45 lines
1.4 KiB
Python
45 lines
1.4 KiB
Python
# roundtable/core/time_range.py
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"""Shared time-range utilities for scoping queries and sparkline data."""
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from __future__ import annotations
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from datetime import datetime, timedelta, timezone
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from typing import TypeVar
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RANGES: dict[str, timedelta] = {
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"1h": timedelta(hours=1),
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"6h": timedelta(hours=6),
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"24h": timedelta(hours=24),
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"7d": timedelta(days=7),
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"30d": timedelta(days=30),
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}
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RANGE_OPTIONS: list[str] = list(RANGES.keys())
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DEFAULT_RANGE = "24h"
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def parse_range(range_str: str | None) -> tuple[datetime, str]:
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"""Return (since_datetime, range_key) from a query-param string like '24h'."""
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key = range_str if range_str in RANGES else DEFAULT_RANGE
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since = datetime.now(timezone.utc) - RANGES[key]
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return since, key
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def bucket_seconds(since: datetime, target_points: int = 80) -> int:
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"""Return bucket width in seconds so that (now - since) / width ≈ target_points.
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Minimum is 60s (one poll interval) so raw data is never re-averaged below
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the collection resolution.
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"""
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range_secs = (datetime.now(timezone.utc) - since).total_seconds()
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return max(60, int(range_secs / target_points))
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T = TypeVar("T")
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def subsample(seq: list[T], n: int = 80) -> list[T]:
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"""Return at most n evenly-distributed elements from seq (preserves order)."""
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if len(seq) <= n:
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return seq
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indices = sorted({int(round(i * (len(seq) - 1) / (n - 1))) for i in range(n)})
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return [seq[i] for i in indices]
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