58 lines
3.2 KiB
Markdown
58 lines
3.2 KiB
Markdown
# Running personal records
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Activity import calculates and persists estimated best efforts for
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1 km, 2 km, 5 km, 10 km, half marathon (21,097.5 m), and marathon (42,195 m).
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These are fastest stretches anywhere within a run, rather than lap times or
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times projected from average pace. All existing running activities participate.
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Following [Strava's elapsed-time convention](https://support.strava.com/en-us/articles/15401661-how-do-best-efforts-work-for-running-on-strava),
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stops inside an effort count. The calculation uses full-resolution FIT cumulative
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distance and timestamps, with linear interpolation at distance boundaries. Missing
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distance/time, backwards distance, and non-increasing timestamps split the data.
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Timestamp gaps count as elapsed time; there is no subtraction for auto-pause.
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No distance or time is inferred from an activity summary when samples are absent.
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The dashboard lists current records. Runs earn historical PR badges if they
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established or strictly improved a record on their activity date; equal times
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do not earn another badge. Import order does not affect the result. Records and
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badges are recalculated from history, so older imports and removals are reflected.
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Comparisons currently appear only in the owner's dashboard and activity page.
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These are estimates from watch data, not verified race records or an exact clone
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of Strava's proprietary calculation. GPS/distance spikes or sparse recording can
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affect results. There is currently no manual effort exclusion or correction UI.
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Imports (FIT upload, Garmin sync and local cache) persist per-run efforts in the
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same transaction as the run. Refreshing recorded data recalculates the efforts.
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`efforts_version` identifies the calculation version; version 0 means pending.
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A current version with an empty list means calculated with no eligible distances.
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Page requests only compare stored efforts; there is no sample-based fallback.
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Raw samples and laps are deferred in list queries. Route availability is also
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persisted, so the dashboard can choose its map without loading historical samples.
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Chronological PR comparisons still happen on page requests, using at most six
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stored efforts per run, preserving correct badges after backfills or removals.
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After `flask --app app db upgrade`, run:
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```sh
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flask --app app backfill-efforts --batch-size 25
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```
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The command commits each bounded batch and skips current-version rows on reruns.
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It includes non-running and incomplete activities, storing an empty result when
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appropriate. `--owner-id ID` limits the operation to one athlete; `--force`
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recalculates current results. It uses row locks on PostgreSQL to coordinate with
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concurrent refreshes, and fixes an upper activity ID at the start so new imports
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do not extend the backfill indefinitely. New imports calculate their own results.
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No FIT files need to be downloaded again. On Dokku:
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```sh
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dokku run stride flask --app app backfill-efforts --batch-size 25
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```
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Until backfill finishes, pending activities do not contribute to records or
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route selection. Keep backfills separate from schema migrations so a large
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history does not delay every deployment.
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Further additions could include second/third-best medals, annual records, manual
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exclusion of bad recordings, and a selected-effort highlight on the route map.
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