File-based ORM for dataclasses.
Project description
Datafiles: A file-based ORM for dataclasses
Datafiles is a bidirectional serialization library for Python dataclasses that automatically synchronizes object instances to the filesystem using type annotations. It supports a variety of file formats with round-trip preservation of formatting and comments, where possible.
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 replace the decorator, including a directory pattern to synchronize instances:
from datafiles import datafile
@datafile("inventory/items/{self.name}.yml")
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
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 # was 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 it directly into an activated virtual environment:
$ pip install datafiles
or add it to your Poetry project:
$ poetry add datafiles
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