kanta/docs/database.md

Kanta Database Format and Design Principles

This document describes the on-disk format and design principles of Kanta. It is intentionally focused on the current standalone package behavior.

Core Principles

1. Append-only durability

• State changes are persisted as appended JSON lines.
• Existing lines are never edited in place.

2. Differential persistence

• Kanta stores diffs (patches), not full state, for normal writes.
• This keeps write volume small and preserves a clear change history.

3. Deterministic replay

• Current state is reconstructed by replaying log records in order.
• Snapshot records accelerate replay while preserving deterministic results.

4. Transactional in-memory writes

• Application code mutates in-memory data inside kanta.transaction(...).
• On success, Kanta computes and queues a diff record.
• On failure, in-memory data is rolled back.

5. Explicit schema evolution

• Schema migration functions are versioned (migrate_vN).
• Migrations run at open time and advance the stored version.

On-Disk Record Types

Kanta uses a newline-delimited stream where each line is either a change record or a snapshot record.

Change record

One JSON object per line:

{"ts":"2026-06-10T02:55:00Z","a":"update","v":5,"u":"user-id","m":"2026-06-10T02:55:00Z","diff":{"users":{"alice":{"age":31}}}}

Fields:

• ts: UTC timestamp of the record.
• a: action name.
• v: schema version after this change.
• u: optional actor identifier.
• m: optional domain modification timestamp.
• diff: jsondiff patch payload.

Snapshot record

Snapshot lines are prefixed with SNAPSHOT , followed by JSON:

SNAPSHOT {"ts":"2026-06-10T00:00:00Z","v":5,"state":{"users":{}},"m":"2026-06-10T00:00:00Z"}

Fields:

• ts: snapshot creation time.
• v: schema version represented by the snapshot.
• state: full state dictionary.
• m: optional domain modification timestamp.

Replay Model

1. Find the last snapshot in the file, if present.
2. Initialize replay state from snapshot state (or {} if none).
3. Replay subsequent change records in order using patch application.
4. The final replay state becomes in-memory kanta.data.

This model provides fast startup for large logs while retaining append-only history.

Serialization Semantics

• In-memory data is defined by an application msgspec.Struct type.
• Kanta round-trips through plain builtins for persistence and diffing.
• Dict keys are serialized as strings (str_keys=True) for stable JSON form.
• Normalization changes introduced by struct decode/encode are logged as migrate:msgspec when they produce a diff.

Transaction Semantics

• kanta.transaction(action=...) captures a pre-transaction snapshot dict.
• By default a transaction updates the modification time m to the current UTC time.
• mtime=True|False|datetime controls the modification time m:
  • True (default) sets m to the current UTC time.
  • False omits m, leaving the previous modification time in effect.
  • A datetime sets m to that explicit value.
• System operations such as migrate:msgspec use mtime=False so they are not considered modifications and do not advance m.
• On success:
  • compute diff between previous builtins and current builtins,
  • queue a ChangeRecord if non-empty,
  • update kanta.mtime when the change carries an m value.
• On exception:
  • restore in-memory data from snapshot,
  • re-raise the exception.

Nested transactions are rejected.

Modification Time

kanta.mtime exposes the last modification time carried forward from change records. It is updated by normal transactions and preserved across snapshots and reloads, while system operations such as migrations leave it unchanged.

Flush and Lifecycle

• Writes are queued in memory.
• kanta.flush() appends queued records to disk.
• A background async task can flush periodically.
• kanta.close() performs final flush and releases file resources.
• async with Kanta(...) guarantees open/close lifecycle management.

Open Modes

• await kanta.open() (default) creates the database file if missing.
• await kanta.open(create=False) fails when the file is missing or empty.

Callbacks

All callbacks are registered via decorators and receive arguments by their annotation types. Parameters without a supported annotation are only allowed when they have a default value.

Bootstrap Callbacks

• Bootstrap callbacks run during open() when the database is empty.
• Register callbacks via:
  • @kanta.bootstrap
  • @kanta.bootstrap(action=..., user=..., mtime=...)
• Bootstrap callbacks may be sync or async. The live root data object is injected by annotating a parameter with the struct type passed to Kanta, and the Kanta instance itself can be injected by annotating a parameter with Kanta.
• Multiple bootstrap callbacks are supported:
  • callbacks execute in registration order,
  • exactly one bootstrap ChangeRecord is queued,
  • bootstrap metadata (action, user, mtime) is taken from the last callback registration.
• If any bootstrap callback raises, Kanta closes and removes the database file, then re-raises the exception.

Fatal Error Handlers

• Fatal background persistence errors can be handled with @kanta.fatal_error.
• Handlers may be sync or async. The DatabaseError is injected by annotating a parameter with DatabaseError; Kanta may also be injected.
• Multiple handlers are supported and invoked in registration order. A failing handler is logged and does not prevent subsequent handlers from running.

Transaction Log Formatting

• Logfmt callbacks prettify identifiers in the change log and are registered with @kanta.logfmt.
• A logfmt callback is called for every value Kanta renders: diff values, path components, and the transaction user. It receives the value as its first parameter and optionally a path: str parameter with the dot-notation path to the value. The special path "$user" is used when rendering the transaction actor, replacing the old user_display parameter.
• The callback returns str | None: a string replaces the default rendering, while None means "fall through to the next formatter".
• State dicts can be injected via DictPre (Annotated[dict, "pre"]) and DictPost (Annotated[dict, "post"]); the Kanta instance can also be injected.
• Alternatively, a logfmt callback can be a class inheriting from LogFmt; the framework instantiates it with the state dicts and calls its resolve(value, path) -> str | None method.
• Multiple logfmt callbacks are stacked in registration order; the first callback to return a non-None result wins. If none handle a value, Kanta falls back to its default formatting.

The decorator accepts an optional path so the callback only runs for values at that exact path:

@kanta.logfmt(path="$user")
def resolve_user(value: str, current: DictPost) -> str | None:
    return current.get("users", {}).get(value, {}).get("name")

@kanta.logfmt(path="users.uuid-1")
def resolve_user_key(value: str) -> str | None:
    return names_by_id.get(value)

Migrations

• Migration source is configured on Kanta(...) via migrations=.
• Accepted values:
  • imported module object,
  • import path string.
• Migrations mutate replayed dict state in-place and return the new version.

Safety Invariants

• Any detected out-of-transaction mutation is treated as a fatal consistency violation.
• Flush failures mark the instance as failed and trigger shutdown behavior.
• Object identity of kanta.data is preserved across rollback when possible, minimizing stale-reference hazards for callers.