Function jcache_execute

docs/cli.py:186–206

Execute outdated notebooks in parallel, capped at EXEC_JOBS workers. jupyter-cache's parallel pool sizes itself from os.cpu_count() with no CLI knob, so we run jcache in a shim that patches cpu_count — keeping load sane on small machines.

(force=False)

def jcache_execute(force=False):
    """Execute outdated notebooks in parallel, capped at EXEC_JOBS workers.

    jupyter-cache's parallel pool sizes itself from os.cpu_count() with no CLI
    knob, so we run jcache in a shim that patches cpu_count — keeping load sane
    on small machines.
    """
    shim = (
        f"import os; os.cpu_count = lambda: {int(EXEC_JOBS)}; "
        "from jupyter_cache.cli.commands.cmd_main import jcache; jcache()"
    )
    cmd = [sys.executable, "-c", shim, "project", "execute",
           "--executor", "local-parallel", "--timeout", EXEC_TIMEOUT]
    if force:
        cmd.append("--force")
    print(f"⚡ Executing {'ALL' if force else 'outdated'} notebooks "
          f"({EXEC_JOBS} parallel, {EXEC_TIMEOUT}s/cell timeout)...")
    result = subprocess.run(cmd, input="y\n", text=True, check=False)
    if result.returncode != 0:
        sys.exit(result.returncode)
    return result


def clean_docs():