doeff 0.4.1

Pragmatic do-notation and effects system for Python

doeff - Algebraic Effects for Python

doeff is an algebraic effects runtime for Python with one-shot continuations and a Rust VM. Programs are written with generator-based @do notation and executed through explicit handler stacks.

Installation

pip install doeff

Quick Start

from doeff import do, run, WithHandler
from doeff_core_effects import Ask, Get, Put, Tell
from doeff_core_effects.handlers import reader, state, writer
from doeff_core_effects.scheduler import scheduled

@do
def counter_program():
    yield Put("counter", 0)
    yield Tell("Starting computation")
    count = yield Get("counter")
    yield Put("counter", count + 1)
    return count + 1

# Compose handlers explicitly with WithHandler
prog = counter_program()
prog = WithHandler(writer(), prog)
prog = WithHandler(state(), prog)
prog = WithHandler(reader(env={"greeting": "hello"}), prog)
result = run(scheduled(prog))
print(result)  # 1

Runtime API

Entrypoint	Signature	Use case
run	run(doexpr)	Execute a DoExpr program to completion

run() takes a single DoExpr (program node) and returns the result value directly. Handlers are composed explicitly using WithHandler(handler, body). Use scheduled(prog) to wrap with the scheduler for concurrency effects.

Handler Composition

Handlers are installed with WithHandler(handler, body). Stack multiple handlers by nesting:

from doeff import do, run, WithHandler, Resume, Pass
from doeff_core_effects import Ask

@do
def my_handler(effect, k):
    if isinstance(effect, Ask):
        return (yield Resume(k, "hello"))
    yield Pass(effect, k)

@do
def prog():
    return (yield Ask("greeting"))

result = run(WithHandler(my_handler, prog()))
print(result)  # hello

Handlers are @do functions that receive (effect, k). They can:

• yield Resume(k, value) — resume the continuation with a value
• yield Pass(effect, k) — forward the effect to outer handlers
• yield Transfer(k, value) — tail-resume (handler done after this)

Effect Surface

Core effects (from doeff_core_effects):

• Reader: Ask(key), Local(env, program)
• State: Get(key), Put(key, value)
• Writer: Tell(message), slog(msg, **kwargs)
• Error: Try(program) — returns Ok(value) or Err(error)
• Observe: Listen(program, types=...) — collect effects during execution

Scheduler effects (from doeff_core_effects.scheduler):

• Concurrency: Spawn(program), Wait(task), Gather(*tasks), Race(*tasks)
• Promises: CreatePromise(), CompletePromise(p, v), FailPromise(p, e)
• External: CreateExternalPromise() — bridge external threads
• Semaphores: CreateSemaphore(n), AcquireSemaphore(s), ReleaseSemaphore(s)

Handlers

Built-in handlers (from doeff_core_effects.handlers):

Handler	Factory	Effects handled
Reader	reader(env={...})	Ask
Lazy Ask	lazy_ask(env={...})	Ask, Local (with caching)
State	state(initial={...})	Get, Put
Writer	writer()	Tell / WriterTellEffect
Try	try_handler	Try
Slog	slog_handler()	Slog
Local	local_handler	Local
Listen	listen_handler	Listen
Await	await_handler()	Await
Scheduler	scheduled(prog)	Spawn, Wait, Gather, Race, etc.

Scheduler and Concurrency

from doeff import do, run, WithHandler
from doeff_core_effects import Tell
from doeff_core_effects.handlers import writer
from doeff_core_effects.scheduler import scheduled, Spawn, Wait, Gather

@do
def worker(label):
    yield Tell(f"working: {label}")
    return label

@do
def main():
    t1 = yield Spawn(worker("a"))
    t2 = yield Spawn(worker("b"))
    results = yield Gather(t1, t2)
    return results

result = run(scheduled(WithHandler(writer(), main())))
print(result)  # ['a', 'b']

CLI

# Run a program with auto-discovered interpreter
doeff run --program myapp.module.program

# With explicit interpreter
doeff run --program myapp.program --interpreter myapp.interpreter

# With environment
doeff run --program myapp.program --env myapp.default_env

# Inline code
doeff run -c 'return 42'

# Apply transform (T -> Program[U])
doeff run --program myapp.program --apply myapp.transforms.wrap

# JSON output
doeff run --program myapp.program --format json

The CLI supports automatic interpreter/environment discovery via doeff-indexer. See docs/14-cli-auto-discovery.md for marker syntax and hierarchy rules.

Development

uv sync --reinstall  # rebuild Rust VM
uv run pytest

License

MIT License. See LICENSE.