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[ Source: cachey  ]

Package: python3-cachey (0.2.1-3)

Caching mindful of computation/storage costs

Humans repeat stuff. Caching helps.

Normal caching policies like LRU aren't well suited for analytic computations where both the cost of recomputation and the cost of storage routinely vary by one million or more.

Cachey tries to hold on to values that have the following characteristics

 1. Expensive to recompute (in seconds)
 2. Cheap to store (in bytes)
 3. Frequently used
 4. Recenty used

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    heap with decrease-key and increase-key operations for Python 3

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