Hey! These docs are for version 2.8, which is no longer officially supported. Click here for the latest version, 2.11!

Processes

How to safely run subprocesses in your plugin.

It is not safe to use subprocess.run() like you normally would because this can break caching and will not leverage Pants's parallelism. Instead, Pants has safe alternatives with Process and InteractiveProcess.

Process

Overview

Process is similar to subprocess.Popen(). The process will run in the background, and you can run multiple processes in parallel.

from pants.engine.process import Process, ProcessResult
from pants.engine.rules import Get, rule

@rule
async def demo(...) -> Foo:
    result = await Get(
        ProcessResult,
        Process(
            argv=["/bin/echo", "hello world"],
            description="Demonstrate processes.",
        )
    )
    logger.info(result.stdout.decode())
    logger.info(result.stderr.decode())

This will return a ProcessResult object, which has the fields stdout: bytes, stderr: bytes, and output_digest: Digest.

The process will run in a temporary directory and is hermetic, meaning that it cannot read any arbitrary file from your project and that it will be stripped of environment variables. This sandbox is important for reproducibility and to allow running your Process anywhere, such as through remote execution.

📘

Debugging a Process

Setting the --no-process-execution-local-cleanup flag will cause the sandboxes of Processes to be preserved and logged to the console for inspection.

It can be very helpful while editing Process definitions!

Input Files

To populate the temporary directory with files, use the parameter input_digest: Digest. It's common to use MergeDigests to combine multiple Digests into one single input_digest.

Environment Variables

To set environment variables, use the parameter env: Mapping[str, str]. @rules are prevented from accessing os.environ (it will always be empty) because this reduces reproducibility and breaks caching. Instead, either hardcode the value or add a Subsystem option for the environment variable in question, or request the Environment type in your @rule.

The Environment type contains a subset of the environment that Pants was run in, and is requested via a EnvironmentRequest that lists the variables to consume.

from pants.engine.environment import Environment, EnvironmentRequest
from pants.engine.rules import Get, rule

@rule
async def partial_env(...) -> Foo:
    relevant_env = await Get(Environment, EnvironmentRequest(["RELEVANT_VAR", "PATH"]))
    ..

Output Files

To capture output files from the process, set output_files: Iterable[str] and/or output_directories: Iterable[str]. Then, you can use the ProcessResult.output_digest field to get a Digest of the result.

output_directores captures that directory and everything below it.

Timeouts

To use a timeout, set the timeout_seconds: int field. Otherwise, the process will never time out, unless the user cancels Pants.

📘

Process caching

By default, a Process will be cached to ~/.cache/pants/lmdb_store if the exit_code is 0.

If it not safe to cache your Process—usually the case when you know that a process accesses files outside of its sandbox—you can change the cacheability of your Process using the ProcessCacheScope parameter:

from pants.engine.process import Process, ProcessCacheScope, ProcessResult

@rule
async def demo(...) -> Foo:
    process = Process(
        argv=["/bin/echo", "hello world"],
        description="Not persisted between Pants runs ('sessions').",
        cache_scope=ProcessCacheScope.PER_SESSION,
    )
    ..

ProcessCacheScope supports other options as well, including ALWAYS.

FallibleProcessResult

Normally, a ProcessResult will raise an exception if the return code is not 0. Instead, a FallibleProcessResult allows for any return code.

Use Get(FallibleProcessResult, Process) if you expect that the process may fail, such as when running a linter or tests.

Like ProcessResult, FallibleProcessResult has the attributes stdout: bytes, stderr: bytes, and output_digest: Digest, and it adds exit_code: int.

InteractiveProcess

InteractiveProcess is similar to subprocess.run(). The process will run in the foreground, optionally with access to the workspace.

Because the process is potentially side-effecting, you may only run an InteractiveProcess in an @goal_rule as an Effect.

from pants.engine.rules import Effect, goal_rule
from pants.engine.process import InteractiveProcess, InteractiveProcessResult

@goal_rule
async def hello_world() -> HelloWorld:
    # This demonstrates opening a Python REPL.
    result = await Effect(
        InteractiveProcessResult,
        InteractiveProcess(argv=["/usr/bin/python"]),
    )
    return HelloWorld(exit_code=result.exit_code)

You may either set the parameter input_digest: Digest, or you may set run_in_workspace=True. When running in the workspace, you will have access to any file in the build root. If the process can safely be restarted, set the restartable=True flag, which will allow the engine to interrupt and restart the process if its inputs have changed.

To set environment variables, use the parameter env: Mapping[str, str], like you would with Process. You can also set hermetic_env=False to inherit the environment variables from the parent ./pants process.

The Effect will return an InteractiveProcessResult, which has a single field exit_code: int.


Did this page help you?