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Bring the README back in step with the commands it gives

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Four things had drifted. It told you to run `fluksio login` two lines above
saying `serve` signs you in — one of the two had to go, and it is the login.
It ran `fluksio sync` before `fluksio run`, which `run` now does itself. The
pipeline snippet passed `prepare` and `evaluate` to `Flow` without importing
them, so copying it got a NameError on the one example that matters. And the
site link was relative, which resolves to nothing on the page this file exists
to be — pypi.org.

Added one sentence, on installing into the environment you already work in,
because it is the reason a reader's own imports keep working and there is
nowhere else on this page they would learn it.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012ue1tkFWB1bcGy3aWhCKpU
This commit is contained in:
stroblme
2026-08-24 18:31:51 +02:00
co-authored by Claude Fable 5
parent 7e4f03369b
commit 47e513b658
1 changed files with 13 additions and 12 deletions
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backend/README.md
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@@ -9,17 +9,14 @@ pip install fluksio
fluksio serve
```
Then login once (the token is stored on your device) with the credentials shown after the previous command
and you're ready to go — `serve` signs you in itself and says where it put the
token, so there is no login step. (`fluksio login` is for an engine somewhere
else.)
```sh
fluksio login --url http://127.0.0.1:8000
```
and you're ready to go!
Fluksio keeps a SQLite database, a git repository of your flows and an artifact
store in a `.fluksio` beside your code — one installation per project, found
the way `.git` is. It prints an admin password once, and signs you in itself.
Install it into the environment you already work in and your nodes run on that
one, so everything you had imported is still importable. Fluksio keeps a SQLite
database, a git repository of your flows and an artifact store in a `.fluksio`
beside your code — one installation per project, found the way `.git` is.
## For data science
@@ -47,6 +44,8 @@ def fit(dataset, lr, epochs=25):
```python
# myresearch/pipeline.py
from fluksio import Flow, Port
from myresearch.data import prepare
from myresearch.evaluate import evaluate
from myresearch.train import fit
train = Flow("train", nodes=[prepare, fit, evaluate],
@@ -57,10 +56,12 @@ Fluksio will automatically infer the order of nodes based on the inputs and outp
When everything is set, you can launch your first run as follows:
```sh
fluksio sync myresearch
fluksio run train --lr 0.05 --wait
```
That syncs your code and then runs it, so after an edit the command is the same
one again.
Checkout our [documentation](https://docs.fluksio.com/getting-started/data-science/) for more infos.
## Some other features
@@ -75,7 +76,7 @@ Checkout our [documentation](https://docs.fluksio.com/getting-started/data-scien
*out* over one websocket, so nothing there has to be reachable.
Fluksio can also be used for facility automation.
Visit us on [Fluksio.com](fluksio.com) or go straight to our [documentation](https://docs.fluksio.com).
Visit us on [fluksio.com](https://fluksio.com) or go straight to our [documentation](https://docs.fluksio.com).
## License