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[loop-cycle-50] refactor: replace bare sqlite3.connect() with context managers batch 2 (#157) (#180)

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This commit is contained in:
hermes
2026-03-15 11:58:43 -04:00
parent bea2749158
commit bcd6d7e321
16 changed files with 512 additions and 510 deletions
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159
src/spark/memory.py
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@@ -13,6 +13,8 @@ spark_memories — consolidated insights extracted from event patterns
import logging
import sqlite3
import uuid
from collections.abc import Generator
from contextlib import closing, contextmanager
from dataclasses import dataclass
from datetime import UTC, datetime
from pathlib import Path
@@ -55,42 +57,43 @@ class SparkMemory:
expires_at: str | None
def _get_conn() -> sqlite3.Connection:
@contextmanager
def _get_conn() -> Generator[sqlite3.Connection, None, None]:
DB_PATH.parent.mkdir(parents=True, exist_ok=True)
conn = sqlite3.connect(str(DB_PATH))
conn.row_factory = sqlite3.Row
conn.execute("PRAGMA journal_mode=WAL")
conn.execute("PRAGMA busy_timeout=5000")
conn.execute("""
CREATE TABLE IF NOT EXISTS spark_events (
id TEXT PRIMARY KEY,
event_type TEXT NOT NULL,
agent_id TEXT,
task_id TEXT,
description TEXT NOT NULL DEFAULT '',
data TEXT NOT NULL DEFAULT '{}',
importance REAL NOT NULL DEFAULT 0.5,
created_at TEXT NOT NULL
)
""")
conn.execute("""
CREATE TABLE IF NOT EXISTS spark_memories (
id TEXT PRIMARY KEY,
memory_type TEXT NOT NULL,
subject TEXT NOT NULL DEFAULT 'system',
content TEXT NOT NULL,
confidence REAL NOT NULL DEFAULT 0.5,
source_events INTEGER NOT NULL DEFAULT 0,
created_at TEXT NOT NULL,
expires_at TEXT
)
""")
conn.execute("CREATE INDEX IF NOT EXISTS idx_events_type ON spark_events(event_type)")
conn.execute("CREATE INDEX IF NOT EXISTS idx_events_agent ON spark_events(agent_id)")
conn.execute("CREATE INDEX IF NOT EXISTS idx_events_task ON spark_events(task_id)")
conn.execute("CREATE INDEX IF NOT EXISTS idx_memories_subject ON spark_memories(subject)")
conn.commit()
return conn
with closing(sqlite3.connect(str(DB_PATH))) as conn:
conn.row_factory = sqlite3.Row
conn.execute("PRAGMA journal_mode=WAL")
conn.execute("PRAGMA busy_timeout=5000")
conn.execute("""
CREATE TABLE IF NOT EXISTS spark_events (
id TEXT PRIMARY KEY,
event_type TEXT NOT NULL,
agent_id TEXT,
task_id TEXT,
description TEXT NOT NULL DEFAULT '',
data TEXT NOT NULL DEFAULT '{}',
importance REAL NOT NULL DEFAULT 0.5,
created_at TEXT NOT NULL
)
""")
conn.execute("""
CREATE TABLE IF NOT EXISTS spark_memories (
id TEXT PRIMARY KEY,
memory_type TEXT NOT NULL,
subject TEXT NOT NULL DEFAULT 'system',
content TEXT NOT NULL,
confidence REAL NOT NULL DEFAULT 0.5,
source_events INTEGER NOT NULL DEFAULT 0,
created_at TEXT NOT NULL,
expires_at TEXT
)
""")
conn.execute("CREATE INDEX IF NOT EXISTS idx_events_type ON spark_events(event_type)")
conn.execute("CREATE INDEX IF NOT EXISTS idx_events_agent ON spark_events(agent_id)")
conn.execute("CREATE INDEX IF NOT EXISTS idx_events_task ON spark_events(task_id)")
conn.execute("CREATE INDEX IF NOT EXISTS idx_memories_subject ON spark_memories(subject)")
conn.commit()
yield conn
# ── Importance scoring ──────────────────────────────────────────────────────
@@ -149,17 +152,16 @@ def record_event(
parsed = {}
importance = score_importance(event_type, parsed)
conn = _get_conn()
conn.execute(
"""
INSERT INTO spark_events
(id, event_type, agent_id, task_id, description, data, importance, created_at)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
""",
(event_id, event_type, agent_id, task_id, description, data, importance, now),
)
conn.commit()
conn.close()
with _get_conn() as conn:
conn.execute(
"""
INSERT INTO spark_events
(id, event_type, agent_id, task_id, description, data, importance, created_at)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
""",
(event_id, event_type, agent_id, task_id, description, data, importance, now),
)
conn.commit()
# Bridge to unified event log so all events are queryable from one place
try:
@@ -188,7 +190,6 @@ def get_events(
min_importance: float = 0.0,
) -> list[SparkEvent]:
"""Query events with optional filters."""
conn = _get_conn()
query = "SELECT * FROM spark_events WHERE importance >= ?"
params: list = [min_importance]
@@ -205,8 +206,8 @@ def get_events(
query += " ORDER BY created_at DESC LIMIT ?"
params.append(limit)
rows = conn.execute(query, params).fetchall()
conn.close()
with _get_conn() as conn:
rows = conn.execute(query, params).fetchall()
return [
SparkEvent(
id=r["id"],
@@ -224,15 +225,14 @@ def get_events(
def count_events(event_type: str | None = None) -> int:
"""Count events, optionally filtered by type."""
conn = _get_conn()
if event_type:
row = conn.execute(
"SELECT COUNT(*) FROM spark_events WHERE event_type = ?",
(event_type,),
).fetchone()
else:
row = conn.execute("SELECT COUNT(*) FROM spark_events").fetchone()
conn.close()
with _get_conn() as conn:
if event_type:
row = conn.execute(
"SELECT COUNT(*) FROM spark_events WHERE event_type = ?",
(event_type,),
).fetchone()
else:
row = conn.execute("SELECT COUNT(*) FROM spark_events").fetchone()
return row[0]
@@ -250,17 +250,16 @@ def store_memory(
"""Store a consolidated memory. Returns the memory id."""
mem_id = str(uuid.uuid4())
now = datetime.now(UTC).isoformat()
conn = _get_conn()
conn.execute(
"""
INSERT INTO spark_memories
(id, memory_type, subject, content, confidence, source_events, created_at, expires_at)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
""",
(mem_id, memory_type, subject, content, confidence, source_events, now, expires_at),
)
conn.commit()
conn.close()
with _get_conn() as conn:
conn.execute(
"""
INSERT INTO spark_memories
(id, memory_type, subject, content, confidence, source_events, created_at, expires_at)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
""",
(mem_id, memory_type, subject, content, confidence, source_events, now, expires_at),
)
conn.commit()
return mem_id
@@ -271,7 +270,6 @@ def get_memories(
limit: int = 50,
) -> list[SparkMemory]:
"""Query memories with optional filters."""
conn = _get_conn()
query = "SELECT * FROM spark_memories WHERE confidence >= ?"
params: list = [min_confidence]
@@ -285,8 +283,8 @@ def get_memories(
query += " ORDER BY created_at DESC LIMIT ?"
params.append(limit)
rows = conn.execute(query, params).fetchall()
conn.close()
with _get_conn() as conn:
rows = conn.execute(query, params).fetchall()
return [
SparkMemory(
id=r["id"],
@@ -304,13 +302,12 @@ def get_memories(
def count_memories(memory_type: str | None = None) -> int:
"""Count memories, optionally filtered by type."""
conn = _get_conn()
if memory_type:
row = conn.execute(
"SELECT COUNT(*) FROM spark_memories WHERE memory_type = ?",
(memory_type,),
).fetchone()
else:
row = conn.execute("SELECT COUNT(*) FROM spark_memories").fetchone()
conn.close()
with _get_conn() as conn:
if memory_type:
row = conn.execute(
"SELECT COUNT(*) FROM spark_memories WHERE memory_type = ?",
(memory_type,),
).fetchone()
else:
row = conn.execute("SELECT COUNT(*) FROM spark_memories").fetchone()
return row[0]