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	`eb024d33eb394bd859e74d106031eac69143543f0bdd2e88124e60805cedc766`
MD5	`62dca20a3d2205447cf9d9dc941dc3f3`
BLAKE2b-256	`67c5c2a3af782095846bcc5fd65143ef7fae2e5c1a37867c5cabdec3b05e973e`

Algorithm	Hash digest
SHA256	`a4fb5e72536c450633aebeb5480b647213db442e2b827601d48989ff34c850f0`
MD5	`9756df70a5538cbc9ae5a9f9c8946974`
BLAKE2b-256	`24c3b8d02bae34ad04c3fa99044bba62ccbe8ab3296f1be73b866bc098469e17`

Algorithm	Hash digest
SHA256	`dee4351de82589dfe56995e28d3adf29ae9e5f45c8c3633d7b218bcbc905adda`
MD5	`99c8641bef3dc4349d6e3ddc14e7b2f0`
BLAKE2b-256	`712008e93a1dcd89580e9f597c9d5dd2f2fbd342ac462774a21a98db243a5577`

Algorithm	Hash digest
SHA256	`9a98c7e5bda1bc7c904731af363e5fd330a739c05d848c6515b1bd749fab7ae3`
MD5	`d23b60621275a9eefb31ab2364f270a9`
BLAKE2b-256	`e9b22bc6f8b4956082b8370228b235e2af52d15663c35126148a02101c23fc40`

Algorithm	Hash digest
SHA256	`b88366d8c543d977d7015f6865cf90800651f2786bb613c84247354af89aeb41`
MD5	`540a9dc6d6ffac3e6f056af32ec2b7b4`
BLAKE2b-256	`ef6b2b9979e9e3d075657f77c768c975c2d7a5675a3bddb05125941e182bdfc4`

pysciqlop-cache 0.1.11

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	`d0a30c0117e474f25136a4e94f01a9b044a3f05446de6d5e3e2be6747feb01c2`
MD5	`b81e8ea69afa09a03d6f3f021fe04245`
BLAKE2b-256	`f4cd4fe38a7d26f0a3161402230a0971beee798085fa24a189708afb174a2f9c`

Algorithm	Hash digest
SHA256	`022f5d5ec4f956755b2fd8b65d781dd6067bb5cecfb2cb644b3f670999e847a4`
MD5	`edec50a50bd30533858b04810c6b8ac0`
BLAKE2b-256	`f14b84ffe330476db8db41f938e7d24380c90c5fdd2b33514739a1fe8dd6c181`

Algorithm	Hash digest
SHA256	`1381cbc43bdd4cd57baa70daff8b2bff882e22ee7f85514bc057d14d6ca0ab9a`
MD5	`b87ccdbd96a88680d038b9a5875c86f9`
BLAKE2b-256	`701b5b6118c998b67edd209da55f1a18d76adec31dd5d39112fbb23b8ea91952`

Algorithm	Hash digest
SHA256	`c0c0094e8c865dfe451abfb215dead96acf9c77967b6676976efd174d074b831`
MD5	`1275bb3b1d1827144049d44caa2385b5`
BLAKE2b-256	`0ae63f040d71ebdafe982c9a693def79b947305ce7312b0ab9486511943da8ed`

Algorithm	Hash digest
SHA256	`6af4136bb0db1fe6951f1dca8e590b1ac45b921d308418390fd386dec7d98308`
MD5	`d83e06fd75e0bd948e29eeb49d4fd6c9`
BLAKE2b-256	`0460f92b09df58b8bdad150603e7c90ee929d257497a78f90ef4074606132755`

Algorithm	Hash digest
SHA256	`606387a4e7ea63afd6a705d1fd0e924851677140400d72a8f71d0eae5800f3bf`
MD5	`7c904d75329280bc4d752689959cbf3e`
BLAKE2b-256	`b5ee651ff73f6447c20972db85b1c7794077f1deffa23ebec24c0bd652160fda`

Algorithm	Hash digest
SHA256	`04728bcb5f87fc44523e2f721abd2ab7b59d9b6483d2cf3408ed5eef8a0e8fd1`
MD5	`9780666f1b8e289e39f6366a12d54741`
BLAKE2b-256	`418e002eabeb1b6b7cda408caa4e262da6f8db9b72bbeffa023c7d2fd4a2e55b`

Algorithm	Hash digest
SHA256	`387e9431cf7d1addc7aa80678e3c4fd3bd5fa19a734a350c4a802b4177613fda`
MD5	`7f70d43712243c585029f97e0f1e7156`
BLAKE2b-256	`5070dd6d84d9064566c05387fe120b0e968074d6b7876e0d2543279bc127c199`

Algorithm	Hash digest
SHA256	`1e7ab6adfe3e58d6efa4bd9b9f126c22aa859639b7578b868ea9f427b64ebee9`
MD5	`511c91fc6353a3091aa73c48d1905db3`
BLAKE2b-256	`7fd5c685ceb084a1a07b1634292b31b71e909749f34a220176584001d7910ab0`

Algorithm	Hash digest
SHA256	`57d1811ba5e2f161e3640e2854be9e8fba286d6ecd867f0905cd63ce53992cdf`
MD5	`ae5f60fe946205b6c5dd2b5b7f2b22f9`
BLAKE2b-256	`54f793a3fb5ffe65d27ce388668e263b17fe55b3c3ae10cc09f6157e319720cd`