Send func_adl expressions to a ServiceX endpoint
This package contains the single object ServiceXSourceXAOD
and ServiceXSourceUpROOT
which can be used as a root of a func_adl
expression to query large LHC datasets from an active ServiceX
instance located on the net.
See below for simple examples.
servicex
documentationfunc_adl
documentation
To use func_adl
on servicex
, the only func_adl
package you need to install this package. All others required will be pulled in as dependencies of this package.
See the further information for documentation above to understand how this works. Here is a quick sample that will run against an ATLAS xAOD
backend in servicex
to get out jet pt's for those jets with pt > 30
GeV.
from func_adl_servicex import ServiceXSourceXAOD
dataset_xaod = "mc15_13TeV:mc15_13TeV.361106.PowhegPythia8EvtGen_AZNLOCTEQ6L1_Zee.merge.DAOD_STDM3.e3601_s2576_s2132_r6630_r6264_p2363_tid05630052_00"
ds = ServiceXSourceXAOD(dataset_xaod)
data = (
ds
.SelectMany('lambda e: (e.Jets("AntiKt4EMTopoJets"))')
.Where('lambda j: (j.pt()/1000)>30')
.Select('lambda j: j.pt()')
.AsAwkwardArray(["JetPt"])
.value()
)
print(data['JetPt'])
See the further information for documentation above to understand how this works. Here is a quick sample that will run against an CMS Run 1 AOD
backend in servicex
. It turns against a 6 TB CMS Open Data dataset, selecting global muons with a pT greater than 30 GeV.
from func_adl_servicex import ServiceXSourceCMSRun1AOD
dataset_xaod = "cernopendata://16"
ds = ServiceXSourceCMSRun1AOD(dataset_xaod)
data = (
ds
.SelectMany(lambda e: e.TrackMuons("globalMuons"))
.Where(lambda m: m.pt() > 30)
.Select(lambda m: m.pt())
.AsAwkwardArray(['mu_pt'])
.value()
)
print(data['mu_pt'])
See the further information for documentation above to understand how this works. Here is a quick sample that will run against a ROOT file (TTree) in the uproot
backend in servicex
to get out jet pt's. Note that the image name tag is likely wrong here. See XXX to get the current one.
from servicex import ServiceXDataset
from func_adl_servicex import ServiceXSourceUpROOT
dataset_uproot = "user.kchoi:user.kchoi.ttHML_80fb_ttbar"
uproot_transformer_image = "sslhep/servicex_func_adl_uproot_transformer:issue6"
sx_dataset = ServiceXDataset(dataset_uproot, image=uproot_transformer_image)
ds = ServiceXSourceUpROOT(sx_dataset, "nominal")
data = (
ds.Select("lambda e: {
'lep_pt_1': e.lep_Pt_1,
'lep_pt_2': e.lep_Pt_2
}")
.value()
print(data)
It is possible to run on local files. This works well when testing or building out your code, but is horrible if you need to run on a large number of files. It is recommended to use this only with a single file. It is, for the most part, a drop-in replacement for the ServiceX
backend version.
First, you must install the local
variant of func_adl_servicex
. If you are using pip
, you can do the following:
pip install func_adl_servicex[local]
With that installed, the following will work:
from func_adl_servicex import SXLocalxAOD
dataset_xaod = "my_local_xaod.root"
ds = SXLocalxAOD(dataset_xaod)
data = (ds
.SelectMany('lambda e: (e.Jets("AntiKt4EMTopoJets"))')
.Where('lambda j: (j.pt()/1000)>30')
.Select('lambda j: j.pt()')
.AsAwkwardArray(["JetPt"])
.value()
)
print(data['JetPt'])
And replace SXLocalxAOD
with SXLocalCMSRun1AOD
for using CMS backend (and, of course, update the query).
PR's are welcome! Feel free to add an issue for new features or questions.
The master
branch is the most recent commits that both pass all tests and are slated for the next release. Releases are tagged. Modifications to any released versions are made off those tags.
This is for people working with the back-ends that run in servicex
.
This is the qastle
produced for an xAOD dataset:
(call EventDataset 'ServiceXDatasetSource')
(the actual dataset name is passed in the servicex
web API call.)
This is the qastle
produced for a ROOT flat file:
(call EventDataset 'ServiceXDatasetSource' 'tree_name')