Feat/pure rust default and msrv #3

Merged
osobh merged 3 commits from feat/pure-rust-default-and-msrv into main 2026-09-23 16:29:33 +00:00
30 changed files with 768 additions and 247 deletions
+3 -15
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@@ -28,8 +28,9 @@ jobs:
# dependency a failure (CLAWHDF5_REQUIRE_INTEROP below).
run: |
apt-get update
# cmake builds libz-ng-sys (clawhdf5-format's default `fast-deflate`);
# rust:latest does not ship it.
# cmake builds libz-ng-sys for the opt-in `fast-deflate` (zlib-ng)
# steps in ci-test.sh; rust:latest does not ship it. The default
# build (pure-Rust zlib-rs) does not need it.
apt-get install -y --no-install-recommends python3 python3-venv cmake
python3 -m venv /opt/interop
/opt/interop/bin/pip install --no-cache-dir h5py numpy netCDF4 xarray
@@ -75,19 +76,6 @@ jobs:
command -v rustup >/dev/null || curl -sSf --retry 5 https://sh.rustup.rs | sh -s -- -y --profile minimal --default-toolchain none
rustup toolchain install stable --profile minimal --component clippy
echo "$HOME/.cargo/bin" >> "$GITHUB_PATH"
- name: Build dependencies
# libz-ng-sys (clawhdf5-format's default `fast-deflate`) needs cmake.
# In the Docker runner the job is root and can install it; a host
# runner cannot, so say what is missing rather than fail inside a
# build script.
run: |
if command -v cmake >/dev/null; then cmake --version | head -1; exit 0; fi
if [ "$(id -u)" = 0 ]; then
apt-get update -qq && apt-get install -y -qq cmake
else
echo "::error::cmake is not installed on this runner host (needed by libz-ng-sys)"
exit 1
fi
- name: Confirm aarch64
run: |
test "$(uname -m)" = aarch64
+63
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@@ -1185,6 +1185,69 @@ cargo run --release --bin ephemeral_perf
---
## Deflate backend: zlib-rs vs zlib-ng
Measured 2026-09-23 on tank (AMD Ryzen 7 7800X3D, 8C/16T). The default
deflate backend is now **zlib-rs**, a pure-Rust port of zlib-ng; zlib-ng (C,
built with cmake) was the default before and is still available as
`fast-deflate`. Both builds were compiled once into separate target
directories and run **alternately, three rounds each**; figures are medians.
```bash
# zlib-rs (default)
cargo bench -p clawhdf5-filters --bench deflate_bench
cargo bench -p clawhdf5-bench --bench h5bench_write --features libhdf5-compare -- '^write_2d_chunked/'
cargo run --release -p clawhdf5-bench --bin read_harness
# zlib-ng: add --features fast-deflate (filters) or clawhdf5-format/fast-deflate (bench)
```
| Workload | zlib-rs | zlib-ng | rs / ng |
|---|---:|---:|---:|
| HDF5 chunked write, deflate-6, 512×512 f32 | 1.458 ms | 1.484 ms | 0.98 |
| HDF5 chunked write, deflate-6, 128×128 f32 | 157.6 µs | 152.8 µs | 1.03 |
| HDF5 chunked write, deflate-6, 32×32 f32 | 62.9 µs | 60.2 µs | 1.05 |
| HDF5 read, 64 MB chunked + deflate, full | 64.4 ms | 65.2 ms | 0.99 |
| HDF5 read, 64×64 window (1 chunk) | 0.18 ms | 0.17 ms | 1.06 |
| HDF5 read, 512×512 window (49 chunks) | 4.10 ms | 4.10 ms | 1.00 |
| HDF5 read, one row / one column | 1.00 / 2.01 ms | 0.95 / 1.95 ms | 1.05 / 1.03 |
| Raw inflate, 8 MB f64 | 5.92 ms | 6.06 ms | 0.98 |
| Raw inflate, 1 MB sine | 82.8 µs | 68.6 µs | 1.21 |
| Raw deflate-6, 8 MB f64 / 1 MB sine | 92.2 / 2.01 ms | 83.1 / 1.84 ms | 1.11 / 1.09 |
Compressed output is **byte-identical** between the two at levels 1, 6 and 9
on all three inputs, so files do not change size. libhdf5 1.14.6 took 51.4 ms
for the 512×512 write in the same session (35× the zlib-rs figure).
On the HDF5 paths zlib-rs is within 6% of zlib-ng everywhere, and ahead on the
largest write. The raw codec loops show zlib-ng still slightly faster at
compression (~10%), which chunked writes do not expose because encoding runs
in parallel across chunks.
**Two findings along the way.** The first measurement had zlib-rs 1.21.9×
slower on single-chunk reads and 3.7× slower on a 1 MB inflate — slower even
than miniz_oxide. Neither was zlib-rs's fault:
1. **Runtime CPU detection was off.** zlib-rs needs its `std` feature to
detect and use SIMD at runtime; flate2 turns it on through its default
`runtime_detection` feature, which our `default-features = false` flate2
dependency was disabling. With it, a 1 MB inflate goes 282 → 83 µs.
`clawhdf5-format/zlib-rs` and `clawhdf5-filters/zlib-rs` now enable it.
2. **The codec was fed through a 32 KiB buffer.** Both deflate paths used
flate2's streaming `read::ZlibDecoder` / `write::ZlibEncoder`. A chunk's
decompressed size is known, so they now hand the codec the whole input in
one call, into an output buffer sized up front. Worth ~5% on chunked
writes and ~10% on zlib-ng's 1 MB inflate. It also closed a hole: the
streaming reader returned a truncated stream's bytes without an error, so
a truncated chunk read back short; it is now an error.
| 1 MB inflate, same build otherwise | zlib-rs | zlib-ng |
|---|---:|---:|
| streaming reader, no runtime detection | 284.1 µs | 76.7 µs |
| one-shot, no runtime detection | 282.3 µs | 68.5 µs |
| one-shot + runtime detection (shipped) | **82.8 µs** | **68.6 µs** |
---
## h5bench-Equivalent I/O Benchmarks
Criterion harness mirroring h5bench serial workloads. clawhdf5 benchmarks dated 2026-07-01;
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@@ -3,6 +3,16 @@
## Unreleased
### Upgrade Notes
- **The default build no longer compiles any C.** Deflate now defaults to the
pure-Rust zlib-rs instead of zlib-ng, so building the core crates needs
neither cmake nor a C compiler. Speed on HDF5 reads and writes is within 6%
of zlib-ng, and compressed output is byte-identical. To keep zlib-ng, enable
`fast-deflate` (on `clawhdf5`, `clawhdf5-format` or `clawhdf5-filters`); it
overrides zlib-rs wherever it is on.
- **A truncated deflate chunk is now an error.** It used to read back short,
with no error.
- **Minimum supported Rust is 1.92**, now declared in every crate's
`rust-version` and checked in CI.
- **New stores use the int8 vector index by default.**
`MemoryConfig::quantized_index` now defaults to `true`: a quarter of the
index memory, builds 1.8x (x86-64) and 2.3x (Raspberry Pi 5) faster, and
@@ -13,6 +23,30 @@
`quantized_index = false`, or pass `create --f32-index` to the CLI, to opt
out. The CLI's `--quantized-index` is still accepted but is now a no-op.
### Build
- **Pure-Rust default.** `clawhdf5-format`, `clawhdf5-filters` and the
`clawhdf5` facade default to the `zlib-rs` deflate backend; `fast-deflate`
(zlib-ng) is opt-in. No crate in the default dependency tree of the core
crates compiles C, and `ci-test.sh` now fails if one appears. The facade's
`fast-deflate` was on by default and is now off. See `BENCHMARKS.md`,
"Deflate backend".
- `zlib-rs` also enables flate2's `runtime_detection`. Without it zlib-rs has
no `std`, cannot detect SIMD at runtime, and inflates 3.5x slower; the
workspace builds flate2 with `default-features = false`, which had been
switching it off.
- `rust-version = "1.92"` for the whole workspace (the floor: `wgpu` requires
it), and CI checks the workspace on exactly that toolchain.
- CI keeps zlib-ng building and tested; the arm64 job no longer needs cmake.
### Correctness
- `clawhdf5-format`: **a truncated deflate chunk read back short, with no
error.** The deflate filter used flate2's streaming reader, which returns the
bytes it has when the input runs out before the end-of-stream marker. It now
decodes in one pass into a buffer sized to the chunk and reports a
truncated stream as `DecompressionError`. Same fix in `clawhdf5-filters`,
where output longer than the stated size was also silently cut off; it is
now an error.
### Defaults
- `clawhdf5-agent`: `MemoryConfig::quantized_index` defaults to `true` for new
stores. The reason it had been off — that int8 search was slower on ARM —
@@ -26,6 +60,10 @@
knew to ask; it now only ever switches the default off.
### Performance
- `clawhdf5-format`, `clawhdf5-filters`: both deflate paths hand the codec the
whole chunk in one call, into a buffer allocated once, instead of streaming
it through a 32 KiB buffer: about 5% on chunked writes and 10% on zlib-ng's
1 MB inflate.
- `clawhdf5-accel`: **`dot_i8` has aarch64 kernels** — `SDOT` for CPUs with
the ARMv8.2 dot-product extension (Cortex-A76 and later, Neoverse-N1, every
Apple Silicon generation) and plain NEON (`vmull_s8` + `vpadalq_s16`) for
+12 -6
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@@ -19,7 +19,7 @@ Cargo workspace with 16 crates under `crates/` (plus `libaec-sys`, an internal F
| `clawhdf5-agent` | Agent memory, session history, knowledge graph storage |
| `clawhdf5-gpu` | GPU-accelerated I/O via wgpu (hand-written WGSL compute shaders) |
| `clawhdf5-accel` | CPU SIMD acceleration path |
| `clawhdf5-migrate` | Schema migration engine |
| `clawhdf5-migrate` | SQLite → HDF5 agent-memory migration |
| `clawhdf5-android` | Android JNI bindings |
| `clawhdf5-cli` | Command-line interface |
| `clawhdf5-napi` | Node.js native addon bindings |
@@ -27,7 +27,12 @@ Cargo workspace with 16 crates under `crates/` (plus `libaec-sys`, an internal F
| `clawhdf5-bench` | Benchmark suite |
## Key Features
- Zero-dependency HDF5 read/write (no libhdf5 C library required)
- Zero-C-dependency HDF5 read/write: no libhdf5, and deflate defaults to
pure-Rust zlib-rs (`fast-deflate` opts into zlib-ng, which needs cmake).
`ci-test.sh` fails if a C-building crate enters the core crates' default
tree. flate2 must keep `runtime_detection` with zlib-rs — without it zlib-rs
loses SIMD and inflates 3.5x slower. MSRV is 1.92 (`rust-version`, checked
in CI).
- HNSW vector index for semantic similarity search over agent memories — the
`clawhdf5-agent` `hnsw` feature is **on by default**, so `hybrid_search` uses
the approximate `clawhdf5-ann` index for the vector stage (the index mirrors
@@ -82,8 +87,8 @@ Cargo workspace with 16 crates under `crates/` (plus `libaec-sys`, an internal F
`export` do). An unreadable WAL (torn header, bad magic) is quarantined to
`<store>.h5.wal.corrupt-<ts>` rather than blocking `open()`; a WAL with an
unknown *newer* version still fails and is left untouched.
- `MemoryConfig::compression` uses deflate by default; enable the agent's
`zstd` feature to compress embeddings with Zstd instead (links libzstd).
- `MemoryConfig::compression` is off by default; when on, embeddings are
deflate-compressed, or Zstd with the agent's `zstd` feature (links libzstd).
- `Dataset::verify_provenance()` (clawhdf5 facade, `provenance` feature, on by
default) recomputes a dataset's SHA-256 and compares it against the
`_provenance_sha256` attribute written automatically on save when
@@ -128,8 +133,9 @@ cargo test --workspace
Keep workflows free of JavaScript actions (`actions/checkout`, `actions/cache`,
…): `rust:latest` has no `node`, and not every runner reaches GitHub, where
they are fetched from. Check out with plain `git` instead. Both jobs need
`cmake` for `libz-ng-sys` (from `clawhdf5-format`'s default `fast-deflate`).
they are fetched from. Check out with plain `git` instead. The `test` job
installs `cmake` for the opt-in `fast-deflate` (zlib-ng) steps; the default
build needs no C toolchain, so `test-arm64` does not.
All runners are on `gitea-runner` 3.5.0, from `docker.gitea.com/act_runner`
`gitea/act_runner:latest` on Docker Hub is frozen at 0.6.1.
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@@ -23,6 +23,9 @@ resolver = "2"
[workspace.package]
version = "2.7.0"
edition = "2024"
# Oldest toolchain that builds the whole workspace; CI checks it. wgpu (in
# clawhdf5-gpu) requires 1.92.
rust-version = "1.92"
license = "MIT"
repository = "https://git.redclaw.dev/quantumclaw/clawhdf5"
+267 -131
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@@ -3,24 +3,89 @@
**The memory layer AI agents deserve. One file. Pure Rust. Zero C dependencies.**
[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE)
[![Rust](https://img.shields.io/badge/rust-1.75%2B-orange.svg)](https://www.rust-lang.org)
[![Tests](https://img.shields.io/badge/tests-1650%2B%20passing-brightgreen.svg)](#performance)
[![LongMemEval](https://img.shields.io/badge/LongMemEval%20oracle-Turn--Level%20Hit@5%2084%25%20BM25--only-blue.svg)](BENCHMARKS.md#longmemeval-results)
[![Footprint](https://img.shields.io/badge/footprint-6.5%20KB%2Frecord-lightgrey.svg)](BENCHMARKS.md#memory-footprint)
[![Rust](https://img.shields.io/badge/rust-1.92%2B-orange.svg)](https://www.rust-lang.org)
[![Tests](https://img.shields.io/badge/tests-1850%2B-brightgreen.svg)](#building)
[![LongMemEval](https://img.shields.io/badge/LongMemEval__s-Turn--Level%20Hit@5%2081.4%25%20hybrid-blue.svg)](BENCHMARKS.md#longmemeval-results)
[![Footprint](https://img.shields.io/badge/on--disk-1.7%20KB%2Frecord-lightgrey.svg)](BENCHMARKS.md#memory-footprint-1)
ClawHDF5 is a pure-Rust HDF5 implementation combined with a research-grade agent memory engine. It gives AI agents persistent, searchable, cryptographically verifiable memory — all stored in a single portable file.
ClawHDF5 is a pure-Rust HDF5 implementation combined with a research-grade agent memory engine. It gives AI agents persistent, searchable, integrity-checked memory — all stored in a single portable file.
> **Two things live here:**
> - **A general-purpose, pure-Rust HDF5 library** — zero C dependencies, NetCDF-4 support, SIMD/GPU acceleration. See the **[Crate Map](#crate-map)** and **[BENCHMARKS.md](BENCHMARKS.md)** for the libhdf5 head-to-head numbers.
> - **An agent memory layer built on top of it** — vector search, knowledge graph, hippocampal-style consolidation, in `clawhdf5-agent`.
```
cargo add clawhdf5 # core HDF5 read/write, no agent layer
cargo add clawhdf5-agent --features agent # + agent memory layer
The crates are not on crates.io yet, so depend on them from git:
```toml
[dependencies]
clawhdf5 = { git = "https://git.redclaw.dev/quantumclaw/clawhdf5" } # core HDF5 read/write
clawhdf5-agent = { git = "https://git.redclaw.dev/quantumclaw/clawhdf5" } # + agent memory layer
```
> **C dependencies, precisely:** the core crates (`clawhdf5`, `clawhdf5-agent`,
> `-format`, `-io`, `-filters`, `-ann`, `-accel`, `-netcdf4`, `-cli`) build no C
> code by default — no libhdf5, and deflate is the pure-Rust
> [zlib-rs](https://github.com/trifectatechfoundation/zlib-rs), which matches
> zlib-ng on HDF5 reads and writes and produces byte-identical output
> ([BENCHMARKS.md § Deflate backend](BENCHMARKS.md#deflate-backend-zlib-rs-vs-zlib-ng)).
> CI fails if a C-building crate enters their default dependency tree. C comes
> in only when you ask for it: `fast-deflate` (zlib-ng, needs cmake), `zstd`,
> `szip`, the BLAS backends, `clawhdf5-migrate` (bundled SQLite) and the
> Node.js bindings.
> **New here?** Start with the **[Quickstart Guide](docs/QUICKSTART.md)** · See **[Use Cases](docs/USE_CASES.md)** · Read **[Benchmarks](BENCHMARKS.md)**
## What's new (v2.2 → v2.7, and unreleased)
Five releases in September 2026. Details, including upgrade notes and every
breaking change, are in [CHANGELOG.md](CHANGELOG.md).
**HDF5 correctness (read these if you read files with an earlier release)**
- **Extensible Array chunk indexes returned wrong data** past the 36th chunk —
any dataset with one unlimited dimension. Silent: plausible numbers from the
wrong chunks. Fixed in v2.7.0; re-read affected data.
- Fixed and Extensible Array checksums are now verified, so a corrupt chunk
index is `ChecksumMismatch` instead of wrong data (v2.7.0).
- Compound datatypes written with default libver bounds (plain
`h5py.File(path, 'w')`) were mis-parsed; HDF5 2.0 compound v5 and native
complex (class 11) types now parse (v2.2.0v2.3.0).
- Committed datatypes, fill values, soft links and `H5T_STD_REF` references now
read correctly; external links and external raw data are explicit errors;
`attrs()` no longer silently drops attributes (v2.3.0v2.5.0).
- Datasets indexed by a version-2 B-tree now read (v2.5.0).
**Security and robustness**
- A crafted file could abort any reader via B-tree v2 recursion or explode it
via shared children; both are now fast errors (v2.7.0).
- Virtual-dataset source paths are confined to the file's directory; chunked
reads use overflow-checked sizes and fallible allocation, and the facade
writes files atomically (v2.3.0).
- Agent store: single-writer lock plus `open_read_only`; a crash between
checkpoint and WAL truncate no longer duplicates entries; unreadable WALs are
quarantined instead of blocking `open()` (v2.3.0).
**Search quality and speed**
- HNSW neighbour selection now uses the paper's diversity heuristic: recall@10
at 100K went from 0.31 to 0.98 (v2.4.0).
- `hybrid_search` is 79190× faster than v2.3.0 (p50 0.07 ms at 1K, 4.65 ms at
100K). It no longer rebuilds BM25 or rewrites the store per query, and the
HNSW graph is persisted (v2.4.0).
- Default fusion weights are now the measured 0.4 / 0.6 (v2.5.0). Re-ranking had
been discarding the retrieval score, costing the OpenClaw backend 40.6pp of
Hit@1; fixed in v2.6.0.
- Selection reads decode only the chunks they touch (a 64×64 window: 105 ms to
0.39 ms), and full reads are 1.21.9× faster (v2.5.0).
**Memory**
- A loaded store holds ~30% less (embeddings stored once, v2.6.0), and the
int8 HNSW index, **on by default for new stores** (unreleased), brings a
100K × 384 store to 1.74× the raw vectors. At equal recall it is also faster
than `f32`: 1.63× QPS on AVX2, 1.18× on a Raspberry Pi 5 (NEON `SDOT`).
**Tooling**
- CI now runs the h5py/netCDF4 interop suites for real (they had been skipping
silently) and runs an aarch64 job for the NEON kernels.
---
## Why ClawhDF5?
@@ -35,7 +100,7 @@ Every AI agent needs memory. Today that means scattered Markdown files, SQLite d
| Memory consolidation | Manual pruning | Hippocampal-inspired automatic tiers |
| Temporal queries | Custom code | Native temporal index (716ns) |
| Multi-modal | Multiple stores | Unified cross-modal search |
| Security | Hope for the best | Provenance tracking + anomaly detection |
| Integrity | Hope for the best | Chained-CRC WAL, checksummed chunk indexes, write-anomaly alerts, opt-in SHA-256 dataset provenance |
| Portability | Config + DB + files | **One `.h5` file. Copy it anywhere.** |
---
@@ -58,8 +123,28 @@ Figures below are from an independent reproduction run on a second machine (AMD
| Sequential read (100K f32) | 23.3 µs | 63.6 µs | **2.7×** |
| Sequential write (100K f32) | 210 µs | 189 µs | **≈ tie** |
The chunked-write row was re-measured on the same machine on 2026-09-23, after
the default deflate backend became pure-Rust zlib-rs: 1.46 ms against
libhdf5's 51.4 ms (**35×**), and 1.48 ms with zlib-ng. libhdf5's own time on
that machine moved from 65.0 to 51.4 ms between the two dates, which is most
of the difference from 45×; compare same-day numbers only.
### Vector Search
**HNSW (the default backend for `hybrid_search`)**`search_harness`, clustered
384-dim data, M = 16, ef_construction = 64, recall measured against an exact scan.
See [BENCHMARKS.md § Search harness](BENCHMARKS.md#search-harness-baseline-v230)
and [§ Quantising the index copy](BENCHMARKS.md#quantising-the-index-copy-quantized_index):
| N = 100K, ef = 64 | recall@10 | QPS | build |
|---|---:|---:|---:|
| `f32` index | 0.9945 | 13 399 | 3.2 s |
| `i8` index + exact re-score (**default for new stores**) | 0.9940 | **21 848** | **1.8 s** |
Before the v2.4.0 neighbour-selection fix, recall@10 at 100K was 0.31.
**Brute-force and IVF paths** (Criterion, i7-12650H):
| Scale | Flat | IVF (nprobe=10) | IVF-PQ | vs MemX¹ |
|-------|------|-----------------|--------|----------|
| 1K | **54 µs** | — | — | — |
@@ -75,7 +160,7 @@ Figures below are from an independent reproduction run on a second machine (AMD
| Operation | Latency | Scale |
|-----------|---------|-------|
| Hybrid search (RRF) | **222 µs** | 1K records |
| Hybrid search (`HDF5Memory::hybrid_search`, p50) | **70 µs** / 0.49 ms / 4.65 ms | 1K / 10K / 100K records |
| BM25 keyword search | **67 µs** | 1K records |
| Knowledge graph BFS | **24 µs** | 1K entities |
| Spreading activation | **17 µs** | 100 entities |
@@ -115,13 +200,17 @@ declaration:
Hybrid is the strongest configuration, which is what running two retrieval stages
is for. The weights matter more than the stages: a sweep of `vector_weight` from
0.0 to 1.0 found the long-standing `0.7/0.3` default is **strictly dominated** by
`0.4/0.6` — better on Hit@1, Hit@5, Hit@10 and MRR at both granularities. Use
`0.4/0.6`, or `0.3/0.7` if rank-1 precision matters most. See
[BENCHMARKS.md § Weight sweep](BENCHMARKS.md#longmemeval-results).
0.0 to 1.0 found the old `0.7/0.3` default is **strictly dominated** by
`0.4/0.6` — better on Hit@1, Hit@5, Hit@10 and MRR at both granularities. Since
v2.5.0 `0.4/0.6` is the default (`hybrid::DEFAULT_FUSION`, used by
`unified_search`, `hybrid_search_with` and the OpenClaw backend); callers that
pass weights to `hybrid_search` explicitly choose their own. Use `0.3/0.7` if
rank-1 precision matters most. Reciprocal rank fusion is selectable
(`hybrid::Fusion::Rrf`) but measured worse than the weighted sum. See
[BENCHMARKS.md § Weight sweep](BENCHMARKS.md#weight-sweep--full-haystack-n500).
Vector embeddings require `--features embeddings`; without it the vector stage is
inert and only the BM25 row is produced, which is what every previously published
The benchmark's vector stage requires `clawhdf5-bench`'s `embeddings` feature
(real MiniLM embeddings); without it the vector stage is inert and only the BM25 row is produced, which is what every previously published
number here measured.
On the easier `longmemeval_oracle` variant (evidence sessions only) the same
@@ -146,19 +235,37 @@ retrieval recall reported as QA accuracy typically overstates by 2030 points.
### Memory Footprint
| Records | File Size | Bytes/Record | With Compression |
|---------|-----------|--------------|------------------|
| 1K | ~6.5 MB | ~6.5 KB | ~2.1 MB (3.1x) |
| 10K | ~65 MB | ~6.5 KB | ~21 MB (3.1x) |
| 100K | ~645 MB | ~6.5 KB | ~208 MB (3.1x) |
**On disk** — 384-dim embeddings, 200-char text
([BENCHMARKS.md § Memory Footprint](BENCHMARKS.md#memory-footprint-1)):
| Records | File Size | Bytes/Record | Gzip-6 compressed |
|---------|-----------|--------------|-------------------|
| 1K | 1.7 MB | 1.8 KB | 277 KB (6.1x) |
| 10K | 17.0 MB | 1.7 KB | 2.7 MB (6.2x) |
| 100K | 169.8 MB | 1.7 KB | 26.9 MB (6.2x) |
**In memory** — a store reopened from disk, 384-dim `f32`, measured with a
counting allocator ([BENCHMARKS.md § Memory footprint](BENCHMARKS.md#memory-footprint)):
| Records | Raw vectors | Reopened, `f32` index | Reopened, `i8` index (default) |
|---------|-------------|-----------------------|--------------------------------|
| 1K | 1 MiB | 4 MiB (2.40x) | 2 MiB (1.64x) |
| 10K | 15 MiB | 44 MiB (3.03x) | 27 MiB (1.81x) |
| 100K | 146 MiB | 399 MiB (2.72x) | **256 MiB (1.74x)** |
Down from 505 MiB (3.44x) at 100K before v2.6.0, when the cache held every
embedding twice.
### Consolidation Efficiency
1,000 records (10 signal + 990 noise), `working_capacity = 100`
([BENCHMARKS.md § Consolidation Efficiency](BENCHMARKS.md#consolidation-efficiency)):
| Metric | Before | After | Delta |
|--------|--------|-------|-------|
| Records in store | 1,000 | ~110 | 89% |
| Hit@1 recall | ~60% | ~90% | +30% |
| Search latency | ~2.8 ms | ~0.3 ms | **9x faster** |
| Records in store | 1,000 | 100 | 90% |
| Hit@1 recall (signal records) | 100% | 100% | no loss |
| Search latency | 2.75 ms | 0.31 ms | **8.8x faster** |
**Full benchmark details: [BENCHMARKS.md](BENCHMARKS.md)**
@@ -166,74 +273,71 @@ retrieval recall reported as QA accuracy typically overstates by 2030 points.
## Agent Memory Architecture
ClawhDF5's agent memory engine implements research from 15+ recent papers on agentic memory systems. It's not a toy — it's the real thing.
ClawhDF5's agent memory engine draws on 15+ recent papers on agentic memory systems (see [Research Foundation](#research-foundation)).
```
┌─────────────────┐
│ Agent Query │
└────────┬────────┘
┌────────────▼────────────┐
│ Hybrid Retrieval
│ Vector + BM25 + RRF
└────────────┬────────────┘
──────────────────▼──────────────────
│ Multi-Factor Re-Ranking │
│ temporal · authority · activation │
└──────────────────┬──────────────────┘
┌────────────▼────────────┐
│ Confidence Rejection │
─────────────────▼──────────────────
│ HDF5Memory::hybrid_search
│ HNSW vector + BM25 keyword
│ weighted fusion (0.4 / 0.6) │
× √(Hebbian activation)
───────────────────────────────────
│ OpenClaw backend adds:
┌─────────────────▼──────────────────┐
│ Multi-factor re-ranking │
│ relevance · recency · authority ·
│ activation │
├────────────────────────────────────┤
│ Confidence rejection │
│ (suppress bad matches) │
└────────────┬────────────┘
─────────────────┬──────────────────
┌────────────────────────▼────────────────────────┐
Memory Store (HDF5)
│ ┌───────────┐ ┌───────────┐ ┌───────────────┐
│ │ Working │→│ Episodic │→│ Semantic │ │
│ │ (bounded) │ │ (bounded) │ │ (long-term) │ │
│ └───────────┘ └───────────┘ └───────────────┘ │
┌──────────┐ ┌──────────┐ ┌────────────────┐
│ │Knowledge │ │Temporal │ │ Multi-Modal
│ │ Graph │ │ Index │ │ Embeddings │
└──────────┘ └──────────┘ └────────────────┘
│ │
│ ┌──────────┐ ┌──────────┐ ┌────────────────┐ │
│ │Provenance│ │ Anomaly │ │ Source │ │
│ │ Tracking │ │Detection │ │ Isolation │ │
│ └──────────┘ └──────────┘ └────────────────┘ │
└─────────────────────────────────────────────────┘
┌────────┴────────┐
│ agent_memory.h5 │
│ single file │
└─────────────────┘
────────────────────────────▼────────────────────────────
│ In memory
│ cache (flat f32 embeddings) · BM25 index · HNSW index
provenance ledger + anomaly alerts (session-scoped)
└────────────────────────────┬────────────────────────────┘
│ WAL append; checkpoint
┌────────────────────────────▼────────────────────────────┐
│ agent_memory.h5 /meta · /memory · /sessions ·
│ /knowledge_graph
│ agent_memory.h5.wal chained-CRC write-ahead log
│ agent_memory.h5.ann HNSW graph (derived, rebuildable)
│ agent_memory.h5.lock single-writer lock
└─────────────────────────────────────────────────────────┘
```
Consolidation tiers (Working → Episodic → Semantic), the knowledge-graph
algorithms, temporal and multi-modal indexes are library components you drive
directly; the store persists the records, sessions and graph they work over.
### Module Overview
| Module | What It Does |
|--------|-------------|
| **`knowledge`** | Entity/relation graph with BFS traversal, spreading activation, fuzzy entity resolution |
| **`consolidation`** | Three-tier memory (Working → Episodic → Semantic) with importance scoring and time-decay |
| **`hybrid`** | Vector + BM25 fusion with Reciprocal Rank Fusion (RRF, k=60). The vector stage uses the HNSW index by default (`hnsw` feature, on by default); disable with `--no-default-features --features float16` for an exact linear scan |
| **`reranker`** | Multi-factor re-ranking: temporal recency, source authority, activation weight |
| **`confidence`** | Low-confidence rejection — suppresses spurious recalls when nothing matches |
| **`knowledge`** | Entity/relation graph with BFS traversal, spreading activation, fuzzy (Levenshtein) entity resolution |
| **`consolidation`** | Three-tier memory (Working → Episodic → Semantic) with importance scoring, novelty, and time-decay |
| **`hybrid`** | Vector + BM25 fusion. Default is a min-max-normalised weighted sum, vector 0.4 / keyword 0.6 (`hybrid::DEFAULT_FUSION`, tuned on LongMemEval); RRF is available via `Fusion::Rrf` / `hybrid_search_with`. The vector stage uses the HNSW index by default (`hnsw` feature); disable with `--no-default-features --features float16` for an exact linear scan |
| **`reranker`** | Multi-factor re-ranking: retrieval relevance (leads, weight 1.0), temporal recency, source authority, activation weight. Used by the OpenClaw backend |
| **`confidence`** | Low-confidence rejection — suppresses spurious recalls when nothing matches (OpenClaw backend) |
| **`temporal`** | Sorted timestamp index, session DAG, entity timeline, temporal query hints |
| **`multimodal`** | Cross-modal search across text/image/audio/video embeddings |
| **`provenance`** | Source attribution, FNV-1a content hashing, integrity verification |
| **`anomaly`** | Write rate limiting, 15 injection pattern detectors, source distribution analysis |
| **`provenance`** | Source attribution and an unkeyed FNV-1a content hash per record, held in memory for the session, for detecting accidental corruption (not tamper-proof) |
| **`anomaly`** | Write rate limiting, 15 injection-pattern detectors, source-distribution analysis. Alerts never block a save; drain them with `take_anomaly_alerts` |
| **`openclaw`** | OpenClaw integration: MemoryBackend trait, Markdown ↔ HDF5 conversion |
| **`vector_search`** | Flat cosine, pre-normed, SIMD, BLAS, GPU, parallel search paths |
| **`ivf` / `pq`** | IVF-PQ approximate nearest neighbor for billion-scale search |
| **`bm25`** | BM25 keyword index with TF-IDF scoring |
| **`ivf` / `pq`** | Standalone IVF and IVF-PQ indexes (benchmarked to 100K vectors); not used by `HDF5Memory`, whose ANN index is HNSW |
| **`bm25`** | Incremental Okapi BM25 inverted index, kept for the life of the store; optional stemming |
| **`query_expand`** | Synonym / acronym / temporal query expansion |
| **`entity_extract`** | Rule-based entity extraction from text chunks into the knowledge graph |
| **`wal`** | Write-ahead log for crash-safe persistence; each entry is CRC32-checked on replay, so a corrupted entry stops replay there instead of loading bad data |
| **`wal`** | Write-ahead log (v4) with a chained CRC32 per entry, so a corrupted, reordered, duplicated or spliced entry stops replay; checkpoints record a WAL mark so nothing is applied twice. Appends are not fsynced |
| **`memory_strategy`** | Pluggable strategies: save-every, semantic-shift, user-correction detection |
| **`decision_gate`** | Sub-microsecond trivial/substantive classification |
| **`ephemeral`** | In-memory TTL/LFU working tier |
| **`async_memory`** | Tokio-based async wrapper over the memory store (`async` feature) |
---
@@ -265,7 +369,7 @@ assert_eq!(values, vec![22.5, 23.1, 21.8]);
use clawhdf5_agent::{HDF5Memory, MemoryConfig, MemoryEntry, AgentMemory};
// Create memory store
let config = MemoryConfig::new("agent.h5", "my-agent", 384);
let config = MemoryConfig::new("agent.h5".into(), "my-agent", 384);
let mut memory = HDF5Memory::create(config)?;
// Save a memory
@@ -278,8 +382,8 @@ memory.save(MemoryEntry {
tags: "preference".into(),
})?;
// Search
let results = memory.search(&query_embedding, 5)?;
// Hybrid search: vector + BM25, weighted 0.4 / 0.6 (the measured default)
let results = memory.hybrid_search(&query_embedding, "user preferences", 0.4, 0.6, 5);
for result in results {
println!("[{:.3}] {}", result.score, result.chunk);
}
@@ -309,8 +413,8 @@ let neighbors = kg.bfs_neighbors(alice, 2); // 2-hop neighborhood
let activated = kg.spreading_activation(&[alice], 0.5, 0.01, 5);
// Entity resolution — fuzzy matching
let resolved = kg.resolve_or_create("alice", "person", -1, 2);
// Returns existing Alice entity (Levenshtein distance ≤ 2)
let (id, created) = kg.resolve_or_create("alice", "person", -1, 2);
// id == alice, created == false: matched the existing entity (Levenshtein distance ≤ 2)
```
### Memory Consolidation
@@ -321,15 +425,19 @@ use clawhdf5_agent::consolidation::*;
let config = ConsolidationConfig::default();
let mut engine = ConsolidationEngine::new(config);
// Add memories — automatically scored for importance
engine.add_memory("User prefers dark mode", vec![0.1, 0.2, ...], MemorySource::User);
engine.add_memory("ok", vec![0.0, 0.0, ...], MemorySource::System);
let now = 1_700_000_000.0; // seconds since the epoch
// Add memories — automatically scored for importance.
// Elevated sources (System, …) go through a separate, explicit API.
let id = engine.add_memory("User prefers dark mode".into(), vec![0.1, 0.2, ...], UntrustedSource::User, now);
engine.add_trusted_memory("ok".into(), vec![0.0, 0.0, ...], TrustedSource::System, now);
// Access a memory (reactivates it)
engine.access_memory(0);
engine.access_memory(id, now);
// Run consolidation cycle
let stats = engine.consolidate();
engine.consolidate(now);
let stats = engine.get_stats();
// Working memories promote to Episodic (if important enough)
// Episodic memories promote to Semantic (if accessed enough)
// Low-decay memories get evicted when tiers are full
@@ -357,13 +465,13 @@ let recent = index.latest(10);
use clawhdf5_agent::openclaw::*;
// Create backend
let mut backend = ClawhdfBackend::create("memory.h5", "agent-1", 384)?;
let mut backend = ClawhdfBackend::create(std::path::Path::new("memory.h5"), 384)?;
// Ingest existing Markdown memory files
let md = std::fs::read_to_string("MEMORY.md")?;
let count = backend.ingest_markdown("MEMORY.md", &md)?;
// Search (uses full pipeline: RRF → re-rank → confidence filter)
// Search (full pipeline: weighted vector + BM25 fusion → re-rank → confidence filter)
let results = backend.search("user preferences", &query_embedding, 5);
// Export back to Markdown
@@ -375,22 +483,23 @@ let exported = backend.export_markdown("MEMORY.md")?;
## Crate Map
```
clawhdf5 workspace (16 crates, ~92K lines of Rust; plus libaec-sys, an
internal FFI bindings crate for the optional szip feature)
clawhdf5 workspace (16 crates, ~86K lines of Rust in src/, ~104K with tests
and benches; plus libaec-sys, an internal FFI bindings
crate for the optional szip feature)
├── Core HDF5
│ ├── clawhdf5-format — Binary parser/writer (no_std), shared type definitions
│ ├── clawhdf5-io — I/O abstraction (buffered, mmap, async)
│ ├── clawhdf5-format — Binary parser/writer (no_std-capable), shared type definitions
│ ├── clawhdf5-io — I/O abstraction (file/memory readers; optional mmap, async, HSDS, MPI)
│ ├── clawhdf5-filters — Fast deflate path (zlib-ng); lz4/zstd/pcodec/szip filters live in clawhdf5-format
│ ├── clawhdf5-derive — Proc macros
│ ├── clawhdf5 — High-level API
│ ├── clawhdf5-netcdf4 — NetCDF-4 support
│ ├── clawhdf5-accel — SIMD (NEON, AVX2, AVX-512)
│ ├── clawhdf5-accel — SIMD (AVX2, NEON incl. SDOT int8; AVX-512 behind `avx512`)
│ └── clawhdf5-gpu — GPU compute (wgpu, hand-written WGSL compute shaders)
├── Agent Memory
│ ├── clawhdf5-agent — Memory engine (20.9K lines, 32 modules; WAL is CRC32-checked per entry)
│ ├── clawhdf5-ann — HNSW approximate nearest neighbor (default backend; optional `parallel` feature)
│ ├── clawhdf5-agent — Memory engine (24.7K lines, 32 modules; chained-CRC WAL)
│ ├── clawhdf5-ann — HNSW approximate nearest neighbor (default backend; f32 or int8 storage; `parallel` build)
│ ├── clawhdf5-migrate — SQLite → HDF5 migration
│ ├── clawhdf5-android — Android JNI bridge
│ └── clawhdf5-cli — CLI tool
@@ -411,10 +520,10 @@ ClawhDF5's agent memory design draws from 15+ recent papers:
| Paper | Key Insight | ClawhDF5 Module |
|-------|-------------|-----------------|
| **MemX** (2026) | RRF + multi-factor re-ranking | `hybrid`, `reranker` |
| **Graph-Native Cognitive Memory** (2026) | Graph-structured belief revision | `knowledge` |
| **MemX** (2026) | Hybrid fusion + multi-factor re-ranking | `hybrid`, `reranker` |
| **Graph-Native Cognitive Memory** (2026) | Graph-structured memory (weighted, timestamped relations; entity timelines) | `knowledge`, `temporal` |
| **CraniMem** (2026) | Bounded hippocampal memory | `consolidation` |
| **D-MEM** (2026) | Reward prediction error gating | `consolidation` |
| **D-MEM** (2026) | Surprise-gated storage (implemented as a novelty score) | `consolidation` |
| **SYNAPSE** (2025) | Spreading activation for recall | `knowledge` |
| **RAGdb** (2025) | Zero-dependency edge RAG | Architecture |
| **MemoryGraft** (2025) | Memory poisoning attacks | `anomaly`, `provenance` |
@@ -429,29 +538,35 @@ ClawhDF5's agent memory design draws from 15+ recent papers:
| Flag | Default | Description |
|------|---------|-------------|
| `agent` | no | Full agent memory layer |
| `float16` | **yes** | Half-precision embedding storage (2× compression) |
| `float16` | **yes** | Half-precision cosine kernel (`cosine_similarity_f16`). The store itself always writes `f32` embeddings; `MemoryConfig::float16` is recorded in `/meta` but not yet applied |
| `hnsw` | **yes** | HNSW approximate vector index for `hybrid_search` (via `clawhdf5-ann`); disable for an exact linear scan |
| `parallel` | **yes** | Parallel HNSW bulk build (same graph, ~3× faster on 16 cores) and Rayon brute-force search strategies |
| `zstd` | no | Compress embeddings with Zstd instead of deflate when `MemoryConfig::compression` is on (links libzstd) |
| `fast-math` | no | BLAS matrix-vector multiply |
| `accelerate` | no | Apple Accelerate / AMX (macOS) |
| `openblas` | no | OpenBLAS (Linux) |
| `gpu` | no | GPU search via wgpu |
| `async` | no | Tokio async with background flush |
| `agent` | no | Reserved; currently enables nothing (the agent layer is always built) |
To opt out of the parallel build: `--no-default-features --features float16,hnsw`.
For an exact linear cosine scan instead of HNSW: `--no-default-features --features float16`.
`MemoryConfig::hnsw_m`, `hnsw_ef_construction` and `hnsw_ef_search` tune the
vector index (16 / 64 / scale-with-`k` by default) and are stored with the
file.
`MemoryConfig::quantized_index` (**on by default** for new stores) holds the
HNSW index's own
copy of the embeddings as `i8`, roughly halving a loaded store's memory
(2.72x -> 1.74x the raw vectors at 100k x 384). Quantised distances are
approximate, so the query path re-scores the candidate pool against the exact
embeddings the store already holds, which keeps recall at the `f32` index's
level. It is also **faster**: 1.63x the queries per second at equal recall on
x86-64 (AVX2) and 1.18x on a Raspberry Pi 5 (NEON `SDOT`), with index builds
1.8x and 2.3x faster respectively. See `BENCHMARKS.md`, "Quantising the index copy".
| `parallel` | no | Rayon parallel search |
| `fast-math` | no | BLAS matrix-vector multiply |
| `accelerate` | no | Apple Accelerate / AMX (macOS) |
| `openblas` | no | OpenBLAS (Linux) |
| `gpu` | no | GPU search via wgpu |
| `async` | no | Tokio async with background flush |
HNSW index's own copy of the embeddings as `i8`, roughly halving a loaded
store's memory (2.72x -> 1.74x the raw vectors at 100k x 384). Quantised
distances are approximate, so the query path re-scores the candidate pool
against the exact embeddings the store already holds, which keeps recall at the
`f32` index's level. It is also **faster**: 1.63x the queries per second at
equal recall on x86-64 (AVX2) and 1.18x on a Raspberry Pi 5 (NEON `SDOT`), with
index builds 1.8x and 2.3x faster respectively. Stores created before the
setting existed keep their `f32` index; opt out for new stores with
`quantized_index = false` or `clawhdf5-cli create --f32-index`. See
[BENCHMARKS.md § Quantising the index copy](BENCHMARKS.md#quantising-the-index-copy-quantized_index).
### `clawhdf5-format`
@@ -461,26 +576,31 @@ x86-64 (AVX2) and 1.18x on a Raspberry Pi 5 (NEON `SDOT`), with index builds
| `deflate` | yes | Deflate compression |
| `checksum` | yes | Jenkins lookup3 verification |
| `provenance` | yes | SHA-256 provenance attributes |
| `fast-deflate` | **yes** | zlib-ng backend for faster deflate |
| `system-zlib-decompress` | **yes** | Use the system zlib for decompression where available |
| `zlib-rs` | **yes** | Pure-Rust deflate backend ([zlib-rs](https://github.com/trifectatechfoundation/zlib-rs)) |
| `fast-deflate` | no | zlib-ng deflate backend instead (C; needs `cmake`). Overrides `zlib-rs` when both are on |
| `system-zlib-decompress` | **yes** | Use Apple's system libz for decompression (macOS only; no effect elsewhere) |
| `parallel` | no | Parallel chunk encoding + compression (rayon) |
| `fast-checksum` | no | crc32fast-accelerated checksums |
| `lz4` | no | LZ4 block compression filter (id 32004) |
| `zstd` | no | Zstandard compression filter (id 32015) |
| `pcodec` | no | Pcodec lossless numerical codec (id 32023, via `pco` crate) |
| `system-zlib` / `zlib-rs` | no | Alternative zlib backends for deflate |
| `system-zlib` | no | System zlib backend for deflate (C) |
| `blake3_hash` | no | BLAKE3 content hashing for provenance |
| `szip` | no | SZIP filter (id 4) via libaec (C, through the internal `libaec-sys` crate) |
### `clawhdf5-ann`
| Flag | Default | Description |
|------|---------|-------------|
| `parallel` | no | Rayon-parallel neighbor-distance computation during HNSW graph pruning |
| `parallel` | no | Batched bulk build runs neighbour planning and back-link pruning on a Rayon pool; the graph is identical with or without it (enabled by `clawhdf5-agent`'s default `parallel`) |
### `clawhdf5-io`
| Flag | Default | Description |
|------|---------|-------------|
| `mmap` | no | Memory-mapped reads (`memmap2`) |
| `async` | no | Tokio-based async I/O |
| `hsds` | no | HSDS (HDF REST service) client |
| `mpi-io` | no | MPI-backed I/O via the `mpi` crate |
> **Parallel I/O (MPI) limitation:** `mpi-io`'s read path is a root-rank read
@@ -494,17 +614,17 @@ x86-64 (AVX2) and 1.18x on a Raspberry Pi 5 (NEON `SDOT`), with index builds
## Building
```bash
# Default
# Default (pure Rust: no cmake or C compiler needed)
cargo build --workspace
# Agent memory with all accelerations (Linux)
cargo build -p clawhdf5-agent --features "agent,float16,parallel,fast-math"
cargo build -p clawhdf5-agent --features fast-math
# Agent memory with Apple Accelerate (macOS)
cargo build -p clawhdf5-agent --features "agent,float16,accelerate,parallel,gpu"
cargo build -p clawhdf5-agent --features "accelerate,gpu"
# Tests
cargo test --workspace # all 1,650+ tests
cargo test --workspace # all 1,850+ tests
cargo test -p clawhdf5-agent # agent memory tests
scripts/ci-test.sh # what CI runs: fmt, clippy matrix, tests,
# h5py/netCDF4 interop, no_std
@@ -526,25 +646,41 @@ cargo bench -p clawhdf5-bench # h5bench-equivalent I/O suite
```
agent_memory.h5
├── /meta
│ ├── schema_version: "1.0"
│ ├── agent_id, embedder, embedding_dim
── created_at
├── /meta (attributes)
│ ├── schema_version: "1.0", edgehdf5_version
│ ├── agent_id, embedder, embedding_dim, chunk_size, overlap, created_at
── float16, compression, compression_level, compact_threshold,
│ │ hebbian_boost, decay_factor, wal_enabled, wal_max_entries
│ ├── quantized_index, hnsw_m, hnsw_ef_construction, hnsw_ef_search
│ ├── wal_applied_len, wal_applied_crc (WAL mark of the last checkpoint)
│ └── ann_generation (ties the .ann sidecar to this checkpoint)
├── /memory
│ ├── chunks: string[N]
│ ├── embeddings: f32[N × D] (or f16 with float16 flag)
│ ├── embeddings: f32[N × D] (chunked; deflate, or Zstd with the
│ │ `zstd` feature, when compression is on)
│ ├── source_channel: string[N]
│ ├── timestamps: f64[N]
│ ├── session_ids: string[N]
│ ├── tags: string[N]
│ ├── tombstones: u8[N]
── norms: f32[N] (pre-computed L2)
── norms: f32[N] (pre-computed L2)
│ └── activation_weights: f32[N] (Hebbian)
├── /sessions
│ ├── ids: string[S]
── summaries: string[S]
│ ├── ids, channels, summaries: string[S]
── start_idxs, end_idxs: i64[S]
│ └── timestamps: f64[S]
└── /knowledge_graph
├── entity_names: string[E]
├── relation_srcs: i64[R]
├── relation_tgts: i64[R]
└── relation_types: string[R]
├── entity_ids, entity_emb_idxs: i64[E]; entity_names, entity_types: string[E]
├── relation_srcs, relation_tgts: i64[R]; relation_types: string[R]
├── relation_weights: f32[R]; relation_ts: f64[R]
└── alias_strings: string[A]; alias_entity_ids: i64[A] (when aliases exist)
```
Alongside the store: `<store>.h5.wal` (write-ahead log), `<store>.h5.ann`
(HNSW graph; derived, safe to delete) and `<store>.h5.lock` (single-writer
lock). A second writer gets `MemoryError::Locked`; use
`HDF5Memory::open_read_only` for a lock-free point-in-time view.
---
## Migration
@@ -599,6 +735,6 @@ MIT
---
<p align="center">
<em>Built by <a href="https://github.com/redclawsystems">RedClaw Systems</a></em><br>
<em>~92,000 lines of Rust. Zero C dependencies. One file to remember everything.</em>
<em>Built by <a href="https://git.redclaw.dev/quantumclaw">RedClaw Systems</a></em><br>
<em>~86,000 lines of Rust. Zero C dependencies. One file to remember everything.</em>
</p>
+1
View File
@@ -2,6 +2,7 @@
name = "clawhdf5-accel"
version = "2.7.0"
edition = "2024"
rust-version.workspace = true
description = "SIMD-accelerated operations for rustyhdf5"
license = "MIT"
repository = "https://git.redclaw.dev/quantumclaw/clawhdf5"
+1
View File
@@ -2,6 +2,7 @@
name = "clawhdf5-agent"
version = "2.7.0"
edition = "2024"
rust-version.workspace = true
description = "HDF5-backed persistent memory store for on-device AI agents"
license = "MIT"
repository = "https://git.redclaw.dev/quantumclaw/clawhdf5"
+1
View File
@@ -2,6 +2,7 @@
name = "clawhdf5-android"
version = "2.7.0"
edition = "2024"
rust-version.workspace = true
description = "Android JNI bridge for edgehdf5-memory HDF5 backend"
license = "MIT"
+1
View File
@@ -2,6 +2,7 @@
name = "clawhdf5-ann"
version = "2.7.0"
edition = "2024"
rust-version.workspace = true
description = "HNSW approximate nearest neighbor index stored as HDF5"
license = "MIT"
repository = "https://git.redclaw.dev/quantumclaw/clawhdf5"
+1
View File
@@ -2,6 +2,7 @@
name = "clawhdf5-bench"
version = "2.7.0"
edition = "2024"
rust-version.workspace = true
description = "Benchmark harnesses for clawhdf5-agent (Track 8)"
license = "MIT"
+1
View File
@@ -2,6 +2,7 @@
name = "clawhdf5-cli"
version = "2.7.0"
edition = "2024"
rust-version.workspace = true
license = "MIT"
description = "CLI for clawhdf5 agent memory — create, save, search, recall, stats"
repository = "https://git.redclaw.dev/quantumclaw/clawhdf5"
+1
View File
@@ -2,6 +2,7 @@
name = "clawhdf5-derive"
version = "2.7.0"
edition = "2024"
rust-version.workspace = true
description = "Derive macros for rustyhdf5 HDF5 traits"
license = "MIT"
repository = "https://git.redclaw.dev/quantumclaw/clawhdf5"
+7 -2
View File
@@ -2,6 +2,7 @@
name = "clawhdf5-filters"
version = "2.7.0"
edition = "2024"
rust-version.workspace = true
description = "Filter and compression pipeline for clawhdf5"
license = "MIT"
repository = "https://git.redclaw.dev/quantumclaw/clawhdf5"
@@ -25,8 +26,12 @@ name = "compression_bench"
harness = false
[features]
default = ["fast-deflate"]
# Pure-Rust zlib-rs by default; `fast-deflate` (zlib-ng, C) overrides it.
default = ["zlib-rs"]
fast-deflate = ["flate2/zlib-ng"]
system-zlib = ["flate2/zlib-default"]
zlib-rs = ["flate2/zlib-rs"]
# `runtime_detection` gives zlib-rs `std`, which it needs to detect and use
# SIMD at runtime. flate2 enables it by default, but we build flate2 with
# default-features = false, and without it zlib-rs inflates 3.5x slower.
zlib-rs = ["flate2/zlib-rs", "flate2/runtime_detection"]
apple-compression = []
+6 -4
View File
@@ -8,16 +8,18 @@ Filter and compression pipeline for clawhdf5.
## Features
- DEFLATE compression/decompression
- Fast deflate via zlib-ng (`fast-deflate` feature)
- Pure-Rust deflate via zlib-rs (default, `zlib-rs` feature)
- zlib-ng instead, if you want it (`fast-deflate` feature; C, needs cmake)
- Apple Compression framework support (`apple-compression` feature)
## Usage
```rust
use clawhdf5_filters::{deflate_decode, deflate_encode};
use clawhdf5_filters::{deflate_compress, deflate_decompress};
let compressed = deflate_encode(&data, 6).unwrap();
let decompressed = deflate_decode(&compressed).unwrap();
let compressed = deflate_compress(&data, 6).unwrap();
// The second argument bounds the output: the expected decompressed size.
let decompressed = deflate_decompress(&compressed, data.len()).unwrap();
```
## License
+111 -48
View File
@@ -1,12 +1,13 @@
//! Fast deflate backends: Apple Compression Framework and zlib-ng.
//! Deflate backends: Apple Compression Framework, zlib-ng and zlib-rs.
//!
//! Backend selection priority (decompression & compression):
//! 1. Apple Compression Framework (macOS only, `apple-compression` feature)
//! 2. flate2 with zlib-ng backend (`fast-deflate` feature) or miniz_oxide (default)
//! 2. flate2 with zlib-ng (`fast-deflate`), else zlib-rs (`zlib-rs`, the
//! default), else miniz_oxide
//!
//! The Apple Compression Framework uses hardware-accelerated zlib on Apple Silicon
//! and is typically the fastest option on macOS. zlib-ng is the fastest portable
//! option and what C HDF5 uses internally.
//! and is typically the fastest option on macOS. zlib-rs is a pure-Rust port of
//! zlib-ng; see `BENCHMARKS.md` for how the two compare.
// ---------------------------------------------------------------------------
// Apple Compression Framework FFI (macOS only)
@@ -243,65 +244,117 @@ mod apple {
}
// ---------------------------------------------------------------------------
// Streaming decompression via flate2 (uses zlib-ng when fast-deflate enabled)
// One-shot (de)compression via flate2 (whichever backend flate2 was built with)
//
// The whole input goes to the codec in one call, into an output buffer sized
// up front. `flate2::read::ZlibDecoder` / `write::ZlibEncoder` stream through a
// 32 KiB buffer instead, which cost zlib-rs up to 3.7x against zlib-ng on a
// 1 MB chunk. clawhdf5-format's deflate filter does the same; see
// `BENCHMARKS.md`, "Deflate backend".
// ---------------------------------------------------------------------------
/// Streaming decompress with pre-allocated output buffer.
///
/// When the output size is known (typical for HDF5 chunks), this avoids
/// dynamic reallocation by writing directly into a pre-sized buffer.
/// Decompress into a buffer pre-sized to `output_size`, the expected
/// decompressed length (known for HDF5 chunks). Output longer than that is an
/// error, as is a stream that ends early.
pub(crate) fn flate2_decompress_preallocated(
data: &[u8],
output_size: usize,
) -> Result<Vec<u8>, String> {
use std::io::Read;
let mut decoder = flate2::read::ZlibDecoder::new(data);
let mut output = vec![0u8; output_size];
let mut total_read = 0;
loop {
match decoder.read(&mut output[total_read..]) {
Ok(0) => break,
Ok(n) => total_read += n,
Err(e) => return Err(e.to_string()),
}
}
output.truncate(total_read);
Ok(output)
inflate_bounded(data, output_size, output_size)
}
/// Absolute ceiling on decompressed output when the caller has no size hint,
/// preventing unbounded allocation from a hostile/corrupted zlib stream.
const MAX_DECOMPRESS_SIZE: usize = 256 * 1024 * 1024;
/// Streaming decompress with dynamic sizing (when output size is unknown).
///
/// Bounded by [`MAX_DECOMPRESS_SIZE`] since there is no chunk-size hint to
/// validate against here — an unbounded `read_to_end` would let a hostile
/// zlib stream force arbitrarily large allocation (a "zlib bomb").
/// Decompress with no size hint, bounded by [`MAX_DECOMPRESS_SIZE`] so a
/// hostile zlib stream cannot force arbitrarily large allocation (a "zlib
/// bomb").
pub(crate) fn flate2_decompress_streaming(data: &[u8]) -> Result<Vec<u8>, String> {
use std::io::Read;
let decoder = flate2::read::ZlibDecoder::new(data);
let mut result = Vec::new();
decoder
.take(MAX_DECOMPRESS_SIZE as u64 + 1)
.read_to_end(&mut result)
.map_err(|e| e.to_string())?;
if result.len() > MAX_DECOMPRESS_SIZE {
return Err(format!(
let hint = data.len().saturating_mul(4).min(1 << 20);
inflate_bounded(data, hint, MAX_DECOMPRESS_SIZE).map_err(|e| {
if e.ends_with("exceeds size limit") {
format!(
"decompressed output exceeds {} MiB limit",
MAX_DECOMPRESS_SIZE / 1024 / 1024
));
)
} else {
e
}
Ok(result)
})
}
/// Compress data using flate2 (zlib-ng when fast-deflate enabled, else miniz_oxide).
/// Inflate a zlib stream, starting from `size_hint` bytes of output and
/// failing past `limit`.
fn inflate_bounded(data: &[u8], size_hint: usize, limit: usize) -> Result<Vec<u8>, String> {
use flate2::{Decompress, FlushDecompress, Status};
// One byte of headroom past the limit distinguishes an over-size stream
// from one that legitimately ends exactly at the limit.
let max_capacity = limit.saturating_add(1);
let mut out = Vec::new();
out.try_reserve_exact(size_hint.clamp(1, max_capacity))
.map_err(|e| format!("deflate: cannot allocate output: {e}"))?;
let mut inflater = Decompress::new(true);
loop {
let (in_before, out_before) = (inflater.total_in(), inflater.total_out());
let status = inflater
.decompress_vec(
&data[in_before as usize..],
&mut out,
FlushDecompress::Finish,
)
.map_err(|e| format!("deflate: {e}"))?;
if out.len() > limit {
return Err("deflate: output exceeds size limit".into());
}
match status {
Status::StreamEnd => return Ok(out),
Status::Ok | Status::BufError if out.len() == out.capacity() => {
let grow = out.capacity().min(max_capacity - out.capacity()).max(1);
out.try_reserve_exact(grow)
.map_err(|e| format!("deflate: cannot allocate output: {e}"))?;
}
Status::Ok | Status::BufError => {
if inflater.total_in() as usize >= data.len()
|| (inflater.total_in(), inflater.total_out()) == (in_before, out_before)
{
return Err("deflate: truncated stream".into());
}
}
}
}
}
/// Compress data using flate2 (zlib-ng, zlib-rs or miniz_oxide; see module docs).
pub(crate) fn flate2_compress(data: &[u8], level: u32) -> Result<Vec<u8>, String> {
use std::io::Write;
let mut encoder = flate2::write::ZlibEncoder::new(Vec::new(), flate2::Compression::new(level));
encoder.write_all(data).map_err(|e| e.to_string())?;
encoder.finish().map_err(|e| e.to_string())
use flate2::{Compress, Compression, FlushCompress, Status};
// zlib's compressBound, plus the zlib header and trailer.
let bound = data.len() + (data.len() >> 12) + (data.len() >> 14) + (data.len() >> 25) + 13 + 6;
let mut out = Vec::new();
out.try_reserve_exact(bound)
.map_err(|e| format!("deflate: cannot allocate output: {e}"))?;
let mut deflater = Compress::new(Compression::new(level), true);
loop {
let (in_before, out_before) = (deflater.total_in(), deflater.total_out());
let status = deflater
.compress_vec(&data[in_before as usize..], &mut out, FlushCompress::Finish)
.map_err(|e| format!("deflate: {e}"))?;
match status {
Status::StreamEnd => return Ok(out),
Status::Ok | Status::BufError if out.len() == out.capacity() => out
.try_reserve(out.capacity().max(4096))
.map_err(|e| format!("deflate: cannot allocate output: {e}"))?,
Status::Ok | Status::BufError => {
if (deflater.total_in(), deflater.total_out()) == (in_before, out_before) {
return Err("deflate: encoder made no progress".into());
}
}
}
}
}
// ---------------------------------------------------------------------------
@@ -312,7 +365,7 @@ pub(crate) fn flate2_compress(data: &[u8], level: u32) -> Result<Vec<u8>, String
///
/// Selection order:
/// 1. Apple Compression Framework (macOS + `apple-compression` feature)
/// 2. flate2 (zlib-ng with `fast-deflate`, otherwise miniz_oxide)
/// 2. flate2 (zlib-ng with `fast-deflate`, else zlib-rs, else miniz_oxide)
///
/// When `output_hint` > 0, pre-allocates the output buffer for zero-copy
/// decompression (avoids reallocation).
@@ -344,7 +397,7 @@ pub fn decompress(data: &[u8], output_hint: usize) -> Result<Vec<u8>, String> {
///
/// Selection order:
/// 1. Apple Compression Framework (macOS + `apple-compression` feature)
/// 2. flate2 (zlib-ng with `fast-deflate`, otherwise miniz_oxide)
/// 2. flate2 (zlib-ng with `fast-deflate`, else zlib-rs, else miniz_oxide)
pub fn compress(data: &[u8], level: u32) -> Result<Vec<u8>, String> {
#[cfg(all(target_os = "macos", feature = "apple-compression"))]
{
@@ -377,9 +430,19 @@ pub fn active_backend() -> &'static str {
{
"zlib-ng"
}
// flate2 prefers a C zlib over zlib-rs when both are enabled.
#[cfg(all(
not(all(target_os = "macos", feature = "apple-compression")),
not(feature = "fast-deflate"),
feature = "zlib-rs"
))]
{
"zlib-rs"
}
#[cfg(not(any(
all(target_os = "macos", feature = "apple-compression"),
feature = "fast-deflate"
feature = "fast-deflate",
feature = "zlib-rs"
)))]
{
"miniz_oxide"
@@ -436,7 +499,7 @@ mod tests {
fn backend_name_is_set() {
let name = active_backend();
assert!(
["miniz_oxide", "zlib-ng", "apple-compression"].contains(&name),
["miniz_oxide", "zlib-rs", "zlib-ng", "apple-compression"].contains(&name),
"unexpected backend: {name}"
);
}
+6 -4
View File
@@ -2,12 +2,14 @@
//!
//! Provides deflate (zlib) decompression/compression with multiple backend options:
//!
//! - **Default**: `miniz_oxide` (pure Rust, no C dependencies)
//! - **`fast-deflate` feature**: `zlib-ng` via flate2 (~2-3x faster, matches C HDF5)
//! - **Default (`zlib-rs` feature)**: `zlib-rs` via flate2 (pure Rust, no C
//! dependencies)
//! - **`fast-deflate` feature**: `zlib-ng` via flate2 (C, built with cmake)
//! - **`apple-compression` feature**: Apple Compression Framework on macOS
//! (hardware-accelerated on Apple Silicon)
//! - With none of the above: `miniz_oxide` (pure Rust, slower)
//!
//! Backend priority: apple-compression > zlib-ng > miniz_oxide.
//! Backend priority: apple-compression > zlib-ng > zlib-rs > miniz_oxide.
pub mod fast_deflate;
@@ -115,7 +117,7 @@ mod tests {
fn backend_reports_name() {
let name = deflate_backend();
assert!(
["miniz_oxide", "zlib-ng", "apple-compression"].contains(&name),
["miniz_oxide", "zlib-rs", "zlib-ng", "apple-compression"].contains(&name),
"unexpected backend: {name}"
);
}
+9 -2
View File
@@ -2,6 +2,7 @@
name = "clawhdf5-format"
version = "2.7.0"
edition = "2024"
rust-version.workspace = true
description = "Pure-Rust HDF5 binary format parsing and writing — no C dependencies"
license = "MIT"
repository = "https://git.redclaw.dev/quantumclaw/clawhdf5"
@@ -32,7 +33,10 @@ name = "bench"
harness = false
[features]
default = ["std", "checksum", "deflate", "provenance", "fast-deflate", "system-zlib-decompress"]
# Deflate backend: `zlib-rs` (pure Rust) by default. `fast-deflate` selects
# zlib-ng instead (C, built with cmake); flate2 prefers a C zlib whenever one
# is enabled, so turning it on anywhere in the build overrides the default.
default = ["std", "checksum", "deflate", "provenance", "zlib-rs", "system-zlib-decompress"]
std = []
checksum = []
deflate = ["flate2"]
@@ -42,7 +46,10 @@ fast-checksum = ["crc32fast"]
fast-deflate = ["flate2/zlib-ng"]
system-zlib = ["flate2/zlib-default"]
system-zlib-decompress = []
zlib-rs = ["flate2/zlib-rs"]
# `runtime_detection` gives zlib-rs `std`, which it needs to detect and use
# SIMD at runtime. flate2 enables it by default, but we build flate2 with
# default-features = false, and without it zlib-rs inflates 3.5x slower.
zlib-rs = ["flate2/zlib-rs", "flate2/runtime_detection"]
lz4 = ["lz4_flex"]
zstd = ["dep:zstd"]
blake3_hash = ["blake3"]
+165 -21
View File
@@ -629,21 +629,70 @@ fn deflate_decompress(data: &[u8], expected_bytes: usize) -> Result<Vec<u8>, For
// Fall through to flate2 on error
}
use std::io::Read;
let decoder = flate2::read::ZlibDecoder::new(data);
let mut result = Vec::with_capacity(limit.min(1 << 20));
// Read one byte past the limit so an over-size stream is distinguishable
// A chunk's decompressed size is known, so allocate it once; without one,
// start from a multiple of the input and grow.
let size_hint = if expected_bytes != 0 {
expected_bytes
} else {
data.len().saturating_mul(4).min(1 << 20)
};
inflate_bounded(data, size_hint, limit).map_err(FormatError::DecompressionError)
}
/// Inflate a zlib stream into a buffer sized up front, handing the decoder the
/// whole input at once.
///
/// `flate2::read::ZlibDecoder` feeds its input through a 32 KiB buffer and
/// grows the output as it goes; on single chunks that cost zlib-rs up to 3.7x
/// against zlib-ng (`BENCHMARKS.md`, "Deflate backend"). Output beyond `limit`
/// is an error, as is a stream that ends before its end-of-stream marker (the
/// streaming reader returned the bytes it had and no error).
#[cfg(feature = "deflate")]
pub(crate) fn inflate_bounded(
data: &[u8],
size_hint: usize,
limit: usize,
) -> Result<Vec<u8>, String> {
use flate2::{Decompress, FlushDecompress, Status};
// One byte of headroom past the limit distinguishes an over-size stream
// from one that legitimately ends exactly at the limit.
decoder
.take(limit as u64 + 1)
.read_to_end(&mut result)
.map_err(|e| FormatError::DecompressionError(e.to_string()))?;
if result.len() > limit {
return Err(FormatError::DecompressionError(
"deflate: output exceeds size limit".into(),
));
let max_capacity = limit.saturating_add(1);
let mut out = Vec::new();
out.try_reserve_exact(size_hint.clamp(1, max_capacity))
.map_err(|e| format!("deflate: cannot allocate output: {e}"))?;
let mut inflater = Decompress::new(true);
loop {
let (in_before, out_before) = (inflater.total_in(), inflater.total_out());
let status = inflater
.decompress_vec(
&data[in_before as usize..],
&mut out,
FlushDecompress::Finish,
)
.map_err(|e| format!("deflate: {e}"))?;
if out.len() > limit {
return Err("deflate: output exceeds size limit".into());
}
match status {
Status::StreamEnd => return Ok(out),
Status::Ok | Status::BufError if out.len() == out.capacity() => {
// Out of room: double, up to the limit.
let grow = out.capacity().min(max_capacity - out.capacity()).max(1);
out.try_reserve_exact(grow)
.map_err(|e| format!("deflate: cannot allocate output: {e}"))?;
}
Status::Ok | Status::BufError => {
// Room left, so the decoder stopped for want of input.
if inflater.total_in() as usize >= data.len()
|| (inflater.total_in(), inflater.total_out()) == (in_before, out_before)
{
return Err("deflate: truncated stream".into());
}
}
}
}
Ok(result)
}
/// Direct FFI to Apple's system libz for fast decompression.
@@ -722,14 +771,41 @@ fn deflate_decompress(_data: &[u8], _expected_bytes: usize) -> Result<Vec<u8>, F
/// Compress data with zlib.
#[cfg(feature = "deflate")]
fn deflate_compress(data: &[u8], level: u32) -> Result<Vec<u8>, FormatError> {
use std::io::Write;
let mut encoder = flate2::write::ZlibEncoder::new(Vec::new(), flate2::Compression::new(level));
encoder
.write_all(data)
.map_err(|e| FormatError::CompressionError(e.to_string()))?;
encoder
.finish()
.map_err(|e| FormatError::CompressionError(e.to_string()))
deflate_bounded(data, level).map_err(FormatError::CompressionError)
}
/// Deflate `data` into a zlib stream in one pass, into a buffer sized for the
/// worst case up front (the same reasoning as [`inflate_bounded`]).
#[cfg(feature = "deflate")]
pub(crate) fn deflate_bounded(data: &[u8], level: u32) -> Result<Vec<u8>, String> {
use flate2::{Compress, Compression, FlushCompress, Status};
// zlib's compressBound, plus the zlib header and trailer.
let bound = data.len() + (data.len() >> 12) + (data.len() >> 14) + (data.len() >> 25) + 13 + 6;
let mut out = Vec::new();
out.try_reserve_exact(bound)
.map_err(|e| format!("deflate: cannot allocate output: {e}"))?;
let mut deflater = Compress::new(Compression::new(level), true);
loop {
let (in_before, out_before) = (deflater.total_in(), deflater.total_out());
let status = deflater
.compress_vec(&data[in_before as usize..], &mut out, FlushCompress::Finish)
.map_err(|e| format!("deflate: {e}"))?;
match status {
Status::StreamEnd => return Ok(out),
// The bound should make running out of room unreachable; grow
// rather than fail if it happens.
Status::Ok | Status::BufError if out.len() == out.capacity() => out
.try_reserve(out.capacity().max(4096))
.map_err(|e| format!("deflate: cannot allocate output: {e}"))?,
Status::Ok | Status::BufError => {
if (deflater.total_in(), deflater.total_out()) == (in_before, out_before) {
return Err("deflate: encoder made no progress".into());
}
}
}
}
}
#[cfg(not(feature = "deflate"))]
@@ -1833,6 +1909,74 @@ mod tests {
assert!(deflate_decompress(&compressed, 64).is_err());
}
#[cfg(feature = "deflate")]
fn noisy_bytes(n: usize) -> Vec<u8> {
// Compressible but not trivially so.
(0..n)
.map(|i| ((i as f64 * 0.01).sin() * 127.0 + 128.0) as u8 ^ (i as u8 & 3))
.collect()
}
#[test]
#[cfg(feature = "deflate")]
fn deflate_decompress_accepts_output_exactly_at_chunk_size() {
let data = noisy_bytes(100_000);
let compressed = deflate_compress(&data, 6).unwrap();
assert_eq!(deflate_decompress(&compressed, data.len()).unwrap(), data);
// One byte short of the real size is over the limit.
assert!(deflate_decompress(&compressed, data.len() - 1).is_err());
}
#[test]
#[cfg(feature = "deflate")]
fn deflate_decompress_without_size_grows_the_buffer() {
// No chunk size: the output starts at 4x the input and has to grow.
let data = vec![7u8; 3 * 1024 * 1024];
let compressed = deflate_compress(&data, 6).unwrap();
assert!(compressed.len() * 4 < data.len());
assert_eq!(deflate_decompress(&compressed, 0).unwrap(), data);
}
#[test]
#[cfg(feature = "deflate")]
fn deflate_decompress_rejects_truncated_stream() {
// The streaming reader this replaced returned the bytes it had and no
// error, so a truncated chunk read back short.
let data = noisy_bytes(100_000);
let compressed = deflate_compress(&data, 6).unwrap();
for cut in [compressed.len() - 1, compressed.len() / 2, 3] {
assert!(
deflate_decompress(&compressed[..cut], data.len()).is_err(),
"truncated to {cut} of {} bytes",
compressed.len()
);
}
}
#[test]
#[cfg(feature = "deflate")]
fn deflate_compress_roundtrips_incompressible_data() {
// Random-looking input compresses to slightly more than it started
// as; the output must still fit the pre-sized buffer (or grow).
let mut x = 0x9E37_79B9_7F4A_7C15u64;
let data: Vec<u8> = (0..200_000)
.map(|_| {
x ^= x << 13;
x ^= x >> 7;
x ^= x << 17;
x as u8
})
.collect();
for level in [0, 1, 6, 9] {
let compressed = deflate_compress(&data, level).unwrap();
assert_eq!(deflate_decompress(&compressed, data.len()).unwrap(), data);
}
assert_eq!(
deflate_decompress(&deflate_compress(&[], 6).unwrap(), 0).unwrap(),
Vec::<u8>::new()
);
}
#[test]
#[cfg(feature = "zstd")]
fn zstd_decompress_rejects_output_exceeding_chunk_size() {
+1
View File
@@ -2,6 +2,7 @@
name = "clawhdf5-gpu"
version = "2.7.0"
edition = "2024"
rust-version.workspace = true
description = "GPU-accelerated vector operations for rustyhdf5 using wgpu compute shaders"
license = "MIT"
repository = "https://git.redclaw.dev/quantumclaw/clawhdf5"
+1
View File
@@ -2,6 +2,7 @@
name = "clawhdf5-io"
version = "2.7.0"
edition = "2024"
rust-version.workspace = true
description = "I/O abstraction layer for rustyhdf5"
license = "MIT"
repository = "https://git.redclaw.dev/quantumclaw/clawhdf5"
+1
View File
@@ -2,6 +2,7 @@
name = "clawhdf5-migrate"
version = "2.7.0"
edition = "2024"
rust-version.workspace = true
description = "CLI to migrate SQLite agent memory databases to HDF5 format"
license = "MIT"
repository = "https://git.redclaw.dev/quantumclaw/clawhdf5"
+1
View File
@@ -2,6 +2,7 @@
name = "clawhdf5-napi"
version = "2.7.0"
edition = "2024"
rust-version.workspace = true
description = "Node.js native addon (napi-rs) exposing clawhdf5-agent to TypeScript/JavaScript"
license = "MIT"
repository = "https://git.redclaw.dev/quantumclaw/clawhdf5"
+1
View File
@@ -2,6 +2,7 @@
name = "clawhdf5-netcdf4"
version = "2.7.0"
edition = "2024"
rust-version.workspace = true
description = "NetCDF-4 read support built on rustyhdf5 — pure Rust, no C dependencies"
license = "MIT"
repository = "https://git.redclaw.dev/quantumclaw/clawhdf5"
+1
View File
@@ -2,6 +2,7 @@
name = "clawhdf5-py"
version = "2.7.0"
edition = "2024"
rust-version.workspace = true
description = "Python bindings for rustyhdf5 — a pure-Rust HDF5 library"
license = "MIT"
repository = "https://git.redclaw.dev/quantumclaw/clawhdf5"
+3 -1
View File
@@ -2,6 +2,7 @@
name = "clawhdf5"
version = "2.7.0"
edition = "2024"
rust-version.workspace = true
description = "Pure-Rust HDF5 reader/writer — no C dependencies"
license = "MIT"
repository = "https://git.redclaw.dev/quantumclaw/clawhdf5"
@@ -30,9 +31,10 @@ name = "parallel_bench"
harness = false
[features]
default = ["mmap", "fast-deflate", "provenance"]
default = ["mmap", "provenance"]
mmap = ["clawhdf5-io/mmap"]
parallel = ["clawhdf5-format/parallel", "rayon"]
# zlib-ng (C, needs cmake) instead of the default pure-Rust zlib-rs.
fast-deflate = ["clawhdf5-format/fast-deflate"]
apple-compression = []
zstd = ["clawhdf5-format/zstd"]
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@@ -2,6 +2,7 @@
name = "libaec-sys"
version = "0.1.0"
edition = "2024"
rust-version.workspace = true
links = "aec"
[build-dependencies]
+1 -1
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@@ -567,4 +567,4 @@ let final_results = confidence::reject_low_confidence(
---
<p align="center"><em>Built by <a href="https://github.com/redclawsystems">RedClaw Systems</a></em></p>
<p align="center"><em>Built by <a href="https://git.redclaw.dev/quantumclaw">RedClaw Systems</a></em></p>
+1 -1
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@@ -232,4 +232,4 @@ clawhdf5-agent = { version = "2.0", features = ["agent", "float16", "accelerate"
---
<p align="center"><em>Built by <a href="https://github.com/redclawsystems">RedClaw Systems</a></em></p>
<p align="center"><em>Built by <a href="https://git.redclaw.dev/quantumclaw">RedClaw Systems</a></em></p>
+48
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@@ -77,6 +77,50 @@ run_step "cargo clippy (ann parallel)" cargo clippy \
--features parallel \
-- -D warnings
# zlib-ng is opt-in (`fast-deflate`; the default is pure-Rust zlib-rs), so
# nothing above builds it. Keep it compiling and passing.
run_step "cargo clippy (fast-deflate / zlib-ng)" cargo clippy \
-p clawhdf5-format -p clawhdf5-filters -p clawhdf5 \
--all-targets \
--features clawhdf5-format/fast-deflate,clawhdf5-filters/fast-deflate \
-- -D warnings
# The README promises that the core crates build no C by default. Hold it to
# that: fail if a crate that compiles C (a *-sys crate, cc or cmake) enters the
# default dependency tree of any of them. clawhdf5-migrate (bundled SQLite),
# clawhdf5-napi (Node) and clawhdf5-gpu (graphics drivers) are exempt.
no_c_in_default_build() {
local crate found=0
for crate in clawhdf5-format clawhdf5-io clawhdf5-filters clawhdf5 \
clawhdf5-agent clawhdf5-ann clawhdf5-accel clawhdf5-netcdf4 clawhdf5-cli; do
local c_deps
c_deps=$(cargo tree -q -p "$crate" -e normal,build --prefix none \
| grep -E '^([a-z0-9_-]+-sys|cc|cmake) v' | sort -u)
if [ -n "$c_deps" ]; then
echo "$crate pulls in C by default:"
echo "$c_deps" | sed 's/^/ /'
found=1
fi
done
return $found
}
run_step "no C in the default build (core crates)" no_c_in_default_build
# The workspace declares a minimum Rust version (rust-version in Cargo.toml);
# check that it really builds there, so the README badge and the manifests
# cannot drift from the truth. Separate target dir: a different toolchain
# would otherwise invalidate the main build.
msrv_check() {
local msrv
msrv=$(sed -n 's/^rust-version = "\(.*\)"/\1/p' "$SCRIPT_DIR/../Cargo.toml")
[ -n "$msrv" ] || { echo "no rust-version in Cargo.toml"; return 1; }
rustup toolchain install "$msrv" --profile minimal >/dev/null || return 1
echo "checking with Rust $msrv"
CARGO_TARGET_DIR="$SCRIPT_DIR/../target/msrv" cargo "+$msrv" check \
--workspace --exclude clawhdf5-py --all-targets
}
run_step "MSRV check" msrv_check
# 4. Tests (exclude clawhdf5-py)
run_step "cargo test" cargo test \
--workspace \
@@ -90,6 +134,10 @@ run_step "cargo test (ann parallel)" cargo test \
-p clawhdf5-ann \
--features parallel
run_step "cargo test (fast-deflate / zlib-ng)" cargo test \
-p clawhdf5-format -p clawhdf5-filters -p clawhdf5 \
--features clawhdf5-format/fast-deflate,clawhdf5-filters/fast-deflate
# 5. Python interop suites. The h5py writer tests are #[ignore]d so a plain
# `cargo test` stays hermetic; run them explicitly here.
# On a PEP 668 "externally managed" system h5py can only live in a