A data scientist keeps their code where it is and decorates it: `@node`
declares a function's ports beside the function, `Flow(name, nodes=[...])`
says which of them make a flow, and `use(fn, wire=..., **settings)` rebinds
one for a single flow. `fluksio sync` uploads the document plus a generated
import shim per node, so the store still holds a complete, runnable,
git-versioned definition while the code it imports stays theirs.
`fluksio login|run|runs` and `flow.submit().wait()` are the client half, over
the run endpoints that already existed. Runs record the user repository's
commit beside the store's, so "what code produced this number" is answerable
on the side that now holds the code.
- `fluksio/sdk/`: ports, decorators, the flow builder and its checks, the shim
generator, an HTTP client and sync. Standard library only at import, so
`from fluksio import node` in a training script pulls in no engine.
- `FlowDef.origin` marks a flow code-defined; `Run.origin_commit` carries the
repository's commit; `POST /modules/refresh` retires the workers without an
install, which every sync calls — a worker holds the imported package in
memory, so an edit to it is invisible until the process goes.
- The canvas shows a generated body read-only and names the repository to edit
instead; a body edited there stops the next sync rather than being discarded.
- The worker's reporter carries inert `Port`, `node`, `use` and `Flow`, since
the shim imports a module whose first line declares them.
- `examples/myresearch` is the worked example, `make sync-example` uploads it.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012ue1tkFWB1bcGy3aWhCKpU
`pip install fluksio && fluksio serve` on a machine with no Docker, no
database and no configuration — which is the case this is for: a node on
a cluster where ports cannot be opened. It makes its data directory, its
key and an admin account, prints the password once, and serves. Pairing
is `fluksio enroll <code> --portal …`, doing what the Settings screen
does through the same function, before the engine starts and without one
running — a machine nobody can route to has no browser pointed at it
either. The portal serves the dashboard, so nothing is served here.
Two things had to give way. `fastapi[standard]` pulls a cloud CLI that
wants sentry-sdk 2.x while we pinned below it — no pip resolution
existed, so the pin is lifted, which the comment beside it had been
waiting for and which also lets the Python cap go. And `uv` is now a
dependency rather than something to find on PATH: the Modules screen is
how a data scientist installs torch, and it was quietly falling back to
the engine's own interpreter.
The CLI imports nothing from the engine before it has set DATA_DIR — the
settings are built on the first import of core.config, and reaching it
early put the database in the working directory. There is a test for
that now, because the failure is silent.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
A wheel whose top-level module is `app` collides with anything else in a
user's venv, so the package that is about to be published takes the name
it is published under. Only the Python package moves; the repo, the
Docker WORKDIR and the compose project keep theirs.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
stroblmeandClaude Fable 5