https://github.com/spoorn/nemoize
Python Memoizer for classes, functions, and methods
https://github.com/spoorn/nemoize
cache decorator decorators decorators-python memoize memoize-decorator memoized memoizer python python3
Last synced: 23 days ago
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Python Memoizer for classes, functions, and methods
- Host: GitHub
- URL: https://github.com/spoorn/nemoize
- Owner: spoorn
- License: mit
- Created: 2022-05-19T08:32:55.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2022-05-20T12:03:28.000Z (about 3 years ago)
- Last Synced: 2025-04-15T17:16:59.656Z (about 1 month ago)
- Topics: cache, decorator, decorators, decorators-python, memoize, memoize-decorator, memoized, memoizer, python, python3
- Language: Python
- Homepage: https://pypi.org/project/nemoize/
- Size: 16.6 KB
- Stars: 3
- Watchers: 1
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# nemoize
Simple Python Memoizer decorator for classes, functions, and methods.
# Installation
nemoize is available on PyPi
```commandline
python3 -m pip install nemoize
```
Or you can install manually via the built distribution (wheel)/source dist from [PyPi](pypi.org/project/nemoize) or [github](https://github.com/spoorn/nemoize).
# How to Use
Import
```python
from nemoize import memoize
```
Then use the `@memoize` decorator on various entities as seen below
### Using on a Class
```python
@memoize
class Test:
def __init__(self, value):
self._value = value
@property
def value(self):
return self._value
```
### Using on a function
```python
@memoize
def test_func():
return "hoot"
```
### Using on an instance method
```python
class Owl:
def __init__(self):
self.food = 1337
pass
@memoize(max_size=5)
def eat(self, num):
self.food -= num
```
## Configuration
There are also various configuration parameters to `memoize()`:
- `@memoize(max_size=13)` : Max number of entries to keep in the cache:
- `@memoize(cache_exceptions=True)` : Also cache exceptions, so any raised Exceptions will be the exact same Exception instance:
- `@memoize(max_size=13, cache_exceptions=True)` : Together
- `@memoize(arg_hash_function=str)` : Changes the hash function on arg and each keyword-arg to use the str() function, which can make lists "hashable"
# Testing
The unit tests in `test/unit/test_memoize.py` run through various use cases of using the @memoize annotation on classes, functions, and instance methods.
# Benchmarking
There is a benchmarking utility under [`benchmark/`](https://github.com/spoorn/nemoize/tree/main/benchmark) that is used for benchmarking nemoize performance against other options and non-memoized scenarios.
Example numbers:
```commandline
Benchmark test for Memoized vs Non-memoized classes with [1000] computations in their__init__() methods for [1000000] iterations
Non-memoized class creation + empty method call average time (ms): 0.01550699806213379
Memoized class creation + empty method call average time (ms): 0.0012589995861053468
Benchmark test for @memoize, non-memoized, a @simplified_memoize, and @functools.lru_cache comparison usingfunction calculating fibonacci sum for [100] fib numbers, for [10000000] iterations
@simplified_memoize fib average time (ms): 0.0001555999994277954
@memoize fib average time (ms): 4.4699978828430175e-05
@memoize(cache_exceptions=True) (to avoid delegation to functools.lru_cache) fib average time (ms): 0.00034309999942779544
@functools.lru_cache fib average time (ms): 4.440000057220459e-05
```