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Python bindings for MongrelDB Kit — the application-facing persistence layer (schema model, migrations, relational constraints, query APIs, embedded SQL, storage tuning) for MongrelDB. Runs the columnar engine in-process via PyO3.

Project description

MongrelDB logo

MongrelDB Kit

The application-facing persistence layer for MongrelDB - schema-aware query builder, migrations, relational constraints, and stable semantics across TypeScript, Rust, Python, and CLI surfaces.

crates.io npm PyPI

Packages And Tools

Surface Package / crate Install or run
TypeScript @visorcraft/mongreldb-kit npm install @visorcraft/mongreldb-kit @visorcraft/mongreldb
Rust mongreldb-kit cargo add mongreldb-kit
Python mongreldb-kit pip install mongreldb-kit
CLI mongreldb-kit-cli (mongreldb-kit binary) cargo run -p mongreldb-kit-cli -- --help

What It Provides

  • Schema helpers for typed tables, stable table/column ids, defaults, indexes, checks, unique constraints, and foreign keys. Full type set: int64, float64, bool, text, bytes (BLOB), timestamp, date, date64, time64, interval, decimal128, UUID, JSON, and array columns.
  • Synchronous TypeScript CRUD/query builder with predicates, ordering, projections, aggregates, joins, subqueries, CTEs, batch inserts, updates, and deletes.
  • Rust and Python APIs backed by the same Rust core and verified with cross-language conformance fixtures.
  • Migration runner with content-addressed checksums, stored schema catalog, table renames, and SQL views.
  • Embedded SQL surface (sql / sqlArrow / sqlRows) with recursive CTEs, window functions, CREATE TABLE AS SELECT, materialized views, multi-statement execution, and a mongreldb_fts_rank relevance-scoring UDF.
  • Storage tuning (spill thresholds, compaction zstd, result-cache sizing, index build policy), trigger config, and per-table introspection (run count, page-cache stats, memtable/cache lengths).
  • Non-blocking async I/O variants (putAsync / queryAsync / countAsync / …) and WriteBuffer micro-batching for high-throughput ingest (TypeScript).
  • Engine-side trigger management plus SQL-backed virtual/external table helpers.
  • Extended SQL Function helpers for JSON, date/time, aggregate, and math-style SQL calls.
  • User/role/credentials management with optional storage-layer enforcement: Argon2id-hashed catalog users, roles, GRANT/REVOKE table-level permissions, daemon HTTP Basic + Bearer auth, and opt-in require_auth credential enforcement (credentialed open/create constructors, enable_auth/disable_auth, offline recovery) - exposed through every language API, the embedded SQL surface, and the CLI (user / role / auth subcommands).
  • Relational constraint enforcement on top of MongrelDB transactions: not-null, type/range/string validation, unique/composite unique, foreign keys, and cascade/set-null/restrict deletes.
  • Multi-process file locking, replication, and change-data-capture via the daemon.

Documentation

History retention and time-travel reads

Both the embedded KitDatabase and the daemon client RemoteDatabase expose history-retention controls:

// TypeScript
db.setHistoryRetentionEpochs(100);   // embedded: number argument
remote.setHistoryRetentionEpochs(100n); // remote: bigint argument
console.log(db.historyRetentionEpochs());     // bigint
console.log(remote.historyRetentionEpochs()); // bigint
console.log(db.earliestRetainedEpoch());      // bigint
# Python (embedded)
db.set_history_retention_epochs(100)
print(db.history_retention_epochs())  # int
print(db.earliest_retained_epoch())   # int

# Python (remote)
remote.set_history_retention_epochs(100)
print(remote.history_retention_epochs())
print(remote.earliest_retained_epoch())

Set retention before writing the data you want to time-travel back to. Embedded databases initially keep only the latest epoch. The daemon defaults to 1024 epochs unless MONGRELDB_HISTORY_RETENTION_EPOCHS overrides it. Increasing retention later cannot restore history that has already been removed. Read past snapshots with db.rowsAtEpoch('table', epoch) (embedded) or SELECT ... AS OF EPOCH <epoch> (embedded SQL and the daemon).

Quick Example

Minimal TypeScript schema and CRUD flow:

TypeScript

import {
  KitDatabase,
  Schema,
  table,
  int,
  text,
  sequenceDefault,
  unique,
  eq
} from '@visorcraft/mongreldb-kit';

const users = table('users', {
  columns: [
    int('id', { primaryKey: true, default: sequenceDefault('users_id_seq') }),
    text('email', { nullable: false }),
    text('name', { nullable: true })
  ],
  primaryKey: 'id',
  unique: [unique(['email'], { name: 'users_email_uq' })]
});

const schema = new Schema([users]);
const db = KitDatabase.openSync('./app-data', schema);

db.migrateSync(schema, [
  {
    version: 1,
    name: 'initial',
    up({ ensureTable }) {
      ensureTable(users);
    }
  }
]);

const alice = db.insertInto(users)
  .values({ email: 'alice@example.com', name: 'Alice' })
  .executeSync();

const [row] = db.selectFrom(users)
  .where(eq(users.id, alice.id))
  .executeSync();

console.log(row);
db.close();

See the language docs for complete runnable examples in TypeScript, Rust, and Python.

Development Notes

  • TypeScript requires Node.js 22+ and the native @visorcraft/mongreldb peer dependency.
  • A MongrelDB database path is a data directory, not a single database file.
  • In this mono-repo checkout, the TypeScript package loads the native addon from the sibling MongrelDB repo. Build crates/mongreldb-node there with npm run build in release mode before benchmarking; stale debug .node builds make bulk paths much slower.

Building and testing

# Rust
rtk cargo check --workspace
rtk cargo test --workspace

# TypeScript
cd packages/kit
rtk npm ci
rtk npm run build
rtk npm run check
rtk npm test

# Python
cd python/mongreldb_kit
rtk python -m venv .venv
rtk .venv/bin/pip install maturin
rtk maturin develop
rtk .venv/bin/pytest ../../python/tests ../../tests/conformance/python

# CLI
rtk cargo run -p mongreldb-kit-cli -- --help

License

MIT OR Apache-2.0

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