def register_function(self, container_type='docker', location=None, ep_id=None, group=None):
from funcx import FuncXClient
assert self.extr_func is not None, "Extractor function must first be registered!"
if location is None:
location = self.store_url
fxc = FuncXClient()
container_id = fxc.register_container(
location=location,
container_type=container_type,
name='kube-tabular',
description='I don\'t think so!',
)
self.func_id = fxc.register_function(self.extr_func,
ep_id,
group=group,
container_uuid=container_id,
description="A sum function")
print(f"The function has been updated! "
f"Please copy/paste the following code into {self.func_id} function class:\n")
print(self.func_id)
return self.func_id
# xpcs_x = XPCSExtractor()
# xpcs_x = NetCDFExtractor()
# xpcs_x = JsonXMLExtractor()
# xpcs_x = HDFExtractor()
# xpcs_x = ImagesExtractor()
# xpcs_x = KeywordExtractor()
# xpcs_x = PythonExtractor()
# xpcs_x = TabularExtractor()
xpcs_x = CCodeExtractor()
# xpcs_x = TikaExtractor()
ep_id = "2293034e-4c9f-459c-a6f0-0ed310a8e618"
extractor_name = "matio"
repo_name = "mdf"
container_uuid = fxc.register_container(f'/home/tskluzac/.xtract/.containers/xtract-{extractor_name}.img', 'singularity')
print("Container UUID: {}".format(container_uuid))
fn_uuid = fxc.register_function(base_extractor,
container_uuid=container_uuid,
description="Tabular test function.")
print("FN_UUID : ", fn_uuid)
task_batch_size = 1 # 128
fx_batch_size = 64 # 32
hdf_count = 0
task_batches = Queue()
missing_file = "/Users/tylerskluzacek/missing_files.json"
missing_file_0 = "/Users/tylerskluzacek/missing_mdf2.json"
# missing_file = None
# missing_file = None
"""
This script will run the Gladier team's XPCS script on each
file from the 2021-1 file set on Petrel. It will do so on Theta.
"""
# TODO:
# 1. Point to the right xpcs_data file.
# 2. Point to the right bunch of metadata files.
fxc = FuncXClient()
xpcs_x = XPCSExtractor()
trimester = "2019-3"
ep_id = "12ff7fa9-a76b-4188-82ea-1c0081c3c73a"
container_uuid = fxc.register_container('/home/tskluzac/.xtract/.containers/xtract-xpcs.img', 'singularity')
print("Container UUID: {}".format(container_uuid))
fn_uuid = fxc.register_function(base_extractor,
container_uuid=container_uuid,
description="Tabular test function.")
print("FN_UUID : ", fn_uuid)
task_batch_size = 128
fx_batch_size = 32
max_tasks_at_ep = 5000
hdf_count = 0
task_batches = Queue()
max_count = 500000
# 'xtract-netcdf/xtract-netcdf.img'
]
def hello_container(event):
import os
return f"Container version: {os.environ['container_version']}"
for container in all_containers:
print(f"Using funcX version: {funcx.__version__}")
fxc = FuncXClient()
base_path = '/home/tskluzac/ext_repos/'
container_path = os.path.join(base_path, container)
print(f"Container path: {container_path}")
container_uuid = fxc.register_container(container_path, 'singularity')
fn_uuid = fxc.register_function(
hdf_extract,
container_uuid=container_uuid,
description="New sum function defined without string spec")
print(f"FN UUID: {fn_uuid}")
res = fxc.run(sample_hdf_1, endpoint_id=js_ep_id, function_id=fn_uuid)
print(res)
for i in range(100):
# TODO: break when successful
try:
x = fxc.get_result(res)
print(x)
break
# * Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# * Neither the name of the copyright holder nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from funcx import FuncXClient
from sx_multi import run_coffea_processor
fxc = FuncXClient()
container_id = fxc.register_container(
"bengal1/funcx_coffea:add_schema_to_notebooks", "docker",
"Coffea Processor")
function_id = fxc.register_function(
run_coffea_processor,
"Run your coffea process code in a setup environment",
container_uuid=container_id)
print("Function_ID is ", function_id)
# id_list = ['dbc7a749-f689-419c-b114-2f9eb8146496']
id_list = ['c8f24648-6b96-4d58-ac14-93ccf81da12c']
def sleep_func(file_ls):
import time
#
# # for item in file_ls:
# # with open(item, 'r') as f:
# # f.close()
#
# time.sleep(sleep_s)
return "hello, world!"
# func_id = fxc.register_function(function=sleep_func, function_name='hpdc_sleep_extractor')
container_uuid = fxc.register_container('/home/tskluzac/xtract-matio.img', 'singularity')
print("Container UUID: {}".format(container_uuid))
func_id = fxc.register_function(matio_extract,
#ep_id, # TODO: We do not need ep id here
container_uuid=container_uuid,
description="New sum function defined without")
for fx_id in id_list:
for i in range(1,10):
task_id = fxc.run({'event'}, endpoint_id=fx_id, function_id=func_id)
while True:
result = fxc.get_batch_result([task_id])
print(result)
