datafiles 0.2b2

File-based ORM for dataclasses.

Datafiles: A file-based ORM for dataclasses

Datafiles is a bidirectional serialization library for Python dataclasses that automatically synchronizes objects to the filesystem using type annotations. It supports a variety of file formats with round-trip preservation of formatting and comments, where possible. By default, saves are automatic and include the minimum data needed to restore an object.

Usage

Take an existing dataclass such as this example from the documentation:

from dataclasses import dataclass

@dataclass
class InventoryItem:
    """Class for keeping track of an item in inventory."""

    name: str
    unit_price: float
    quantity_on_hand: int = 0

    def total_cost(self) -> float:
        return self.unit_price * self.quantity_on_hand

and decorate it with directory pattern to synchronize instances:

from datafiles import datafile

@datafile("inventory/items/{self.name}.yml")
@dataclass
class InventoryItem:
    ...

Then, work with instances of the class as normal:

>>> item = InventoryItem("widget", 3)

# inventory/items/widget.yml

unit_price: 3.0

Changes to the object are automatically saved to the filesystem:

>>> item.quantity_on_hand += 100

# inventory/items/widget.yml

unit_price: 3.0
quantity_on_hand: 100

Changes to the filesystem are automatically reflected in the object:

# inventory/items/widget.yml

unit_price: 2.5  # <= manually changed from "3.0"
quantity_on_hand: 100

>>> item.unit_price
2.5

Demo: Jupyter Notebook

Installation

Because datafiles relies on dataclasses and type annotations, Python 3.7+ is required. Install this library directly into an activated virtual environment:

$ pip install datafiles

or add it to your Poetry project:

$ poetry add datafiles

Documentation

To see additional syncrhonization and formatting options, please consult the full documentation.