Metadata-Version: 2.1
Name: cachegenius
Version: 0.1.0
Summary: Speed-up your code by automatically identifying functions that should use caching in your code!
Home-page: https://github.com/NicolasMICAUX/cachegenius
Author: Nicolas Micaux
Keywords: cache,caching,automatically
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Topic :: Utilities
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Python: >=3.5
Description-Content-Type: text/markdown

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  <h1 align="center">CacheGenius</h3>

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    Speed-up your code by automatically identifying functions that should use caching!
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<!-- ABOUT THE PROJECT -->
## About The Project

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Have you ever spent hours trying to speed up some code, only to finally realize you're computing the same things 2 or 3 times, which means some caching does the trick ? What a waste of time !

🧞‍♂️ CacheGenius automatically identifies functions that should use caching in your code, so you can speed-up your code effortlessly!

<!-- GETTING STARTED -->
## Getting Started
Using CacheGenius is very simple.

Install CacheGenius with pip :
```sh
pip install cachegenius
```

To analyse an entire module `mypackage`, with all the functions and methods it contains, add this lines at the begginning of your code:
```python
import mypackage
import cachegenius

cachegenius(mypackage)
```

Now, use your module functions as usual. CacheGenius will automatically analyze all the functions you call, and will tell you if you should use caching or not.
```
>>> cachegenius.report()
Function: mokemodule.mokescript.my_func
Should cache: True
```

## Advanced usage
You can use the different parameters of `cachegenius.report()` to change the temporary files path, and print more infos using `debug`.  
Two parameters are available to tune the cost of computing and memory, that are used to decide if caching is worth it or not.

```python
def report(
    autocache_path: str       = "cachegenius_data/",
    debug: bool               = True,
    cost_per_comput_hr: float = 0.1,  # $/hr
    cost_per_mem_gb: float    = 0.2   # $/gb
)
```
You can clean all temporary files with `cachegenius.empty()`.


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## Contributing
_(Section in english)_  

### Roadmap/todo
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_For every todo, just click on the link to find the discussion where I describe how I would do it._  
See the [open issues](https://github.com/NicolasMICAUX/cachegenius/issues) for a full list of proposed features (and known issues).

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### How to contribute
Contributing is an awesome way to learn, inspire, and help others. Any contributions you make are **greatly appreciated**, even if it's just about styling and best practices.

If you have a suggestion that would make this project better, please fork the repo and create a pull request.  
Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (`git checkout -b feature/YourAmazingFeature`)
3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the Branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request


## Authors
This library was created by [Nicolas MICAUX](https://github.com/NicolasMICAUX).


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