core

Execution

Send code, get back what it printed. There is no machine to create first and nothing left running afterwards — the process starts straight into fresh namespaces with its limits already set, so a run costs milliseconds rather than a container boot. Big environments like pytorch are bind-mounted read-only off the host instead of reinstalled per run.

language codes

Every run names its language. It is never inferred — not from a file extension, not from the code itself. A .py file is as likely to be torch as plain Python, and inline code has no extension at all, so one rule you apply every time beats two with a boundary to remember.

code	language	written as
python	Python 3	.py
node	Node.js	.js

The code is python, not python3 — which Python the image ships is ours to change. There is no pytorch code either: torch is a library inside the Python environment, not a language, so torch code is python like any other. bzlabs languages and boltzlabs.languages() return this list live.

python

Either the code itself or a path to read it from — plus the language, in both cases. The path is resolved on your machine, so the platform only ever receives code, never a path it would have to trust.

run.py

import boltzlabs

print(boltzlabs.execute("print(sum(range(101)))", language="python"))   # 5050
print(boltzlabs.execute(file="train.py", language="python"))
print(boltzlabs.execute("console.log(40 + 2)", language="node"))        # 42

boltzlabs.execute(file="slow.py", language="python", timeout=120)   # default is 30s
boltzlabs.languages()   # the codes above, from the platform

The result is the same object sb.exec() returns, so printing it gives you the output and testing it gives you success:

result.py

res = boltzlabs.execute(file="tests.py", language="python")

print(res)          # stdout
if res:             # True when the exit code was 0
    ...
res.check()         # raises if it failed

# .stdout .stderr .exit_code .duration_ms when you want them.
# A non-zero exit is data, not an exception: your program failed, not the call.

cli

shell

bzlabs run --language python train.py
bzlabs run --language python -c 'print(1)'
bzlabs run --language node app.js
bzlabs run --language python slow.py --timeout 120

bzlabs languages     # the codes

Your program's exit code becomes the CLI's, so && and || compose the way they would locally.

limits

languages

python · node

timeout

30 s default, 300 max

code size

1 MiB

filesystem

wiped after each run

Every run gets its own workspace and that workspace is destroyed with the process, so nothing one run writes can be seen by the next. When you want state to survive between commands — installed packages, files, a process left running — use a sandbox instead: the first command pays for the boot and every one after it is free.