https://github.com/furechan/tempcache
Python caching using temporary files
https://github.com/furechan/tempcache
caching python tempfiles
Last synced: about 2 months ago
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Python caching using temporary files
- Host: GitHub
- URL: https://github.com/furechan/tempcache
- Owner: furechan
- License: mit
- Created: 2023-12-04T19:57:24.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-26T04:39:48.000Z (2 months ago)
- Last Synced: 2025-02-26T05:29:32.788Z (2 months ago)
- Topics: caching, python, tempfiles
- Language: Python
- Homepage:
- Size: 53.7 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE.txt
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README
# Python library to cache data and function results in temporary files
This library offers a simple way to cache data and function results using temporary files, including a mechanism for automatic expiration after a certain time.
Dy default, the package uses the `pickle` module to serialize data and hash key values.
> **Note**
For more advanced use cases you may want to look at the `Memory` class
in [joblib](https://github.com/joblib/joblib).
## Basic Usage
An instance of the `TempCache` class be used as a decorator
to automatically cache the results of a function.
```python
from tempcache import TempCache
CACHE_MAX_AGE = 24 * 60 * 60 * 2 # two days
cache = TempCache("mycache", max_age=CACHE_MAX_AGE)
@cache
def long_running(...):
...
result = long_running(...)
```
## Caching results at the call site
You can also use a `TempCache` object to cache a result
at the call site with the `cache_result` method.
```python
from tempcache import TempCache
CACHE_MAX_AGE = 24 * 60 * 60 * 2 # two days
cache = TempCache("mycache", max_age=CACHE_MAX_AGE)
def long_running(...):
...
result = cache.cache_result(long_running, ...)
```
## Advanced usage
In cases where the function or some of its arguments
are defined in the `__main__` namespace or in a jupyter notebook
and cannot be pickled by `pickle` you can use a different pickle module
like `cloupickle`.
```python
import cloudpickle
from tempcache import TempCache
CACHE_MAX_AGE = 24 * 60 * 60 * 2 # two days
cache = TempCache("mycache",
pickler=cloudpickle,
max_age=CACHE_MAX_AGE)
key = ...
# key object can be complex as long as it is pickle-able
item = cache.item_for_key(key)
# cache item for the given key whether it exists or not
# load item if it exists
if item.exists():
value = item.load()
# save item
item.save(value)
```
## Examples
Examples notebooks are in the `extras` folder.
## Installation
You can install this package with `pip`.
```console
pip install tempcache
```
## Related Projects
- [joblib](https://github.com/joblib/joblib)
Computing with Python functions
- [percache](https://pypi.org/project/percache/)
Persistently cache results of callables
- [disckcache](https://pypi.org/project/diskcache/)
Disk and file backed cache library compatible with Django
- [cloudpickle](https://github.com/cloudpipe/cloudpickle)
Extended pickling support for Python objects