oj-persistence 0.0.3

Thread-safe persistence management with pluggable storage backends

oj-persistence

Thread-safe persistence management with pluggable storage backends.

Installation

pip install oj-persistence

Install only the driver packages you need (see Storage backends):

pip install psycopg2-binary   # PostgreSQL via SqlAlchemyStore
pip install asyncpg           # PostgreSQL via AsyncSqlAlchemyStore
pip install pymysql           # MySQL/MariaDB via SqlAlchemyStore
pip install aiosqlite         # SQLite via AsyncSqliteStore / AsyncSqlAlchemyStore

Quick start

from oj_persistence import PersistenceManager, SqliteStore

pm = PersistenceManager()

# Register stores by name — all data ops go through the manager
pm.get_or_create('users', lambda: SqliteStore('users.db'))

pm.create('users', 'u1', {'name': 'Alice', 'role': 'admin'})
pm.upsert('users', 'u2', {'name': 'Bob',   'role': 'viewer'})

pm.read('users', 'u1')                                    # {'name': 'Alice', 'role': 'admin'}
pm.update('users', 'u1', {'name': 'Alice', 'role': 'owner'})
pm.delete('users', 'u2')

admins = pm.list('users', predicate=lambda v: v['role'] == 'owner')

CRUDL semantics

Method	Behaviour
create	Raises KeyError if key already exists
read	Returns None if key is missing
update	Raises KeyError if key does not exist
upsert	Creates or overwrites — never raises
delete	No-op if key is missing
list	Returns all values, optionally filtered

Storage backends

Choosing a backend

Use case	Recommended backend
Local file persistence, indexed key lookups	SqliteStore
External database (PostgreSQL, MySQL, SQL Server)	SqlAlchemyStore
Shared cache, high-throughput writes, TTL	RedisStore
Heterogeneous / schema-free documents	TinyDbStore
Append-heavy streaming, rarely rewritten records	NdjsonFileStore
Versioned records with full history	VersionedStore
Tests or ephemeral in-process caching	InMemoryStore

Sync backends

Class	Backed by	Notes
SqliteStore	SQLite (sqlite3)	O(log n) key ops; optional JSON field indexes; zero extra deps
SqlAlchemyStore	Any SQLAlchemy database	PostgreSQL, MySQL, SQL Server, Oracle via connection URL
RedisStore	Redis	Native key-value; SET NX/XX for strict create/update; SCAN-based list
TinyDbStore	TinyDB	Schema-free documents; native query DSL via .query()
InMemoryStore	In-process dict	Fastest; not persistent; no extra deps
VersionedStore	Any AbstractStore	Envelope wrapper; preserves full history; read_latest() and list_versions()
NdjsonFileStore	NDJSON file	O(1) append-creates; O(n) reads/updates; best for streaming writes
FlatFileStore	JSON file	Full load/save per op; simple but slow for large datasets
IjsonFileStore	JSON file	Streaming reads via ijson; lower memory than FlatFileStore
CsvFileStore	CSV file	Field values round-trip as strings

Async backends

Async backends implement AsyncAbstractStore and are designed for use with io_chains PersistenceLink and other async pipelines.

Class	Backed by	Notes
AsyncSqliteStore	SQLite	Wraps SqliteStore via asyncio.to_thread
AsyncSqlAlchemyStore	Any SQLAlchemy async database	Native async via create_async_engine; requires initialize() or context manager
AsyncRedisStore	Redis	Native async via redis.asyncio; SCAN-based list
AsyncInMemoryStore	In-process dict	Zero overhead; no locking needed (asyncio is single-threaded)
AsyncNdjsonFileStore	NDJSON file	Buffered writes flushed on context exit or batch-size trigger
AsyncVersionedStore	Any AsyncAbstractStore	Async envelope wrapper; full history with read_latest() and list_versions()

Usage examples

SqlAlchemyStore — external databases

from oj_persistence import SqlAlchemyStore

# PostgreSQL
store = SqlAlchemyStore('postgresql+psycopg2://user:pass@host/db')

# MySQL / MariaDB
store = SqlAlchemyStore('mysql+pymysql://user:pass@host/db')

# SQL Server via PyODBC
store = SqlAlchemyStore('mssql+pyodbc://user:pass@host/db?driver=ODBC+Driver+17+for+SQL+Server')

# Custom table name and engine options
store = SqlAlchemyStore('postgresql+psycopg2://...', table='my_cache', pool_size=10)

RedisStore

import redis
from oj_persistence import RedisStore

client = redis.Redis(host='redis.internal', port=6379, ssl=True)
store = RedisStore(client, prefix='myapp:users:')

store.upsert('u1', {'name': 'Alice'})
store.read('u1')   # {'name': 'Alice'}

TinyDbStore — document queries

from tinydb import where
from oj_persistence import TinyDbStore

store = TinyDbStore('data.json')
store.upsert('1', {'name': 'Alice', 'city': 'NYC'})
store.upsert('2', {'name': 'Bob',   'city': 'LA'})

# Standard AbstractStore interface
store.list(lambda v: v['city'] == 'NYC')

# TinyDB-native query DSL
store.query(where('_value')['city'] == 'NYC')

NdjsonFileStore — streaming writes

NDJSON is well-suited to pipelines that append many records and rarely need to rewrite existing ones. Reads and updates require a full file scan (O(n)), so it is not the right choice for key-lookup-heavy workloads.

from oj_persistence import NdjsonFileStore

store = NdjsonFileStore('events.ndjson')
store.create('evt:1', {'type': 'login', 'user': 'u1'})   # O(1) append
store.read('evt:1')                                        # O(n) scan

SqliteStore — JSON field indexes and list_by_field

SQL-backed stores support pushing equality filters into the database so an index is actually exercised — skipping the Python-side predicate scan entirely.

from oj_persistence import SqliteStore

store = SqliteStore('users.db')
store.upsert('u1', {'name': 'Alice', 'role': 'admin'})
store.upsert('u2', {'name': 'Bob',   'role': 'viewer'})

# Create a database index on a JSON field
store.add_json_index('$.role')

# Filter pushed into SQL — index is used
admins = store.list_by_field('$.role', 'admin')   # [{'name': 'Alice', 'role': 'admin'}]

list_by_field and add_json_index are available on SqliteStore, AsyncSqliteStore, SqlAlchemyStore, and AsyncSqlAlchemyStore.

Via the manager:

pm.list_by_field('users', '$.role', 'admin')
await async_pm.list_by_field('users', '$.role', 'admin')

VersionedStore — full history with latest-read

Wrap any store to store every write as an immutable version, keyed by {key}#{seq}. Standard CRUDL operates on the latest version; the full history is always available.

from oj_persistence import VersionedStore, SqliteStore

store = VersionedStore(SqliteStore('history.db'))

store.upsert('u1', {'name': 'Alice', 'role': 'admin'})
store.upsert('u1', {'name': 'Alice', 'role': 'owner'})  # second version

store.read_latest('u1')    # {'name': 'Alice', 'role': 'owner'}
store.list_versions('u1')  # [{_key, _seq, _inserted_at, _value}, ...]
store.list()               # [latest value per key]

The async variant AsyncVersionedStore mirrors this interface with await.

AsyncPersistenceManager — async registry

AsyncPersistenceManager is the async counterpart to PersistenceManager. Registry methods (register, get_store, get_or_create, unregister) are synchronous; all data operations are async.

from oj_persistence import AsyncPersistenceManager, AsyncSqliteStore

pm = AsyncPersistenceManager()
pm.get_or_create('users', lambda: AsyncSqliteStore('users.db'))

await pm.upsert('users', 'u1', {'name': 'Alice'})
await pm.read('users', 'u1')

# SQL pushdown via list_by_field
await pm.list_by_field('users', '$.role', 'admin')

# Relational join across two async stores
ON = lambda u, o: u['id'] == o['user_id']
pairs = await pm.join('users', 'orders', on=ON, how='left')

Async pipeline (io_chains PersistenceLink)

import redis.asyncio as aioredis
from oj_persistence import AsyncRedisStore, AsyncSqlAlchemyStore

# Redis — zero-latency writes in a hot pipeline
client = aioredis.Redis(host='redis.internal')
store = AsyncRedisStore(client, prefix='feed:')

async with store:
    await store.upsert('item:1', {'title': 'Breaking news'})

# PostgreSQL — durable writes via asyncpg
async with AsyncSqlAlchemyStore('postgresql+asyncpg://user:pass@host/db') as store:
    await store.upsert('item:1', {'title': 'Breaking news'})

File store compression

All file-backed stores (NdjsonFileStore, CsvFileStore, FlatFileStore, IjsonFileStore) accept a compression parameter. Compression is applied transparently at open time — no changes to CRUDL calls.

from oj_persistence import NdjsonFileStore, CsvFileStore

# Explicit codec
store = NdjsonFileStore('data.ndjson.gz', compression='gzip')

# Auto-detect from extension (.gz, .bz2, .xz, .lzma)
store = CsvFileStore('data.csv.gz', compression='auto')

store.upsert('u1', {'name': 'Alice', 'role': 'admin'})
store.read('u1')   # decompressed transparently

Supported codecs: 'gzip', 'bz2', 'lzma' (also matches .xz), 'auto'.

Streaming files to disk — from_stream / stream_to_file

Download a byte stream directly to disk, then open it as a store. Two patterns are supported: a one-step classmethod or a standalone utility.

One step (recommended):

import httpx
from oj_persistence import CsvFileStore, NdjsonFileStore

async with httpx.AsyncClient() as client:
    response = await client.get('https://example.com/users.csv.gz', stream=True)

    # Stream bytes to disk, decompress on open
    store = await CsvFileStore.from_stream(
        response.aiter_bytes(),
        '/tmp/users.csv.gz',
        compression='auto',
    )

users = store.list()

Two steps (store the file, open later):

from oj_persistence.utils.streaming import stream_to_file, stream_to_file_sync

# Async
path = await stream_to_file(response.aiter_bytes(), '/tmp/data.ndjson')

# Sync (also accepts file-like objects with .read())
import requests
r = requests.get('https://example.com/data.ndjson', stream=True)
path = stream_to_file_sync(r.iter_content(chunk_size=65536), '/tmp/data.ndjson')

store = NdjsonFileStore(path)

stream_to_file accepts AsyncIterable[bytes], Iterable[bytes], or any file-like object with a .read(n) method. Writes go to a UUID-named temp file in the same directory and are renamed atomically on success. On failure the temp file is deleted unless debug=True (or OJ_PERSISTENCE_DEBUG=1 is set in the environment).

# Leave temp files on disk for inspection after failures
path = await stream_to_file(source, '/tmp/out.ndjson', debug=True)

# Or set the environment variable once for the whole process
# OJ_PERSISTENCE_DEBUG=1 python my_script.py

Relational joins

ON = lambda user, order: user['id'] == order['user_id']

results = pm.join('users', 'orders', on=ON, how='left',
                  where=lambda u, o: o['total'] > 100)
# returns list of (left_val, right_val) tuples; unmatched sides are None

Supported how values: inner (default), left, right, outer.

Note: joins call list() on both stores and perform an O(m × n) nested loop in Python. For large datasets, prefer a query pushed down to the database via SqlAlchemyStore or SqliteStore.

Custom stores

from oj_persistence.store.base import AbstractStore             # sync
from oj_persistence.store.async_base import AsyncAbstractStore  # async
from oj_persistence.store.abstract_file import AbstractFileStore  # file-backed (adds compression + from_stream)

class MyStore(AbstractStore):
    def create(self, key, value): ...
    def read(self, key): ...
    def update(self, key, value): ...
    def upsert(self, key, value): ...
    def delete(self, key): ...
    def list(self, predicate=None): ...

pm.register('custom', MyStore())

Inherit from AbstractFileStore to get compression and from_stream / from_stream_sync for free in any file-backed custom store.

Requirements

• Python >= 3.11
• ijson — required for IjsonFileStore
• tinydb — required for TinyDbStore
• sqlalchemy>=2.0 — required for SqlAlchemyStore / AsyncSqlAlchemyStore
• redis>=5.0 — required for RedisStore / AsyncRedisStore

Database drivers (install only what you need):

Backend	Sync driver	Async driver
PostgreSQL	psycopg2-binary	asyncpg
MySQL / MariaDB	pymysql	aiomysql
SQL Server	pyodbc	—
SQLite	stdlib sqlite3	aiosqlite

For testing without a live Redis server: pip install "fakeredis[lua]".