semvec/pypi-packages huggingface dataset:
touch-cache 0.1.0
touch_cache is a smart memoization library that tracks the files opened during the process. The cache is automatically invalidated when one of the used file is modified (more recent) than the cache.
License: MIT
Requires Python: >=3.8

# Introduction 

`touch_cache` is a smart memoization library that tracks the **files opened** during the process.
The cache is **automatically invalidated** when one of the used file is modified (more recent) than the cache. 

`touch_cache` also watch any change in the **code of the function itself**, or the values of the **global variables** used by them.

It is particularly suitable for a dev environements in data science, for speeding dev iterations / debug 
of a pipeline having some heavy steps, while making sure the output is always  **up to date** with input data and parameters.

# Installation 

> pip install touch_cache

# Usage 

## Basic function 

This library provides a single decorator **touch_cache**. 
The files used in the process are tracked via the usage of the standard function `open()`

```python

from touch_cache import touch_cache
from pathlib import Path

INPUT_FILE = "data/input.dat"

@touch_cache
def long_running_function(param1:int):
    
    print("Running ...")
    
    with open(INPUT_FILE) as f :
        res = some_long_process(f)
    
    return res

# First call 
res = long_running_function(1)
# will print "Running ..."

# Second call 
res = long_running_function(1)
# will us the cached value and NOT print 'Running ...'

# Touch INPUT file 
# This may be any external update of it
Path(INPUT_FILE).touch()

# Thirds call 
res = long_running_function(1)
# Input file modified ==> will invalidate the cache and run again
# "Running ..."
```

## Configure cache folder

By default, cache data will be pickled on dick using [cloudpickle](https://pypi.org/project/cloudpickle/) in the folder `.cache`.
You can choose another folder with **set_cache_dir()**.

```python
from touch_cache import set_cache_dir

set_cache_dir("/some/folder")
```

## Clean cache



## Manually track files

`touch_cache` hooks to the standard function `open()` to track the files used. This works in most cases (including Pandas).
some external libraries might use low level C code that doesn't directly calls `open()`. 
In such case, you need to manually tell `touch_cache` that a file has been used, with the function **using_file()**.

```python
from touch_cache import using_file, touch_cache
from third_parthy_library import load_some_file

@touch_cache
def long_running_function(param1:int):
  
    # Manually register this input file
    using_file(INPUT_FILE)
      
    intermediate = load_some_file(INPUT_FILE)
    res = some_long_process(intermediate)
    
    return res

```

# License 

[MIT license](LICENSE)


# Author 

[Raphael Jolivet](https://rjo.name)