Add honeycomb completion heatmap and data migration framework
- Add completion_summary endpoint data to residence detail response - Track completed_from_column on task completions (overdue/due_soon/upcoming) - Add GetCompletionSummary repo method with monthly aggregation - Add one-time data migration framework (data_migrations table + registry) - Add backfill migration to classify historical completions - Add standalone backfill script for manual/dry-run usage Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Trey t
206
internal/database/migration_backfill_completion_columns.go
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206
internal/database/migration_backfill_completion_columns.go
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package database
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import (
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"sort"
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"time"
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"github.com/rs/zerolog/log"
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"gorm.io/gorm"
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)
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const daysThreshold = 30 // "due soon" window, matches app default
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func init() {
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RegisterDataMigration("20250601_backfill_completion_columns", backfillCompletionColumns)
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}
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func backfillCompletionColumns(tx *gorm.DB) error {
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// Query all completions that still have the default value
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type completionRow struct {
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ID uint
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TaskID uint
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CompletedAt time.Time
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}
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var completions []completionRow
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err := tx.Table("task_taskcompletion").
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Select("id, task_id, completed_at").
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Where("completed_from_column = ? OR completed_from_column IS NULL OR completed_from_column = ''", "completed_tasks").
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Order("task_id, completed_at ASC").
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Scan(&completions).Error
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if err != nil {
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return err
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}
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log.Info().Int("total_completions", len(completions)).Msg("Backfill: found completions to classify")
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if len(completions) == 0 {
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log.Info().Msg("Backfill: nothing to backfill")
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return nil
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}
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// Load all tasks referenced by these completions
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taskIDs := make(map[uint]bool)
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for _, c := range completions {
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taskIDs[c.TaskID] = true
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}
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taskIDList := make([]uint, 0, len(taskIDs))
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for id := range taskIDs {
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taskIDList = append(taskIDList, id)
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}
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type taskRow struct {
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ID uint
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DueDate *time.Time
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NextDueDate *time.Time
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FrequencyID *uint
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CustomIntervalDays *int
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}
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var tasks []taskRow
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err = tx.Table("task_task").
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Select("id, due_date, next_due_date, frequency_id, custom_interval_days").
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Where("id IN ?", taskIDList).
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Scan(&tasks).Error
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if err != nil {
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return err
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}
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taskMap := make(map[uint]*taskRow, len(tasks))
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for i := range tasks {
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taskMap[tasks[i].ID] = &tasks[i]
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}
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// Load frequency intervals
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type freqRow struct {
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ID uint
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Name string
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Days *int
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}
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var frequencies []freqRow
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err = tx.Table("task_taskfrequency").Select("id, name, days").Scan(&frequencies).Error
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if err != nil {
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return err
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}
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freqMap := make(map[uint]*freqRow, len(frequencies))
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for i := range frequencies {
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freqMap[frequencies[i].ID] = &frequencies[i]
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}
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// Group completions by task
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taskCompletions := make(map[uint][]completionRow)
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for _, c := range completions {
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taskCompletions[c.TaskID] = append(taskCompletions[c.TaskID], c)
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}
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for taskID := range taskCompletions {
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sort.Slice(taskCompletions[taskID], func(i, j int) bool {
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return taskCompletions[taskID][i].CompletedAt.Before(taskCompletions[taskID][j].CompletedAt)
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})
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}
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// Classify each completion
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type updateEntry struct {
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completionID uint
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column string
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}
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var updates []updateEntry
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stats := map[string]int{
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"overdue_tasks": 0,
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"due_soon_tasks": 0,
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"upcoming_tasks": 0,
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"no_due_date": 0,
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}
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for taskID, comps := range taskCompletions {
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task, ok := taskMap[taskID]
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if !ok {
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continue
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}
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// Determine interval for recurring tasks
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var intervalDays int
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if task.FrequencyID != nil {
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if freq, ok := freqMap[*task.FrequencyID]; ok {
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if freq.Name == "Custom" && task.CustomIntervalDays != nil {
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intervalDays = *task.CustomIntervalDays
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} else if freq.Days != nil {
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intervalDays = *freq.Days
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}
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}
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}
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isRecurring := intervalDays > 0
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if !isRecurring {
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effectiveDate := task.DueDate
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if effectiveDate == nil {
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for _, c := range comps {
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stats["no_due_date"]++
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updates = append(updates, updateEntry{c.ID, "completed_tasks"})
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}
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continue
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}
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for _, c := range comps {
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column := classifyCompletion(c.CompletedAt, *effectiveDate, daysThreshold)
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stats[column]++
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updates = append(updates, updateEntry{c.ID, column})
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}
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} else {
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effectiveDate := task.DueDate
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if effectiveDate == nil && task.NextDueDate != nil {
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est := task.NextDueDate.AddDate(0, 0, -intervalDays*len(comps))
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effectiveDate = &est
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}
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if effectiveDate == nil {
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for _, c := range comps {
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stats["no_due_date"]++
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updates = append(updates, updateEntry{c.ID, "completed_tasks"})
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}
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continue
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}
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currentDueDate := *effectiveDate
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for _, c := range comps {
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column := classifyCompletion(c.CompletedAt, currentDueDate, daysThreshold)
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stats[column]++
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updates = append(updates, updateEntry{c.ID, column})
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currentDueDate = c.CompletedAt.AddDate(0, 0, intervalDays)
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}
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}
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}
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log.Info().
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Int("overdue", stats["overdue_tasks"]).
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Int("due_soon", stats["due_soon_tasks"]).
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Int("upcoming", stats["upcoming_tasks"]).
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Int("no_due_date", stats["no_due_date"]).
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Int("total_updates", len(updates)).
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Msg("Backfill: classification results")
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// Apply updates
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for _, u := range updates {
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if err := tx.Table("task_taskcompletion").
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Where("id = ?", u.completionID).
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Update("completed_from_column", u.column).Error; err != nil {
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return err
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}
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}
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log.Info().Int("total_updated", len(updates)).Msg("Backfill: complete")
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return nil
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}
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// classifyCompletion determines what kanban column a task was in when completed.
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func classifyCompletion(completedAt time.Time, dueDate time.Time, threshold int) string {
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completedDay := time.Date(completedAt.Year(), completedAt.Month(), completedAt.Day(), 0, 0, 0, 0, time.UTC)
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dueDay := time.Date(dueDate.Year(), dueDate.Month(), dueDate.Day(), 0, 0, 0, 0, time.UTC)
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if completedDay.After(dueDay) {
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return "overdue_tasks"
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}
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daysBefore := dueDay.Sub(completedDay).Hours() / 24
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if daysBefore <= float64(threshold) {
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return "due_soon_tasks"
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}
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return "upcoming_tasks"
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}
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