File-based ORM for dataclasses.
Project description
Datafiles: A file-based ORM for dataclasses
Datafiles is a bidirectional serialization library for Python dataclasses to 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, changes are automatically saved and only 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
Objects can also be restored from the filesystem:
>>> from datafiles import Missing
>>> item = InventoryItem("widget", Missing)
>>> assert item.unit_price == 2.5
>>> assert item.quantity_on_hand == 100
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.
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