|
1 | | -from datetime import datetime |
| 1 | +from datetime import datetime as dt, timedelta, UTC |
2 | 2 |
|
3 | 3 | from fastapi import APIRouter |
4 | 4 |
|
5 | | -from asu.util import get_redis_client |
| 5 | +from asu.util import get_redis_ts |
6 | 6 |
|
7 | 7 | router = APIRouter() |
8 | 8 |
|
9 | 9 |
|
10 | | -def get_redis_ts(): |
11 | | - return get_redis_client().ts() |
| 10 | +DAY_MS = 24 * 60 * 60 * 1000 |
| 11 | +N_DAYS = 30 |
12 | 12 |
|
13 | 13 |
|
14 | 14 | @router.get("/builds-per-day") |
15 | | -def get_builds_per_day(): |
16 | | - ts = get_redis_ts() |
17 | | - now = int(datetime.utcnow().timestamp() * 1000) |
18 | | - start = now - 30 * 24 * 60 * 60 * 1000 # last 30 days |
| 15 | +def get_builds_per_day() -> dict: |
| 16 | + """ |
| 17 | + References: |
| 18 | + https://redis.readthedocs.io/en/latest/redismodules.html#redis.commands.timeseries.commands.TimeSeriesCommands.range |
| 19 | + https://www.chartjs.org/docs/latest/charts/line.html |
| 20 | + """ |
| 21 | + |
| 22 | + # "stop" is next midnight to define buckets on exact day boundaries. |
| 23 | + stop = dt.now(UTC).replace(hour=0, minute=0, second=0, microsecond=0) |
| 24 | + stop += timedelta(days=1) |
| 25 | + stop = int(stop.timestamp() * 1000) |
| 26 | + start = stop - N_DAYS * DAY_MS |
| 27 | + |
| 28 | + stamps = list(range(start, stop, DAY_MS)) |
| 29 | + labels = [str(dt.fromtimestamp(stamp // 1000, UTC))[:10] + "Z" for stamp in stamps] |
19 | 30 |
|
20 | | - # aggregate all time series labeled with stats=builds |
21 | | - results = ts.mrange( |
| 31 | + ts = get_redis_ts() |
| 32 | + rc = ts.client |
| 33 | + range_options = dict( |
22 | 34 | from_time=start, |
23 | | - to_time=now, |
24 | | - filters=["stats=builds"], |
25 | | - with_labels=False, |
| 35 | + to_time=stop, |
| 36 | + align=start, # Ensures alignment of X values with "stamps". |
26 | 37 | aggregation_type="sum", |
27 | | - bucket_size_msec=86400000, # 1 day (24 hours) |
| 38 | + bucket_size_msec=DAY_MS, |
28 | 39 | ) |
29 | 40 |
|
30 | | - # create a map from timestamp to build count |
31 | | - daily_counts = {} |
32 | | - |
33 | | - for entry in results: |
34 | | - data = list(entry.values())[0][1] |
35 | | - for ts, value in data: |
36 | | - daily_counts[ts] = daily_counts.get(ts, 0) + int(value) |
37 | | - |
38 | | - # sort by timestamp |
39 | | - sorted_data = sorted(daily_counts.items()) |
40 | | - |
41 | | - labels = [datetime.utcfromtimestamp(ts / 1000).isoformat() for ts, _ in sorted_data] |
42 | | - values = [count for _, count in sorted_data] |
| 41 | + def get_dataset(event: str, color: str) -> dict: |
| 42 | + """Fills "data" array completely, supplying 0 for missing values.""" |
| 43 | + key = f"stats:build:{event}" |
| 44 | + result = ts.range(key, **range_options) if rc.exists(key) else [] |
| 45 | + data_map = dict(result) |
| 46 | + return { |
| 47 | + "label": event.title(), |
| 48 | + "data": [data_map.get(stamp, 0) for stamp in stamps], |
| 49 | + "color": color, |
| 50 | + } |
43 | 51 |
|
44 | 52 | return { |
45 | 53 | "labels": labels, |
46 | | - "datasets": [{"label": "Builds per day", "data": values}], |
| 54 | + "datasets": [ |
| 55 | + # See add_build_event for valid "event" values. |
| 56 | + get_dataset("requests", "green"), |
| 57 | + get_dataset("cache-hits", "orange"), |
| 58 | + get_dataset("failures", "red"), |
| 59 | + ], |
47 | 60 | } |
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