Davide Scaini
5ad3aee8f6
- "unlisted" = not shown in the public feed, but GPS track, timeseries and detail JSON are all accessible by direct URL (security by obscurity) - "private" accepted as legacy alias everywhere (backward compat with existing data on disk) - New writes from Strava sync / ZIP upload / sidecar use "unlisted" - Only "no_gps" now suppresses the GPS track - isUnlisted() helper in format.ts used by all Svelte/Astro components - SCHEMA.md and CLAUDE.md document the privacy model and the distinction between "unlisted" and "no_gps"
60 lines
2.2 KiB
Python
60 lines
2.2 KiB
Python
"""Downsample a list of DataPoints to at most 1 sample/second and build
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the BAS timeseries object (parallel arrays)."""
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from datetime import datetime
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from typing import Optional
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from bincio.extract.models import DataPoint
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def build_timeseries(
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points: list[DataPoint],
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started_at: datetime,
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privacy: str = "public",
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) -> dict:
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"""Return the BAS `timeseries` object.
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privacy='no_gps' → lat/lon set to null. All other privacy levels
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(including 'unlisted') retain GPS in the timeseries.
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Downsamples so at most one point per second is emitted.
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"""
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if not points:
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return {"t": []}
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include_gps = privacy not in ("no_gps", "private") # "private" = legacy alias for "unlisted"
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# Downsample: keep at most one point per second
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sampled: list[DataPoint] = []
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last_t: Optional[int] = None
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for p in points:
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t = int((p.timestamp - started_at).total_seconds())
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if t < 0:
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continue
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if last_t is not None and t <= last_t:
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continue # skip sub-second duplicates and non-monotonic points
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sampled.append(p)
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last_t = t
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ts_vals = [int((p.timestamp - started_at).total_seconds()) for p in sampled]
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lat_vals = [round(p.lat, 7) if p.lat is not None else None for p in sampled] if include_gps else None
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lon_vals = [round(p.lon, 7) if p.lon is not None else None for p in sampled] if include_gps else None
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ele_vals = [round(p.elevation_m, 1) if p.elevation_m is not None else None for p in sampled]
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spd_vals = [round(p.speed_kmh, 2) if p.speed_kmh is not None else None for p in sampled]
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hr_vals = [p.hr_bpm for p in sampled]
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cad_vals = [p.cadence_rpm for p in sampled]
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pwr_vals = [p.power_w for p in sampled]
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tmp_vals = [round(p.temperature_c, 1) if p.temperature_c is not None else None for p in sampled]
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result: dict = {
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"t": ts_vals,
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"lat": lat_vals,
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"lon": lon_vals,
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"elevation_m": ele_vals,
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"speed_kmh": spd_vals,
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"hr_bpm": hr_vals,
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"cadence_rpm": cad_vals,
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"power_w": pwr_vals,
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"temperature_c": tmp_vals,
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}
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return result
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