Metadata-Version: 2.1
Name: datafiles
Version: 0.11.1
Summary: File-based ORM for dataclasses.
Home-page: https://pypi.org/project/datafiles
License: MIT
Keywords: dataclasses,serialization,type-annotations,object-relational mapping,YAML,JSON,TOML
Author: Jace Browning
Author-email: jacebrowning@gmail.com
Requires-Python: >=3.7,<4.0
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Software Development
Classifier: Topic :: Utilities
Requires-Dist: PyYAML (>=5.2,<6.0)
Requires-Dist: cached_property (>=1.5,<2.0)
Requires-Dist: classproperties (>=0.1.3,<0.2.0)
Requires-Dist: minilog (>=2.0,<3.0)
Requires-Dist: parse (>=1.12,<2.0)
Requires-Dist: ruamel.yaml (>=0.16.10,<0.17.0)
Requires-Dist: tomlkit (>=0.5.3,<0.6.0)
Requires-Dist: typing-extensions (>=3.7,<4.0)
Project-URL: Documentation, https://datafiles.readthedocs.io
Project-URL: Repository, https://github.com/jacebrowning/datafiles
Description-Content-Type: text/markdown

# Datafiles: A file-based ORM for dataclasses

Datafiles is a bidirectional serialization library for Python [dataclasses](https://docs.python.org/3/library/dataclasses.html) 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 data 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](https://www.youtube.com/watch?v=moYkuNrmc1I&feature=youtu.be&t=1225) for a demo of this in action!

## Overview

Take an existing dataclass such as [this example](https://docs.python.org/3/library/dataclasses.html#module-dataclasses) from the documentation:

```python
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 a directory pattern to synchronize instances:

```python
from datafiles import datafile

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

Then, work with instances of the class as normal:

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

```yaml
# inventory/items/widget.yml

unit_price: 3.0
```

Changes to the object are automatically saved to the filesystem:

```python
>>> item.quantity_on_hand += 100
```

```yaml
# inventory/items/widget.yml

unit_price: 3.0
quantity_on_hand: 100
```

Changes to the filesystem are automatically reflected in the object:

```yaml
# inventory/items/widget.yml

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

```python
>>> item.unit_price
2.5
```

Objects can also be restored from the filesystem:

```python
>>> from datafiles import Missing
>>> item = InventoryItem("widget", Missing)
>>> item.unit_price
2.5
>>> item.quantity_on_hand
100
```

## 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](https://poetry.eustace.io/) project:

```
$ poetry add datafiles
```

## Documentation

To see additional synchronization and formatting options, please consult the [full documentation](https://datafiles.readthedocs.io).

