Examples

Simple Func_ADL Example

This simple example reads a single root file form the CERN Opendata repo

from servicex_client.dataset_identifier import FileListDataset
from servicex_client.models import ResultFormat
from servicex_client.servicex_client import ServiceXClient

sx = ServiceXClient(backend="localhost")
dataset_id = FileListDataset("root://eospublic.cern.ch//eos/opendata/atlas/OutreachDatasets/2020-01-22/4lep/MC/mc_345060.ggH125_ZZ4lep.4lep.root")  # NOQA 501

ds = sx.func_adl_dataset(dataset_id, codegen="uproot",
                         title="Root",
                         result_format=ResultFormat.parquet)

sx3 = ds.Select(lambda e: {'lep_pt': e['lep_pt']}). \
    Where(lambda e: e['lep_pt'] > 1000). \
    as_pandas()
print(sx3)

Func_ADL Example With Rucio Dataset

This example uses the Rucio Dataset Identifier and returns a list of downloaded parquet files

from servicex_client.dataset_identifier import RucioDatasetIdentifier
from servicex_client.models import ResultFormat
from servicex_client.servicex_client import ServiceXClient

sx = ServiceXClient(backend="testing4")

dataset_id = RucioDatasetIdentifier("user.kchoi:user.kchoi.fcnc_tHq_ML.ttH.v8")

ds = sx.func_adl_dataset(dataset_id)

sx2 = ds.Select(lambda e: {'el_pt': e['el_pt']})\
    .set_result_format(ResultFormat.parquet)\
    .as_files()

print(sx2)

Python Code Generator

This example is using the python code generator. For this we don’t use func_adl, but pass in a python function that assumes a filename comes in as an argument and returns an awkward array

from servicex_client.dataset_identifier import FileListDataset
from servicex_client.servicex_client import ServiceXClient

sx = ServiceXClient(backend="testing4")
dataset_id = FileListDataset("root://eospublic.cern.ch//eos/opendata/atlas/OutreachDatasets/2020-01-22/4lep/MC/mc_345060.ggH125_ZZ4lep.4lep.root")  # NOQA 501

ds = sx.python_dataset(dataset_id, codegen="python", title="Python")


def run_query(input_filenames=None):
    import uproot
    o = uproot.lazy({input_filenames: "mini"})
    return o.lep_pt


sx3 = ds.with_uproot_function(run_query).as_pandas()
print(sx3)

Bigger Uproot