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aa3366a797
It turns out that build_image_inner() in docker.rs was calling .elapsed() on a SystemTime to compute the tar mtime. That gives you "seconds since modification" — which is *not* what mtime means. Mtime is seconds since the Unix epoch. The fix is .duration_since(UNIX_EPOCH) like a normal person would use. While at it, the docker logs() call was passing None for options, which means it wasn't actually requesting stdout or stderr. So we were collecting logs from a stream that might not have any. Explicitly set stdout: true and stderr: true. The emulation runtime had a fun behavioral mismatch with Docker and Podman: it returned Err on non-zero exit codes, swallowing all stdout/stderr output. Docker and Podman return Ok with the exit code and let the caller decide what to do. The engine already handles non-zero exit codes in the Ok path, so the emulation was just silently eating useful output for no reason. The UI had a bounds check in next_job() that was mysteriously absent from previous_job() — the kind of inconsistency that waits patiently for someone to hit a stale workflow index and get a panic. Added the same .filter() guard. String slicing in the log processor wasn't checking char boundaries, which is fine until someone's log contains a multi-byte UTF-8 character before a bracket. Added is_char_boundary() checks. Step validation was accepting steps with only a 'name' field and no 'uses' or 'run', which is not a valid step in GitHub Actions. Fixed the validation to require at least one of the two fields that actually *do* something. Replaced .expect() calls on directory reads in main.rs with proper error handling. Panicking because a directory isn't readable is not great user experience.
wrkflw-executor
The execution engine that runs GitHub Actions workflows locally (Docker, Podman, or emulation).
- Features:
- Job graph execution with
needsordering and parallelism - Docker/Podman container steps and emulation mode
- Basic environment/context wiring compatible with Actions
- Job graph execution with
- Used by:
wrkflwCLI and TUI
API sketch
use wrkflw_executor::{execute_workflow, ExecutionConfig, RuntimeType};
let cfg = ExecutionConfig {
runtime: RuntimeType::Docker,
verbose: true,
preserve_containers_on_failure: false,
};
// Path to a workflow YAML
let workflow_path = std::path::Path::new(".github/workflows/ci.yml");
let result = execute_workflow(workflow_path, cfg).await?;
println!("workflow status: {:?}", result.summary_status);
Prefer using the wrkflw binary for a complete UX across validation, execution, and logs.