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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MD5	`d676bc6cb4c381a2ce61f0c3ecd79bd5`
BLAKE2b-256	`d986e30a2a5760d1c20092512db6772e9bed78007c7b22bfd79fc61eec0855bb`

Algorithm	Hash digest
SHA256	`e7d7e1cc958c7aa90b8e41ca00e4097372589c44335a8111d4c4d1e371a5c37a`
MD5	`bf9093b72288619389479faa70db9ece`
BLAKE2b-256	`c416124d7b6ad11f6f5cb3ac332911e746a293ae54b618164c21840638e4246f`

Algorithm	Hash digest
SHA256	`906e8ba8371aa03ca35b50a43073f11752e1f2b650e94cea3e93b67fa56b08db`
MD5	`70a62b0589bd1a3644e5f70bbd36b93d`
BLAKE2b-256	`24487accedcd7bac0cf3498fd4c4ec39858e5eb4a0d62cb076a6897bf5bbf835`

Algorithm	Hash digest
SHA256	`f6ba6466c2463c427865171433913f4fcea43bbee133130af6d8979132e15723`
MD5	`8caed33c3d475f12b849be4d74e2b367`
BLAKE2b-256	`d1a0b8bc45e9b35f43c6445329f5e2874d9b823286089073979bf87ac7f5f2bf`

Algorithm	Hash digest
SHA256	`aa123a8f7bdd2de2446912108804853c4b5d75cb566ccf040d739925db21ee8f`
MD5	`c2f298d011875499e98665ffa12244d8`
BLAKE2b-256	`10e346e884d833da584d699c65d5c548265fb237ed37b8a6154bc541a3d8320c`

pysciqlop-cache 0.1.8

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	`1cb44f9dc3ae624732cb09fcee5fcf3659a2b872e527ec0cd2b03ccd1c9a45d3`
MD5	`5482b92b232662eb41041b50c15a071d`
BLAKE2b-256	`a6759d05367dfa71898c3dccc69cd00bbc9d8bbf8170d697f8e196fda87b3391`

Algorithm	Hash digest
SHA256	`43a18cf7d2747091ab0e8230f32efde1da78ff4b9bd10d19d94558030fccfb19`
MD5	`2afddb04e0bed6e6676705f0bab1433f`
BLAKE2b-256	`c4ec7c5540f402fd5b47caf97d00551a233308adba2ce743372c5d36454277d8`

Algorithm	Hash digest
SHA256	`73afa03ff619f63933b8ee0d95b99d9d8f10232539714112fe49d45ea0f5d77c`
MD5	`51b11743e23a78eb04d62b507930a1f9`
BLAKE2b-256	`573e8601b4d0a634ea7f5bca7d23a452342d0d657e8b9445de1672f1db74f7e9`

Algorithm	Hash digest
SHA256	`5f1eba525ed8be0218d842dc69ac3d66be47825494f9736c08c40544dda8a010`
MD5	`4c9521666303ba7d65d60ff80af077d2`
BLAKE2b-256	`0a4b3d6e779c588fd51d713ed15806742bb2db22e7543b5b6436d344285f8426`

Algorithm	Hash digest
SHA256	`e358bc4e7240d9d8d20ec67f38b0b4296548b3ffd175a11b5d1b66bcfdd5fc15`
MD5	`68269e106e255cbae33ae69027a501fa`
BLAKE2b-256	`d3baa6b82d9f097e802a976f9803a844dee6880c827748b6589eb9bc619fee3e`

Algorithm	Hash digest
SHA256	`7c2dd26e135f8f8be45822079b283339543f1227bf82ea95e4e4dfab1604469f`
MD5	`dc6c0b729b79ae973dd150f771362b76`
BLAKE2b-256	`90041659a587023e084bd2645e56ebf8b4e4cfc9d856f7a6e050e182b13182fc`

Algorithm	Hash digest
SHA256	`e3d2af46d5bfe986f6d1b021ae85ffefbb3a9c3d189cac9da7bc793823c698a1`
MD5	`d87ce75a4683501efe19f7849b1bd878`
BLAKE2b-256	`938caaf52087b44a288adc5f18cb5d11c42d79e24ab318ebbada59baed4719b8`

Algorithm	Hash digest
SHA256	`e0f20c2e43f4a5d65320aa8b9b22752d474253b2dd376b6d7530f93a3ae46cda`
MD5	`25674eb61f80871467c2155ed26e0389`
BLAKE2b-256	`20471b7c72da2b50d847d27a5310b950c6d4751757a9e3814767731f07352fcd`

Algorithm	Hash digest
SHA256	`b026b37613532de2fb11d3f997cf8dc12d28798cfe2d633be5b71256e4f72f2f`
MD5	`8f422469e7909c8f041779729a2bec99`
BLAKE2b-256	`819349c558591f390b253dcc5d1fa4d127a1222f51b71f2719d16940d1bea2f5`

Algorithm	Hash digest
SHA256	`7db3ecfaa986c1bf932b146c36a034f1c9a3f136304184c3923b7dcec3ed9c02`
MD5	`83c0e18a37830e4b73aff65c9e421ad4`
BLAKE2b-256	`9a5d6b96aac2cafe70d2e2d14e38abf228379dee2aca5201903cc9d561778392`