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File-based ORM for dataclasses.

Project description

Datafiles: A file-based ORM for Python dataclasses

Datafiles is a bidirectional serialization library for Python dataclasses to synchronize objects to the filesystem using type annotations. It supports a variety of file formats with round-trip preservation of formatting and comments, where possible. Object changes are automatically saved to disk and only include the minimum data needed to restore each object.

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Some common use cases include:

  • Coercing user-editable files into the proper Python types
  • Storing program configuration and state in version control
  • Loading data fixtures for demonstration or testing purposes
  • Synchronizing application state using file sharing services
  • Prototyping data models agnostic of persistence backends

Watch my lightning talk for a demo of this in action!


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

from dataclasses import 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 a directory pattern to synchronize instances:

from datafiles import datafile

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

Objects can also be restored from the filesystem:

>>> from datafiles import Missing
>>> item = InventoryItem("widget", Missing)
>>> item.unit_price
>>> item.quantity_on_hand


Install this library directly into an activated virtual environment:

$ pip install datafiles

or add it to your Poetry project:

$ poetry add datafiles


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

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