Nodrix 2.1.0

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Nodrix is a high-performance typed runtime for local and distributed streaming graphs. It runs Python and C++ nodes in one graph, preserves zero-copy paths where the memory domain permits, and makes every copy, drop, restart, queue, and network export observable.

Nodrix 2.1 highlights

Nodrix 2.1 adds Provider API 1: independently installed providers are discovered from signed metadata, checked for API/version/features and trust, then imported lazily only when selected. Existing Core, Media, Vision, Recording and ROS 2 Node ids continue through a compatibility adapter.

nodrix provider list
nodrix provider verify example.echo
nodrix doctor --provider ros2
nodrix doctor --deep --json

Production pipelines verify provider signatures and explicit allowlist membership before executing provider import-time code.

The official Vision provider adds a native NCNN production block:

use: vision.ncnn_detector_native
model: models/yolo26n_ncnn_model
imgsz: 320
threads: 4

Preprocessing, NCNN inference, YOLO decoding, filtering, and NMS execute in C++ through Plugin C ABI 2. The previous vision.ncnn_detector remains the Python reference backend.

Nodrix 2.0 establishes stable Manifest v2, Python SDK and Plugin C ABI 2 contracts while keeping existing Manifest v1 pipelines readable. It adds reusable Fragments, signed offline plugins, production validation, automatic recording, OpenTelemetry lifecycle traces, optional ROS 2 adapters, a packaged standalone C++ runner, and direct external C ABI plugin execution in engine: native.

nodrix migrate pipeline.yaml --to v2
nodrix validate pipeline.v2.yaml --production
nodrix run pipeline.v2.yaml --production

Multi-rate detection and tracking remain available without duplicating stale work:

source 30 FPS ─┬─ latest frame → detector ~10 FPS ─┐
               └─ every frame → realtime tracker ──┤
                                                   └─ tracks at source rate

nodrix init camera_app --template vision
cd camera_app
nodrix inspect
nodrix run
nodrix top

vision.realtime_bytetrack predicts on every source frame, applies each detection once, and replays delayed measurements through bounded state history. Native C++20 IoU association is used by the production block. Encoder and NCNN selection are hardware-first and always expose the selected backend and any fallback.

Core model

Pipeline manifest
       ↓ validate / lock
Executable typed graph
       ↓
Node → Port → Edge → Node
       ├─ in-process zero-copy
       ├─ shared-memory process isolation
       ├─ device-memory contracts
       └─ named LAN streams

No detector, tracker, camera, or fixed stage is mandatory. A graph can be Capture → Inference → Output, Source → Sink, a branched media graph, LiDAR processing, audio, or custom typed data.

Install

Install the core runtime and CLI from PyPI:

python3 -m venv .venv
source .venv/bin/activate
pip install nodrix
nodrix --version

Optional media and viewer dependencies:

pip install "nodrix[viewer]"
pip install "nodrix[media]"
pip install "nodrix[vision,media,viewer]"

Use nodrix[vision-ncnn] only when the Python NCNN reference backend is also required. Official wheels already contain the native NCNN provider.

Raspberry Pi and offline source installation

Nodrix 2.1.0 can be built without PyPI build isolation when the runtime dependencies are already present:

python3 -m pip install . --no-build-isolation --no-deps

Use scripts/install_offline.sh for a dependency preflight. See docs/OFFLINE_INSTALL_RU.md.

For an isolated CLI installation:

pipx install nodrix

Release wheels cover Linux x86-64, Linux ARM64, macOS Apple Silicon, and Windows x86-64. Each wheel contains the native extensions and nodrix/bin/nodrix-native-runner plus the native NCNN provider; production execution does not compile code on first use. When no compatible wheel exists, building the included source distribution requires CMake, a C++20 compiler, and Python development headers. Native NCNN source builds are opt-in as documented in the 2.1 release notes.

Empty project and templates

nodrix init my_project

This creates an intentionally empty project skeleton. Runnable examples are explicit:

nodrix init camera_app --template vision
nodrix init media_app --template media
nodrix init device_app --template device
nodrix init package_app --template package

Run and reproduce

cd my_project
nodrix validate --strict
nodrix lock
nodrix run --locked

Every run receives its own artifact directory:

.nodrix/runs/<run-id>/
├── manifest.yaml
├── resolved-manifest.yaml
├── nodrix.lock
├── runtime.json
├── environment.json
├── status.json
├── metrics.jsonl
├── errors.jsonl
├── logs/
├── outputs/
└── summary.json

Stable Python API

from nodrix import Message, Node

class Multiply(Node):
    input_types = {"input": "core.object"}
    output_types = {"output": "core.object"}

    def process(self, inputs):
        message = inputs["input"]
        return {
            "output": message.with_updates(
                payload={"value": message.payload["value"] * 2}
            )
        }

Nodrix 2.x preserves the public Node, SourceNode, SinkNode, Message, NodeContext, manifest models, buffer, memory, error, and lifecycle contracts. Existing nodes that override open, flush, and close continue to work through lifecycle adapters.

Lifecycle and health

Lifecycle states:

created → configuring → ready → starting → running → stopping → stopped
                                      ├→ degraded / restarting
                                      └→ failed

nodrix status
nodrix health
nodrix health --watch

Process-isolated nodes can use watchdog recovery:

nodes:
  detector:
    uses: ./nodes/detector.py:Detector
    execution:
      isolation: process
    failure:
      policy: restart_node
      max_restarts: 5
    health:
      timeout_ms: 2000
      on_timeout: restart

Local packages

nodrix init my_nodes --template package
cd my_nodes
nodrix package build .
nodrix package install dist/my-nodes-1.0.0.ndpkg

Use an installed node by stable package reference:

nodes:
  processor:
    uses: my-nodes/passthrough

.ndpkg installation verifies the complete member set and SHA-256 checksums before extraction, rejects traversal/symlinks/platform filename collisions and decompression bombs, and atomically installs immutable versions. Packages may be signed and verified with an Ed25519 key. The local registry is offline by design; Nodrix does not silently download or execute marketplace code.

Secure named streams

Only explicitly exported ports become network streams. Local edges remain direct and do not pay network or serialization overhead.

streams:
  bind_host: 0.0.0.0
  max_message_bytes: 67108864
  tls:
    enabled: true
    certificate: secrets/server.crt
    private_key: secrets/server.key
  exports:
    - name: /camera/front/h264
      from: encoder.encoded
      queue:
        capacity: 1
        policy: latest
      access:
        mode: token
        token_env: NODRIX_CAMERA_TOKEN
        allow_ips: ["192.168.1.0/24"]

export NODRIX_STREAM_TOKEN=...
nodrix stream echo /camera/front/h264 --ca secrets/ca.crt
nodrix-viewer /camera/front/h264

TLS endpoints are advertised as nodrix+tls://. Certificate verification is mandatory; mutual TLS is available with client_ca and require_client_certificate.

Production validation

nodrix validate --strict
nodrix run --production
nodrix inspect --memory
nodrix plan pipeline.yaml
nodrix diagnose runs/RUN-ID
nodrix explain edge source.output:sink.input --pipeline pipeline.yaml

The validator checks graph cycles, port/type compatibility, memory transfers, unsupported copies, open LAN streams, stream backpressure, watchdog/isolation conflicts, resource configuration, and native plugin loading.

The production gate additionally requires Manifest v2 and explicit health timeouts, rejects fallback-permitting acceleration, relative model paths, unverified required plugins, unencrypted/open LAN exports, and planned payload copies. Direct native libraries additionally require an absolute path inside security.native_plugin_allowlist and cannot be world-writable.

nodrix optimize writes separate benchmark variants and a decision report. It never edits or applies the production pipeline.

Metrics, resources and runs

# runtime.metrics.listen can be stored in pipeline.yaml
nodrix run
nodrix top
nodrix metrics --format prometheus
nodrix runs list
nodrix runs show <run-id>
nodrix runs compare <run-a> <run-b>

Plugin C ABI 2.0

nodrix native inspect ./libdetector.so

Plugin C ABI 2.0 uses numeric ABI 131072, opaque handles and function tables. C++ standard-library objects and exceptions never cross the shared library boundary. Correlation strings and host/device memory ownership have explicit lifetime rules. Incompatible plugins are rejected before node creation. External source, processor, and sink plugins can execute entirely in the standalone runner:

runtime:
  engine: native
nodes:
  detector:
    uses: native:/opt/nodrix/plugins/libdetector.so#vision.detector

Main capabilities carried into 1.0

  • Python/C++ unified graph executor;
  • native bounded queues and reusable buffer pools;
  • shared-memory process isolation with zero-copy input/output paths;
  • stable CPU, shared, DMA-BUF, CUDA, ROCm, Vulkan, OpenCL, Metal, NPU, DLPack, and external-memory contracts;
  • DLPack interoperability;
  • .ndrx universal record/play;
  • FFmpeg Media Pack and H.264/H.265 named streams;
  • low-latency nodrix-viewer;
  • typed custom-message generation for Python and C++;
  • local/LAN stream discovery without a mandatory agent.

Honest limitations

Memory-domain contracts and planning are stable, but a declared domain is not a built-in hardware backend. Validated paths are listed in docs/PLATFORM_CAPABILITIES.md. The reference FFmpeg source and overlay still use host BGR frames; complete V4L2 DMA-BUF capture and CUDA IPC operators remain hardware-specific plugins. ROS 2 adapters are generic Python adapters, not a claim of loaned-message image or PointCloud2 zero-copy. placement is a deployment contract, not a central scheduler.

See docs/BLOCKS.md, docs/COMPACT_MANIFEST.md, docs/PROFILES.md, docs/RESOURCE_TELEMETRY.md, docs/BENCHMARKING.md, docs/MULTI_RATE_VISION.md, docs/PROVIDER_API.md, docs/RELEASE_2.1.0.md, docs/RELEASE_2.0.0.md, CONTRIBUTING.md, and PUBLISHING_RU.md.

Project links

Data verified by PyPI on Jul 30, 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 (2.8.0)

1 maintainer

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

Credits

Author: CactysFedya

Maintainer: Nodrix contributors

GitHub Statistics

Data verified by PyPI on Jul 30, 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

Apache Software License

Requires

Python >=3.11

Provides Extra

vision vision-ncnn viewer media security otel all dev

Tags

streaming dataflow graph-runtime computer-vision zero-copy shared-memory cpp edge-computing

Classifiers

Report project as malware

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Release history Release notifications | RSS feed

2.8.0

1 file

Pre-release

2.3.0a1

1 file

This release

2.1.0 This release

17 files

2.0.0

17 files

1.4.1

13 files

1.4.0

13 files

1.3.0

13 files

1.2.1

13 files

1.2.0

13 files

1.0.0

13 files

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