules []model.Schedule, taskClass *model.TaskClass) ([]model.UserWeekSchedule, error) {
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//1.先构建时间格子
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g := buildTimeGrid(schedules, taskClass)
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//2.根据时间格子和排课策略计算每个任务块的具体安排时间
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allocatedItems, err := computeAllocation(g, taskClass.Items, *taskClass.Strategy)
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if err != nil {
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return nil, err
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}
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// 3. 把这些时间通过 DTO 函数回填到涉及周的 UserWeekSchedule 结构中,供前端展示。
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return conv.PlanningResultToUserWeekSchedules(schedules, allocatedItems), nil
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}
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// SmartPlanningRawItems 执行粗排算法并直接返回已分配的任务项列表。
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//
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// 与 SmartPlanningMainLogic 共享完全相同的构建网格和分配逻辑,
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// 但不做展示格式转换,直接返回 allocatedItems(每项的 EmbeddedTime 已回填)。
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// 供 Agent 排程链路使用,避免从展示结构反向解析导致信息丢失。
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func SmartPlanningRawItems(schedules []model.Schedule, taskClass *model.TaskClass) ([]model.TaskClassItem, error) {
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g := buildTimeGrid(schedules, taskClass)
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return computeAllocation(g, taskClass.Items, *taskClass.Strategy)
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}
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// SmartPlanningRawItemsMulti 执行“多任务类共享资源池”粗排。
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//
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// 职责边界:
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// 1. 复用现有 SmartPlanningRawItems 的单任务类分配能力,不重写核心算法;
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// 2. 通过“增量占位”把前一个任务类的建议结果写入共享工作日程,供后续任务类避让;
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// 3. 返回聚合后的 allocatedItems(每项 EmbeddedTime 已回填);
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// 4. 不负责展示结构转换(由 service/conv 层处理)。
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func SmartPlanningRawItemsMulti(schedules []model.Schedule, taskClasses []*model.TaskClass) ([]model.TaskClassItem, error) {
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if len(taskClasses) == 0 {
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return []model.TaskClassItem{}, nil
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}
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// 1. 构建“工作副本”:
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// 1.1 原始 schedules 不直接修改,避免污染调用方数据;
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// 1.2 后续每完成一个任务类分配,就把结果增量写入 workingSchedules。
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workingSchedules := cloneSchedulesForPlanning(schedules)
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allAllocated := make([]model.TaskClassItem, 0)
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// 2. syntheticEventID 用于给“虚拟占位任务”分配唯一 EventID。
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// 2.1 采用负数区间,避免和数据库自增正数 EventID 冲突;
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// 2.2 每个任务块占用一个 synthetic event,跨节次共享同一 eventID。
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nextSyntheticEventID := -1
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for _, taskClass := range taskClasses {
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if taskClass == nil {
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continue
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}
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if taskClass.Strategy == nil {
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return nil, fmt.Errorf("task_class_id=%d 缺少 strategy 配置", taskClass.ID)
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}
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// 3. 复用单任务类粗排。
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allocatedItems, err := SmartPlanningRawItems(workingSchedules, taskClass)
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if err != nil {
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// 3.1 明确标注失败任务类,便于上层快速定位。
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return nil, fmt.Errorf("task_class_id=%d 粗排失败: %w", taskClass.ID, err)
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}
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allAllocated = append(allAllocated, allocatedItems...)
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// 4. 把本任务类分配结果转成“虚拟 Schedule 占位”追加回工作副本。
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// 4.1 目的:让后续任务类把这些已分配任务当成 Occupied,避免重叠;
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// 4.2 若某任务块没有 EmbeddedTime,直接跳过,不阻断后续。
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virtualSchedules, nextID := buildVirtualSchedulesFromAllocated(allocatedItems, taskClass, nextSyntheticEventID)
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nextSyntheticEventID = nextID
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if len(virtualSchedules) > 0 {
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workingSchedules = append(workingSchedules, virtualSchedules...)
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}
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}
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return allAllocated, nil
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}
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// cloneSchedulesForPlanning 深拷贝 schedules,确保后续在算法中安全修改。
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//
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// 说明:
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// 1. 主要拷贝 Schedule 结构体本身;
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// 2. Event 指针做浅字段复制,避免共享同一 Event 指针导致意外改写;
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// 3. EmbeddedTask 在粗排阶段不参与状态写入,保留原值即可。
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func cloneSchedulesForPlanning(src []model.Schedule) []model.Schedule {
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if len(src) == 0 {
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return []model.Schedule{}
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}
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dst := make([]model.Schedule, len(src))
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for i := range src {
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dst[i] = src[i]
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if src[i].Event != nil {
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eventCopy := *src[i].Event
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dst[i].Event = &eventCopy
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}
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}
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return dst
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}
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// buildVirtualSchedulesFromAllocated 将已分配任务块转成“虚拟占位 schedules”。
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//
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// 设计目的:
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// 1. 让后续任务类在共享资源池里自动避让已分配任务;
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// 2. 不落库,仅用于内存中的粗排冲突控制;
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// 3. 通过 Type=task + CanBeEmbedded=false 强制标记为不可再嵌入。
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func buildVirtualSchedulesFromAllocated(allocatedItems []model.TaskClassItem, taskClass *model.TaskClass, eventIDStart int) ([]model.Schedule, int) {
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if len(allocatedItems) == 0 {
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return []model.Schedule{}, eventIDStart
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}
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userID := 0
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if taskClass != nil && taskClass.UserID != nil {
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userID = *taskClass.UserID
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}
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virtual := make([]model.Schedule, 0)
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nextEventID := eventIDStart
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for _, item := range allocatedItems {
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if item.EmbeddedTime == nil {
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continue
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}
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taskName := "未命名任务"
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if item.Content != nil && *item.Content != "" {
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taskName = *item.Content
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}
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location := ""
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event := &model.ScheduleEvent{
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ID: nextEventID,
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UserID: userID,
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Name: taskName,
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Location: &location,
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Type: "task",
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CanBeEmbedded: false,
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}
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for section := item.EmbeddedTime.SectionFrom; section <= item.EmbeddedTime.SectionTo; section++ {
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virtual = append(virtual, model.Schedule{
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EventID: nextEventID,
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UserID: userID,
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Week: item.EmbeddedTime.Week,
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DayOfWeek: item.EmbeddedTime.DayOfWeek,
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Section: section,
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Event: event,
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Status: "normal",
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})
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}
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nextEventID--
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}
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return virtual, nextEventID
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}
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// buildTimeGrid 构建一个时间格子,标记出哪些时间段被占用、哪些被屏蔽、哪些是水课
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func buildTimeGrid(schedules []model.Schedule, taskClass *model.TaskClass) *grid {
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// 🚀 核心修正:获取精确的起始坐标
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startW, startD, _ := conv.RealDateToRelativeDate(taskClass.StartDate.Format(conv.DateFormat))
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endW, endD, _ := conv.RealDateToRelativeDate(taskClass.EndDate.Format(conv.DateFormat))
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// 将信息初始化到 grid 结构中
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g := &grid{
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data: make(map[int]map[int][13]slotNode),
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startWeek: startW,
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startDay: startD,
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endWeek: endW,
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endDay: endD,
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}
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//标记屏蔽时段 (Blocked)
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for _, blockIdx := range taskClass.ExcludedSlots {
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sFrom, sTo := (blockIdx-1)*2+1, blockIdx*2
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for w := startW; w <= endW; w++ {
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for d := 1; d <= 7; d++ { //🚀 注意:这里的屏蔽是针对每天的,所以直接循环 1-7 天
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for s := sFrom; s <= sTo; s++ {
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g.setNode(w, d, s, slotNode{Status: Blocked})
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}
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}
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}
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}
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// 标记整天屏蔽:
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// 1. excluded_days_of_week 表示“这些星期几整天都不允许粗排”;
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// 2. 与 excluded_slots 一样属于硬约束,因此直接写入 Blocked;
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// 3. 一旦工作日容量不足,粗排应直接失败,而不是偷偷排到被排除的星期里。
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for _, blockedDay := range taskClass.ExcludedDaysOfWeek {
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for w := startW; w <= endW; w++ {
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for s := 1; s <= 12; s++ {
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g.setNode(w, blockedDay, s, slotNode{Status: Blocked})
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}
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}
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}
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// 映射日程 (尊重 Blocked 且只处理范围内的数据)
|
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for _, s := range schedules {
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if s.Week >= startW && s.Week <= endW {
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if g.getNode(s.Week, s.DayOfWeek, s.Section).Status == Blocked {
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continue
|
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}
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status := Occupied
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// 只有当课程允许嵌入且当前事件支持嵌入时,才标记为 Filler
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if *taskClass.AllowFillerCourse && s.Event.CanBeEmbedded {
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status = Filler
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}
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g.setNode(s.Week, s.DayOfWeek, s.Section, slotNode{Status: status, EventID: uint(s.EventID)})
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}
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}
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return g
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}
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|
||||
// computeAllocation 是核心函数,负责根据当前的时间格子状态和排课策略,计算出每个任务块的具体安排时间
|
||||
/*func computeAllocation(g *grid, items []model.TaskClassItem, strategy string) ([]model.TaskClassItem, error) {
|
||||
if len(items) == 0 {
|
||||
return items, nil
|
||||
}
|
||||
|
||||
// 🚀 核心修正 1:获取真正的开始坐标(周、天、节)
|
||||
// 这里假设你已经通过 conv 把 StartDate 换成了 w1, d1, s1
|
||||
startW := g.startWeek
|
||||
startD := g.startDay // 建议从 conv 传入具体的 DayOfWeek
|
||||
startS := 1
|
||||
|
||||
// 1. 获取可用资源总量
|
||||
totalAvailable := g.countAvailableSlots(0, 0, 0)
|
||||
// 假设每个任务块至少占用 2 个原子槽位
|
||||
totalRequired := len(items) * 2
|
||||
|
||||
// 🚀 核心改进:容量预判
|
||||
if totalAvailable < totalRequired {
|
||||
// 如果连最基本的坑位都不够,直接报错,不进行任何编排
|
||||
return nil, respond.TimeNotEnoughForAutoScheduling
|
||||
}
|
||||
|
||||
// 🚀 核心修正 2:步长改为“逻辑间隔”,不再是物理跳跃
|
||||
// gap 表示:每两个任务之间,我们要故意空出多少个“可用位”
|
||||
gap := 0
|
||||
if strategy == "steady" && totalAvailable > totalRequired {
|
||||
gap = (totalAvailable - totalRequired) / (len(items) + 1)
|
||||
}
|
||||
|
||||
currW, currD, currS := startW, startD, startS
|
||||
lastPlacedIndex := -1
|
||||
for i := range items {
|
||||
w, d, s := g.FindNextAvailable(currW, currD, currS)
|
||||
if w == -1 || w > g.endWeek {
|
||||
break
|
||||
}
|
||||
|
||||
node := g.getNode(w, d, s)
|
||||
slotLen := 2
|
||||
if node.Status == Filler {
|
||||
slotLen = 1
|
||||
currID := node.EventID
|
||||
for checkS := s + 1; checkS <= 12; checkS++ {
|
||||
if next := g.getNode(w, d, checkS); next.Status == Filler && next.EventID == currID {
|
||||
slotLen++
|
||||
} else {
|
||||
break
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
endS := s + slotLen - 1
|
||||
items[i].EmbeddedTime = &model.TargetTime{
|
||||
SectionFrom: s, SectionTo: endS,
|
||||
Week: w, DayOfWeek: d,
|
||||
}
|
||||
|
||||
for sec := s; sec <= endS; sec++ {
|
||||
g.setNode(w, d, sec, slotNode{Status: Occupied})
|
||||
}
|
||||
|
||||
// 🚀 核心修正 3:基于“可用位”推进指针,而非物理索引
|
||||
// 我们要在 grid 中向后数出 gap 个可用位置,作为下一个任务的起点
|
||||
currW, currD, currS = g.skipAvailableSlots(w, d, endS, gap)
|
||||
|
||||
lastPlacedIndex = i // 记录最后一个成功安放的任务索引
|
||||
}
|
||||
// 🚀 核心改进:结果完整性校验
|
||||
if lastPlacedIndex < len(items)-1 {
|
||||
return nil, fmt.Errorf("排程中断:由于时间片碎片化,仅成功安排了 %d/%d 个任务块,请尝试扩充时间范围或删减屏蔽位", lastPlacedIndex+1, len(items))
|
||||
return nil, respond.TimeNotEnoughForAutoScheduling
|
||||
}
|
||||
|
||||
return items, nil
|
||||
}*/
|
||||
|
||||
type slotCoord struct {
|
||||
w, d, s int
|
||||
}
|
||||
|
||||
// planningSlotCandidate 表示一次“可落位任务块”的候选结果。
|
||||
//
|
||||
// 职责边界:
|
||||
// 1. 负责把“游标位置”映射成真正可落地的周/天/节次区间;
|
||||
// 2. 不负责写入 grid,占位仍由 computeAllocation 统一执行;
|
||||
// 3. 通过 coordIndex 告诉上层“本次是从哪个逻辑切片位置开始命中的”,便于继续推进游标。
|
||||
type planningSlotCandidate struct {
|
||||
coordIndex int
|
||||
week int
|
||||
dayOfWeek int
|
||||
sectionFrom int
|
||||
sectionTo int
|
||||
}
|
||||
|
||||
// countDayAvailable 统计某一天当前还可用于粗排的节次数。
|
||||
//
|
||||
// 职责边界:
|
||||
// 1. 只把 Free/Filler 视为“仍可消费”的资源;
|
||||
// 2. 不区分其来源是纯空位还是可嵌入课程,因为对粗排而言二者都代表后续还能放任务;
|
||||
// 3. 仅用于候选打分,不直接参与最终合法性判断。
|
||||
func (g *grid) countDayAvailable(week, day int) int {
|
||||
if g == nil {
|
||||
return 0
|
||||
}
|
||||
count := 0
|
||||
for section := 1; section <= 12; section++ {
|
||||
node := g.getNode(week, day, section)
|
||||
if node.Status == Free || node.Status == Filler {
|
||||
count++
|
||||
}
|
||||
}
|
||||
return count
|
||||
}
|
||||
|
||||
// countDayOccupied 统计某一天当前已被 existing/virtual/task 占住的节次数。
|
||||
func (g *grid) countDayOccupied(week, day int) int {
|
||||
if g == nil {
|
||||
return 0
|
||||
}
|
||||
count := 0
|
||||
for section := 1; section <= 12; section++ {
|
||||
if g.getNode(week, day, section).Status == Occupied {
|
||||
count++
|
||||
}
|
||||
}
|
||||
return count
|
||||
}
|
||||
|
||||
// collectPlanningCandidatesFromCursor 收集从给定游标开始仍然合法的候选落位。
|
||||
//
|
||||
// 设计说明:
|
||||
// 1. 这里复用现有 findNextCandidateFromCursor 的合法性规则,避免复制一套“什么叫合法双节”的判断;
|
||||
// 2. 通过跳过已命中候选的跨度,减少同一课程块被重复返回;
|
||||
// 3. 保留快照上的 coordIndex,供 steady 策略计算“距离目标位置有多远”。
|
||||
func (g *grid) collectPlanningCandidatesFromCursor(coords []slotCoord, startCursor int) []planningSlotCandidate {
|
||||
if g == nil || startCursor >= len(coords) {
|
||||
return nil
|
||||
}
|
||||
candidates := make([]planningSlotCandidate, 0, 16)
|
||||
seen := make(map[string]struct{})
|
||||
for cursor := startCursor; cursor < len(coords); {
|
||||
candidate, found := g.findNextCandidateFromCursor(coords, cursor)
|
||||
if !found {
|
||||
break
|
||||
}
|
||||
key := fmt.Sprintf("%d-%d-%d-%d", candidate.week, candidate.dayOfWeek, candidate.sectionFrom, candidate.sectionTo)
|
||||
if _, exists := seen[key]; !exists {
|
||||
seen[key] = struct{}{}
|
||||
candidates = append(candidates, candidate)
|
||||
}
|
||||
nextCursor := candidate.coordIndex + (candidate.sectionTo - candidate.sectionFrom + 1)
|
||||
if nextCursor <= cursor {
|
||||
nextCursor = cursor + 1
|
||||
}
|
||||
cursor = nextCursor
|
||||
}
|
||||
return candidates
|
||||
}
|
||||
|
||||
func computeSteadyTargetCursor(totalAvailable, totalItems, itemIndex int) int {
|
||||
if totalAvailable <= 1 || totalItems <= 1 {
|
||||
return 0
|
||||
}
|
||||
target := ((itemIndex + 1) * totalAvailable) / (totalItems + 1)
|
||||
if target < 0 {
|
||||
return 0
|
||||
}
|
||||
if target >= totalAvailable {
|
||||
return totalAvailable - 1
|
||||
}
|
||||
return target
|
||||
}
|
||||
|
||||
func planningDayOrdinal(week, day int) int {
|
||||
return week*7 + day
|
||||
}
|
||||
|
||||
func absInt(value int) int {
|
||||
if value < 0 {
|
||||
return -value
|
||||
}
|
||||
return value
|
||||
}
|
||||
|
||||
// chooseSteadyCandidate 为 steady 策略挑选“更均衡、更分散、更留余地”的候选位。
|
||||
//
|
||||
// 评分原则:
|
||||
// 1. 先尽量接近本任务在窗口中的目标分布位置;
|
||||
// 2. 再偏好当前已占用更少的天,避免单日继续堆高;
|
||||
// 3. 再惩罚与同任务类既有落位过近或同日重复,降低同科过度集中;
|
||||
// 4. 最后惩罚吃掉当天最后一小段缓冲,给后续调整保留容错空间。
|
||||
func (g *grid) chooseSteadyCandidate(
|
||||
coords []slotCoord,
|
||||
targetCursor int,
|
||||
placedDayOrdinals []int,
|
||||
) (planningSlotCandidate, bool) {
|
||||
candidates := g.collectPlanningCandidatesFromCursor(coords, 0)
|
||||
if len(candidates) == 0 {
|
||||
return planningSlotCandidate{}, false
|
||||
}
|
||||
|
||||
best := candidates[0]
|
||||
bestScore := int(^uint(0) >> 1)
|
||||
for _, candidate := range candidates {
|
||||
slotSpan := candidate.sectionTo - candidate.sectionFrom + 1
|
||||
distancePenalty := absInt(candidate.coordIndex-targetCursor) * 10
|
||||
dayOccupiedPenalty := g.countDayOccupied(candidate.week, candidate.dayOfWeek) * 25
|
||||
remainingAvailable := g.countDayAvailable(candidate.week, candidate.dayOfWeek) - slotSpan
|
||||
bufferPenalty := 0
|
||||
if remainingAvailable < 2 {
|
||||
bufferPenalty = 80
|
||||
}
|
||||
|
||||
dayOrdinal := planningDayOrdinal(candidate.week, candidate.dayOfWeek)
|
||||
rhythmPenalty := 0
|
||||
for _, placed := range placedDayOrdinals {
|
||||
diff := absInt(dayOrdinal - placed)
|
||||
switch {
|
||||
case diff == 0:
|
||||
rhythmPenalty += 180
|
||||
case diff == 1:
|
||||
rhythmPenalty += 60
|
||||
}
|
||||
}
|
||||
|
||||
score := distancePenalty + dayOccupiedPenalty + bufferPenalty + rhythmPenalty + candidate.coordIndex
|
||||
if score < bestScore {
|
||||
bestScore = score
|
||||
best = candidate
|
||||
}
|
||||
}
|
||||
return best, true
|
||||
}
|
||||
|
||||
// getAllAvailable 获取窗口内所有可用的原子节次坐标(逻辑一维化)。
|
||||
//
|
||||
// 设计说明:
|
||||
// 1. 这里返回的是“快照坐标”,后续任务落位后,快照中的部分坐标可能失效;
|
||||
// 2. 因此 computeAllocation 在真正落位前会再次检查 grid 当前状态,避免覆盖占位。
|
||||
func (g *grid) getAllAvailable() []slotCoord {
|
||||
var coords []slotCoord
|
||||
for w := g.startWeek; w <= g.endWeek; w++ {
|
||||
dayMap, hasData := g.data[w]
|
||||
for d := 1; d <= 7; d++ {
|
||||
// 1. 头尾边界裁剪:只遍历任务类有效日期窗口。
|
||||
if w == g.startWeek && d < g.startDay {
|
||||
continue
|
||||
}
|
||||
if w == g.endWeek && d > g.endDay {
|
||||
break
|
||||
}
|
||||
|
||||
var dayData [13]slotNode
|
||||
if hasData {
|
||||
dayData = dayMap[d]
|
||||
}
|
||||
|
||||
// 2. 仅记录可用格子(Free/Filler)。
|
||||
for s := 1; s <= 12; s++ {
|
||||
if dayData[s].Status == Free || dayData[s].Status == Filler {
|
||||
coords = append(coords, slotCoord{w: w, d: d, s: s})
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
return coords
|
||||
}
|
||||
|
||||
// findNextCandidateFromCursor 从当前 cursor 起向后寻找“可真正落位”的候选块。
|
||||
//
|
||||
// 职责边界:
|
||||
// 1. 负责“挑选起点”:从逻辑切片 coords 中向后扫描,直到命中可放置位置;
|
||||
// 2. 不负责“真正占位”:这里只做判断,不修改 grid 状态;
|
||||
// 3. 输入输出语义:
|
||||
// - startCursor:当前逻辑游标(已包含 steady 策略的间隔效果);
|
||||
// - found=false:表示从该游标到窗口末尾都无法再放置任务块。
|
||||
//
|
||||
// 关键约束:
|
||||
// 1. 普通空位(Free)必须满足“连续 2 节都可用”才允许落位;
|
||||
// 2. 可嵌入课程(Filler)沿用“整块嵌入”语义:命中课程任意节次,都回溯到课程块起点并整块占用;
|
||||
// 3. 若某个坐标在前序迭代中已占用(coords 为快照可能过期),直接跳过继续扫描。
|
||||
func (g *grid) findNextCandidateFromCursor(coords []slotCoord, startCursor int) (candidate planningSlotCandidate, found bool) {
|
||||
for idx := startCursor; idx < len(coords); idx++ {
|
||||
loc := coords[idx]
|
||||
node := g.getNode(loc.w, loc.d, loc.s)
|
||||
|
||||
// 1. 快照过期校验:
|
||||
// 1.1 前序任务落位后,该坐标可能已变成 Occupied;
|
||||
// 1.2 若不二次校验,会出现覆盖已占位节次的风险。
|
||||
if node.Status != Free && node.Status != Filler {
|
||||
continue
|
||||
}
|
||||
|
||||
// 2. Filler 处理:
|
||||
// 2.1 先识别课程块边界;
|
||||
// 2.2 再在课程块内部寻找“奇数起点的双节对齐位”(1-2/3-4/...);
|
||||
// 2.3 找不到合法双节位则跳过该课程块,不允许退化成单节或偶数起点跨对齐块。
|
||||
if node.Status == Filler {
|
||||
blockFrom := loc.s
|
||||
currID := node.EventID
|
||||
|
||||
// 2.1 向左回溯到同一 EventID 的起点。
|
||||
for checkS := loc.s - 1; checkS >= 1; checkS-- {
|
||||
prev := g.getNode(loc.w, loc.d, checkS)
|
||||
if prev.Status == Filler && prev.EventID == currID {
|
||||
blockFrom = checkS
|
||||
continue
|
||||
}
|
||||
break
|
||||
}
|
||||
|
||||
// 2.2 向右扩展到同一 EventID 的终点。
|
||||
blockTo := blockFrom
|
||||
for checkS := blockFrom + 1; checkS <= 12; checkS++ {
|
||||
next := g.getNode(loc.w, loc.d, checkS)
|
||||
if next.Status == Filler && next.EventID == currID {
|
||||
blockTo = checkS
|
||||
continue
|
||||
}
|
||||
break
|
||||
}
|
||||
|
||||
// 2.3 在课程块中按“双节对齐位”查找合法起点(必须为奇数节)。
|
||||
pairFrom := blockFrom
|
||||
if pairFrom%2 == 0 {
|
||||
pairFrom++
|
||||
}
|
||||
for ; pairFrom+1 <= blockTo; pairFrom += 2 {
|
||||
// 虽然理论上 Filler 都可用,这里仍做显式校验,防止后续规则扩展导致误判。
|
||||
if g.isAvailable(loc.w, loc.d, pairFrom) && g.isAvailable(loc.w, loc.d, pairFrom+1) {
|
||||
return planningSlotCandidate{
|
||||
coordIndex: idx,
|
||||
week: loc.w,
|
||||
dayOfWeek: loc.d,
|
||||
sectionFrom: pairFrom,
|
||||
sectionTo: pairFrom + 1,
|
||||
}, true
|
||||
}
|
||||
}
|
||||
continue
|
||||
}
|
||||
|
||||
// 3. Free 处理:必须严格满足“奇数起点双节对齐位”。
|
||||
// 3.1 起点必须是奇数节(1/3/5/7/9/11);
|
||||
// 3.2 且后一节可用;不允许偶数起点(如 8-9)跨对齐块。
|
||||
if loc.s%2 == 0 {
|
||||
continue
|
||||
}
|
||||
if loc.s >= 12 || !g.isAvailable(loc.w, loc.d, loc.s+1) {
|
||||
continue
|
||||
}
|
||||
|
||||
return planningSlotCandidate{
|
||||
coordIndex: idx,
|
||||
week: loc.w,
|
||||
dayOfWeek: loc.d,
|
||||
sectionFrom: loc.s,
|
||||
sectionTo: loc.s + 1,
|
||||
}, true
|
||||
}
|
||||
|
||||
return planningSlotCandidate{}, false
|
||||
}
|
||||
|
||||
// computeAllocation 根据当前时间格与策略,为每个任务块计算建议落位时间。
|
||||
//
|
||||
// 职责边界:
|
||||
// 1. 负责“粗排落位”与“内存占位状态更新”;
|
||||
// 2. 不负责持久化写库(由 service/dao 层负责);
|
||||
// 3. 不负责最终展示结构转换(由 conv 层负责)。
|
||||
//
|
||||
// 失败语义:
|
||||
// 1. 返回 TimeNotEnoughForAutoScheduling 表示“时间片总量或连续性不足”;
|
||||
// 2. 返回 nil error 表示所有 items 都已成功回填 EmbeddedTime。
|
||||
func computeAllocation(g *grid, items []model.TaskClassItem, strategy string) ([]model.TaskClassItem, error) {
|
||||
if len(items) == 0 {
|
||||
return items, nil
|
||||
}
|
||||
|
||||
// 1. 预处理可用坐标快照,并做容量下限校验(每个任务默认至少 2 节)。
|
||||
coords := g.getAllAvailable()
|
||||
totalAvailable := len(coords)
|
||||
totalRequired := len(items) * 2
|
||||
if totalAvailable < totalRequired {
|
||||
return nil, respond.TimeNotEnoughForAutoScheduling
|
||||
}
|
||||
|
||||
// 2. 计算间隔策略:
|
||||
// 2.1 rapid:沿用“尽快塞满”的线性前进;
|
||||
// 2.2 steady:不再只靠 gap 跳格子,而是结合目标位置、单日负载、同科分散和缓冲保留做候选打分。
|
||||
gap := 0
|
||||
if strategy == "steady" {
|
||||
gap = (totalAvailable - totalRequired) / (len(items) + 1)
|
||||
}
|
||||
|
||||
// 3. 线性分配主循环:
|
||||
// 3.1 cursor 是逻辑切片游标(不是物理节次指针);
|
||||
// 3.2 每次成功落位后,按“命中索引 + 占用长度 + gap”推进;
|
||||
// 3.3 若当前位置不满足约束(例如后继节被占),继续向后扫描,不降级为 1 节。
|
||||
cursor := gap
|
||||
lastPlacedIndex := -1
|
||||
placedDayOrdinals := make([]int, 0, len(items))
|
||||
|
||||
for i := range items {
|
||||
var (
|
||||
candidate planningSlotCandidate
|
||||
found bool
|
||||
)
|
||||
if strategy == "steady" {
|
||||
targetCursor := computeSteadyTargetCursor(totalAvailable, len(items), i)
|
||||
candidate, found = g.chooseSteadyCandidate(coords, targetCursor, placedDayOrdinals)
|
||||
} else {
|
||||
if cursor >= totalAvailable {
|
||||
break
|
||||
}
|
||||
candidate, found = g.findNextCandidateFromCursor(coords, cursor)
|
||||
}
|
||||
if !found {
|
||||
break
|
||||
}
|
||||
|
||||
// 5. 回填任务块建议时间。
|
||||
items[i].EmbeddedTime = &model.TargetTime{
|
||||
SectionFrom: candidate.sectionFrom,
|
||||
SectionTo: candidate.sectionTo,
|
||||
Week: candidate.week,
|
||||
DayOfWeek: candidate.dayOfWeek,
|
||||
}
|
||||
|
||||
// 6. 写入内存占位状态:
|
||||
// 6.1 这是后续候选判断的真实依据;
|
||||
// 6.2 失败兜底:纯内存操作无外部 IO,不存在部分提交问题。
|
||||
for sec := candidate.sectionFrom; sec <= candidate.sectionTo; sec++ {
|
||||
g.setNode(candidate.week, candidate.dayOfWeek, sec, slotNode{Status: Occupied})
|
||||
}
|
||||
|
||||
// 7. 推进游标并记录成功位置。
|
||||
slotLen := candidate.sectionTo - candidate.sectionFrom + 1
|
||||
if strategy != "steady" {
|
||||
cursor = candidate.coordIndex + slotLen + gap
|
||||
}
|
||||
placedDayOrdinals = append(placedDayOrdinals, planningDayOrdinal(candidate.week, candidate.dayOfWeek))
|
||||
lastPlacedIndex = i
|
||||
}
|
||||
|
||||
// 8. 完整性校验:
|
||||
// 8.1 只要有任一任务未落位,就返回统一的“时间不足”错误;
|
||||
// 8.2 避免出现“部分任务有时间、部分任务为空”的半成品结果。
|
||||
if lastPlacedIndex < len(items)-1 {
|
||||
return nil, respond.TimeNotEnoughForAutoScheduling
|
||||
}
|
||||
|
||||
return items, nil
|
||||
}
|
||||
154
backend/services/schedule/core/planning/smart_planning_test.go
Normal file
154
backend/services/schedule/core/planning/smart_planning_test.go
Normal file
@@ -0,0 +1,154 @@
|
||||
package planning
|
||||
|
||||
import (
|
||||
"testing"
|
||||
|
||||
"github.com/LoveLosita/smartflow/backend/services/runtime/model"
|
||||
"github.com/LoveLosita/smartflow/backend/shared/respond"
|
||||
)
|
||||
|
||||
// newTestGrid 创建仅用于单测的最小 grid。
|
||||
//
|
||||
// 职责边界:
|
||||
// 1. 只负责初始化时间窗口与 data 容器;
|
||||
// 2. 不负责填充节次状态(由各测试用例自行设置)。
|
||||
func newTestGrid(startWeek, startDay, endWeek, endDay int) *grid {
|
||||
return &grid{
|
||||
data: make(map[int]map[int][13]slotNode),
|
||||
startWeek: startWeek,
|
||||
startDay: startDay,
|
||||
endWeek: endWeek,
|
||||
endDay: endDay,
|
||||
}
|
||||
}
|
||||
|
||||
// setDayStatus 批量设置某一天 1~12 节的状态。
|
||||
func setDayStatus(g *grid, week, day int, status slotStatus) {
|
||||
for s := 1; s <= 12; s++ {
|
||||
g.setNode(week, day, s, slotNode{Status: status})
|
||||
}
|
||||
}
|
||||
|
||||
// setSectionStatus 设置单个节次状态。
|
||||
func setSectionStatus(g *grid, week, day, section int, status slotStatus) {
|
||||
g.setNode(week, day, section, slotNode{Status: status})
|
||||
}
|
||||
|
||||
// TestComputeAllocation_SkipIsolatedOneSlot 验证“孤立 1 节”不会被错误写成任务。
|
||||
//
|
||||
// 用例意图:
|
||||
// 1. 第一天只放一个孤立可用节次(10 节),后继 11 节被屏蔽;
|
||||
// 2. 第二天提供一个合法的连续 2 节(1-2 节);
|
||||
// 3. 期望算法跳过第一天孤立节次,把任务落到第二天 1-2 节。
|
||||
func TestComputeAllocation_SkipIsolatedOneSlot(t *testing.T) {
|
||||
g := newTestGrid(1, 1, 1, 2)
|
||||
|
||||
// 1. 先全部置为 Blocked,避免默认 Free 干扰本用例。
|
||||
setDayStatus(g, 1, 1, Blocked)
|
||||
setDayStatus(g, 1, 2, Blocked)
|
||||
|
||||
// 2. 构造“孤立 1 节 + 合法 2 节”场景。
|
||||
setSectionStatus(g, 1, 1, 10, Free) // 第一天仅 10 节可用,11/12 仍然 Blocked。
|
||||
setSectionStatus(g, 1, 2, 1, Free)
|
||||
setSectionStatus(g, 1, 2, 2, Free)
|
||||
|
||||
items := []model.TaskClassItem{{ID: 1}}
|
||||
got, err := computeAllocation(g, items, "rapid")
|
||||
if err != nil {
|
||||
t.Fatalf("期望分配成功,实际报错: %v", err)
|
||||
}
|
||||
if len(got) != 1 || got[0].EmbeddedTime == nil {
|
||||
t.Fatalf("期望回填 1 条 EmbeddedTime,实际: %+v", got)
|
||||
}
|
||||
|
||||
tt := got[0].EmbeddedTime
|
||||
if tt.Week != 1 || tt.DayOfWeek != 2 || tt.SectionFrom != 1 || tt.SectionTo != 2 {
|
||||
t.Fatalf("期望落位到 W1D2 1-2 节,实际: week=%d day=%d from=%d to=%d",
|
||||
tt.Week, tt.DayOfWeek, tt.SectionFrom, tt.SectionTo)
|
||||
}
|
||||
}
|
||||
|
||||
// TestComputeAllocation_RejectAllIsolatedSlots 验证“全是孤立 1 节”时应返回时间不足。
|
||||
//
|
||||
// 用例意图:
|
||||
// 1. 虽然总可用节次数量达到 2,但它们分散成两个孤立 1 节;
|
||||
// 2. 业务要求普通任务默认必须 2 连续节,因此应整体失败而不是偷偷降级为 1 节。
|
||||
func TestComputeAllocation_RejectAllIsolatedSlots(t *testing.T) {
|
||||
g := newTestGrid(1, 1, 1, 2)
|
||||
|
||||
// 1. 先全部置为 Blocked。
|
||||
setDayStatus(g, 1, 1, Blocked)
|
||||
setDayStatus(g, 1, 2, Blocked)
|
||||
|
||||
// 2. 仅放两个彼此分离的孤立可用节次。
|
||||
setSectionStatus(g, 1, 1, 10, Free)
|
||||
setSectionStatus(g, 1, 2, 10, Free)
|
||||
|
||||
items := []model.TaskClassItem{{ID: 1}}
|
||||
_, err := computeAllocation(g, items, "rapid")
|
||||
if err == nil {
|
||||
t.Fatalf("期望返回时间不足错误,实际为 nil")
|
||||
}
|
||||
if err.Error() != respond.TimeNotEnoughForAutoScheduling.Error() {
|
||||
t.Fatalf("期望错误=%s,实际=%s", respond.TimeNotEnoughForAutoScheduling.Error(), err.Error())
|
||||
}
|
||||
}
|
||||
|
||||
// TestComputeAllocation_RejectEvenStartPair 验证偶数起点双节(如 8-9)不允许作为粗排结果。
|
||||
//
|
||||
// 用例意图:
|
||||
// 1. 构造一个看似连续的 8-9 空位;
|
||||
// 2. 同时给出一个合法的 11-12 对齐空位;
|
||||
// 3. 期望算法跳过 8-9,选择 11-12。
|
||||
func TestComputeAllocation_RejectEvenStartPair(t *testing.T) {
|
||||
g := newTestGrid(1, 1, 1, 1)
|
||||
|
||||
// 1. 全部先置为 Blocked,避免默认 Free 干扰判断。
|
||||
setDayStatus(g, 1, 1, Blocked)
|
||||
|
||||
// 2. 构造“偶数起点双节 + 合法奇数起点双节”。
|
||||
setSectionStatus(g, 1, 1, 8, Free)
|
||||
setSectionStatus(g, 1, 1, 9, Free)
|
||||
setSectionStatus(g, 1, 1, 11, Free)
|
||||
setSectionStatus(g, 1, 1, 12, Free)
|
||||
|
||||
items := []model.TaskClassItem{{ID: 1}}
|
||||
got, err := computeAllocation(g, items, "rapid")
|
||||
if err != nil {
|
||||
t.Fatalf("期望分配成功,实际报错: %v", err)
|
||||
}
|
||||
if got[0].EmbeddedTime == nil {
|
||||
t.Fatalf("期望回填 EmbeddedTime,实际为 nil")
|
||||
}
|
||||
|
||||
tt := got[0].EmbeddedTime
|
||||
if tt.SectionFrom != 11 || tt.SectionTo != 12 {
|
||||
t.Fatalf("期望落位到 11-12,实际落位到 %d-%d", tt.SectionFrom, tt.SectionTo)
|
||||
}
|
||||
}
|
||||
|
||||
// TestComputeAllocation_FillerNeedOddEvenPair 验证 Filler 课程块也必须满足奇数起点双节对齐。
|
||||
//
|
||||
// 用例意图:
|
||||
// 1. 仅提供一个 Filler 课程块 8-9(偶数起点);
|
||||
// 2. 即使总可用节数为 2,也不能被当作合法落位;
|
||||
// 3. 期望返回时间不足错误。
|
||||
func TestComputeAllocation_FillerNeedOddEvenPair(t *testing.T) {
|
||||
g := newTestGrid(1, 1, 1, 1)
|
||||
|
||||
// 1. 全部先置为 Blocked。
|
||||
setDayStatus(g, 1, 1, Blocked)
|
||||
|
||||
// 2. 课程块 8-9 标记为 Filler,但其起点为偶数,不满足对齐规则。
|
||||
g.setNode(1, 1, 8, slotNode{Status: Filler, EventID: 1001})
|
||||
g.setNode(1, 1, 9, slotNode{Status: Filler, EventID: 1001})
|
||||
|
||||
items := []model.TaskClassItem{{ID: 1}}
|
||||
_, err := computeAllocation(g, items, "rapid")
|
||||
if err == nil {
|
||||
t.Fatalf("期望返回时间不足错误,实际为 nil")
|
||||
}
|
||||
if err.Error() != respond.TimeNotEnoughForAutoScheduling.Error() {
|
||||
t.Fatalf("期望错误=%s,实际=%s", respond.TimeNotEnoughForAutoScheduling.Error(), err.Error())
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user