# Path: kubeface/client.py
# def run_multiple(function, values):
#     def add_args(parser):
#     def from_args(args):
#     def __init__(
#             self,
#             backend,
#             max_simultaneous_tasks=10,
#             poll_seconds=30.0,
#             storage="gs://kubeface",
#             cache_key_prefix=None,
#             never_cleanup=False,
#             wait_to_raise_task_exception=False,
#             speculation_percent=0,
#             speculation_runtime_percentile=99,
#             speculation_max_reruns=1):
#     def __getstate__(self):
#     def next_cache_key(self):
#     def submit(self, tasks, num_tasks=None, cache_key=None):
#     def map(
#             self,
#             function,
#             iterable,
#             items_per_task=1,
#             num_items=None,
#             cache_key=None):
#         def grouped():
#     def mark_jobs_done(self, job_names=None):
#     def cleanup_job(self, job_name):
#     def job_summary(self, job_names=None, include_done=False):
#     def cleanup(self):
#     def remote_object(self, value):
# class Client(object):
# 
# Path: kubeface/common.py
# def check_call(*args, **kwargs):
# def configure_logging(args=None, verbose=False):
# def human_readable_memory_size(num, suffix='B'):
# def truncate(s, max_length):


import math
import argparse
import subprocess
from numpy import testing
from kubeface import (
    client,
    common)
from . import util



common.configure_logging(verbose=True)


def client_from_commandline_args(argv):
    parser = argparse.ArgumentParser()
    client.Client.add_args(parser)
    args = parser.parse_args(argv)

# Path: kubeface/client.py
# def run_multiple(function, values):
#     def add_args(parser):
#     def from_args(args):
#     def __init__(
#             self,
#             backend,
#             max_simultaneous_tasks=10,
#             poll_seconds=30.0,
#             storage="gs://kubeface",
#             cache_key_prefix=None,
#             never_cleanup=False,
#             wait_to_raise_task_exception=False,
#             speculation_percent=0,
#             speculation_runtime_percentile=99,
#             speculation_max_reruns=1):
#     def __getstate__(self):
#     def next_cache_key(self):
#     def submit(self, tasks, num_tasks=None, cache_key=None):
#     def map(
#             self,
#             function,
#             iterable,
#             items_per_task=1,
#             num_items=None,
#             cache_key=None):
#         def grouped():
#     def mark_jobs_done(self, job_names=None):
#     def cleanup_job(self, job_name):
#     def job_summary(self, job_names=None, include_done=False):
#     def cleanup(self):
#     def remote_object(self, value):
# class Client(object):
# 
# Path: kubeface/common.py
# def check_call(*args, **kwargs):
# def configure_logging(args=None, verbose=False):
# def human_readable_memory_size(num, suffix='B'):
# def truncate(s, max_length):


# Path: tests/test_job_command.py
import math
import argparse
import subprocess
from numpy import testing
from kubeface import (
    client,
    common)
from . import util




common.configure_logging(verbose=True)


def client_from_commandline_args(argv):
    parser = argparse.ArgumentParser()
    client.Client.add_args(parser)
    args = parser.parse_args(argv)

    return client.Client.from_args(args)