tf_tree

A transform tree engine: store time-stamped rigid-body transforms between named coordinate frames and answer "where was frame A relative to frame B at time t?" — fast enough to sit inside a control loop, with diagnostics good enough to debug at 3 a.m.

Linux-first. The single-process engine is portable Rust and much of it compiles elsewhere; everything that maps memory — attaching to a live arena, the frozen .tft backend, tf_tree freeze — is Linux-only and behind a default-off shm feature. That sentence is here rather than in SUPPORT.md alone because nobody should meet it as a build error.

Start where you change nothing

Point it at a recording you already have. No node joins anyone's launch file, no robot is redeployed, and doctor --from-bag needs no features at all:

git clone https://github.com/NoeFontana/tf_tree && cd tf_tree
cargo install --path crates/tf_tree_cli --features shm   # shm: `freeze` maps memory

tf_tree doctor --from-bag drive.mcap                # what is wrong with this /tf traffic
tf_tree freeze --from-bag drive.mcap -o drive.tft   # keep the answer

drive.tft is a frozen transform index, and it is the arena itself written to disk. There are no pointers anywhere in the arena — every internal reference is an offset — so opening one is an mmap, with no parsing, no deserialization and no fixups (PHASE5 §2.1). Sixteen dataloader workers map the same file, the kernel charges the shared clean pages exactly once and the untouched ones not at all (measured basis: PHASE2 §3.8), and each worker queries in its own address space: no IPC, and no ROS node inside the training loop.

import numpy as np, tf_tree

# Open per worker, after the fork/spawn — docs/PHASE5.md §4.3 says why.
tree   = tf_tree.open_file("drive.tft")
plan   = tree.plan("base_link", "lidar_top")           # compile the route once
stamps = np.asarray(batch_stamps_ns, dtype=np.int64)   # integer nanoseconds
poses  = plan.at(stamps, layout="quat_twist")          # (N, 13) float64

The whole batch is one call into Rust. layout="quat_twist" appends the body twist to each pose, in the plan's source frame: it is the analytic derivative of the same interpolation the pose came from, not a finite difference between two lookups.

docs/PHASE5.md §2.2 is where that argument is made in the project's own words. A perception dataloader today does one of three bad things — re-parses the bag in every worker, precomputes poses into a pickle and loses the ability to query at arbitrary times, or runs a ROS node to serve transforms during training. This replaces all three and asks nobody to migrate anything, which is also why it is the part that shipped first.

Numbers belong where they can be reproduced, not in this section. just bench-report measures your host and writes report/{results.json,index.html}; the standing figures and their caveats are in docs/benchmarks/. Benchmarks, and what they are worth below explains why a row there may legitimately read UNAVAILABLE.

Status

On crates.io from 0.0.1; on PyPI from 0.0.2. The five engine crates are published — cargo add tf_tree. The Python wheel starts at 0.0.2, because the 0.0.1 commit did not compile off Linux and no wheel for it exists or can; see CHANGELOG.md. 0.0.x promises nothing between releases — cargo treats every one as incompatible with every other, so pin exactly.

Phase What it is Status
1 Single-process engine: arena, seqlock buffers, plans, SE(3) math Implemented
2 Shared memory: rendezvous, fd passing, claims as leases, reaping Implemented, except the daemon/recorder surface (§9–§10) and §11.3's fault injection. §3.5's ownership migration has the protocol and not the trigger: kill the arena's owner and lookups keep being served, but no new process can join
3 Python bindings (PyO3, zero intermediate allocation) Implemented
4 C ABI, C++ wrapper, ROS 2 ingest bridge, derivatives Done, except §5.9's affinity knobs and §6.3's replay rows. at_with_derivatives, both headers, the header-only C++ wrapper with its CMake package, and both halves of the ingest bridge — the rclcpp package in ros/tf_tree_ros included. §7's benchmark gate is partial
5 Frozen .tft arena, bag ingestion, diagnostics, tf_tree top Mostly done. FORMAT_VERSION = 3, the frozen arena (§2), the offline Python API (§4), the §5 counters and tf_tree top — terminal and --web (§7) — all landed. Ingestion is MCAP only (§3); the TFT001–TFT019 catalogue reports all nineteen ids, of which sixteen can detect (§6). §8 is deliberately not built. §9's benchmark artifact and §10's release readiness are partial
6–8 Multi-host, tf2 compatibility shim, replication Not started; Phase 7 is gated by D21 and none of its four gates is met

The per-phase §0.0 tables in docs/ are the source of truth, not this one — PHASE2.md, PHASE4.md, PHASE5.md. If this table and one of those disagree, the phase document is right and this is stale.

CI runs again as of 2026-08-16, after a gap since 2026-07-23 that ended when this repository was made public. A green check is evidence once more — of what the jobs cover. Gate locally with just first; CI is the second opinion.

First five minutes, with no data at all

The block above assumes you have a recording. This one assumes only the clone:

just quickstart        # uv-managed interpreter + venv, with the extension installed into it
.venv/bin/python

import tf_tree

tree = tf_tree.build([("map", "base"), ("base", "cam")])
# stamp in integer nanoseconds; pose is [qw, qx, qy, qz, x, y, z]
tf_tree.push(tree, "base", "map", 1_000, [1.0, 0.0, 0.0, 0.0, 1.0, 2.0, 3.0])
tf_tree.push(tree, "base", "map", 2_000, [1.0, 0.0, 0.0, 0.0, 3.0, 4.0, 5.0])

print(tree.plan("map", "base").at(1_500)[:3, 3])   # -> [2. 3. 4.]

That is a real result and not a toy: the query lands halfway between two samples, so the printed translation is their interpolated midpoint, and plan() is the object you keep — compiling the route once and evaluating it many times is the whole shape of the fast path.

Two things surprise people, both deliberate:

  • Stamps are integer nanoseconds. There is no float-seconds overload. At a 2026 epoch the ULP of float64 seconds is 238 ns, so every interval in a 1 kHz stream is wrong after a round trip.
  • Nothing returns a view into shared memory. An edge's samples are a ring another process is overwriting, and correct reads go through a seqlock. "Zero copy" here means no intermediate allocation — use Plan.at_into to supply the destination.

Rust is cargo add tf_tree; Python is pip install transform_tree — the distribution name differs from the import name, because PyPI refuses tf_tree as too close to the existing tftree (0008 records the measurement). import tf_tree either way. just alone lists everything the repository can do.

Is this a tf2 replacement?

It is not tf2, not a fork of it, and not affiliated with ROS. It is an independent engine that solves the same problem with a different data structure, and it is deliberately named so that people looking for a tf2 alternative can find it (0008 records that decision).

There is no drop-in tf2_ros::Buffer shim, and building one is not scheduled. That is Phase 7, gated by D21 on operating evidence this project has not yet produced; docs/PHASE7.md is what such a shim would have to be — including the places it would deliberately refuse to reproduce tf2's behaviour — and its §0.0 lists four gates, none of them met. What exists today instead is the ingest bridge (docs/PHASE4.md §5): a node that subscribes to /tf and fills an arena, which is a one-way seam and not a compatibility layer.

Two things worth stating precisely, because the loose versions of both are wrong:

  • The documented tf2 cost is listener and buffer CPU, per node — not /tf bandwidth. Autoware's ManagedTransformBuffer (in autoware_universe) reports taking a LiDAR sensing pipeline from 13 TF listener nodes to 0 — four per-sensor legs at 3 each plus the concatenation node (autowarefoundation/autoware#5385; the upstream discussion about moving it into tf2 is ros2/geometry2#758). That is a third-party report about their own stack, not a tf_tree measurement, and it is cited for the shape of the problem this engine's process model addresses. No claim is made about /tf bandwidth: no quantified public source for one exists.
  • Errors are Copy identifiers a program can branch on, with the prose in a separate layer (docs/API.md R5) — a lookup failure names the offending edge as data, not as a formatted string. That is a durable API-shape difference and deliberately not a claim about any particular tf2 defect; the misattributed-extrapolation one people cite (ros2/geometry2#832) was fixed by PR #896, merged 2026-03-18 and backported to Kilted, Jazzy and Humble (#897–#899). Marketing against a bug somebody already fixed is how a README goes stale in public.

Shared memory IPC is not a sandbox

Processes sharing a tf_tree arena are mutually trusting, same-user, cooperating processes. A read-write participant can corrupt any part of the arena, and no checksum would change that — it holds a writable mapping of the same pages (PHASE2.md §3.10). Do not attach a process you would not run as yourself. SECURITY.md draws the line between this and an actual vulnerability.

Three things the design does guarantee, and they are the ones that matter on a robot:

  • A read-only participant cannot corrupt anything, enforced by the MMU, not by convention. It is the default for consumers (D18), and it converts a class of whole-system failures into a single-process fault.
  • A participant that crashes, at any instruction, cannot corrupt the arena or wedge anyone else. A killed writer's edge is reclaimed; a killed interner's entry is recoverable; a killed mutator does not leave a permanently locked topology.
  • A participant that hangs cannot be mistaken for a crashed one. Liveness is the kernel's answer about a file lock, not a heartbeat timeout, so a SIGSTOPped publisher keeps its claims and a stalled one is never reaped out from under itself.

fork() is the sharp edge worth knowing about up front: the arena is mapped MADV_DONTFORK, so a child has no mapping and every inherited handle reports ChildDetached. Python's multiprocessing defaults to fork on Linux — open inside the worker, or use the spawn start method. A frozen .tft is the deliberate exception: it is a private read-only mapping, a child inherits it intact, and poisoning it would break multiprocessing for offline users to defend against a hazard they do not have (docs/PHASE5.md §4.3).

Workspace

crates/
├── tf_tree_math/    no_std SE(3)/SO(3) + dual quaternions; #![forbid(unsafe_code)]
├── tf_tree_arena/   no_std+alloc pointer-free arena + layout math
├── tf_tree_core/    no_std+alloc engine: interning, topology, seqlock buffers, plans
├── tf_tree/         std facade: builder, plan-cached lookup, Display errors
├── tf_tree_ipc/     zero-config rendezvous: runtime dir, OFD lock file, attach protocol
├── tf_tree_c/       C ABI + header-only C++ wrapper
├── tf_tree_bridge/  the ROS-independent half of the /tf ingest bridge
├── tf_tree_ingest/  MCAP -> arena: the two passes behind `ingest` and `freeze --from-bag`
├── tf_tree_py/      PyO3 bindings — binds the Rust core directly, not the C ABI
├── tf_tree_bench/   criterion benches, tf2 differential harness, the §9 report
├── tf_tree_tf2_sys/ the tf2 side of that differential harness — needs a ROS 2 install
└── tf_tree_cli/     binary `tf_tree` (alias `tft`): tree / echo / doctor / top /
                     ingest / freeze / topology / participants / bench
ros/                 ament_cmake packages: the §5 rclcpp bridge, and the DDS comparison
xtask/               loom, miri, and bench-gate runners
docs/                PROJECT.md, API.md, PHASE1–5.md, RUNBOOK.md, benchmarks/, decisions/

tf_tree_py and tf_tree_tf2_sys are outside the cargo --workspace build on purpose — they link libpython and a ROS 2 install respectively, neither of which a clean checkout can assume. ros/ is outside it for the same reason and is not cargo at all. Each has just recipes of its own (just py-*, just ros-build / just ros-test, just tf2-check), which is what "gate locally" means for them.

Five crates are intended for crates.io: tf_tree, tf_tree_core, tf_tree_math, tf_tree_arena, tf_tree_ipc. The rest carry publish = false with the reason in their manifest.

Commands

just quickstart     # clean clone -> a Python REPL with the extension installed
just build          # cargo build --workspace --all-targets
just test           # nextest + doctests
just lint           # fmt --check + clippy -D warnings
just loom           # concurrency model checking
just miri           # UB checking (arena + core + the facade's one unsafe)
just bench          # benchmark suite + go/no-go gate
just bench-report   # the PHASE5 §9 artifact -> report/{results.json,index.html}
just bench-check    # the same artifact against the committed baseline
just shm-torture    # PHASE2 §11.4's multi-process soak (30 min; nightly)

just --list for everything.

Benchmarks, and what they are worth

just bench-report emits report/results.json and report/index.html with a full provenance header. It is built so it cannot print a number it has no right to: it probes the host, and a row it cannot measure fairly comes out UNAVAILABLE with the reason and the command that produces it on a host that can. On a 4-core development machine that means most rows are gaps — which is the correct output, not a broken tool. docs/PHASE5.md §9.3 is the rule it enforces, and it includes a "where tf_tree is worse" section, in the same table.

just bench-check re-runs it and compares against the committed baseline in crates/tf_tree_bench/baseline/results.json, failing if a claim was withdrawn, a row was dropped, the arena layout changed, or a directional number moved past the slack the baseline itself records. It compares claims, not hosts: CPU model, core count, kernel, governor, load and every reason string are ignored, so the gate means the same thing on any machine. just bench-baseline-update regenerates the baseline; that diff belongs in the commit that causes it.

Standing numbers and their caveats live in docs/benchmarks/.

Reading order

  1. docs/PROJECT.md — overview, architecture, roadmap, and the decision log D1–D22 in §5.
  2. docs/API.md — the cross-cutting contract: six rules (§1) every binding obeys, and the §7 checklist a new surface passes. It is not a phase and authorizes nothing on its own.
  3. The phase spec you care about: PHASE1 … PHASE5. Each opens with its own status table.
  4. docs/decisions/ — the records for things the phase specs do not cover.

Contributing and support

CONTRIBUTING.md · SUPPORT.md (response expectations, platform support, MSRV policy) · SECURITY.md · CODE_OF_CONDUCT.md

MSRV is 1.87. just msrv reads the number out of [workspace.package] rust-version, builds --locked on exactly that toolchain, and checks that every hand-written rust-version — and this line — still agrees with it.

Licence

Dual MIT / Apache-2.0, at your option. See NOTICE.

Project links

Data verified by PyPI on Aug 22, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.0.5)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for NoeFontana from gravatar.com NoeFontana

Credits

Author: Noé Fontana

GitHub Statistics

Data verified by PyPI on Aug 22, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

MIT OR Apache-2.0
View SPDX License List

Requires

Python >=3.10

Classifiers

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

transform_tree-0.0.4.tar.gz (706.8 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

transform_tree-0.0.4-cp314-cp314t-win_amd64.whl (315.9 kB view details)

Uploaded CPython 3.14tWindows x86-64

transform_tree-0.0.4-cp314-cp314t-manylinux_2_28_x86_64.whl (468.5 kB view details)

Uploaded CPython 3.14tmanylinux: glibc 2.28+ x86-64

transform_tree-0.0.4-cp314-cp314t-manylinux_2_28_aarch64.whl (444.3 kB view details)

Uploaded CPython 3.14tmanylinux: glibc 2.28+ ARM64

transform_tree-0.0.4-cp314-cp314t-macosx_11_0_arm64.whl (359.2 kB view details)

Uploaded CPython 3.14tmacOS 11.0+ ARM64

transform_tree-0.0.4-cp39-abi3-win_amd64.whl (330.1 kB view details)

Uploaded CPython 3.9+Windows x86-64

transform_tree-0.0.4-cp39-abi3-musllinux_1_2_x86_64.whl (693.6 kB view details)

Uploaded CPython 3.9+musllinux: musl 1.2+ x86-64

transform_tree-0.0.4-cp39-abi3-musllinux_1_2_aarch64.whl (632.0 kB view details)

Uploaded CPython 3.9+musllinux: musl 1.2+ ARM64

transform_tree-0.0.4-cp39-abi3-manylinux_2_28_x86_64.whl (479.3 kB view details)

Uploaded CPython 3.9+manylinux: glibc 2.28+ x86-64

transform_tree-0.0.4-cp39-abi3-manylinux_2_28_aarch64.whl (453.3 kB view details)

Uploaded CPython 3.9+manylinux: glibc 2.28+ ARM64

transform_tree-0.0.4-cp39-abi3-macosx_11_0_arm64.whl (370.7 kB view details)

Uploaded CPython 3.9+macOS 11.0+ ARM64

transform_tree-0.0.4-cp39-abi3-macosx_10_12_x86_64.whl (388.8 kB view details)

Uploaded CPython 3.9+macOS 10.12+ x86-64

File details

Details for the file transform_tree-0.0.4.tar.gz.

File metadata

  • Download URL: transform_tree-0.0.4.tar.gz
  • Upload date:
  • Size: 706.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for transform_tree-0.0.4.tar.gz
Algorithm Hash digest
SHA256 4b30110b981652c830b90f0ff0c4fb0c4a61940651429ae095ebc7bd9a8eee3e
MD5 12e1d787b1ab4b5ae7b7f8cfddb2609d
BLAKE2b-256 0d80865de4ed57c89387691337004918f8feba8526dcfcb16b51ff5eb6db6ccb

See more details on using hashes here.

Provenance

The following attestation bundles were made for transform_tree-0.0.4.tar.gz:

Publisher: wheels.yml on NoeFontana/tf_tree

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file transform_tree-0.0.4-cp314-cp314t-win_amd64.whl.

File metadata

File hashes

Hashes for transform_tree-0.0.4-cp314-cp314t-win_amd64.whl
Algorithm Hash digest
SHA256 516dac18579ec2c54d3913ffac1212c5d441f969b1b3756592435589bc6cdac1
MD5 8052b991480abc80f0e66b306837c85d
BLAKE2b-256 a12fb0df79a195257d012a88c401825ffc03c67c6e7ae695ece0594ffca1744c

See more details on using hashes here.

Provenance

The following attestation bundles were made for transform_tree-0.0.4-cp314-cp314t-win_amd64.whl:

Publisher: wheels.yml on NoeFontana/tf_tree

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file transform_tree-0.0.4-cp314-cp314t-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for transform_tree-0.0.4-cp314-cp314t-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 a48542cfba5daa61b93b5770d7a4e37f7c37b493b66c5ed7745daa392703bc7b
MD5 99121c5e1bacf6d9bb4ef98d997d2eb9
BLAKE2b-256 230ad96d61202af0d6cc18c9c370d3068a802e19e721c016680ad47d8758cdf5

See more details on using hashes here.

Provenance

The following attestation bundles were made for transform_tree-0.0.4-cp314-cp314t-manylinux_2_28_x86_64.whl:

Publisher: wheels.yml on NoeFontana/tf_tree

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file transform_tree-0.0.4-cp314-cp314t-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for transform_tree-0.0.4-cp314-cp314t-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 3b5d0772c76d025dee22cfe8d53c6800027116ecada3cabc03298d0324b44f1a
MD5 22aaf95acc25f4f663b639ef2a6aaea9
BLAKE2b-256 2884de173a9aeca5e684986c91c4e16bb18e99e0243fc5bf017ee6dc5a96cfff

See more details on using hashes here.

Provenance

The following attestation bundles were made for transform_tree-0.0.4-cp314-cp314t-manylinux_2_28_aarch64.whl:

Publisher: wheels.yml on NoeFontana/tf_tree

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file transform_tree-0.0.4-cp314-cp314t-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for transform_tree-0.0.4-cp314-cp314t-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1e84ac5018090f0d469d6241e87c86f4687d784cd8f1ade6de04d90cd3fbbbd8
MD5 c39824a650f714ebe2a2789b9423f00f
BLAKE2b-256 3670e175065cd4b5b8909ad9e375c095d77513b2eb85678eda939ec0c6455275

See more details on using hashes here.

Provenance

The following attestation bundles were made for transform_tree-0.0.4-cp314-cp314t-macosx_11_0_arm64.whl:

Publisher: wheels.yml on NoeFontana/tf_tree

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file transform_tree-0.0.4-cp39-abi3-win_amd64.whl.

File metadata

File hashes

Hashes for transform_tree-0.0.4-cp39-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 677d5c5051f601913e91395222d951c88f5ee95e9e3ed69b429aea9c8212232c
MD5 f4ba7f2efe9e82344c34f91da73abc3b
BLAKE2b-256 5f8d5278a8a842d3a111271d86ebf5d91ef9491750daa8f1a4314bf36d90843d

See more details on using hashes here.

Provenance

The following attestation bundles were made for transform_tree-0.0.4-cp39-abi3-win_amd64.whl:

Publisher: wheels.yml on NoeFontana/tf_tree

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file transform_tree-0.0.4-cp39-abi3-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for transform_tree-0.0.4-cp39-abi3-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 115b74c56f8b00dad14284ff4126db57dc6d2d4122fadc74a1395392cf27fec1
MD5 5462785c80831b73d2b5eebd7d280434
BLAKE2b-256 4bcb095f75243380af9c4acf6357a09441c599b80a26b2ee73fd2e6bf815b4f3

See more details on using hashes here.

Provenance

The following attestation bundles were made for transform_tree-0.0.4-cp39-abi3-musllinux_1_2_x86_64.whl:

Publisher: wheels.yml on NoeFontana/tf_tree

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file transform_tree-0.0.4-cp39-abi3-musllinux_1_2_aarch64.whl.

File metadata

File hashes

Hashes for transform_tree-0.0.4-cp39-abi3-musllinux_1_2_aarch64.whl
Algorithm Hash digest
SHA256 312172c45061e5308c8b2e65a4ec33198a6470c6637a9e2a702a2debe00777be
MD5 191db64164386993bc740ee9f1dc06e0
BLAKE2b-256 90bc1960f8dbc8fb69676d41c5d81962f73246c128210f99123d346b1da557b7

See more details on using hashes here.

Provenance

The following attestation bundles were made for transform_tree-0.0.4-cp39-abi3-musllinux_1_2_aarch64.whl:

Publisher: wheels.yml on NoeFontana/tf_tree

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file transform_tree-0.0.4-cp39-abi3-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for transform_tree-0.0.4-cp39-abi3-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 784c3181394321f89112800ed517d8e4e4aa0e170406b9797c58a56064d55470
MD5 694bf554cee4de0c18f153a139ccd8b8
BLAKE2b-256 65028a81b87e1af1d6d8cdb5586434b8f885e0054d926292e8bde4d745d0c3a8

See more details on using hashes here.

Provenance

The following attestation bundles were made for transform_tree-0.0.4-cp39-abi3-manylinux_2_28_x86_64.whl:

Publisher: wheels.yml on NoeFontana/tf_tree

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file transform_tree-0.0.4-cp39-abi3-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for transform_tree-0.0.4-cp39-abi3-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 9f76883fae2648dc73c064a34e2a7786fd040889e9080f8401974e0885f984a1
MD5 500cb4b88f64bc65f738ab7fb962d4ec
BLAKE2b-256 4891e89eb9f542b9586e9597ed29c4deae2ae09d2014be106f3b068dcc03a5a1

See more details on using hashes here.

Provenance

The following attestation bundles were made for transform_tree-0.0.4-cp39-abi3-manylinux_2_28_aarch64.whl:

Publisher: wheels.yml on NoeFontana/tf_tree

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file transform_tree-0.0.4-cp39-abi3-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for transform_tree-0.0.4-cp39-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 612f2ba9c1ed9f93eb289b46728b8ac50cf3f7befed79ae114216f748aed1fcc
MD5 31a5b1a7d84ff9e3be757f8b4088c2b7
BLAKE2b-256 3ca84b2ec368c0cdad4ac49f49e1b3801bec286cd0d7d8323e1589c4388fc04e

See more details on using hashes here.

Provenance

The following attestation bundles were made for transform_tree-0.0.4-cp39-abi3-macosx_11_0_arm64.whl:

Publisher: wheels.yml on NoeFontana/tf_tree

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file transform_tree-0.0.4-cp39-abi3-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for transform_tree-0.0.4-cp39-abi3-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 8af2d7d807a2128cf8f37f261b199254a8aa4fb01231a3365f66b9b54195b18a
MD5 72107b1e11b62367b0e9a72127794546
BLAKE2b-256 7dd49846aa7fc45764d6a0647354048d28ca6bede8998da34d583dcf00dae803

See more details on using hashes here.

Provenance

The following attestation bundles were made for transform_tree-0.0.4-cp39-abi3-macosx_10_12_x86_64.whl:

Publisher: wheels.yml on NoeFontana/tf_tree

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

0.0.5

12 files

This release

0.0.4 This release

12 files

0.0.3

12 files

0.0.2

11 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page