Freshness evaluation
Compares each supplied backup timestamp with an explicit per-site age limit using a reproducible reference time.
Day 028 / Frappe / Backup Operations
Backup Freshness Checker
/ Overview
A dependency-free Python CLI that evaluates sanitized backup timestamps against explicit freshness limits without opening archives or connecting to a live site.
A backup job can appear configured while its latest usable timestamp is already too old, absent or incorrectly dated in the future. Reviewing mixed timestamps manually also invites timezone mistakes.
/ Provided servicesClear thinking.
Clear thinking.
Practical delivery.
Honest classifications
Separates stale, missing and future-dated metadata instead of collapsing every problem into one generic failure.
Read-only reporting
Produces deterministic text or JSON while keeping archives, credentials, databases and backup schedules out of scope.
/ Solution
Backup Freshness Checker validates a bounded JSON list, normalizes timezone-aware timestamps to UTC, compares each age with its explicit limit and reports fresh, stale, missing or future status. It reads supplied metadata only and never discovers, opens, restores, deletes or changes a backup.
/ Impact
Four explicit freshness states
Timezone-aware age calculation
Per-site age limits
Bounded allowlisted JSON input
No archive or live-site access
Eleven passing standard-library tests
Python standard library
Argparse, dataclasses, datetime, pathlib and JSON provide the complete dependency-free command-line workflow.
Backup operations
Models explicit freshness policies and timezone-aware timestamps without claiming that age alone proves restore integrity.
Unittest
Eleven tests cover boundaries, stale, missing and future states, clock skew, validation, sorting and the non-mutating notice.