SciQLop Cache

A fast, persistent key-value cache for Python and C++20. Built on SQLite with hybrid blob/file storage, it stays flat from 100 to 1M+ entries while being 2x faster than diskcache on writes and up to 6x faster in batched transactions.

pip install pysciqlop-cache

Quick Start (Python)

from pysciqlop_cache import Cache

cache = Cache("/tmp/my-cache")
cache["sensor/temperature"] = {"ts": 1710000000, "values": [21.3, 21.5, 21.4]}
print(cache["sensor/temperature"])

Any picklable Python object works out of the box. For better performance with structured data, use the msgspec serializer:

from pysciqlop_cache import Cache, MsgspecSerializer

cache = Cache("/tmp/my-cache", serializer=MsgspecSerializer())

Expiration and Tags

cache.set("session/abc", token, expire=3600)          # expires in 1 hour
cache.set("sensor/temp", data, tag="sensor")           # tagged entry
cache.set("sensor/hum", data, expire=600, tag="sensor")

cache.evict_tag("sensor")   # bulk-remove all "sensor" entries
cache.expire()               # remove all expired entries

LRU Eviction

cache = Cache("/tmp/bounded", max_size=1_000_000_000)  # 1 GB limit
# Least-recently-used entries are evicted automatically in the background

Atomic Transactions

with cache.transact():
    cache["balance"] = cache.get("balance", 0) - amount
    cache["log"] = f"withdrew {amount}"
# Automatically commits on success, rolls back on exception

transact() is reentrant on the same thread, so transactional helpers compose cleanly:

def withdraw(amount):
    with cache.transact():
        cache["balance"] = cache.get("balance", 0) - amount

with cache.transact():        # outer
    withdraw(50)               # nested transact is fine
    withdraw(20)
# Outer commits; if it raises, both withdraws roll back together.

Sharded Concurrency with FanoutCache

For write-heavy concurrent workloads, FanoutCache shards keys across N independent stores:

from pysciqlop_cache import FanoutCache

cache = FanoutCache("/tmp/sharded", shard_count=8, max_size=1_000_000_000)
cache["key"] = "value"         # routed to shard via hash(key) % 8

with cache.transact("key"):   # transaction scoped to key's shard
    cache["key"] = transform(cache["key"])

Lightweight Index

Index and FanoutIndex are bare key-value stores with no expiration, eviction, tags, or stats overhead:

from pysciqlop_cache import Index

idx = Index("/tmp/my-index")
idx["dataset/v2"] = metadata

Distributed Locking

# Cross-process lock backed by atomic add()
with cache.lock("my-resource", expire=30):
    # exclusive access across processes
    do_work()

Memoization

@cache.memoize(expire=300, tag="compute")
def expensive(x, y):
    return heavy_computation(x, y)

expensive(1, 2)  # computed
expensive(1, 2)  # served from cache

Atomic Counters

cache.incr("page_views")             # 1
cache.incr("page_views", delta=5)    # 6
cache.decr("page_views")             # 5

Hit/Miss Statistics

cache = Cache("/tmp/stats")
cache.set("k", "v")
cache.get("k")          # hit
cache.get("missing")    # miss
print(cache.stats())    # {"hits": 1, "misses": 1}
cache.reset_stats()

Integrity Checking

result = cache.check()       # verify structural integrity
result = cache.check(True)   # verify and fix (orphaned files, counter drift)
print(result.ok, result.orphaned_files, result.dangling_rows)

Disk Usage

print(cache.volume())  # total bytes on disk (SQLite DB + file-backed values)
print(cache.size())    # total bytes of stored values only

Dict-like Interface

All store types support the standard Python dict interface:

cache["key"] = value           # set
value = cache["key"]           # get
del cache["key"]               # delete
"key" in cache                 # exists
for key in cache: ...          # iterate keys
len(cache)                     # count

Migrating from diskcache

# Migrate an existing diskcache Cache or FanoutCache
python -m pysciqlop_cache.migrate /old/diskcache /new/sciqlop-cache

# Migrate a diskcache Index
python -m pysciqlop_cache.migrate --type index /old/index /new/index

# Migrate and delete entries from source as they are copied
python -m pysciqlop_cache.migrate --drop /old/diskcache /new/sciqlop-cache

Auto-detects Cache vs FanoutCache, preserves expiration TTLs and tags. Use --type index for Index sources (creates a lightweight sciqlop-cache Index). Also usable as a library:

from pysciqlop_cache.migrate import migrate
result = migrate("/old/cache", "/new/cache", drop=True)
result = migrate("/old/index", "/new/index", store_type="index")
print(result)  # {"migrated": 1234, "skipped": 0, "errors": 0, "elapsed_secs": 1.5}

C++ API

#include "sciqlop_cache/sciqlop_cache.hpp"

// Full-featured cache with expiration, LRU eviction, tags, and stats
Cache cache(".cache/", /*max_size=*/1'000'000'000);

cache.set("key", std::vector<char>{'a', 'b', 'c'});
cache.set("key", data, 60s);                  // with expiration
cache.set("key", data, "mytag");               // with tag
cache.set("key", data, 60s, "mytag");          // both

auto value = cache.get("key");                 // std::optional<Buffer>
cache.del("key");
cache.pop("key");                              // get + delete
cache.add("key", data);                        // set only if absent
cache.touch("key", 120s);                      // update expiration
cache.evict_tag("mytag");                      // bulk remove by tag

// Bare key-value store (no expiration/eviction/tags overhead)
Index index(".index/");

// Atomic counters
cache.incr("counter", 1, /*default=*/0);
cache.decr("counter");

// Integrity and diagnostics
auto cr = cache.check();         // structural integrity
auto cr2 = cache.check(true);    // verify and fix
cache.volume();                  // total disk usage in bytes
cache.stats();                   // {hits, misses}

// Sharded variants for write concurrency
FanoutCache fc(".fc/", /*shard_count=*/8, /*max_size=*/0);
FanoutIndex fi(".fi/", /*shard_count=*/8);

Concurrency

Thread-safe: per-instance mutex + per-instance SQLite connection. Multiple threads can share a single Cache instance.
Multi-process safe: SQLite WAL mode with 600s busy timeout. Multiple processes can open the same cache directory.
Fork-safe: pthread_atfork quiescing makes both a one-shot fork → touch the cache → exit pattern and a reused worker pool (processes forked once, then touching the cache repeatedly over a long lifetime) safe — see docs/known-issues/pool-reuse-fork-safety-gap.md for the investigation.
FanoutCache/FanoutIndex: shard keys across N independent stores for write concurrency. Each shard has its own database and lock.

Performance

Latency scaling (100 to 1M entries, 256-byte values)

Scaling benchmark

Latency distribution

Latency vs value size (64B to 1MB)

Value size benchmark

Batched transactions (per-op cost)

Amortized per-op latency drops significantly with larger batches, especially for small values:

Batch per-op cost

Reproduce

# Scaling benchmarks
PYTHONPATH=build python benchmark/scaling.py --max-entries 1000000 --backend both > results.csv
python benchmark/plot_scaling.py results.csv -o benchmark/scaling_chart.png

PYTHONPATH=build python benchmark/scaling.py --max-entries 1000000 --raw --backend both > raw.csv
python benchmark/plot_scaling.py raw.csv --violin -o benchmark/scaling_violin.png

# Value-size and batch benchmarks
PYTHONPATH=build python benchmark/bench_valuesize.py > benchmark/valuesize_results.csv
python benchmark/plot_valuesize.py benchmark/valuesize_results.csv -o benchmark

Building from Source

pip install meson-python numpy
meson setup build -Dwith_tests=true
meson compile -C build
meson test -C build

License

MIT

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SHA256	`68d549a044dab6db01bfd5b5a648ade741b8c95f0bf9554850da3faf08fc7739`
MD5	`8a2968b8986b03c1c031d22e4361fa62`
BLAKE2b-256	`9b7c2dc2f11392e0747c1eb0c7d83be9b0671de70bef3359884bee226cdaf71b`

Algorithm	Hash digest
SHA256	`7c7745c854e63aaac7588bf75087ac64b15066897a9ef5ad61ce2c32bf0a717f`
MD5	`bf3151401e4b20f86368a47b7e6033fa`
BLAKE2b-256	`a43d0316453ac8d7704424b125f21a4a5ba8cdba5eae645b60fcd0b5ab2556e5`

Algorithm	Hash digest
SHA256	`e0c42adb91339fad8690460298049092c8e4fac5f48e122b9b272babd935a8d7`
MD5	`e82e4e82f488e60d63edb9e84906c65f`
BLAKE2b-256	`a3de3027f906eee9bca08636e75bcc0c1b0d3f061ce217c5ed32b80eecd640ca`

Algorithm	Hash digest
SHA256	`5a6dfb37fcf4115292c39bbf312b5dcc24ad66d9ebd5fec00f770347a9a1bf03`
MD5	`ddfc95a807cf2a2eb75895c17ca685d4`
BLAKE2b-256	`68a29d34213ee69d623525eb469573b124d3bfcfb709188950a4a705479cfd57`

Algorithm	Hash digest
SHA256	`fb066ff3e52caedc4279cc0a2490a23caac51cc41ac7ad601ae60770b2329342`
MD5	`d31b1d863f4e4f1525e5598fbb89d7d4`
BLAKE2b-256	`02ade652b2845237aac602bd1fdfe8c3c7cb817e0250d1d26001786000bc38f5`

pysciqlop-cache 0.1.5

SciQLop Cache

Quick Start (Python)

Expiration and Tags

LRU Eviction

Atomic Transactions

Sharded Concurrency with FanoutCache

Lightweight Index

Distributed Locking

Memoization

Atomic Counters

Hit/Miss Statistics

Integrity Checking

Disk Usage

Dict-like Interface

Migrating from diskcache

C++ API

Concurrency

Performance

Latency scaling (100 to 1M entries, 256-byte values)

Latency vs value size (64B to 1MB)

Batched transactions (per-op cost)

Reproduce

Building from Source

License

Project links

Key dates

1 maintainer

Credits

GitHub Statistics

License

Requires

Classifiers

Download files

Source Distribution

Built Distributions

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Algorithm	Hash digest
SHA256	`a9d2fab4b4cc580c99f1916d0c7464f10d9d031234e52ebabba45583f696edf6`
MD5	`ef5637460dcecd297904985d259cb8b5`
BLAKE2b-256	`36cb75746d2c44f60891d4ba51383321c0a2417cb63f6fb4b2514a7efbe2d9f1`

Algorithm	Hash digest
SHA256	`cd9820ea6c4a9e9ef268da055d35205e8c9f94076e25bbdff8f7a27801e927e7`
MD5	`14018857a7410cb4e060a4954f15b8d0`
BLAKE2b-256	`e5703dea34efc730517c1c3664fea8ad0e082b4bad3527da88d468dcceb4c30e`

Algorithm	Hash digest
SHA256	`8702d8afcc995eb4203395ef231f4c25701b360dfdcd2c9e5d02c3585a919339`
MD5	`0c966b5e3af60982b86714475c73b8b1`
BLAKE2b-256	`7fc8f8cbe70e8ebf73adefcf0fa906bc26dac37b09102697308d8af3c7c4e7ef`

Algorithm	Hash digest
SHA256	`3e55736722497f79dcfff5f31bcc70080a6a361cdbdf6f5b84f1da990b98d8ea`
MD5	`0a301db3d874bd8b484391b92265303e`
BLAKE2b-256	`798561fe6ca725288438afa2b58ee724ce511f134720ea2218ddf57d0c3e330e`

Algorithm	Hash digest
SHA256	`c1265aa4af4becc162dc8481a10db6bfed253d83f85aef07051c948a0d063dc3`
MD5	`d67a49a8a8f76caeb9961152913e2544`
BLAKE2b-256	`bdd84408f94d9c227025330765cec31d21a56e57158e6d4fd74a2580dcc40f7d`

Algorithm	Hash digest
SHA256	`bbf36a0c605ae6dd372203a5fe9731aaa25c74f33fb577dcc4aeb41e6852d47e`
MD5	`a4bb16b3e078f1c1f4d176539c63dca3`
BLAKE2b-256	`19aef95cd8cb298a66aee9bda82f0aa50f7b5c5bb763827f8a497271bc5d047f`

Algorithm	Hash digest
SHA256	`ff5409d721597fa3bd3ea7b72cb9662060e8754629c1a6d6269c27b47b155ca3`
MD5	`1a76b7916dc039298762f997473adc45`
BLAKE2b-256	`3226c07cc3a62021268f989015b36a69395fa24e4acf42b8e53ceb3c89dce9d5`

Algorithm	Hash digest
SHA256	`a765ef3b4ff5b1c28ca108bc50b1fdbf6c4dcb5df5cbbaa5a14bb2fab5e6dfd7`
MD5	`bd4bdcbb23aa160d8c9025727f6fc294`
BLAKE2b-256	`966c0f1bb0979ceb5d117925c9fc31115e2630b73c92fa48acfd854422de8737`

Algorithm	Hash digest
SHA256	`1706ba4b8e94299ae1172c8f0b039f2e95ee1b0946981bdb5e603674fd935cbc`
MD5	`a3cb5523f072a29ae09f0ead4303766b`
BLAKE2b-256	`0a65535bf841122fcd742c3be768298fbd4b107b091221d11514016a5d8e5331`

Algorithm	Hash digest
SHA256	`8e07a833a423b83511bedab228fca0eabf1b3e2a491db3145ec36b98f1dc803b`
MD5	`4b7b3b72e9c771c5feebbc1862295f09`
BLAKE2b-256	`577d6a1cf6010c0fd021d2743445b2d05084f45a9a5417f7ef6d180a4291b52d`