Tutorials
Hands-on walkthroughs covering the core Lakeshore workflow. Each one is self-contained — work through them in order or jump to the one that matches what you need.
| I want to… | Tutorial | Time |
|---|---|---|
| Run my first queue round-trip | Hello UDF | ~5 min |
| Scale to many invocations in parallel | Fan out | ~10 min |
| Declare a cluster in YAML | Compose a cluster | ~10 min |
| Exercise every operator surface | End-to-end smoke | ~30 min |
Start with Hello UDF if this is your first time with the Python SDK — it runs with zero infrastructure. Move to Fan out once a single invocation is comfortable. End-to-end smoke is the operator checklist: providers, daemons, queues, jobs, and completion.
Runnable examples
The full set of runnable examples lives in the
lakeshore-examples
repo. Each directory is self-contained; scripts carry PEP 723 inline
metadata so uv run <script>.py resolves their dependencies.
| Example | What it covers |
|---|---|
01-hello-ssh | SSH provider basics |
02-hello-local-python | Local function dispatch |
05-pipeline-iteration | Chained stages over one plane |
08-queues-cpu-vs-gpu | Mixed CPU + GPU fleet from one lakeshore.yaml |
09-hello-queue-udf | Queue-bound @udf, submit → id → result |
10-fan-out-gather | Fan-out, streaming, and a two-stage pipeline |
14-compose-cluster | A 30-machine compose cluster with mounts and elasticity |
Older examples — EC2 launch, GPU clusters, code mounts, storage access,
compose runtime — live under
_legacy/
and predate the current SDK surface. Read them for shape, not for
copy-paste.
Related happy paths
The CLI, Python SDK, and admin sections each carry numbered happy paths — a narrower "run these commands, expect this output" format that pairs well with these tutorials.