SQLite State

Use this skill when a recurring job must remember what it already did - which items it has alerted on, the last cursor it processed - so it does not re-notify or re-scrape on the next tick. One stdlib SQLite file gives durable, file-locked state with no server and no extra dependency.

When to invoke

• User says: "don't alert the same thing twice", "dedup across runs", "remember the last id", "resume where it left off".
• Code in the conversation is a cron/scheduled script that currently re-processes everything each run.

When NOT to invoke

• State is tiny and ephemeral within a single run - a plain set/dict is enough.
• Multiple machines must share state concurrently; reach for a real server DB instead of a single file.

Concrete example

User input:

My news scraper re-sends the same headlines every hour. Make it only send new ones.

Output:

from state import filter_new, mark_seen

db = "news.db"
fresh = filter_new(db, [a["url"] for a in articles])   # only unseen URLs
for url in fresh:
    send_alert(url)
mark_seen(db, *fresh)                                   # remember them for next run

Pattern to apply

1. Key each item by something stable and unique (URL, id, content hash), not by array position.
2. Use filter_new to decide what to act on, then mark_seen only after the action succeeds.
3. Store progress as a named cursor (set_cursor/get_cursor) so a resumable scraper restarts mid-stream.
4. Enable WAL mode for durable writes with concurrent readers; keep a single writer.
5. Back up or version the one .db file - it is the whole memory of the job.

Reference: assets/state.py.

Source

Distilled from production use across the author's automation projects. v1.0.0. See also: [[pipeline-orchestrator]], [[cron-dispatch]], [[webhook-receiver]].

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