#actor #iot #digital #command-line #actor-model #twin #stream-processing

bin+lib navactor

A cli tool for creating and updating actors from piped input

23 releases (4 breaking)

0.5.3 Jul 25, 2023
0.5.2 May 24, 2023
0.4.2 May 22, 2023
0.3.1 Mar 24, 2023
0.1.7 Jan 26, 2023

#315 in Concurrency

Download history 1/week @ 2024-02-20 3/week @ 2024-02-27 3/week @ 2024-03-12 24/week @ 2024-03-26 118/week @ 2024-04-02

110 downloads per month

MIT license

135KB
3K SLoC

Navactor

Under construction - see NOTES.md

NOT READY FOR REAL WORK

Available as a crate: https://crates.io/crates/navactor

Overview

A CLI *nix-style tool as lab for actor programming.

NOT TRYING TO BE A FRAMEWORK - the use of actors in navactor is in support of an opinionated experimental approach to modeling and inference processing, not a general purpose solution for concurrency, parallelism, or distributed computing.

nv's purpose: ingest piped streams of CRLF-delimited observations, send them to actors, implement the OPERATOR processing, and persist.

The nv command will eventually also work as a networked API server but the initial model for workflow and performance is data-wrangling via the classic powerful and undefeated awk.

The ideas that inspire Navactor and DtLab come from CS insights from the early eighties around tuple spaces for coordination languages and later the actor programming model.

Status

Just a toy implementation in the beginning stages to validate implementation choices (Rust, Tokio, Sqlite, and Petgraph).

Current functionality is limited to the support of "gauge" and "counter" observations presented in the internal observation json format via *nix piped stream.

{ "path": "/actors/two", "datetime": "2023-01-11T23:17:57+0000", "values": {"1": 1, "2": 2, "3": 3}}
{ "path": "/actors/two", "datetime": "2023-01-11T23:17:58+0000", "values": {"1": 100}}
{ "path": "/metadata/mainfile", "datetime": "2023-01-11T23:17:59+0000", "values": {"2": 2.1, "3": 3}}
{ "path": "/actors/two", "datetime": "2023-01-11T23:17:59+0000", "values": {"2": 2.98765, "3": 3}}

Event sourcing via an embedded sqlite store works. Query state and resuming ingestion across multiple runs works.

Using the observation generator in the tests/data dir, the current impl when run in sqlite "write ahead logging" mode (WAL), processes and persists 2000+ observations a second in a tiny disk and memory and cpu footprint.

Messy but working code - I am learning Rust as I recreate the ideas from the DtLab Project. However, Clippy is happy with the code.

My intention is to support all the features of DtLab Project - ie: networked REST-like API and outward webhooks for useful stateful IOT-ish applications.

Install

#latest stable version via https://crates.io/crates/navactor
cargo install navactor

#or from this repo:
cargo install --path .

enable zsh tab completion:

nv completions -s zsh > /usr/local/share/zsh/site-functions/_nv

Usage

if running from source, replace nv with cargo run --

#help
nv -h

#create an actor with telemetry
cat ./tests/data/single_observation_1_1.json | nv update actors

# inspect the state of the actor
nv inspect /actors/one

cat ./tests/data/single_observation_1_2.json | nv update actors
cat ./tests/data/single_observation_1_3.json | nv update actors
nv inspect /actors/one
cat ./tests/data/single_observation_2_2.json | nv update actors
cat ./tests/data/single_observation_2_3.json | nv update actors

The above creates a db file named after the namespace - root of any actor path. In this case, the namespace is 'actors'.

Enable logging via:

#on the cli
cat ./tests/data/single_observation_1_3.json | RUST_LOG="debug,sqlx=warn" nv update actors

#or set and forget via
export RUST_LOG="debug,sqlx=warn"

Developing

Run all tests via:

cargo test

Run specific tests with logging enabled:

# EXAMPLE - runs the json decoder and assertions around datetime and json unmarshalling
# the --nocapture lets the in app logging log according to the RUST_LOG env var (see above)
cargo test --test test_json_decoder_actor -- --nocapture

nv was bootstrapped from Alice Ryhl's very instructive blog post https://ryhl.io/blog/actors-with-tokio

Dependencies

~73MB
~1.5M SLoC