semvec/pypi-packages huggingface dataset:
cachalot 1.5.0
Minimal persistent memoization cache
License: MIT
Requires Python: >=3.5,<4.0
Keywords: memoization,cache

# Cachalot [![PyPI version](https://badge.fury.io/py/cachalot.svg)](https://badge.fury.io/py/cachalot) [![Pipeline status](https://gitlab.com/radek-sprta/cachalot/badges/master/pipeline.svg)](https://gitlab.com/radek-sprta/cachalot/commits/master) [![Coverage report](https://gitlab.com/radek-sprta/cachalot/badges/master/coverage.svg)](https://gitlab.com/radek-sprta/cachalot/commits/master)[![Downloads](http://pepy.tech/badge/cachalot)](http://pepy.tech/project/cachalot)

Cachalot is a minimal persistent memoization cache. It provides a decorator, that stores function result for future use. Perfect for heavy computations and I/O operation (such as web requests). On backend, it uses TinyDB for storage.

## Features
- Simple usage via decorator
- Persistent caching
- Key expiration
- Maximum cache size, to prevent bloat

## Installation
Cachalot requires Python 3.5 or newer to run.

**Python package**

You can easily install Cachalot using pip:

`pip3 install cachalot`

**Manual**

Alternatively, to get the latest development version, you can clone this repository and then manually install it:

```
git clone git@gitlab.com:radek-sprta/cachalot.git
cd cachalot
python3 setup.py install
```

## Usage
```python
from cachalot import Cache

@Cache()
def expensive_function():
    return expensive_calculation()
```

### Advanced usage
```python
from cachalot import Cache

@Cache(path='cache.json', timeout=3600, size=5e3, filesize=1e6, retry=True, renew_on_read=True)
def expensive_function():
    return expensive_calculation()
```

- `path`: Path to the database file. Defaults to .cache.json.
- `timeout`: How long should the data be cached in seconds. Defaults to 0 (infinite).
- `size`: Maximum number of keys cached. Defaults to 0 (infinite).
- `filesize`: Maximum size of database file in bytes. Defaults to 0 (infinite).
- `retry`: Retry if result is blank. Defaults to False.
- `renew_on_read`: Renew the entry, i.e refresh the entry timestamp on reads. Defaults to True

### Manually deleting entries
If you want to manually invalidate an entry, you can calculate the hash of the function call and then pass it the `remove` method.

```python
key = cache.calculate_hash(len)('teststring')
cache.remove(key)
```

For more information, see [documentation][documentation].

## Contributing
For information on how to contribute to the project, please check the [Contributor's Guide][contributing]

## Contact
[mail@radeksprta.eu](mailto:mail@radeksprta.eu)

[incoming+radek-sprta/cachalot@gitlab.com](incoming+radek-sprta/cachalot@gitlab.com)

## License
MIT License

## Credits
This package was created with [Cookiecutter][cookiecutter] and the [python-cookiecutter][python-cookiecutter] project template. Inspired by [Cashier][cachier]

[cachier]: https://github.com/atmb4u/cashier
[contributing]: https://gitlab.com/radek-sprta/cachalot/blob/master/CONTRIBUTING.md
[cookiecutter]: https://github.com/audreyr/cookiecutter
[documentation]: https://radek-sprta.gitlab.io/cachalot
[python-cookiecutter]: https://gitlab.com/radek-sprta/python-cookiecutter