Mycelium-EI-Lang

Mycelium-EI-Lang is a small interpreted language for cultivation models: environment parameters, adapt functions that fire when they change, and genetic, particle swarm and ant colony optimizers.

Status

early stage

0.2.2 is the first release on PyPI that runs .myc programs. It is published as mycelium-ei-language. The older PyPI project mycelium-ei-lang (0.1.0 to 0.1.2) belongs to an account whose two-factor device was lost with a laptop, so it cannot be updated; its interpreter parsed Python syntax and imported a dependency it did not declare, and myc examples/hello_world.myc fails on every install of it. Do not install mycelium-ei-lang.

What does not work yet:

• One file per program. There is no import, no module system and no standard library beyond the builtins listed in docs/reference.md.
• The interpreter walks the syntax tree in Python. Loops of a few hundred thousand iterations take seconds.
• The optimizers, the neural network and the cultivation monitor are demonstration models: small populations, a Hebbian toy network, readings drawn from random.gauss. None of it reads a sensor or controls equipment.
• The Rust crate under compiler/ builds and passes its two tests, but it is a skeleton with no command-line tool. The Python package does not use it. Nothing here compiles to native code or WebAssembly.
• Run only on macOS (arm64). Linux and Windows have not been tried.

Install and first run

Run on 2026-09-11 with CPython 3.13.14 on macOS.

python3 -m venv .venv
. .venv/bin/activate
pip install mycelium-ei-language
myc --version

Output:

mycelium-ei-language 0.2.2

Save this as hello.myc:

// Hello World in Mycelium-EI-Lang

environment {
    temperature: 22.5,
    humidity: 85.0
}

function main() {
    print("Hello from the Mycelium Network!")

    let greeting: string = "Welcome to ecological intelligence programming"
    print(greeting)

    let temp: float = get_env("temperature")
    if temp > 20.0 {
        print("Optimal growth conditions detected")
    } else {
        print("Adjusting environmental parameters...")
    }
}

Then run it:

myc hello.myc

Output:

Hello from the Mycelium Network!
Welcome to ecological intelligence programming
Optimal growth conditions detected

mycelium and python -m mycelium_ei are the same command as myc. The package has no dependencies. The twelve programs in examples/ and the tests are in the repository: git clone https://github.com/MichaelCrowe11/mycelium-ei-lang, then pip install -e . pytest and pytest in the checkout.

What runs today

Each item is covered by a test in tests/; the suite (140 tests) passed on CPython 3.9, 3.10, 3.11, 3.12, 3.13 and 3.14 on macOS on 2026-09-11.

• The language in docs/reference.md: environment blocks, functions, let and const, if/else if/else, while, for over arrays, objects, strings and ints, arrays and objects with methods, string concatenation, mycelium declarations with fields, methods, init and adapt functions, new, and top-level network and signal declarations (tests/test_interpreter.py, tests/test_parser.py, tests/test_lexer.py).
• adapt functions run when set_env or update_global_env changes a parameter; examples/cultivation.myc and examples/neural_network.myc show it (tests/test_examples.py).
• All twelve programs in examples/ run to completion under myc --no-sleep --seed 1 (tests/test_examples.py).
• genetic_optimize, swarm_optimize, ant_optimize and bio_compare in pure Python; a fitness function takes one array or one argument per dimension (tests/test_bio.py, examples/bio_optimization_demo.myc).
• Network builtins: nodes, connections, broadcast signals that print as they arrive (examples/network_demo.myc).
• Toy neural network and simulated cultivation builtins (examples/bio_ml_demo.myc, examples/cultivation_platform_demo.myc).
• Command line: --check, --tokens, --ast, --no-sleep, --seed, - for standard input; errors print as file:line:column: runtime error: ... and exit 1; runaway recursion stops with a message instead of a crash (tests/test_cli.py).
• Importing the package pulls in no third-party module (tests/test_no_dependencies.py).
• cargo build and cargo test pass for compiler/ (one unit test, one doc test).

Limits

• This is an interpreter for small models, not a numerical library. The optimizers search [-1, 1] per dimension with populations of tens; no speed or quality claim is made against established packages.
• create_cultivation and monitor_cultivation simulate a grow room. Do not use them to run one.
• quantum_bio_computing.py and performance_optimizations.py at the repository root are standalone experiments from 2025 that need numpy and numba. They are not part of the package and have no tests.
• The directories crypto-payments/, npm-package/, vscode-extension/, wasm/, snap/, homebrew/, conda-recipe/ and the two Dockerfiles have not been run. The planning documents at the root (roadmaps, monetization, publishing) describe 2025 intentions and prices. They are not an offer.
• Syntax errors are reported one at a time, at the first token the parser cannot place.

License and contact

Proprietary. See LICENSE: viewing and personal non-commercial evaluation only; no copying, modification or redistribution.

Contact: michael@crowelogic.com