MetricPull

MetricPull currently supports:

• 70 Apple Health metrics spanning body measurements, activity, heart health, sleep, vitals, and nutrition
• Summary exports for daily, weekly, or monthly trends
• Log Entries for readable individual measurements, workouts, events, and supported sleep records
• Raw Samples for detailed HealthKit records where supported, including ordinary Heart Rate, Workouts, supported quantity records, Detailed Sleep, Weight, and Blood Pressure, with precise timestamps, provenance, and stored-record identifiers
• Detailed Sleep Records for each stored sleep-analysis segment when Time Asleep is selected alone
• Heart and Workout records — Resting Heart Rate, Walking Heart Rate Average, Cardio Fitness, and Heart Rate Variability support Log Entries and Raw Samples when selected individually; ordinary Heart Rate supports Raw Samples when selected alone; Workouts support Log Entries and Raw Samples when selected alone
• Bounded full-record processing with streamed CSV writing, progress, cancellation, and file-backed Analysis Kit packaging for supported record exports
• Quick Metrics charts and rolling comparisons without exporting
• Reusable built-in and user-created presets
• Configurable dates, aggregation, column order, and Imperial or Metric units
• AI-ready Analysis Kits for every supported export mode
• CSV previews before anything is shared

The product deliberately uses different export modes because a daily trend, a logged event, and a stored HealthKit sample answer different questions.

Summary exports make long-term trends manageable. Log Entries preserve readable individual measurements, workouts, events, and supported sleep records. Raw Samples retain precise HealthKit record timing, provenance, and stored-record identifiers where supported, including ordinary Heart Rate and Workouts. Detailed Sleep Records preserve stored sleep stages and attributed nights without reconstructing or merging them into inferred sessions. Users can choose the representation that matches the analysis rather than forcing every metric into one table shape.

For supported Raw Samples, including supported quantity records, ordinary Heart Rate, Workouts, Weight, and Blood Pressure, MetricPull separates the source that saved a record from the hardware Apple Health reports as generating it when Apple provides those fields. Those fields can differ, and the export explains that distinction instead of presenting a single misleading “device” label. Blood Pressure keeps paired values together while using the enclosing stored correlation for its public timestamp, provenance, and identity.

Supported quantity, ordinary Heart Rate, Workout, Detailed Sleep, Weight, and Blood Pressure Raw Samples include a HealthKit stored-object UUID. That gives overlapping exports record-level identity within the same Health database instead of asking an analyst to guess whether similar rows are the same stored object. For Blood Pressure, the UUID identifies the complete paired correlation rather than either value member. Detailed Sleep guidance still preserves overlapping rows instead of reconciling them by timestamps alone. Workout Raw preserves stored workout records; it does not reconstruct pauses, routes, locations, or overlapping-workout reconciliation.

Raw timestamps retain the local UTC offset active for each sample, including daylight-saving transitions. Interval-capable samples keep both start and end timestamps. Readable Log Entries use local wall-clock time and explicitly direct analysts to Raw Samples when exact offsets matter.

Analysis Kits describe units, columns, missing values, provenance, record identity, date behavior, and known limitations. The goal is not to guarantee a correct conclusion; it is to remove avoidable ambiguity before analysis begins.

MetricPull can export large, record-level datasets, such as years of individual Heart Rate readings or available Workout history. Supported full-record CSV and Analysis Kit exports use bounded acquisition, streamed CSV writing, aggregate progress, cancellation, and file-backed packaging. They do not fall back to unlimited acquisition or require the complete record history or finished file to be held in memory at once.

MetricPull is built as a native iPhone and iPad app using SwiftUI, HealthKit, Observation, and Swift Charts.

The engineering centers on a few durable ideas:

• A read-only dependency boundary separates production HealthKit access from tests and deterministic screenshot fixtures.
• A shared quantity architecture supports multiple record types through common fetching, schemas, formatting, metadata, and instructions, including the low-volume heart record additions.
• Reusable schema generation keeps CSV columns, machine-readable metadata, and human-readable guidance aligned.
• Dedicated paths preserve established Blood Pressure, Weight, Detailed Sleep, Heart Rate, and separate Workout Log/Raw contracts without changing existing Summary, presets, or Quick Metrics behavior.
• Schema and routing contracts keep file output, units, metadata, provenance, and Analysis Kit packaging aligned across export modes.
• The app has no backend or third-party runtime dependency.

The interesting work is less about drawing a CSV row and more about designing a stable contract between HealthKit’s data model, a human-readable file, and the tools that consume it.