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A Rust-powered Python platform for building reactive, data-driven applications with managed effects, actor-based concurrency, content-addressable functions, and a refinement type system.

Project description

Zef 🌿

A Rust-powered Python platform for building reactive, data-driven applications with managed effects, actor-based concurrency, content-addressable functions, and a refinement type system.

Zef treats everything — types, functions, effects, errors — as plain data. Values are contiguous in memory (like FlatBuffers), require no serialization, and cross language and process boundaries without conversion overhead.

What does Zef look like?

Composable Pipelines

from zef import *

names = ['Alice', 'Bob', 'Charlie', 'Dave']

names | filter(Z | length | greater_than(3)) | sort | collect
# ['Alice', 'Charlie', 'Dave']

range(10) | filter(is_prime) | map(multiply(2)) | collect
# [4, 6, 10, 14]

Effects as Data

Side effects are values you construct and then execute. There's a clear syntactic boundary between describing what to do and actually doing it.

# Describe the effect — this is just data
effect = FX.StartHTTPServer(
    routes={
        '/':       ET.HTML(content='<h1>Hello!</h1>'),
        '/api':    ET.JSON(content={'status': 'ok'}),
        '/health': ET.JSON(content={'up': True}),
    },
    port=8080,
)

# Execute it
effect | run

Actors and Streaming

Actors subscribe to topics, receive messages, and produce effects. State is threaded through successive invocations.

from zef import *

topic = ET.Topic('🍃-a0b1c2d3e4f567890abc')

def handle_msg(msg, state):
    effects = [FX.Print(content=f"[{state}] got: {msg}")]
    new_state = state + 1
    return effects, new_state

actor = FX.StartActor(
    input=topic,
    initial_state=0,
    rules={(Any, Any): handle_msg},
) | run

# Send messages — the actor processes them
FX.Publish(target=topic, content='hello') | run
FX.Publish(target=topic, content='world') | run
# [0] got: hello
# [1] got: world

Refinement Types

Types are sets. Compose them with & (intersection) and | (union). Refine with predicates.

Positive = Int & (Z > 0)
SmallPositive = Positive & (Z < 100)

42 | is_a(SmallPositive) | collect    # True
-1 | is_a(SmallPositive) | collect    # False
200 | is_a(SmallPositive) | collect   # False

# Use in function dispatch
EvenInt = Int & (Z % 2 == 0)

Multiple Dispatch

Functions support multiple methods dispatched on argument types — like Julia, but in Python.

@method
def greet(x: String) -> String:
    return f"Hello, {x}!"

@method
def greet(x: Int) -> String:
    return f"Number: {x}"

greet("Alice")   # "Hello, Alice!"
greet(42)        # "Number: 42"

Core Ideas

  • Data-oriented. If it can be expressed as data, it should be. Effects, errors, types, functions — all values.
  • Managed effects. Side effects are declared as values with FX.*, then executed with | run. Pure core, imperative shell.
  • Contiguous memory. Zef values live in contiguous buffers — no pointer chasing, no serialization. The in-memory format is the wire format.
  • Refinement types. Types are sets. Int & (Z > 0) is a type. Compose freely.
  • Content-addressable functions. Functions are identified by UID, not name. Multiple names can point to the same function. Methods are hot-reloadable.
  • Actor concurrency. Actors subscribe to topics, process messages, and produce effects. State is explicit and threaded.
  • Cross-language. Rust core with Python bindings (via PyO3). The same binary data flows between languages without marshaling.

Getting Started

Install from Wheel

Download the latest wheel from GitHub Releases and install:

pip install zef_core-*.whl

Build from Source

git clone git@github.com:UlfBissbort/zef.git
cd zef

# Create a virtual environment
python3 -m venv dev_venv
source dev_venv/bin/activate

# Install maturin
cargo install maturin --locked

# Build and install (release mode recommended — debug is significantly slower at runtime)
cd zef_core
maturin develop --release --features py_bindings

Configure

Create ~/.config/zef/config.zen.py:

ET.ZefConfig(zef_source_dir='/path/to/zef', vault_=['~/zef-vault'])

Verify

>>> import zef
🚅 created shelf allocator of size 64.00 GB on thread ThreadId(1)
🌿 Zef import completed

>>> zef.__version__
'0.1.14'

Running Tests

# Rust tests
cd zef_core && cargo test

# Python tests — run all with the test runner
python run_tests.py

# Run specific tests by pattern
python run_tests.py int64 skip

# Run a single test file directly
python tests/test_int64_layout.py

See notes/How to Write Tests in Zef.md for the full testing guide.

CI/CD

python trigger_build.py          # Bump patch version and trigger build
python trigger_build.py minor    # Bump minor version
python trigger_build.py major    # Bump major version

Creates a git tag and pushes to GitHub, triggering the workflow that builds the wheel and creates a release.

Documentation

The notes/ directory is a linked knowledge base covering architecture, design decisions, and implementation details. Start with notes/Overview.md for the index.

Key guides:

The zefop-search.html file is a standalone searchable reference for all Zef operators.

Tip: The notes use [[wiki-link]] cross-references and work as an Obsidian vault — open notes/ in Obsidian for a browsable, linked view.

Status

Zef is under active development. The API is evolving. The core data structures, type system, effects system, and actor model are functional. Language support is currently Python and Rust, with TypeScript (via WebAssembly) planned.

The Rust codebase produces compiler warnings — a cleanup pass is planned once the type definitions move to the code graph and source generation is unified.

Cross-Compiling for Linux ARM

brew install zig
rustup target add aarch64-unknown-linux-gnu
cd zef_core && maturin build --release --target aarch64-unknown-linux-gnu --zig

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