signal-bot/signal_bot/analytics/usage.py
Krzysztof kuhy Rudnicki 405541be9b
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release: 0.2.6 «Stephanus I» — dodano !analityka
One row per command attempt, not two aggregates written only on success.

command_uses holds last-use only and daily_uses counts successes; both are
rate-limiter state and both are written by store.record_use, which the
dispatcher calls only when a handler returns cleanly. A gate refusal and a
crash returned before it, so a command that failed every time looked exactly
like one nobody ran, and nothing knew which command a counted message was.

command_events now takes every attempt with its outcome, its duration and
the item it served; upstream_calls takes every outbound request made while
serving one. The two writes stay separate on purpose -- recording a refusal
as a use is what slid the cooldown window forward every time somebody was
told to wait -- and test_dispatcher_outcomes asserts last_used does not move.

Backfilled from journald joined against message_events, with daily_uses
filling the residual so the two sources cannot double-count. Two things were
wrong on the first attempt and both were found by measuring rather than by
reasoning: the window has to be symmetric, because sent_at_ms comes from the
sender's phone and the journal stamp from this host (194 of 299 lines landed
*before* their own message, by up to 3.2 s); and matching has to be a global
closest-pair assignment, because per-row greedy cannot separate two commands
seconds apart. Together those took the dropped rows from 137 to zero, and
recovered 418 invocations back to 29 August.

Also: !analityka in the group, twelve Polish lines, naming at most three
people and only ones whose display name has been seen; an Analytics tab with
Nivo charts; and continuous latency measurement, which answers the open
question in DOCS-latency.md -- a text send is 235 ms and an image send about
2.2 s, so the upload really is where the time goes.

EPHEMERAL_TABLES was doing two unrelated jobs and is now two tuples: what a
schema bump rebuilds, and what leaving a group clears. daily_uses left the
first (it is a backfill source now) and stayed in the second, and
_drop_reshaped took over the repair a bump used to do for it.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01T4QTp3h5Q3MvfrwGV8xqPf
2026-08-31 23:19:51 +02:00

198 lines
6.2 KiB
Python

# Copyright (c) 2026 Krzysztof Rudnicki. MIT licence.
"""Family A: who uses which commands, how often, and which nobody uses.
Counts include every source. "How many times was !papież used" is answered
by all three classes of row -- a reconstructed invocation still happened.
Only the questions that need an hour or a duration narrow to ``live``, and
those live in ``hours`` and ``health``.
"""
from __future__ import annotations
from dataclasses import dataclass
from typing import TYPE_CHECKING, Final
if TYPE_CHECKING:
import sqlite3
from collections.abc import Sequence
from signal_bot.analytics.scope import Scope
@dataclass(frozen=True, slots=True)
class CommandUse:
"""One command, and everything countable about it."""
command: str
uses: int
people: int
ok: int
refused: int
errors: int
first_day: str
last_day: str
@property
def failure_rate(self) -> float:
"""Share of attempts that crashed. Refusals are not failures."""
return self.errors / self.uses if self.uses else 0.0
@property
def refusal_rate(self) -> float:
"""Share of attempts a gate turned away.
High is not popular, it is mis-tuned: it means people keep asking
and keep being told no.
"""
return self.refused / self.uses if self.uses else 0.0
@dataclass(frozen=True, slots=True)
class PersonUse:
"""One person's total, by uuid. Names are attached by the caller."""
uuid: str
uses: int
commands: int
favourite: str
BY_COMMAND_SQL: Final = """
SELECT command,
COUNT(*) AS uses,
COUNT(DISTINCT user_uuid) AS people,
SUM(outcome = 'ok') AS ok,
SUM(outcome LIKE 'refused_%') AS refused,
SUM(outcome = 'error') AS errors,
MIN(day) AS first_day,
MAX(day) AS last_day
FROM command_events
WHERE (:group IS NULL OR group_id = :group)
AND outcome != 'unknown_word'
GROUP BY command
ORDER BY uses DESC, command
"""
BY_PERSON_SQL: Final = """
SELECT user_uuid,
COUNT(*) AS uses,
COUNT(DISTINCT command) AS commands
FROM command_events
WHERE (:group IS NULL OR group_id = :group)
AND outcome = 'ok'
GROUP BY user_uuid
ORDER BY uses DESC, user_uuid
"""
FAVOURITE_SQL: Final = """
SELECT user_uuid, command, COUNT(*) AS uses
FROM command_events
WHERE (:group IS NULL OR group_id = :group)
AND outcome = 'ok'
GROUP BY user_uuid, command
ORDER BY user_uuid, uses DESC, command
"""
MATRIX_SQL: Final = """
SELECT user_uuid, command, COUNT(*) AS uses
FROM command_events
WHERE (:group IS NULL OR group_id = :group)
AND outcome = 'ok'
GROUP BY user_uuid, command
ORDER BY user_uuid, command
"""
TOTALS_SQL: Final = """
SELECT COUNT(*) AS attempts,
SUM(outcome = 'ok') AS ok,
COUNT(DISTINCT user_uuid) AS people,
COUNT(DISTINCT command) AS commands
FROM command_events
WHERE (:group IS NULL OR group_id = :group)
AND outcome != 'unknown_word'
"""
def by_command(conn: sqlite3.Connection, scope: Scope) -> list[CommandUse]:
"""Every command that has ever been attempted, most used first."""
return [
CommandUse(
command=str(row["command"]),
uses=int(row["uses"]),
people=int(row["people"]),
ok=int(row["ok"] or 0),
refused=int(row["refused"] or 0),
errors=int(row["errors"] or 0),
first_day=str(row["first_day"]),
last_day=str(row["last_day"]),
)
for row in conn.execute(BY_COMMAND_SQL, scope.params())
]
def _favourites(conn: sqlite3.Connection, scope: Scope) -> dict[str, str]:
"""Each person's most-used command.
The query orders by uses within each person, so the first row seen for
a uuid is the answer and the rest are skipped -- cheaper than a window
function and portable to the ancient sqlite a container might carry.
"""
best: dict[str, str] = {}
for row in conn.execute(FAVOURITE_SQL, scope.params()):
best.setdefault(str(row["user_uuid"]), str(row["command"]))
return best
def by_person(conn: sqlite3.Connection, scope: Scope) -> list[PersonUse]:
"""Who uses the bot, by uuid and most active first.
Deliberately returns uuids. Turning one into a name is the caller's job
and a different rule in each place: the group chat may name only people
whose display name has been seen, the management page may show
everyone, and neither may print a raw uuid or a phone number.
"""
favourites = _favourites(conn, scope)
return [
PersonUse(
uuid=str(row["user_uuid"]),
uses=int(row["uses"]),
commands=int(row["commands"]),
favourite=favourites.get(str(row["user_uuid"]), ""),
)
for row in conn.execute(BY_PERSON_SQL, scope.params())
]
def matrix(conn: sqlite3.Connection, scope: Scope) -> list[tuple[str, str, int]]:
"""Every (person, command, count) triple, for the heatmap on the page.
Never posted into a group -- a per-person breakdown of everybody's
habits is a management-page thing.
"""
return [
(str(row["user_uuid"]), str(row["command"]), int(row["uses"]))
for row in conn.execute(MATRIX_SQL, scope.params())
]
def totals(conn: sqlite3.Connection, scope: Scope) -> dict[str, int]:
"""Attempts, successes, distinct people and distinct commands."""
row = conn.execute(TOTALS_SQL, scope.params()).fetchone()
return {
"attempts": int(row["attempts"] or 0),
"ok": int(row["ok"] or 0),
"people": int(row["people"] or 0),
"commands": int(row["commands"] or 0),
}
def never_used(known: Sequence[str], used: Sequence[CommandUse]) -> list[str]:
"""Registered commands with no recorded attempt at all.
Takes the registry's list rather than reading it, because which commands
exist depends on the group -- the album's are registered only where the
album is -- and this module must not know that.
"""
seen = {use.command for use in used}
return sorted(name for name in known if name not in seen)