dirsql 0.0.25

Ephemeral SQL index over a local directory

dirsql (Python SDK)

Ephemeral SQL index over a local directory. Watches a filesystem, ingests structured files into an in-memory SQLite database, and exposes a SQL query interface. The database is purely in-memory -- the filesystem is always the source of truth.

Installation

pip install dirsql

Requires Python >= 3.12. Ships as a native extension (Rust via PyO3) -- binary wheels are provided for common platforms.

Quick Start

import asyncio
import json
import os
import tempfile
from dirsql import DirSQL, Table

async def main():
    # Create some data files
    root = tempfile.mkdtemp()
    os.makedirs(os.path.join(root, "comments", "abc"), exist_ok=True)
    os.makedirs(os.path.join(root, "comments", "def"), exist_ok=True)

    with open(os.path.join(root, "comments", "abc", "index.jsonl"), "w") as f:
        f.write(json.dumps({"body": "looks good", "author": "alice"}) + "\n")
        f.write(json.dumps({"body": "needs work", "author": "bob"}) + "\n")

    with open(os.path.join(root, "comments", "def", "index.jsonl"), "w") as f:
        f.write(json.dumps({"body": "agreed", "author": "carol"}) + "\n")

    # Define a table: DDL, glob pattern, and an extract function
    db = DirSQL(
        root,
        tables=[
            Table(
                ddl="CREATE TABLE comments (id TEXT, body TEXT, author TEXT)",
                glob="comments/**/index.jsonl",
                extract=lambda path, content: [
                    {
                        "id": os.path.basename(os.path.dirname(path)),
                        "body": row["body"],
                        "author": row["author"],
                    }
                    for line in content.splitlines()
                    for row in [json.loads(line)]
                ],
            ),
        ],
    )
    await db.ready()

    # Query with SQL
    results = await db.query("SELECT * FROM comments WHERE author = 'alice'")
    # [{"id": "abc", "body": "looks good", "author": "alice"}]

asyncio.run(main())

Multiple Tables and Joins

db = DirSQL(
    root,
    tables=[
        Table(
            ddl="CREATE TABLE posts (title TEXT, author_id TEXT)",
            glob="posts/*.json",
            extract=lambda path, content: [json.loads(content)],
        ),
        Table(
            ddl="CREATE TABLE authors (id TEXT, name TEXT)",
            glob="authors/*.json",
            extract=lambda path, content: [json.loads(content)],
        ),
    ],
)
await db.ready()

results = await db.query("""
    SELECT posts.title, authors.name
    FROM posts JOIN authors ON posts.author_id = authors.id
""")

Ignoring Files

Pass ignore patterns to skip files during scanning and watching:

db = DirSQL(
    root,
    ignore=["**/drafts/**", "**/.git/**"],
    tables=[...],
)

Watching for Changes

DirSQL is async by default. The watch() method returns an async iterator of row-level change events.

import asyncio
import json
from dirsql import DirSQL, Table

async def main():
    db = DirSQL(
        "/path/to/data",
        tables=[
            Table(
                ddl="CREATE TABLE items (name TEXT)",
                glob="**/*.json",
                extract=lambda path, content: [json.loads(content)],
            ),
        ],
    )
    await db.ready()

    # Query
    results = await db.query("SELECT * FROM items")

    # Watch for file changes (insert/update/delete/error events)
    async for event in db.watch():
        print(f"{event.action} on {event.table}: {event.row}")
        if event.action == "error":
            print(f"  error: {event.error}")

asyncio.run(main())

API Reference

Table(*, ddl, glob, extract)

Defines how files map to a SQL table.

• ddl (str): A CREATE TABLE statement defining the schema.
• glob (str): A glob pattern matched against file paths relative to root.
• extract (Callable[[str, str], list[dict]]): A function receiving (relative_path, file_content) and returning a list of row dicts. Each dict's keys must match the DDL column names.

DirSQL(root, *, tables, ignore=None)

Creates an in-memory SQLite database indexed from the directory at root. The constructor is sync and returns immediately; scanning runs in a background thread.

• root (str): Path to the directory to index.
• tables (list[Table]): Table definitions.
• ignore (list[str] | None): Glob patterns for paths to skip.

await DirSQL.ready()

Wait for the initial scan to complete. Idempotent -- safe to call multiple times. Raises any exception that occurred during init.

await DirSQL.query(sql) -> list[dict]

Execute a SQL query. Returns a list of dicts keyed by column name. Internal tracking columns (_dirsql_*) are excluded from results.

DirSQL.watch() -> AsyncIterator[RowEvent]

Returns an async iterator that yields RowEvent objects as files change on disk. Starts the filesystem watcher on first iteration.

DirSQL.from_config(path) -> DirSQL

Create a DirSQL instance from a .dirsql.toml config file. Returns immediately; scanning runs in the background. Call await db.ready() before querying.

RowEvent

Emitted by watch() when a file change produces row-level diffs.

• table (str): The affected table name.
• action (str): One of "insert", "update", "delete", "error".
• row (dict | None): The new row (for insert/update) or deleted row (for delete).
• old_row (dict | None): The previous row (for update only).
• error (str | None): Error message (for error events).
• file_path (str | None): The relative file path that triggered the event.

How It Works

The Rust core (rusqlite + notify + walkdir) does the heavy lifting:

1. Startup scan: Walks the directory tree, matches files to tables via glob patterns, calls the user-provided extract function for each file, and inserts rows into an in-memory SQLite database.
2. File watching: Uses the notify crate (inotify on Linux, FSEvents on macOS) to detect file creates, modifications, and deletions.
3. Row diffing: When a file changes, the new rows are diffed against the previous rows for that file, producing granular insert/update/delete events.
4. Python bindings: PyO3 exposes the Rust core as a native Python extension module. The async layer runs blocking operations in a thread pool via asyncio.to_thread.

License

MIT