Python os.sched_getaffinity() Examples

def main():
    tids_train = pd.read_csv('data/train_labels.csv', index_col=0).index
    tids_test = sorted(glob.glob('data/crowdai_fma_test/*.mp3'))
    tids_test = [path.split('/')[-1][:-4] for path in tids_test]
    tids = tids_train.append(pd.Index(tids_test, name='track_id'))

    features = pd.DataFrame(index=tids, columns=columns(), dtype=np.float32)

    # More than usable CPUs to be CPU bound, not I/O bound. Beware memory.
    try:
        nb_workers = int(1.5 * len(os.sched_getaffinity(0)))
    except AttributeError as e:
        nb_workers = 10
    print('Working with {} processes.'.format(nb_workers))
    pool = multiprocessing.Pool(nb_workers)

    it = pool.imap_unordered(compute_features, tids)
    for row in tqdm(it, total=tids.size):
        features.loc[row.name] = row

    save(features, 10)
    test(features, 10) 

def auto_detect_cpus():
    try:
        from os import sched_getaffinity
    except ImportError:
        if os.environ.get("TRAVIS") == "true":
            # workaround https://bitbucket.org/pypy/pypy/issues/2375
            return 2
        try:
            from os import cpu_count
        except ImportError:
            from multiprocessing import cpu_count
    else:

        def cpu_count():
            return len(sched_getaffinity(0))

    try:
        n = cpu_count()
    except NotImplementedError:
        return 1
    return n if n else 1 

def test_cpu_count_affinity():
    if not hasattr(os, 'sched_getaffinity') or not hasattr(shutil, 'which'):
        pytest.skip()

    taskset_bin = shutil.which('taskset')
    python_bin = shutil.which('python')

    if taskset_bin is None or python_bin is None:
        raise pytest.skip()

    try:
        os.sched_getaffinity(0)
    except NotImplementedError:
        pytest.skip()

    res = check_output([taskset_bin, '-c', '0',
                        python_bin, '-c', cpu_count_cmd])

    assert res.strip().decode('utf-8') == '1' 

def available_cpu_cores(fallback: int = 1) -> int:
    """
    Returns the number (an int) of CPU cores available to this **process**, if
    determinable, otherwise the number of CPU cores available to the
    **computer**, if determinable, otherwise the *fallback* number (which
    defaults to 1).
    """
    try:
        # Note that this is the correct function to use, not os.cpu_count(), as
        # described in the latter's documentation.
        #
        # The reason, which the documentation does not detail, is that
        # processes may be pinned or restricted to certain CPUs by setting
        # their "affinity".  This is not typical except in high-performance
        # computing environments, but if it is done, then a computer with say
        # 24 total cores may only allow our process to use 12.  If we tried to
        # naively use all 24, we'd end up with two threads across the 12 cores.
        # This would degrade performance rather than improve it!
        return len(os.sched_getaffinity(0))
    except:
        # cpu_count() returns None if the value is indeterminable.
        return os.cpu_count() or fallback 

def add_make(self):
        try:
            nproc = len(os.sched_getaffinity(0))
        except AttributeError:
            nproc = multiprocessing.cpu_count()
        self.add_indirect_command("libtbx.scons", args=["-j", str(nproc)])
        # run build again to make sure everything is built
        self.add_indirect_command("libtbx.scons", args=["-j", str(nproc)]) 

def get_num_build_jobs():
    """
    Get number of parallel build jobs set by the --parallel command line
    argument of setup.py
    If the command did not receive a setting the environment variable
    NPY_NUM_BUILD_JOBS is checked. If that is unset, return the number of
    processors on the system, with a maximum of 8 (to prevent
    overloading the system if there a lot of CPUs).

    Returns
    -------
    out : int
        number of parallel jobs that can be run

    """
    from numpy.distutils.core import get_distribution
    try:
        cpu_count = len(os.sched_getaffinity(0))
    except AttributeError:
        cpu_count = multiprocessing.cpu_count()
    cpu_count = min(cpu_count, 8)
    envjobs = int(os.environ.get("NPY_NUM_BUILD_JOBS", cpu_count))
    dist = get_distribution()
    # may be None during configuration
    if dist is None:
        return envjobs

    # any of these three may have the job set, take the largest
    cmdattr = (getattr(dist.get_command_obj('build'), 'parallel', None),
               getattr(dist.get_command_obj('build_ext'), 'parallel', None),
               getattr(dist.get_command_obj('build_clib'), 'parallel', None))
    if all(x is None for x in cmdattr):
        return envjobs
    else:
        return max(x for x in cmdattr if x is not None) 

def get_num_build_jobs():
    """
    Get number of parallel build jobs set by the --parallel command line
    argument of setup.py
    If the command did not receive a setting the environment variable
    NPY_NUM_BUILD_JOBS checked and if that is unset it returns 1.

    Returns
    -------
    out : int
        number of parallel jobs that can be run

    """
    from numpy.distutils.core import get_distribution
    try:
        cpu_count = len(os.sched_getaffinity(0))
    except AttributeError:
        cpu_count = multiprocessing.cpu_count()
    envjobs = int(os.environ.get("NPY_NUM_BUILD_JOBS", cpu_count))
    dist = get_distribution()
    # may be None during configuration
    if dist is None:
        return envjobs

    # any of these three may have the job set, take the largest
    cmdattr = (getattr(dist.get_command_obj('build'), 'parallel', None),
               getattr(dist.get_command_obj('build_ext'), 'parallel', None),
               getattr(dist.get_command_obj('build_clib'), 'parallel', None))
    if all(x is None for x in cmdattr):
        return envjobs
    else:
        return max(x for x in cmdattr if x is not None) 

def get_num_build_jobs():
    """
    Get number of parallel build jobs set by the --parallel command line
    argument of setup.py
    If the command did not receive a setting the environment variable
    NPY_NUM_BUILD_JOBS is checked. If that is unset, return the number of
    processors on the system, with a maximum of 8 (to prevent
    overloading the system if there a lot of CPUs).

    Returns
    -------
    out : int
        number of parallel jobs that can be run

    """
    from numpy.distutils.core import get_distribution
    try:
        cpu_count = len(os.sched_getaffinity(0))
    except AttributeError:
        cpu_count = multiprocessing.cpu_count()
    cpu_count = min(cpu_count, 8)
    envjobs = int(os.environ.get("NPY_NUM_BUILD_JOBS", cpu_count))
    dist = get_distribution()
    # may be None during configuration
    if dist is None:
        return envjobs

    # any of these three may have the job set, take the largest
    cmdattr = (getattr(dist.get_command_obj('build'), 'parallel', None),
               getattr(dist.get_command_obj('build_ext'), 'parallel', None),
               getattr(dist.get_command_obj('build_clib'), 'parallel', None))
    if all(x is None for x in cmdattr):
        return envjobs
    else:
        return max(x for x in cmdattr if x is not None) 

def num_cpus():
    try:
        return len(os.sched_getaffinity(0))
    except AttributeError:
        return os.cpu_count() 

def get_num_build_jobs():
    """
    Get number of parallel build jobs set by the --parallel command line
    argument of setup.py
    If the command did not receive a setting the environment variable
    NPY_NUM_BUILD_JOBS is checked. If that is unset, return the number of
    processors on the system, with a maximum of 8 (to prevent
    overloading the system if there a lot of CPUs).

    Returns
    -------
    out : int
        number of parallel jobs that can be run

    """
    from numpy.distutils.core import get_distribution
    try:
        cpu_count = len(os.sched_getaffinity(0))
    except AttributeError:
        cpu_count = multiprocessing.cpu_count()
    cpu_count = min(cpu_count, 8)
    envjobs = int(os.environ.get("NPY_NUM_BUILD_JOBS", cpu_count))
    dist = get_distribution()
    # may be None during configuration
    if dist is None:
        return envjobs

    # any of these three may have the job set, take the largest
    cmdattr = (getattr(dist.get_command_obj('build'), 'parallel', None),
               getattr(dist.get_command_obj('build_ext'), 'parallel', None),
               getattr(dist.get_command_obj('build_clib'), 'parallel', None))
    if all(x is None for x in cmdattr):
        return envjobs
    else:
        return max(x for x in cmdattr if x is not None) 

def test_cpu_affinity(self):
        p = psutil.Process()
        initial = p.cpu_affinity()
        assert initial, initial
        self.addCleanup(p.cpu_affinity, initial)

        if hasattr(os, "sched_getaffinity"):
            self.assertEqual(initial, list(os.sched_getaffinity(p.pid)))
        self.assertEqual(len(initial), len(set(initial)))

        all_cpus = list(range(len(psutil.cpu_percent(percpu=True))))
        # Work around travis failure:
        # https://travis-ci.org/giampaolo/psutil/builds/284173194
        for n in all_cpus if not TRAVIS else initial:
            p.cpu_affinity([n])
            self.assertEqual(p.cpu_affinity(), [n])
            if hasattr(os, "sched_getaffinity"):
                self.assertEqual(p.cpu_affinity(),
                                 list(os.sched_getaffinity(p.pid)))
            # also test num_cpu()
            if hasattr(p, "num_cpu"):
                self.assertEqual(p.cpu_affinity()[0], p.num_cpu())

        # [] is an alias for "all eligible CPUs"; on Linux this may
        # not be equal to all available CPUs, see:
        # https://github.com/giampaolo/psutil/issues/956
        p.cpu_affinity([])
        if LINUX:
            self.assertEqual(p.cpu_affinity(), p._proc._get_eligible_cpus())
        else:
            self.assertEqual(p.cpu_affinity(), all_cpus)
        if hasattr(os, "sched_getaffinity"):
            self.assertEqual(p.cpu_affinity(),
                             list(os.sched_getaffinity(p.pid)))
        #
        self.assertRaises(TypeError, p.cpu_affinity, 1)
        p.cpu_affinity(initial)
        # it should work with all iterables, not only lists
        p.cpu_affinity(set(all_cpus))
        p.cpu_affinity(tuple(all_cpus)) 

def get_num_build_jobs():
    """
    Get number of parallel build jobs set by the --parallel command line
    argument of setup.py
    If the command did not receive a setting the environment variable
    NPY_NUM_BUILD_JOBS is checked. If that is unset, return the number of
    processors on the system, with a maximum of 8 (to prevent
    overloading the system if there a lot of CPUs).

    Returns
    -------
    out : int
        number of parallel jobs that can be run

    """
    from numpy.distutils.core import get_distribution
    try:
        cpu_count = len(os.sched_getaffinity(0))
    except AttributeError:
        cpu_count = multiprocessing.cpu_count()
    cpu_count = min(cpu_count, 8)
    envjobs = int(os.environ.get("NPY_NUM_BUILD_JOBS", cpu_count))
    dist = get_distribution()
    # may be None during configuration
    if dist is None:
        return envjobs

    # any of these three may have the job set, take the largest
    cmdattr = (getattr(dist.get_command_obj('build'), 'parallel', None),
               getattr(dist.get_command_obj('build_ext'), 'parallel', None),
               getattr(dist.get_command_obj('build_clib'), 'parallel', None))
    if all(x is None for x in cmdattr):
        return envjobs
    else:
        return max(x for x in cmdattr if x is not None) 

def cpus_count() -> Optional[int]:
    try:
        return len(os.sched_getaffinity(0))
    except AttributeError:
        return os.cpu_count() 

def log_execution_env_state(app_args, gitroot='.'):
    """Log information about the execution environment.

    It is recommeneded to log this information so it can be used for referencing
    at a later time.

    Args:
        app_args (dict): the command line arguments passed to the application
        git_root: the path to the .git root directory
    """

    def log_git_state():
        """Log the state of the git repository.

        It is useful to know what git tag we're using, and if we have outstanding code.
        """
        repo = Repo(gitroot)
        assert not repo.bare

        if repo.is_dirty():
            logger.debug("Git is dirty")
        try:
            branch_name = repo.active_branch.name
        except TypeError:
            branch_name = "None, Git is in 'detached HEAD' state"
        logger.debug("Active Git branch: %s", branch_name)
        logger.debug("Git commit: %s" % repo.head.commit.hexsha)

    logger.debug("Number of CPUs: %d", len(os.sched_getaffinity(0)))
    logger.debug("Number of GPUs: %d", torch.cuda.device_count())
    logger.debug("CUDA version: %s", torch.version.cuda)
    logger.debug("CUDNN version: %s", torch.backends.cudnn.version())
    logger.debug("Kernel: %s", platform.release())
    if HAVE_LSB:
        logger.debug("OS: %s", lsb_release.get_lsb_information()['DESCRIPTION'])
    logger.debug("Python: %s", sys.version)
    logger.debug("PyTorch: %s", torch.__version__)
    logger.debug("Numpy: %s", np.__version__)
    log_git_state()
    logger.debug("App args: %s", app_args) 

def get_num_build_jobs():
    """
    Get number of parallel build jobs set by the --parallel command line
    argument of setup.py
    If the command did not receive a setting the environment variable
    NPY_NUM_BUILD_JOBS is checked. If that is unset, return the number of
    processors on the system, with a maximum of 8 (to prevent
    overloading the system if there a lot of CPUs).

    Returns
    -------
    out : int
        number of parallel jobs that can be run

    """
    from numpy.distutils.core import get_distribution
    try:
        cpu_count = len(os.sched_getaffinity(0))
    except AttributeError:
        cpu_count = multiprocessing.cpu_count()
    cpu_count = min(cpu_count, 8)
    envjobs = int(os.environ.get("NPY_NUM_BUILD_JOBS", cpu_count))
    dist = get_distribution()
    # may be None during configuration
    if dist is None:
        return envjobs

    # any of these three may have the job set, take the largest
    cmdattr = (getattr(dist.get_command_obj('build'), 'parallel', None),
               getattr(dist.get_command_obj('build_ext'), 'parallel', None),
               getattr(dist.get_command_obj('build_clib'), 'parallel', None))
    if all(x is None for x in cmdattr):
        return envjobs
    else:
        return max(x for x in cmdattr if x is not None) 

def get_num_build_jobs():
    """
    Get number of parallel build jobs set by the --parallel command line
    argument of setup.py
    If the command did not receive a setting the environment variable
    NPY_NUM_BUILD_JOBS is checked. If that is unset, return the number of
    processors on the system, with a maximum of 8 (to prevent
    overloading the system if there a lot of CPUs).

    Returns
    -------
    out : int
        number of parallel jobs that can be run

    """
    from numpy.distutils.core import get_distribution
    try:
        cpu_count = len(os.sched_getaffinity(0))
    except AttributeError:
        cpu_count = multiprocessing.cpu_count()
    cpu_count = min(cpu_count, 8)
    envjobs = int(os.environ.get("NPY_NUM_BUILD_JOBS", cpu_count))
    dist = get_distribution()
    # may be None during configuration
    if dist is None:
        return envjobs

    # any of these three may have the job set, take the largest
    cmdattr = (getattr(dist.get_command_obj('build'), 'parallel', None),
               getattr(dist.get_command_obj('build_ext'), 'parallel', None),
               getattr(dist.get_command_obj('build_clib'), 'parallel', None))
    if all(x is None for x in cmdattr):
        return envjobs
    else:
        return max(x for x in cmdattr if x is not None) 

def get_num_build_jobs():
    """
    Get number of parallel build jobs set by the --parallel command line
    argument of setup.py
    If the command did not receive a setting the environment variable
    NPY_NUM_BUILD_JOBS checked and if that is unset it returns 1.

    Returns
    -------
    out : int
        number of parallel jobs that can be run

    """
    from numpy.distutils.core import get_distribution
    try:
        cpu_count = len(os.sched_getaffinity(0))
    except AttributeError:
        cpu_count = multiprocessing.cpu_count()
    envjobs = int(os.environ.get("NPY_NUM_BUILD_JOBS", cpu_count))
    dist = get_distribution()
    # may be None during configuration
    if dist is None:
        return envjobs

    # any of these three may have the job set, take the largest
    cmdattr = (getattr(dist.get_command_obj('build'), 'parallel', None),
               getattr(dist.get_command_obj('build_ext'), 'parallel', None),
               getattr(dist.get_command_obj('build_clib'), 'parallel', None))
    if all(x is None for x in cmdattr):
        return envjobs
    else:
        return max(x for x in cmdattr if x is not None) 

def _workers_count():
    cpu_count = 0
    try:
        cpu_count = len(os.sched_getaffinity(0))
    except AttributeError:
        cpu_count = os.cpu_count()
    return cpu_count * 4 

def cpu_count(self) -> int:
        return len(os.sched_getaffinity(0)) 

def num_cpus() -> Optional[int]:
    "Get number of cpus"
    try:
        return len(os.sched_getaffinity(0))
    except AttributeError:
        return os.cpu_count() 

def cpu_count():
      # The set of CPUs accessible to the current process (pid 0).
      cpu_set = os.sched_getaffinity(0)
      return len(cpu_set) 

def get_num_build_jobs():
    """
    Get number of parallel build jobs set by the --parallel command line
    argument of setup.py
    If the command did not receive a setting the environment variable
    NPY_NUM_BUILD_JOBS is checked. If that is unset, return the number of
    processors on the system, with a maximum of 8 (to prevent
    overloading the system if there a lot of CPUs).

    Returns
    -------
    out : int
        number of parallel jobs that can be run

    """
    from numpy.distutils.core import get_distribution
    try:
        cpu_count = len(os.sched_getaffinity(0))
    except AttributeError:
        cpu_count = multiprocessing.cpu_count()
    cpu_count = min(cpu_count, 8)
    envjobs = int(os.environ.get("NPY_NUM_BUILD_JOBS", cpu_count))
    dist = get_distribution()
    # may be None during configuration
    if dist is None:
        return envjobs

    # any of these three may have the job set, take the largest
    cmdattr = (getattr(dist.get_command_obj('build'), 'parallel', None),
               getattr(dist.get_command_obj('build_ext'), 'parallel', None),
               getattr(dist.get_command_obj('build_clib'), 'parallel', None))
    if all(x is None for x in cmdattr):
        return envjobs
    else:
        return max(x for x in cmdattr if x is not None) 

def _worker_count():
    cpu_count = 1
    try:
        cpu_count = len(os.sched_getaffinity(0))
    except AttributeError:
        cpu_count = multiprocessing.cpu_count()
    return cpu_count 

def test_cpu_affinity(self):
        p = psutil.Process()
        initial = p.cpu_affinity()
        assert initial, initial
        self.addCleanup(p.cpu_affinity, initial)

        if hasattr(os, "sched_getaffinity"):
            self.assertEqual(initial, list(os.sched_getaffinity(p.pid)))
        self.assertEqual(len(initial), len(set(initial)))

        all_cpus = list(range(len(psutil.cpu_percent(percpu=True))))
        # Work around travis failure:
        # https://travis-ci.org/giampaolo/psutil/builds/284173194
        for n in all_cpus if not TRAVIS else initial:
            p.cpu_affinity([n])
            self.assertEqual(p.cpu_affinity(), [n])
            if hasattr(os, "sched_getaffinity"):
                self.assertEqual(p.cpu_affinity(),
                                 list(os.sched_getaffinity(p.pid)))
            # also test num_cpu()
            if hasattr(p, "num_cpu"):
                self.assertEqual(p.cpu_affinity()[0], p.num_cpu())

        # [] is an alias for "all eligible CPUs"; on Linux this may
        # not be equal to all available CPUs, see:
        # https://github.com/giampaolo/psutil/issues/956
        p.cpu_affinity([])
        if LINUX:
            self.assertEqual(p.cpu_affinity(), p._proc._get_eligible_cpus())
        else:
            self.assertEqual(p.cpu_affinity(), all_cpus)
        if hasattr(os, "sched_getaffinity"):
            self.assertEqual(p.cpu_affinity(),
                             list(os.sched_getaffinity(p.pid)))
        #
        self.assertRaises(TypeError, p.cpu_affinity, 1)
        p.cpu_affinity(initial)
        # it should work with all iterables, not only lists
        if not TRAVIS:
            p.cpu_affinity(set(all_cpus))
            p.cpu_affinity(tuple(all_cpus)) 

def threads_to_use():
    """Returns the number of cores we are allowed to run on"""
    if hasattr(os, 'sched_getaffinity'):
        cores = len(os.sched_getaffinity(0))
    else:
        cores = os.cpu_count()
    return min(_max_threads, cores) 

def test_cpu_affinity(self):
        p = psutil.Process()
        initial = p.cpu_affinity()
        assert initial, initial
        self.addCleanup(p.cpu_affinity, initial)

        if hasattr(os, "sched_getaffinity"):
            self.assertEqual(initial, list(os.sched_getaffinity(p.pid)))
        self.assertEqual(len(initial), len(set(initial)))

        all_cpus = list(range(len(psutil.cpu_percent(percpu=True))))
        # Work around travis failure:
        # https://travis-ci.org/giampaolo/psutil/builds/284173194
        for n in all_cpus if not TRAVIS else initial:
            p.cpu_affinity([n])
            self.assertEqual(p.cpu_affinity(), [n])
            if hasattr(os, "sched_getaffinity"):
                self.assertEqual(p.cpu_affinity(),
                                 list(os.sched_getaffinity(p.pid)))
            # also test num_cpu()
            if hasattr(p, "num_cpu"):
                self.assertEqual(p.cpu_affinity()[0], p.num_cpu())

        # [] is an alias for "all eligible CPUs"; on Linux this may
        # not be equal to all available CPUs, see:
        # https://github.com/giampaolo/psutil/issues/956
        p.cpu_affinity([])
        if LINUX:
            self.assertEqual(p.cpu_affinity(), p._proc._get_eligible_cpus())
        else:
            self.assertEqual(p.cpu_affinity(), all_cpus)
        if hasattr(os, "sched_getaffinity"):
            self.assertEqual(p.cpu_affinity(),
                             list(os.sched_getaffinity(p.pid)))
        #
        self.assertRaises(TypeError, p.cpu_affinity, 1)
        p.cpu_affinity(initial)
        # it should work with all iterables, not only lists
        p.cpu_affinity(set(all_cpus))
        p.cpu_affinity(tuple(all_cpus)) 

def get_num_build_jobs():
    """
    Get number of parallel build jobs set by the --parallel command line
    argument of setup.py
    If the command did not receive a setting the environment variable
    NPY_NUM_BUILD_JOBS is checked. If that is unset, return the number of
    processors on the system, with a maximum of 8 (to prevent
    overloading the system if there a lot of CPUs).

    Returns
    -------
    out : int
        number of parallel jobs that can be run

    """
    from numpy.distutils.core import get_distribution
    try:
        cpu_count = len(os.sched_getaffinity(0))
    except AttributeError:
        cpu_count = multiprocessing.cpu_count()
    cpu_count = min(cpu_count, 8)
    envjobs = int(os.environ.get("NPY_NUM_BUILD_JOBS", cpu_count))
    dist = get_distribution()
    # may be None during configuration
    if dist is None:
        return envjobs

    # any of these three may have the job set, take the largest
    cmdattr = (getattr(dist.get_command_obj('build'), 'parallel', None),
               getattr(dist.get_command_obj('build_ext'), 'parallel', None),
               getattr(dist.get_command_obj('build_clib'), 'parallel', None))
    if all(x is None for x in cmdattr):
        return envjobs
    else:
        return max(x for x in cmdattr if x is not None) 

def cpu_count():
    """Return the number of CPUs the current process can use.

    The returned number of CPUs accounts for:
     * the number of CPUs in the system, as given by
       ``multiprocessing.cpu_count``;
     * the CPU affinity settings of the current process
       (available with Python 3.4+ on some Unix systems);
     * CFS scheduler CPU bandwidth limit (available on Linux only, typically
       set by docker and similar container orchestration systems);
     * the value of the LOKY_MAX_CPU_COUNT environment variable if defined.
    and is given as the minimum of these constraints.
    It is also always larger or equal to 1.
    """
    import math

    try:
        cpu_count_mp = mp.cpu_count()
    except NotImplementedError:
        cpu_count_mp = 1

    # Number of available CPUs given affinity settings
    cpu_count_affinity = cpu_count_mp
    if hasattr(os, 'sched_getaffinity'):
        try:
            cpu_count_affinity = len(os.sched_getaffinity(0))
        except NotImplementedError:
            pass

    # CFS scheduler CPU bandwidth limit
    # available in Linux since 2.6 kernel
    cpu_count_cfs = cpu_count_mp
    cfs_quota_fname = "/sys/fs/cgroup/cpu/cpu.cfs_quota_us"
    cfs_period_fname = "/sys/fs/cgroup/cpu/cpu.cfs_period_us"
    if os.path.exists(cfs_quota_fname) and os.path.exists(cfs_period_fname):
        with open(cfs_quota_fname, 'r') as fh:
            cfs_quota_us = int(fh.read())
        with open(cfs_period_fname, 'r') as fh:
            cfs_period_us = int(fh.read())

        if cfs_quota_us > 0 and cfs_period_us > 0:
            # Make sure this quantity is an int as math.ceil returns a
            # float in python2.7. (See issue #165)
            cpu_count_cfs = int(math.ceil(cfs_quota_us / cfs_period_us))

    # User defined soft-limit passed as an loky specific environment variable.
    cpu_count_loky = int(os.environ.get('LOKY_MAX_CPU_COUNT', cpu_count_mp))
    aggregate_cpu_count = min(cpu_count_mp, cpu_count_affinity, cpu_count_cfs,
                              cpu_count_loky)
    return max(aggregate_cpu_count, 1)