Add TopCP transformer query

examples/TopCP_Dict.py

@@ -0,0 +1,20 @@
+from servicex import query, dataset, deliver
+
+
+spec = {
+    "Sample": [
+        {
+            "Name": "TopCP_Dict",
+            "Dataset": dataset.FileList(
+                [
+                    "root://eospublic.cern.ch//eos/opendata/atlas/rucio/data16_13TeV/DAOD_PHYSLITE.37019878._000001.pool.root.1",  # noqa: E501
+                    "root://eospublic.cern.ch//eos/opendata/atlas/rucio/data16_13TeV/DAOD_PHYSLITE.37019878._000002.pool.root.1",  # noqa: E501
+                    "root://eospublic.cern.ch//eos/opendata/atlas/rucio/data16_13TeV/DAOD_PHYSLITE.37019878._000003.pool.root.1",  # noqa: E501
+                ]
+            ),
+            "Query": query.TopCP(reco_yaml="reco.yaml", max_events=1000),
+        }
+    ]
+}
+
+print(f"Files: {deliver(spec)}")

examples/reco.yaml

@@ -0,0 +1,40 @@
+CommonServices:
+  systematicsHistogram: 'listOfSystematics'
+
+PileupReweighting: {}
+
+EventCleaning:
+    runEventCleaning: False
+    runGRL: False
+
+Electrons:
+  - containerName: 'AnaElectrons'
+    crackVeto: True
+    IFFClassification: {}
+    WorkingPoint:
+      - selectionName: 'loose'
+        identificationWP: 'TightLH'
+        isolationWP: 'NonIso'
+        noEffSF: True
+      - selectionName: 'tight'
+        identificationWP: 'TightLH'
+        isolationWP: 'Tight_VarRad'
+        noEffSF: True
+    PtEtaSelection:
+        minPt: 25000.0
+        maxEta: 2.47
+        useClusterEta: True
+
+# After configuring each container, many variables will be saved automatically.
+Output:
+  treeName: 'reco'
+  vars: []
+  metVars: []
+  containers:
+      # Format should follow: '<suffix>:<output container>'
+      el_: 'AnaElectrons'
+      '': 'EventInfo'
+  commands:
+    # Turn output branches on and off with 'enable' and 'disable'
+
+AddConfigBlocks: []

pyproject.toml

@@ -104,6 +104,7 @@ FuncADL_ATLASxAOD = "servicex.func_adl.func_adl_dataset:FuncADLQuery_ATLASxAOD"
 FuncADL_CMS = "servicex.func_adl.func_adl_dataset:FuncADLQuery_CMS"
 PythonFunction = "servicex.python_dataset:PythonFunction"
 UprootRaw = "servicex.uproot_raw.uproot_raw:UprootRawQuery"
+TopCP = "servicex.topcp.topcp:TopCPQuery"
 
 [project.entry-points.'servicex.dataset']
 Rucio = "servicex.dataset_identifier:RucioDatasetIdentifier"

servicex/topcp/topcp.py

@@ -0,0 +1,137 @@
+# Copyright (c) 2025, IRIS-HEP
+# All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+# * Redistributions of source code must retain the above copyright notice, this
+#   list of conditions and the following disclaimer.
+#
+# * 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.
+
+# pydantic 2 API
+
+import pydantic
+from pathlib import Path
+
+# from servicex.models import DocStringBaseModel
+from typing import Optional, Union
+from ..query_core import QueryStringGenerator
+
+
+@pydantic.dataclasses.dataclass
+class TopCPQuery(QueryStringGenerator):
+    yaml_tag = "!TopCP"
+    default_codegen = "topcp"
+
+    reco_yaml: Optional[Union[Path, str]] = None
+    """Path to the reco.yaml"""
+    parton_yaml: Optional[Union[Path, str]] = None
+    """Path to the parton.yaml"""
+    particle_yaml: Optional[Union[Path, str]] = None
+    """Path to the particle.yaml"""
+    max_events: Optional[int] = -1
+    """Number of events to process"""
+    parton: Optional[bool] = False
+    """Toggles the parton-level analysis"""
+    particle: Optional[bool] = False
+    """Toggles the particle-level analysis"""
+    no_reco: Optional[bool] = False
+    """Toggles off the detector-level analysis"""
+    no_systematics: Optional[bool] = True
+    """Toggles off the computation of systematics"""
+    no_filter: Optional[bool] = False
+    """Save all events regardless of analysis filters (still saves the decision)"""
+
+    @pydantic.model_validator(mode="after")
+    def check_reco_yaml(self):
+        if self.reco_yaml is None and self.no_reco is False:
+            raise ValueError("reco is enabled but reco.yaml is missing!")
+        return self
+
+    @pydantic.model_validator(mode="after")
+    def no_input_yaml(self):
+        if (
+            self.reco_yaml is None
+            and self.parton_yaml is None
+            and self.particle_yaml is None
+        ):
+            raise ValueError("No yaml provided!")
+        return self
+
+    @pydantic.model_validator(mode="after")
+    def no_parton_yaml(self):
+        if self.parton_yaml is None and self.parton is True:
+            raise ValueError("parton is set to True but no parton.yaml provided!")
+        return self
+
+    @pydantic.model_validator(mode="after")
+    def no_paricle_yaml(self):
+        if self.particle_yaml is None and self.particle is True:
+            raise ValueError("particle is set to True but no particle.yaml provided!")
+        return self
+
+    @pydantic.model_validator(mode="after")
+    def no_run(self):
+        if self.no_reco is True and self.particle is False and self.parton is False:
+            raise ValueError("Wrong configuration - no reco, no particle, no parton!")
+        return self
+
+    def generate_selection_string(self):
+        import yaml
+        import json
+
+        recoYaml = None
+        if self.reco_yaml:
+            with open(self.reco_yaml, "r") as reco_file:
+                recoYaml = yaml.safe_load(reco_file)
+
+        partonYaml = None
+        if self.parton_yaml:
+            with open(self.parton_yaml, "r") as parton_file:
+                partonYaml = yaml.safe_load(parton_file)
+
+        particleYaml = None
+        if self.particle_yaml:
+            with open(self.particle_yaml, "r") as particle_file:
+                particleYaml = yaml.safe_load(particle_file)
+
+        query = {
+            "RecoYAML": recoYaml,
+            "PartonYAML": partonYaml,
+            "ParticleYAML": particleYaml,
+            "NEvents": self.max_events,
+            "RunParton": self.parton,
+            "RunParticle": self.particle,
+            "NoReco": self.no_reco,
+            "RunSystematics": self.no_systematics,
+            "NoFilter": self.no_filter,
+        }
+
+        return json.dumps(query)
+
+    @classmethod
+    def from_yaml(cls, _, node):
+        code = node.value
+        import json
+
+        queries = json.loads(code)
+        q = cls(queries)
+        return q