I'm working on a ray tracing project in Python and I'm looking to implement a basic caching mechanism to improve performance. I want to avoid using functools and classes.
custom_cache = {}
def ray_trace(x, y, z):
key = (x, y, z)
if key in custom_cache:
return custom_cache[key]
computed_result = ...
custom_cache[key] = computed_result
return computed_result
How can I improve or optimize this caching mechanism? Are there any best practices or considerations I should keep in mind? I'm particularly interested in alternatives to using classes and functools. Thanks in advance for your help!
You can limit the size of the cache to prevent it from growing indefinitely. When the cache reaches its limit, you can remove the most recently used items. You can modify your code in this way:
from collections import OrderedDict
custom_cache = OrderedDict()
CACHE_SIZE_LIMIT = 1000
def ray_trace(x, y, z):
key = (x, y, z)
if key in custom_cache:
# Move the key to the end to mark it as most recently used
custom_cache.move_to_end(key)
return custom_cache[key]
computed_result = ...
custom_cache[key] = computed_result
if len(custom_cache) > CACHE_SIZE_LIMIT:
custom_cache.popitem(last=False)
return computed_result