scruby 0.36.5

Asynchronous library for building and managing a hybrid database, by scheme of key-value.

Scruby (small shrub)

Asynchronous library for building and managing a hybrid database,
by scheme of key-value.

The library uses fractal-tree addressing and
the search for documents based on the effect of a quantum loop.
The database consists of collections.
The maximum size of the one collection is 16**8=4294967296 branches,
each branch can store one or more keys.
The value of any key in collection can be obtained maximum in 8 steps,
thereby achieving high performance.
The effectiveness of the search for documents based on a quantum loop,
requires a large number of processor threads.

Installation

uv add scruby

Run

# Run Development:
uv run python main.py
# Run Production:
uv run python -OOP main.py

Usage

"""Working with keys."""

import anyio
from datetime import datetime
from zoneinfo import ZoneInfo
from typing import Annotated
from pydantic import EmailStr, Field
from pydantic_extra_types.phone_numbers import PhoneNumber, PhoneNumberValidator
from scruby import Scruby, ScrubyModel, ScrubySettings
from pprint import pprint as pp


class User(ScrubyModel):
    """User model."""
    first_name: str = Field(strict=True)
    last_name: str = Field(strict=True)
    birthday: datetime = Field(strict=True)
    email: EmailStr = Field(strict=True)
    phone: Annotated[PhoneNumber, PhoneNumberValidator(number_format="E164")] = Field(frozen=True)
    # key is always at bottom
    key: str = Field(
        strict=True,
        frozen=True,
        default_factory=lambda data: data["phone"],
    )


async def main() -> None:
    """Example."""
    # Create/get the `User` collection.
    user_coll = await Scruby.collection(User)

    # Create user
    user = User(
        first_name="John",
        last_name="Smith",
        birthday=datetime(1970, 1, 1, tzinfo=ZoneInfo("UTC")),
        email="[e-mail]",
        phone="[phone]",
    )

    # Add data of user to collection.
    await user_coll.add_doc(user)

    # Update user data in a collection
    await user_coll.update_doc(user)

    # Update user details
    user = await user_coll.get_doc("[phone]")
    pp(user)

    # Check for the presence of a key in the collection
    await user_coll.has_key("[phone]")  # => True

    # Delete a document by key
    await user_coll.delete_doc("[phone]")

    # Full database deletion.
    # Hint: The main purpose is tests.
    Scruby.napalm()


if __name__ == "__main__":
    anyio.run(main)

"""Find one document matching the filter.

The search is based on the effect of a quantum loop.
The search effectiveness depends on the number of processor threads.
"""

import anyio
from pydantic import Field
from scruby import Scruby, ScrubyModel, ScrubySettings
from pprint import pprint as pp


class Phone(ScrubyModel):
    """Phone model."""
    brand: str = Field(strict=True, frozen=True)
    model: str = Field(strict=True, frozen=True)
    screen_diagonal: float = Field(strict=True)
    matrix_type: str = Field(strict=True)
    # key is always at bottom
    key: str = Field(
        strict=True,
        frozen=True,
        default_factory=lambda data: f"{data['brand']}:{data['model']}",
    )


async def main() -> None:
    """Example."""
    # Create/Get collection `Phone`.
    phone_coll = await Scruby.collection(Phone)

    # Create phone.
    phone = Phone(
        brand="Samsung",
        model="Galaxy A26",
        screen_diagonal=6.7,
        matrix_type="Super AMOLED",
    )

    # Add phone to collection.
    await phone_coll.add_doc(phone)

    # Find phone by brand.
    phone_details: Phone | None = await phone_coll.find_one(
        filter_fn=lambda doc: doc.brand == "Samsung",
    )
    if phone_details is not None:
        pp(phone_details)
    else:
        print("No Phone!")

    # Find phone by model.
    phone_details: Phone | None = await phone_coll.find_one(
        filter_fn=lambda doc: doc.model == "Galaxy A26",
    )
    if phone_details is not None:
        pp(phone_details)
    else:
        print("No Phone!")

    # Full database deletion.
    # Hint: The main purpose is tests.
    Scruby.napalm()


if __name__ == "__main__":
    anyio.run(main)

"""Find many documents matching the filter.

The search is based on the effect of a quantum loop.
The search effectiveness depends on the number of processor threads.
"""

import anyio
from pydantic import Field
from scruby import Scruby, ScrubyModel, ScrubySettings
from pprint import pprint as pp


class Car(ScrubyModel):
    """Car model."""
    brand: str = Field(strict=True, frozen=True)
    model: str = Field(strict=True, frozen=True)
    year: int = Field(strict=True)
    power_reserve: int = Field(strict=True)
    # key is always at bottom
    key: str = Field(
        strict=True,
        frozen=True,
        default_factory=lambda data: f"{data['brand']}:{data['model']}",
    )


async def main() -> None:
    """Example."""
    # Get collection `Car`.
    car_coll = await Scruby.collection(Car)

    # Create cars.
    for num in range(1, 10):
        car = Car(
            brand="Mazda",
            model=f"EZ-6 {num}",
            year=2025,
            power_reserve=600,
        )
        await car_coll.add_doc(car)

    # Find cars by brand and year.
    car_list: list[Car] | None = await car_coll.find_many(
        filter_fn=lambda doc: doc.brand == "Mazda" and doc.year == 2025,
    )
    if car_list is not None:
        pp(car_list)
    else:
        print("No cars!")

    # Find all cars.
    car_list: list[Car] | None = await car_coll.find_many()
    if car_list is not None:
        pp(car_list)
    else:
        print("No cars!")

    # For pagination output.
    car_list: list[Car] | None = await car_coll.find_many(
        filter_fn=lambda doc: doc.brand == "Mazda",
        limit_docs=5,
        page_number=2,
    )
    if car_list is not None:
        pp(car_list)
    else:
        print("No cars!")

    # Full database deletion.
    # Hint: The main purpose is tests.
    Scruby.napalm()


if __name__ == "__main__":
    anyio.run(main)