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Freedom251 › Blog › Apple Health

Apple Health with Polars: How to Build a Local XML-to-DataFrame Pipeline

By Freedom251 Team · · 5 min read

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Apple Health exports data as XML, but Polars’ documented input readers focus on tabular formats such as CSV, JSON and Parquet—not native XML. The practical route is to parse the export first, normalize its records into typed rows, and then use Polars to filter, aggregate and save the data. That design can make analysis repeatable; “lightning-fast” is not a proven speed claim without a benchmark on a disclosed file and machine.

What this pipeline does—and where Polars fits

The workflow has three distinct stages: export data from the Health app, parse the XML into records, and analyze the normalized rows with Polars. Apple documents the export as XML, while Polars’ input/output documentation lists readers for formats including CSV, JSON and Parquet. The documentation reviewed here does not establish a native XML reader, so do not assume you can pass Apple’s XML file directly to a Polars reader.

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This is file processing, not a HealthKit query. HealthKit is Apple’s framework for apps that access health data with user permission; Apple documents direct reading through methods and queries, including long-running queries. A script that reads an exported file does not use those APIs or inherit their permission flow. See Apple’s HealthKit overview and guide to reading data from HealthKit.

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Export your data from the Health app

Apple’s currently documented route is in Health on iPhone: open your profile, choose “Export All Health Data,” then select a sharing method. Apple says the export is in XML format. Interface labels and placement can change between iOS versions, so confirm the current route on your device. Apple’s instructions are in Share your data in Health on iPhone.

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  • KNOW YOUR SLEEP SCORE—With advanced sleep tracking, Series 11 gives you a daily sleep score. It’s an easy way to help measure and understand the quality of your sleep, so you can make it more restorative.
  • GET HYPERTENSION NOTIFICATIONS—Did you know that Series 11 can spot signs of chronic high blood pressure? By analyzing how your blood vessels respond to beats of the heart, it can notify you of possible hypertension.*
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  1. In the Health app on iPhone, open your profile.
  2. Select “Export All Health Data.”
  3. Choose a sharing method and save the export where you can identify and protect it.
  4. Keep the original export unchanged; develop and test against a separate copy.

There is no universal file-size or record-count estimate established here. Inspect your own export before deciding how much memory or storage your pipeline needs.

Choose a parsing path before creating a DataFrame

For a manageable export

Use an XML parser to read the document’s actual structure, turn each relevant record into a dictionary or row, and accumulate a bounded batch before creating a Polars DataFrame. Check the export itself for its root element, record tags and attributes; do not assume a schema or field coverage that Apple has not guaranteed for your file.

For a larger or repeat-use workflow

Prefer incremental record processing over building a complete in-memory XML tree. Process completed elements and release them where the parser allows, validate unexpected records, and capture parsing failures rather than silently dropping data. This is general XML engineering guidance, not a measured comparison on Apple exports.

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  • A FULL-FEATURED HEALTH TRACKER—Apple Watch Series 11 gives you invaluable insights about your body, right from your wrist. Take an ECG anytime* and get alerts for a high and low heart rate or an irregular rhythm*—so you can stay closer to your heart. You can also view your overnight health tracking metrics with the Vitals app* and be notified of possible sleep apnea.*
  • KNOW YOUR SLEEP SCORE—With advanced sleep tracking, Series 11 gives you a daily sleep score. It’s an easy way to help measure and understand the quality of your sleep, so you can make it more restorative.
  • GET HYPERTENSION NOTIFICATIONS—Did you know that Series 11 can spot signs of chronic high blood pressure? By analyzing how your blood vessels respond to beats of the heart, it can notify you of possible hypertension.*
  • SAFETY FEATURES—A smartwatch that puts your safety first. Series 11 can detect a hard fall or severe car crash, automatically help connect you with emergency services, and notify your emergency contacts.* Check In can automatically notify a loved one when you’ve arrived at your destination.
  • A POWERFUL FITNESS TRACKER—With advanced metrics and motivating features like Pacer, Heart Rate Zones, training load, and Workout Buddy powered by Apple Intelligence from your nearby iPhone*—Series 11 is made to help everyone stay active, from runners and hikers to strength-training enthusiasts.

After normalizing each batch, write it to a supported intermediate format such as Parquet. Polars documents Parquet scanning, lazy scans and sinks in its sources and sinks guide. The XML-to-Parquet step is an engineering recommendation based on Apple’s export format and Polars’ documented readers, not a tested implementation or a requirement.

Design a schema that preserves meaning

A useful long-form table can contain one row per exported record, with nullable columns for record type, value, unit, start and end timestamps, source, device and relevant metadata. The exact fields depend on what appears in the export. Retain original attributes or a raw-record representation so fields outside the normalized schema are not lost.

  • Keep provenance: record the export date, parser version and transformation logic. Preserve source and device details when present.
  • Use explicit types: set or validate column types when creating batches rather than letting inconsistent values silently determine them.
  • Normalize timestamps deliberately: parse them consistently and preserve timezone offsets when supplied.
  • Keep units visible: do not aggregate quantities with different units as if they were interchangeable.
  • Handle missing or unexpected data: use nullable fields where appropriate and log records that fail validation.

These are schema-design practices, not claims that every Apple export contains the same tags, attributes, units or metadata.

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  • A GREAT FITNESS TRACKER—SE 3 can track your workouts in a healthy number of ways—from running and strength training to simply achieving your 10K steps a day. With real-time metrics and Workout Buddy powered by Apple Intelligence from your nearby iPhone,* you’ll hit your goals like never before.
  • KEEP HELP CLOSE AT HAND—SE 3 is a smartwatch that can detect a hard fall or severe car crash and automatically help connect you to emergency services and notify your emergency contacts.* Check In can automatically notify a loved one when you’ve arrived at your destination.
  • WOMEN’S HEALTH INSIGHTS—SE 3 has advanced sensors that track your wrist temperature while you sleep. With this smartwatch, you can log your periods and symptoms, get period predictions, and get notified of cycle deviations.*
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Move normalized rows into Polars

Build DataFrames from bounded batches

For an export that fits your available memory, construct DataFrames from parsed batches and provide explicit schema information or dtypes. You can then concatenate batches or write them incrementally. Batching avoids requiring the XML parser and the entire normalized dataset to remain in memory at the same time, though the actual memory profile depends on the parser, batch size and workload.

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Scan Parquet lazily for repeat analysis

If you write normalized batches to Parquet, start later analyses with Polars’ lazy scan for that format. Lazy execution gives Polars an opportunity to optimize a query before collecting results. For a pipeline whose source is XML, however, the XML parsing and normalization still happen before that scan; laziness does not make the XML stage disappear.

Polars documents multiple supported I/O formats and scan APIs in its input/output reference and lazy API guide. Check the documentation for the Polars version you have installed when choosing specific functions.

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  • GET SMARTER HEALTH INSIGHTS—Apple Watch SE 3 is an advanced health tracker that helps you better understand your body. The smartwatch sends alerts for an irregular heart rhythm, or an unusually high or low heart rate.* You can view your overnight health tracking metrics with the Vitals app,* track your sleep score, and get sleep apnea notifications.*
  • A GREAT FITNESS TRACKER—SE 3 can track your workouts in a healthy number of ways—from running and strength training to simply achieving your 10K steps a day. With real-time metrics and Workout Buddy powered by Apple Intelligence from your nearby iPhone,* you’ll hit your goals like never before.
  • KEEP HELP CLOSE AT HAND—SE 3 is a smartwatch that can detect a hard fall or severe car crash and automatically help connect you to emergency services and notify your emergency contacts.* Check In can automatically notify a loved one when you’ve arrived at your destination.
  • WOMEN’S HEALTH INSIGHTS—SE 3 has advanced sensors that track your wrist temperature while you sleep. With this smartwatch, you can log your periods and symptoms, get period predictions, and get notified of cycle deviations.*
  • GREAT BATTERY LIFE AND FASTER CHARGING—Enjoy a smartwatch with all-day, 18-hour battery life* from sunup to sundown. Then charge up to twice as fast as SE 2* and get up to 8 hours of battery in just 15 minutes.*

What “streaming” means in Polars

Polars’ streaming execution engine can process eligible operations in batches and may support workloads larger than memory. It does not make every operation or every stage of this pipeline streaming. Polars notes that some operations are inherently non-streaming or may not have a streaming implementation; an operation can also fall back to the in-memory engine. See the Polars streaming guide.

Use a supported lazy source, then request streaming execution when collecting a query, for example with collect(engine="streaming"). Inspect the query plan and measure the real workload to see what runs in streaming mode. Even if a Parquet query streams, the earlier XML parsing stage may have different memory behavior.

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Protect the health data throughout the workflow

An exported health file is sensitive. Decide where the original, intermediate Parquet files and analysis outputs will live, and whether any configured sync service or external analysis tool will transfer them elsewhere. A local script can keep processing on your device if you configure it that way, but local processing is not a privacy guarantee for files that are also synced or uploaded.

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Apple Watch Series 11 [GPS 42mm] Smartwatch with Jet Black Aluminum Case with Black Sport Band - S/M. Sleep Score, Fitness Tracker, Health Monitoring, Always-On Display, Water Resistant
  • A FULL-FEATURED HEALTH TRACKER—Apple Watch Series 11 gives you invaluable insights about your body, right from your wrist. Take an ECG anytime* and get alerts for a high and low heart rate or an irregular rhythm*—so you can stay closer to your heart. You can also view your overnight health tracking metrics with the Vitals app* and be notified of possible sleep apnea.*
  • KNOW YOUR SLEEP SCORE—With advanced sleep tracking, Series 11 gives you a daily sleep score. It’s an easy way to help measure and understand the quality of your sleep, so you can make it more restorative.
  • GET HYPERTENSION NOTIFICATIONS—Did you know that Series 11 can spot signs of chronic high blood pressure? By analyzing how your blood vessels respond to beats of the heart, it can notify you of possible hypertension.*
  • SAFETY FEATURES—A smartwatch that puts your safety first. Series 11 can detect a hard fall or severe car crash, automatically help connect you with emergency services, and notify your emergency contacts.* Check In can automatically notify a loved one when you’ve arrived at your destination.
  • A POWERFUL FITNESS TRACKER—With advanced metrics and motivating features like Pacer, Heart Rate Zones, training load, and Workout Buddy powered by Apple Intelligence from your nearby iPhone*—Series 11 is made to help everyone stay active, from runners and hikers to strength-training enthusiasts.

Apple’s permission model applies to apps accessing HealthKit; it does not automatically govern a separate script reading a file you exported. Keep the export and generated files in storage you control, avoid sending them to services you have not evaluated, and remove temporary copies when they are no longer needed.

Measure performance instead of assuming it

No general parsing time, file size, record count or Polars speedup is established for this workflow. “Lightning-fast” should be treated as an aspiration, not a benchmark result. To make a performance claim, report the input export, hardware, software versions, parsing and transformation steps, output, and baseline. Measure the complete pipeline as well as any individual stage you want to compare; a fast Polars aggregation cannot establish that XML parsing or file writing is fast.

For repeatable analysis, preserve the original XML, version the parser and transformations, and save normalized data in a format Polars can scan efficiently. That gives you a clear boundary between Apple’s export, your schema decisions and the queries you run.

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Apple HealthData AnalysisHealth dataPolarsPythonXML

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