diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json
new file mode 100644
index 00000000..1f92b0f9
--- /dev/null
+++ b/.devcontainer/devcontainer.json
@@ -0,0 +1,22 @@
+// For format details, see https://aka.ms/devcontainer.json. For config options, see the
+// README at: https://github.com/devcontainers/templates/tree/main/src/python
+{
+	"name": "Python 3",
+	// Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile
+	"image": "mcr.microsoft.com/devcontainers/python:1-3.11-bullseye"
+
+	// Features to add to the dev container. More info: https://containers.dev/features.
+	// "features": {},
+
+	// Use 'forwardPorts' to make a list of ports inside the container available locally.
+	// "forwardPorts": [],
+
+	// Use 'postCreateCommand' to run commands after the container is created.
+	// "postCreateCommand": "pip3 install --user -r requirements.txt",
+
+	// Configure tool-specific properties.
+	// "customizations": {},
+
+	// Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
+	// "remoteUser": "root"
+}
diff --git a/.pylintrc b/.pylintrc
index a71657a0..285a676e 100644
--- a/.pylintrc
+++ b/.pylintrc
@@ -360,7 +360,7 @@ indent-after-paren=4
 indent-string='    '
 
 # Maximum number of characters on a single line.
-max-line-length=140
+max-line-length=180
 
 # Maximum number of lines in a module.
 max-module-lines=1000
diff --git a/Pipfile b/Pipfile
new file mode 100644
index 00000000..2bd67e90
--- /dev/null
+++ b/Pipfile
@@ -0,0 +1,13 @@
+[[source]]
+url = "https://pypi.org/simple"
+verify_ssl = true
+name = "pypi"
+
+[packages]
+opensearch-benchmark = {file = ".", editable = true}
+
+[dev-packages]
+
+[requires]
+python_version = "3.11"
+python_full_version = "3.11.11"
diff --git a/Pipfile.lock b/Pipfile.lock
new file mode 100644
index 00000000..bb3bb78c
--- /dev/null
+++ b/Pipfile.lock
@@ -0,0 +1,1392 @@
+{
+    "_meta": {
+        "hash": {
+            "sha256": "e1a1134afb3a24381a238ccf58622d1e6dde3ffe2614fe28fb158a2114c071d9"
+        },
+        "pipfile-spec": 6,
+        "requires": {
+            "python_full_version": "3.11.11",
+            "python_version": "3.11"
+        },
+        "sources": [
+            {
+                "name": "pypi",
+                "url": "https://pypi.org/simple",
+                "verify_ssl": true
+            }
+        ]
+    },
+    "default": {
+        "aiohappyeyeballs": {
+            "hashes": [
+                "sha256:5fdd7d87889c63183afc18ce9271f9b0a7d32c2303e394468dd45d514a757745",
+                "sha256:a980909d50efcd44795c4afeca523296716d50cd756ddca6af8c65b996e27de8"
+            ],
+            "markers": "python_version >= '3.8'",
+            "version": "==2.4.4"
+        },
+        "aiohttp": {
+            "hashes": [
+                "sha256:012f176945af138abc10c4a48743327a92b4ca9adc7a0e078077cdb5dbab7be0",
+                "sha256:02c13415b5732fb6ee7ff64583a5e6ed1c57aa68f17d2bda79c04888dfdc2769",
+                "sha256:03b6002e20938fc6ee0918c81d9e776bebccc84690e2b03ed132331cca065ee5",
+                "sha256:04814571cb72d65a6899db6099e377ed00710bf2e3eafd2985166f2918beaf59",
+                "sha256:0580f2e12de2138f34debcd5d88894786453a76e98febaf3e8fe5db62d01c9bf",
+                "sha256:06a8e2ee1cbac16fe61e51e0b0c269400e781b13bcfc33f5425912391a542985",
+                "sha256:076bc454a7e6fd646bc82ea7f98296be0b1219b5e3ef8a488afbdd8e81fbac50",
+                "sha256:0c9527819b29cd2b9f52033e7fb9ff08073df49b4799c89cb5754624ecd98299",
+                "sha256:0dc49f42422163efb7e6f1df2636fe3db72713f6cd94688e339dbe33fe06d61d",
+                "sha256:14cdb5a9570be5a04eec2ace174a48ae85833c2aadc86de68f55541f66ce42ab",
+                "sha256:15fccaf62a4889527539ecb86834084ecf6e9ea70588efde86e8bc775e0e7542",
+                "sha256:24213ba85a419103e641e55c27dc7ff03536c4873470c2478cce3311ba1eee7b",
+                "sha256:31d5093d3acd02b31c649d3a69bb072d539d4c7659b87caa4f6d2bcf57c2fa2b",
+                "sha256:3691ed7726fef54e928fe26344d930c0c8575bc968c3e239c2e1a04bd8cf7838",
+                "sha256:386fbe79863eb564e9f3615b959e28b222259da0c48fd1be5929ac838bc65683",
+                "sha256:3bbbfff4c679c64e6e23cb213f57cc2c9165c9a65d63717108a644eb5a7398df",
+                "sha256:3de34936eb1a647aa919655ff8d38b618e9f6b7f250cc19a57a4bf7fd2062b6d",
+                "sha256:40d1c7a7f750b5648642586ba7206999650208dbe5afbcc5284bcec6579c9b91",
+                "sha256:44224d815853962f48fe124748227773acd9686eba6dc102578defd6fc99e8d9",
+                "sha256:47ad15a65fb41c570cd0ad9a9ff8012489e68176e7207ec7b82a0940dddfd8be",
+                "sha256:482cafb7dc886bebeb6c9ba7925e03591a62ab34298ee70d3dd47ba966370d2c",
+                "sha256:49c7dbbc1a559ae14fc48387a115b7d4bbc84b4a2c3b9299c31696953c2a5219",
+                "sha256:4b2c7ac59c5698a7a8207ba72d9e9c15b0fc484a560be0788b31312c2c5504e4",
+                "sha256:4cca22a61b7fe45da8fc73c3443150c3608750bbe27641fc7558ec5117b27fdf",
+                "sha256:4cfce37f31f20800a6a6620ce2cdd6737b82e42e06e6e9bd1b36f546feb3c44f",
+                "sha256:502a1464ccbc800b4b1995b302efaf426e8763fadf185e933c2931df7db9a199",
+                "sha256:53bf2097e05c2accc166c142a2090e4c6fd86581bde3fd9b2d3f9e93dda66ac1",
+                "sha256:593c114a2221444f30749cc5e5f4012488f56bd14de2af44fe23e1e9894a9c60",
+                "sha256:5d6958671b296febe7f5f859bea581a21c1d05430d1bbdcf2b393599b1cdce77",
+                "sha256:5ef359ebc6949e3a34c65ce20230fae70920714367c63afd80ea0c2702902ccf",
+                "sha256:613e5169f8ae77b1933e42e418a95931fb4867b2991fc311430b15901ed67079",
+                "sha256:61b9bae80ed1f338c42f57c16918853dc51775fb5cb61da70d590de14d8b5fb4",
+                "sha256:6362cc6c23c08d18ddbf0e8c4d5159b5df74fea1a5278ff4f2c79aed3f4e9f46",
+                "sha256:65a96e3e03300b41f261bbfd40dfdbf1c301e87eab7cd61c054b1f2e7c89b9e8",
+                "sha256:65e55ca7debae8faaffee0ebb4b47a51b4075f01e9b641c31e554fd376595c6c",
+                "sha256:68386d78743e6570f054fe7949d6cb37ef2b672b4d3405ce91fafa996f7d9b4d",
+                "sha256:68ff6f48b51bd78ea92b31079817aff539f6c8fc80b6b8d6ca347d7c02384e33",
+                "sha256:6ab29b8a0beb6f8eaf1e5049252cfe74adbaafd39ba91e10f18caeb0e99ffb34",
+                "sha256:77ae58586930ee6b2b6f696c82cf8e78c8016ec4795c53e36718365f6959dc82",
+                "sha256:77c4aa15a89847b9891abf97f3d4048f3c2d667e00f8a623c89ad2dccee6771b",
+                "sha256:78153314f26d5abef3239b4a9af20c229c6f3ecb97d4c1c01b22c4f87669820c",
+                "sha256:7852bbcb4d0d2f0c4d583f40c3bc750ee033265d80598d0f9cb6f372baa6b836",
+                "sha256:7e97d622cb083e86f18317282084bc9fbf261801b0192c34fe4b1febd9f7ae69",
+                "sha256:7f3dc0e330575f5b134918976a645e79adf333c0a1439dcf6899a80776c9ab39",
+                "sha256:80886dac673ceaef499de2f393fc80bb4481a129e6cb29e624a12e3296cc088f",
+                "sha256:811f23b3351ca532af598405db1093f018edf81368e689d1b508c57dcc6b6a32",
+                "sha256:86a5dfcc39309470bd7b68c591d84056d195428d5d2e0b5ccadfbaf25b026ebc",
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+                "sha256:8cc5203b817b748adccb07f36390feb730b1bc5f56683445bfe924fc270b8816",
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+                "sha256:98f5635f7b74bcd4f6f72fcd85bea2154b323a9f05226a80bc7398d0c90763b0",
+                "sha256:99b7920e7165be5a9e9a3a7f1b680f06f68ff0d0328ff4079e5163990d046767",
+                "sha256:9bca390cb247dbfaec3c664326e034ef23882c3f3bfa5fbf0b56cad0320aaca5",
+                "sha256:9e2e576caec5c6a6b93f41626c9c02fc87cd91538b81a3670b2e04452a63def6",
+                "sha256:9ef405356ba989fb57f84cac66f7b0260772836191ccefbb987f414bcd2979d9",
+                "sha256:a55d2ad345684e7c3dd2c20d2f9572e9e1d5446d57200ff630e6ede7612e307f",
+                "sha256:ab7485222db0959a87fbe8125e233b5a6f01f4400785b36e8a7878170d8c3138",
+                "sha256:b1fc6b45010a8d0ff9e88f9f2418c6fd408c99c211257334aff41597ebece42e",
+                "sha256:b78f053a7ecfc35f0451d961dacdc671f4bcbc2f58241a7c820e9d82559844cf",
+                "sha256:b99acd4730ad1b196bfb03ee0803e4adac371ae8efa7e1cbc820200fc5ded109",
+                "sha256:be2b516f56ea883a3e14dda17059716593526e10fb6303189aaf5503937db408",
+                "sha256:beb39a6d60a709ae3fb3516a1581777e7e8b76933bb88c8f4420d875bb0267c6",
+                "sha256:bf3d1a519a324af764a46da4115bdbd566b3c73fb793ffb97f9111dbc684fc4d",
+                "sha256:c49a76c1038c2dd116fa443eba26bbb8e6c37e924e2513574856de3b6516be99",
+                "sha256:c5532f0441fc09c119e1dca18fbc0687e64fbeb45aa4d6a87211ceaee50a74c4",
+                "sha256:c6b9e6d7e41656d78e37ce754813fa44b455c3d0d0dced2a047def7dc5570b74",
+                "sha256:c87bf31b7fdab94ae3adbe4a48e711bfc5f89d21cf4c197e75561def39e223bc",
+                "sha256:cbad88a61fa743c5d283ad501b01c153820734118b65aee2bd7dbb735475ce0d",
+                "sha256:cf14627232dfa8730453752e9cdc210966490992234d77ff90bc8dc0dce361d5",
+                "sha256:db1d0b28fcb7f1d35600150c3e4b490775251dea70f894bf15c678fdd84eda6a",
+                "sha256:ddf5f7d877615f6a1e75971bfa5ac88609af3b74796ff3e06879e8422729fd01",
+                "sha256:e44a9a3c053b90c6f09b1bb4edd880959f5328cf63052503f892c41ea786d99f",
+                "sha256:efb15a17a12497685304b2d976cb4939e55137df7b09fa53f1b6a023f01fcb4e",
+                "sha256:fbbaea811a2bba171197b08eea288b9402faa2bab2ba0858eecdd0a4105753a3"
+            ],
+            "markers": "python_version >= '3.9'",
+            "version": "==3.11.10"
+        },
+        "aiosignal": {
+            "hashes": [
+                "sha256:45cde58e409a301715980c2b01d0c28bdde3770d8290b5eb2173759d9acb31a5",
+                "sha256:a8c255c66fafb1e499c9351d0bf32ff2d8a0321595ebac3b93713656d2436f54"
+            ],
+            "markers": "python_version >= '3.9'",
+            "version": "==1.3.2"
+        },
+        "attrs": {
+            "hashes": [
+                "sha256:8f5c07333d543103541ba7be0e2ce16eeee8130cb0b3f9238ab904ce1e85baff",
+                "sha256:ac96cd038792094f438ad1f6ff80837353805ac950cd2aa0e0625ef19850c308"
+            ],
+            "markers": "python_version >= '3.8'",
+            "version": "==24.3.0"
+        },
+        "boto3": {
+            "hashes": [
+                "sha256:2bbaf1551b1ed55770cb437d7040f1abe6742601103695057b30ce6328eef286",
+                "sha256:c422b68ae76959b9e23b77eb79e41c3483332f7e1de918d2b083c456d8cf234c"
+            ],
+            "markers": "python_version >= '3.8'",
+            "version": "==1.35.82"
+        },
+        "botocore": {
+            "hashes": [
+                "sha256:78dd7bf8f49616d00073698d7bbaf5a115208fe730b7b7afae4456adddb3552e",
+                "sha256:e43b97d8cbf19d35ce3a177f144bd97cc370f0a67d0984c7d7cf105ac198748f"
+            ],
+            "markers": "python_version >= '3.8'",
+            "version": "==1.35.82"
+        },
+        "cachetools": {
+            "hashes": [
+                "sha256:02134e8439cdc2ffb62023ce1debca2944c3f289d66bb17ead3ab3dede74b292",
+                "sha256:2cc24fb4cbe39633fb7badd9db9ca6295d766d9c2995f245725a46715d050f2a"
+            ],
+            "markers": "python_version >= '3.7'",
+            "version": "==5.5.0"
+        },
+        "certifi": {
+            "hashes": [
+                "sha256:1275f7a45be9464efc1173084eaa30f866fe2e47d389406136d332ed4967ec56",
+                "sha256:b650d30f370c2b724812bee08008be0c4163b163ddaec3f2546c1caf65f191db"
+            ],
+            "markers": "python_version >= '3.6'",
+            "version": "==2024.12.14"
+        },
+        "charset-normalizer": {
+            "hashes": [
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+                "sha256:43193c5cda5d612f247172016c4bb71251c784d7a4d9314677186a838ad34858",
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+                "sha256:fe3b385d996ee0822fd46528d9f0443b880d4d05528fd26a9119a54ec3f91c69"
+            ],
+            "markers": "python_version >= '3.8'",
+            "version": "==0.23.0"
+        }
+    },
+    "develop": {}
+}
diff --git a/osbenchmark/aggregator.py b/osbenchmark/aggregator.py
index 016d90f4..b79f8c47 100644
--- a/osbenchmark/aggregator.py
+++ b/osbenchmark/aggregator.py
@@ -3,12 +3,12 @@
 from typing import Any, Dict, List, Union
 import uuid
 
-from osbenchmark.metrics import FileTestExecutionStore
+from osbenchmark.metrics import FileTestExecutionStore, TestExecution
 from osbenchmark import metrics, workload, config
 from osbenchmark.utils import io as rio
 
 class Aggregator:
-    def __init__(self, cfg, test_executions_dict, args):
+    def __init__(self, cfg, test_executions_dict, args) -> None:
         self.config = cfg
         self.args = args
         self.test_executions = test_executions_dict
@@ -21,69 +21,72 @@ def __init__(self, cfg, test_executions_dict, args):
         self.test_procedure_name = None
         self.loaded_workload = None
 
-    def count_iterations_for_each_op(self, test_execution) -> None:
-        matching_test_procedure = next((tp for tp in self.loaded_workload.test_procedures if tp.name == self.test_procedure_name), None)
+    def count_iterations_for_each_op(self, test_execution: TestExecution) -> None:
+        """Count iterations for each operation in the test execution"""
         workload_params = test_execution.workload_params if test_execution.workload_params else {}
-
         test_execution_id = test_execution.test_execution_id
         self.accumulated_iterations[test_execution_id] = {}
 
-        if matching_test_procedure:
-            for task in matching_test_procedure.schedule:
-                task_name = task.name
-                task_name_iterations = f"{task_name}_iterations"
-                if task_name_iterations in workload_params:
-                    iterations = int(workload_params[task_name_iterations])
-                else:
-                    iterations = task.iterations or 1
-                self.accumulated_iterations[test_execution_id][task_name] = iterations
-        else:
-            raise ValueError(f"Test procedure '{self.test_procedure_name}' not found in the loaded workload.")
+        for task in self.loaded_workload.find_test_procedure_or_default(self.test_procedure_name).schedule:
+            task_name = task.name
+            task_name_iterations = f"{task_name}_iterations"
+            iterations = int(workload_params.get(task_name_iterations, task.iterations or 1))
+            self.accumulated_iterations[test_execution_id][task_name] = iterations
 
-    def accumulate_results(self, test_execution: Any) -> None:
-        for item in test_execution.results.get("op_metrics", []):
-            task = item.get("task", "")
+    def accumulate_results(self, test_execution: TestExecution) -> None:
+        """Accumulate results from a single test execution"""
+        for operation_metric in test_execution.results.get("op_metrics", []):
+            task = operation_metric.get("task", "")
             self.accumulated_results.setdefault(task, {})
             for metric in self.metrics:
                 self.accumulated_results[task].setdefault(metric, [])
-                self.accumulated_results[task][metric].append(item.get(metric))
+                self.accumulated_results[task][metric].append(operation_metric.get(metric))
 
     def aggregate_json_by_key(self, key_path: Union[str, List[str]]) -> Any:
-        all_jsons = [self.test_store.find_by_test_execution_id(id).results for id in self.test_executions.keys()]
-
-        # retrieve nested value from a dictionary given a key path
-        def get_nested_value(obj: Dict[str, Any], path: List[str]) -> Any:
+        """
+        Aggregates JSON results across multiple test executions using a specified key path.
+        Handles nested dictionary structures and calculates averages for numeric values
+        """
+        all_json_results = [self.test_store.find_by_test_execution_id(id).results for id in self.test_executions.keys()]
+
+        def get_nested_value(json_data: Dict[str, Any], path: List[str]) -> Any:
+            """
+            Retrieves a value from a nested dictionary structure using a path of keys.
+            """
             for key in path:
-                if isinstance(obj, dict):
-                    obj = obj.get(key, {})
-                elif isinstance(obj, list) and key.isdigit():
-                    obj = obj[int(key)] if int(key) < len(obj) else {}
+                if isinstance(json_data, dict):
+                    json_data = json_data.get(key, {})
+                elif isinstance(json_data, list) and key.isdigit():
+                    json_data = json_data[int(key)] if int(key) < len(json_data) else {}
                 else:
                     return None
-            return obj
+            return json_data
 
-        def aggregate_helper(objects: List[Any]) -> Any:
-            if not objects:
+        def aggregate_json_elements(json_elements: List[Any]) -> Any:
+            if not json_elements:
                 return None
-            if all(isinstance(obj, (int, float)) for obj in objects):
-                avg = sum(objects) / len(objects)
-                return avg
-            if all(isinstance(obj, dict) for obj in objects):
-                keys = set().union(*objects)
-                return {key: aggregate_helper([obj.get(key) for obj in objects]) for key in keys}
-            if all(isinstance(obj, list) for obj in objects):
-                max_length = max(len(obj) for obj in objects)
-                return [aggregate_helper([obj[i] if i < len(obj) else None for obj in objects]) for i in range(max_length)]
-            return next((obj for obj in objects if obj is not None), None)
+            # If all elements are numbers, calculate the average
+            if all(isinstance(obj, (int, float)) for obj in json_elements):
+                return sum(json_elements) / len(json_elements)
+            # If all elements are dictionaries, recursively aggregate their values
+            if all(isinstance(obj, dict) for obj in json_elements):
+                keys = set().union(*json_elements)
+                return {key: aggregate_json_elements([obj.get(key) for obj in json_elements]) for key in keys}
+            # If all elements are lists, recursively aggregate corresponding elements
+            if all(isinstance(obj, list) for obj in json_elements):
+                max_length = max(len(obj) for obj in json_elements)
+                return [aggregate_json_elements([obj[i] if i < len(obj) else None for obj in json_elements]) for i in range(max_length)]
+            # If elements are of mixed types, return the first non-None value
+            return next((obj for obj in json_elements if obj is not None), None)
 
         if isinstance(key_path, str):
             key_path = key_path.split('.')
 
-        values = [get_nested_value(json, key_path) for json in all_jsons]
-        return aggregate_helper(values)
+        nested_values = [get_nested_value(json_result, key_path) for json_result in all_json_results]
+        return aggregate_json_elements(nested_values)
 
-    def build_aggregated_results(self):
-        test_exe = self.test_store.find_by_test_execution_id(list(self.test_executions.keys())[0])
+    def build_aggregated_results_dict(self) -> Dict[str, Any]:
+        """Builds a dictionary of aggregated metrics from all test executions"""
         aggregated_results = {
             "op_metrics": [],
             "correctness_metrics": self.aggregate_json_by_key("correctness_metrics"),
@@ -147,8 +150,30 @@ def build_aggregated_results(self):
 
             aggregated_results["op_metrics"].append(op_metric)
 
-        # extract the necessary data from the first test execution, since the configurations should be identical for all test executions
+        return aggregated_results
+
+    def update_config_object(self, test_execution: TestExecution) -> None:
+        """
+        Updates the configuration object with values from a test execution.
+        Uses the first test execution as reference since configurations should be identical
+        """
         current_timestamp = self.config.opts("system", "time.start")
+        self.config.add(config.Scope.applicationOverride, "builder",
+                        "provision_config_instance.names", test_execution.provision_config_instance)
+        self.config.add(config.Scope.applicationOverride, "system",
+                        "env.name", test_execution.environment_name)
+        self.config.add(config.Scope.applicationOverride, "system", "time.start", current_timestamp)
+        self.config.add(config.Scope.applicationOverride, "test_execution", "pipeline", test_execution.pipeline)
+        self.config.add(config.Scope.applicationOverride, "workload", "params", test_execution.workload_params)
+        self.config.add(config.Scope.applicationOverride, "builder",
+                        "provision_config_instance.params", test_execution.provision_config_instance_params)
+        self.config.add(config.Scope.applicationOverride, "builder", "plugin.params", test_execution.plugin_params)
+        self.config.add(config.Scope.applicationOverride, "workload", "latency.percentiles", test_execution.latency_percentiles)
+        self.config.add(config.Scope.applicationOverride, "workload", "throughput.percentiles", test_execution.throughput_percentiles)
+
+    def build_aggregated_results(self) -> TestExecution:
+        test_exe = self.test_store.find_by_test_execution_id(list(self.test_executions.keys())[0])
+        aggregated_results = self.build_aggregated_results_dict()
 
         if hasattr(self.args, 'results_file') and self.args.results_file != "":
             normalized_results_file = rio.normalize_path(self.args.results_file, self.cwd)
@@ -165,19 +190,7 @@ def build_aggregated_results(self):
 
         print("Aggregate test execution ID: ", test_execution_id)
 
-        # add values to the configuration object
-        self.config.add(config.Scope.applicationOverride, "builder",
-                        "provision_config_instance.names", test_exe.provision_config_instance)
-        self.config.add(config.Scope.applicationOverride, "system",
-                        "env.name", test_exe.environment_name)
-        self.config.add(config.Scope.applicationOverride, "system", "time.start", current_timestamp)
-        self.config.add(config.Scope.applicationOverride, "test_execution", "pipeline", test_exe.pipeline)
-        self.config.add(config.Scope.applicationOverride, "workload", "params", test_exe.workload_params)
-        self.config.add(config.Scope.applicationOverride, "builder",
-                        "provision_config_instance.params", test_exe.provision_config_instance_params)
-        self.config.add(config.Scope.applicationOverride, "builder", "plugin.params", test_exe.plugin_params)
-        self.config.add(config.Scope.applicationOverride, "workload", "latency.percentiles", test_exe.latency_percentiles)
-        self.config.add(config.Scope.applicationOverride, "workload", "throughput.percentiles", test_exe.throughput_percentiles)
+        self.update_config_object(test_exe)
 
         loaded_workload = workload.load_workload(self.config)
         test_procedure_object = loaded_workload.find_test_procedure_or_default(self.test_procedure_name)
@@ -223,7 +236,7 @@ def calculate_weighted_average(self, task_metrics: Dict[str, List[Any]], task_na
 
         return weighted_metrics
 
-    def calculate_rsd(self, values: List[Union[int, float]], metric_name: str):
+    def calculate_rsd(self, values: List[Union[int, float]], metric_name: str) -> Union[float, str]:
         if not values:
             raise ValueError(f"Cannot calculate RSD for metric '{metric_name}': empty list of values")
         if len(values) == 1:
diff --git a/osbenchmark/worker_coordinator/worker_coordinator.py b/osbenchmark/worker_coordinator/worker_coordinator.py
index d08242a9..73001731 100644
--- a/osbenchmark/worker_coordinator/worker_coordinator.py
+++ b/osbenchmark/worker_coordinator/worker_coordinator.py
@@ -52,6 +52,8 @@
 # Messages sent between worker_coordinators
 #
 ##################################
+
+
 class PrepareBenchmark:
     """
     Initiates preparation steps for a benchmark. The benchmark should only be started after StartBenchmark is sent.
@@ -75,6 +77,7 @@ class PrepareWorkload:
     Initiates preparation of a workload.
 
     """
+
     def __init__(self, cfg, workload):
         """
         :param cfg: Benchmark internal configuration object.
@@ -221,22 +224,27 @@ def __init__(self):
         self.cluster_details = None
 
     def receiveMsg_PoisonMessage(self, poisonmsg, sender):
-        self.logger.error("Main worker_coordinator received a fatal indication from load generator (%s). Shutting down.", poisonmsg.details)
+        self.logger.error(
+            "Main worker_coordinator received a fatal indication from load generator (%s). Shutting down.", poisonmsg.details)
         self.coordinator.close()
-        self.send(self.start_sender, actor.BenchmarkFailure("Fatal workload or load generator indication", poisonmsg.details))
+        self.send(self.start_sender, actor.BenchmarkFailure(
+            "Fatal workload or load generator indication", poisonmsg.details))
 
     def receiveMsg_BenchmarkFailure(self, msg, sender):
-        self.logger.error("Main worker_coordinator received a fatal exception from load generator. Shutting down.")
+        self.logger.error(
+            "Main worker_coordinator received a fatal exception from load generator. Shutting down.")
         self.coordinator.close()
         self.send(self.start_sender, msg)
 
     def receiveMsg_BenchmarkCancelled(self, msg, sender):
-        self.logger.info("Main worker_coordinator received a notification that the benchmark has been cancelled.")
+        self.logger.info(
+            "Main worker_coordinator received a notification that the benchmark has been cancelled.")
         self.coordinator.close()
         self.send(self.start_sender, msg)
 
     def receiveMsg_ActorExitRequest(self, msg, sender):
-        self.logger.info("Main worker_coordinator received ActorExitRequest and will terminate all load generators.")
+        self.logger.info(
+            "Main worker_coordinator received ActorExitRequest and will terminate all load generators.")
         self.status = "exiting"
 
     def receiveMsg_ChildActorExited(self, msg, sender):
@@ -246,13 +254,16 @@ def receiveMsg_ChildActorExited(self, msg, sender):
             if self.status == "exiting":
                 self.logger.info("Worker [%d] has exited.", worker_index)
             else:
-                self.logger.error("Worker [%d] has exited prematurely. Aborting benchmark.", worker_index)
-                self.send(self.start_sender, actor.BenchmarkFailure("Worker [{}] has exited prematurely.".format(worker_index)))
+                self.logger.error(
+                    "Worker [%d] has exited prematurely. Aborting benchmark.", worker_index)
+                self.send(self.start_sender, actor.BenchmarkFailure(
+                    "Worker [{}] has exited prematurely.".format(worker_index)))
         else:
             self.logger.info("A workload preparator has exited.")
 
     def receiveUnrecognizedMessage(self, msg, sender):
-        self.logger.info("Main worker_coordinator received unknown message [%s] (ignoring).", str(msg))
+        self.logger.info(
+            "Main worker_coordinator received unknown message [%s] (ignoring).", str(msg))
 
     @actor.no_retry("worker_coordinator")  # pylint: disable=no-value-for-parameter
     def receiveMsg_PrepareBenchmark(self, msg, sender):
@@ -264,7 +275,8 @@ def receiveMsg_PrepareBenchmark(self, msg, sender):
     def receiveMsg_StartBenchmark(self, msg, sender):
         self.start_sender = sender
         self.coordinator.start_benchmark()
-        self.wakeupAfter(datetime.timedelta(seconds=WorkerCoordinatorActor.WAKEUP_INTERVAL_SECONDS))
+        self.wakeupAfter(datetime.timedelta(
+            seconds=WorkerCoordinatorActor.WAKEUP_INTERVAL_SECONDS))
 
     @actor.no_retry("worker_coordinator")  # pylint: disable=no-value-for-parameter
     def receiveMsg_WorkloadPrepared(self, msg, sender):
@@ -273,7 +285,8 @@ def receiveMsg_WorkloadPrepared(self, msg, sender):
 
     @actor.no_retry("worker_coordinator")  # pylint: disable=no-value-for-parameter
     def receiveMsg_JoinPointReached(self, msg, sender):
-        self.coordinator.joinpoint_reached(msg.worker_id, msg.worker_timestamp, msg.task)
+        self.coordinator.joinpoint_reached(
+            msg.worker_id, msg.worker_timestamp, msg.task)
 
     @actor.no_retry("worker_coordinator")  # pylint: disable=no-value-for-parameter
     def receiveMsg_UpdateSamples(self, msg, sender):
@@ -289,13 +302,15 @@ def receiveMsg_WakeupMessage(self, msg, sender):
                 self.post_process_timer = 0
                 self.coordinator.post_process_samples()
             self.coordinator.update_progress_message()
-            self.wakeupAfter(datetime.timedelta(seconds=WorkerCoordinatorActor.WAKEUP_INTERVAL_SECONDS))
+            self.wakeupAfter(datetime.timedelta(
+                seconds=WorkerCoordinatorActor.WAKEUP_INTERVAL_SECONDS))
 
     def create_client(self, host):
         return self.createActor(Worker, targetActorRequirements=self._requirements(host))
 
     def start_worker(self, worker_coordinator, worker_id, cfg, workload, allocations):
-        self.send(worker_coordinator, StartWorker(worker_id, cfg, workload, allocations))
+        self.send(worker_coordinator, StartWorker(
+            worker_id, cfg, workload, allocations))
 
     def drive_at(self, worker_coordinator, client_start_timestamp):
         self.send(worker_coordinator, Drive(client_start_timestamp))
@@ -305,10 +320,12 @@ def complete_current_task(self, worker_coordinator):
 
     def on_task_finished(self, metrics, next_task_scheduled_in):
         if next_task_scheduled_in > 0:
-            self.wakeupAfter(datetime.timedelta(seconds=next_task_scheduled_in), payload=WorkerCoordinatorActor.RESET_RELATIVE_TIME_MARKER)
+            self.wakeupAfter(datetime.timedelta(seconds=next_task_scheduled_in),
+                             payload=WorkerCoordinatorActor.RESET_RELATIVE_TIME_MARKER)
         else:
             self.coordinator.reset_relative_time()
-        self.send(self.start_sender, TaskFinished(metrics, next_task_scheduled_in))
+        self.send(self.start_sender, TaskFinished(
+            metrics, next_task_scheduled_in))
 
     def _requirements(self, host):
         if host == "localhost":
@@ -320,7 +337,8 @@ def on_cluster_details_retrieved(self, cluster_details):
         self.cluster_details = cluster_details
 
     def prepare_workload(self, hosts, cfg, workload):
-        self.logger.info("Starting prepare workload process on hosts [%s]", hosts)
+        self.logger.info(
+            "Starting prepare workload process on hosts [%s]", hosts)
         self.children = [self._create_workload_preparator(h) for h in hosts]
         msg = PrepareWorkload(cfg, workload)
         for child in self.children:
@@ -330,7 +348,8 @@ def _create_workload_preparator(self, host):
         return self.createActor(WorkloadPreparationActor, targetActorRequirements=self._requirements(host))
 
     def _after_workload_prepared(self):
-        cluster_version = self.cluster_details["version"] if self.cluster_details else {}
+        cluster_version = self.cluster_details["version"] if self.cluster_details else {
+        }
         for child in self.children:
             self.send(child, thespian.actors.ActorExitRequest())
         self.children = []
@@ -354,7 +373,8 @@ def load_local_config(coordinator_config):
         "telemetry"
     ])
     # set root path (normally done by the main entry point)
-    cfg.add(config.Scope.application, "node", "benchmark.root", paths.benchmark_root())
+    cfg.add(config.Scope.application, "node",
+            "benchmark.root", paths.benchmark_root())
     return cfg
 
 
@@ -362,6 +382,7 @@ class TaskExecutionActor(actor.BenchmarkActor):
     """
     This class should be used for long-running tasks, as it ensures they do not block the actor's messaging system
     """
+
     def __init__(self):
         super().__init__()
         self.pool = concurrent.futures.ThreadPoolExecutor(max_workers=1)
@@ -406,10 +427,12 @@ def receiveMsg_WakeupMessage(self, msg, sender):
         if self.executor_future is not None and self.executor_future.done():
             e = self.executor_future.exception(timeout=0)
             if e:
-                self.logger.exception("Worker failed. Notifying parent...", exc_info=e)
+                self.logger.exception(
+                    "Worker failed. Notifying parent...", exc_info=e)
                 # the exception might be user-defined and not be on the load path of the original sender. Hence, it
                 # cannot be deserialized on the receiver so we convert it here to a plain string.
-                self.send(self.parent, actor.BenchmarkFailure("Error in task executor", str(e)))
+                self.send(self.parent, actor.BenchmarkFailure(
+                    "Error in task executor", str(e)))
             else:
                 self.executor_future = None
                 self.send(self.parent, ReadyForWork())
@@ -420,6 +443,7 @@ def receiveMsg_BenchmarkFailure(self, msg, sender):
         # sent by our no_retry infrastructure; forward to master
         self.send(self.parent, msg)
 
+
 class WorkloadPreparationActor(actor.BenchmarkActor):
     class Status(Enum):
         INITIALIZING = "initializing"
@@ -439,8 +463,10 @@ def __init__(self):
         self.workload = None
 
     def receiveMsg_PoisonMessage(self, poisonmsg, sender):
-        self.logger.error("Workload Preparator received a fatal indication from a load generator (%s). Shutting down.", poisonmsg.details)
-        self.send(self.original_sender, actor.BenchmarkFailure("Fatal workload preparation indication", poisonmsg.details))
+        self.logger.error(
+            "Workload Preparator received a fatal indication from a load generator (%s). Shutting down.", poisonmsg.details)
+        self.send(self.original_sender, actor.BenchmarkFailure(
+            "Fatal workload preparation indication", poisonmsg.details))
 
     @actor.no_retry("workload preparator")  # pylint: disable=no-value-for-parameter
     def receiveMsg_ActorExitRequest(self, msg, sender):
@@ -462,14 +488,16 @@ def receiveMsg_PrepareWorkload(self, msg, sender):
         tpr = WorkloadProcessorRegistry(self.cfg)
         self.workload = msg.workload
         self.logger.info("Preparing workload [%s]", self.workload.name)
-        self.logger.info("Reloading workload [%s] to ensure plugins are up-to-date.", self.workload.name)
+        self.logger.info(
+            "Reloading workload [%s] to ensure plugins are up-to-date.", self.workload.name)
         # the workload might have been loaded on a different machine (the coordinator machine) so we force a workload
         # update to ensure we use the latest version of plugins.
         load_workload(self.cfg)
         load_workload_plugins(self.cfg, self.workload.name, register_workload_processor=tpr.register_workload_processor,
-                           force_update=True)
+                              force_update=True)
         # we expect on_prepare_workload can take a long time. seed a queue of tasks and delegate to child workers
-        self.children = [self._create_task_executor() for _ in range(num_cores(self.cfg))]
+        self.children = [self._create_task_executor()
+                         for _ in range(num_cores(self.cfg))]
         for processor in tpr.processors:
             self.processors.put(processor)
         self._seed_tasks(self.processors.get())
@@ -498,7 +526,8 @@ def receiveMsg_ReadyForWork(self, msg, sender):
         else:
             next_task = None
         new_msg = DoTask(next_task, self.cfg)
-        self.logger.debug("Workload Preparator sending %s to %s", vars(new_msg), sender)
+        self.logger.debug(
+            "Workload Preparator sending %s to %s", vars(new_msg), sender)
         self.send(sender, new_msg)
 
     @actor.no_retry("workload preparator")  # pylint: disable=no-value-for-parameter
@@ -509,7 +538,7 @@ def receiveMsg_WorkerIdle(self, msg, sender):
 
 def num_cores(cfg):
     return int(cfg.opts("system", "available.cores", mandatory=False,
-                         default_value=multiprocessing.cpu_count()))
+                        default_value=multiprocessing.cpu_count()))
 
 
 class WorkerCoordinator:
@@ -555,11 +584,13 @@ def create_os_clients(self):
         all_hosts = self.config.opts("client", "hosts").all_hosts
         opensearch = {}
         for cluster_name, cluster_hosts in all_hosts.items():
-            all_client_options = self.config.opts("client", "options").all_client_options
+            all_client_options = self.config.opts(
+                "client", "options").all_client_options
             cluster_client_options = dict(all_client_options[cluster_name])
             # Use retries to avoid aborts on long living connections for telemetry devices
             cluster_client_options["retry-on-timeout"] = True
-            opensearch[cluster_name] = self.os_client_factory(cluster_hosts, cluster_client_options).create()
+            opensearch[cluster_name] = self.os_client_factory(
+                cluster_hosts, cluster_client_options).create()
         return opensearch
 
     def prepare_telemetry(self, opensearch, enable):
@@ -571,18 +602,27 @@ def prepare_telemetry(self, opensearch, enable):
 
         if enable:
             devices = [
-                telemetry.NodeStats(telemetry_params, opensearch, self.metrics_store),
-                telemetry.ExternalEnvironmentInfo(os_default, self.metrics_store),
-                telemetry.ClusterEnvironmentInfo(os_default, self.metrics_store),
+                telemetry.NodeStats(
+                    telemetry_params, opensearch, self.metrics_store),
+                telemetry.ExternalEnvironmentInfo(
+                    os_default, self.metrics_store),
+                telemetry.ClusterEnvironmentInfo(
+                    os_default, self.metrics_store),
                 telemetry.JvmStatsSummary(os_default, self.metrics_store),
                 telemetry.IndexStats(os_default, self.metrics_store),
-                telemetry.MlBucketProcessingTime(os_default, self.metrics_store),
+                telemetry.MlBucketProcessingTime(
+                    os_default, self.metrics_store),
                 telemetry.SegmentStats(log_root, os_default),
-                telemetry.CcrStats(telemetry_params, opensearch, self.metrics_store),
-                telemetry.RecoveryStats(telemetry_params, opensearch, self.metrics_store),
-                telemetry.TransformStats(telemetry_params, opensearch, self.metrics_store),
-                telemetry.SearchableSnapshotsStats(telemetry_params, opensearch, self.metrics_store),
-                telemetry.SegmentReplicationStats(telemetry_params, opensearch, self.metrics_store)
+                telemetry.CcrStats(
+                    telemetry_params, opensearch, self.metrics_store),
+                telemetry.RecoveryStats(
+                    telemetry_params, opensearch, self.metrics_store),
+                telemetry.TransformStats(
+                    telemetry_params, opensearch, self.metrics_store),
+                telemetry.SearchableSnapshotsStats(
+                    telemetry_params, opensearch, self.metrics_store),
+                telemetry.SegmentReplicationStats(
+                    telemetry_params, opensearch, self.metrics_store)
             ]
         else:
             devices = []
@@ -594,20 +634,24 @@ def wait_for_rest_api(self, opensearch):
         if client.wait_for_rest_layer(os_default, max_attempts=40):
             self.logger.info("REST API is available.")
         else:
-            self.logger.error("REST API layer is not yet available. Stopping benchmark.")
-            raise exceptions.SystemSetupError("OpenSearch REST API layer is not available.")
+            self.logger.error(
+                "REST API layer is not yet available. Stopping benchmark.")
+            raise exceptions.SystemSetupError(
+                "OpenSearch REST API layer is not available.")
 
     def retrieve_cluster_info(self, opensearch):
         try:
             return opensearch["default"].info()
         except BaseException:
-            self.logger.exception("Could not retrieve cluster info on benchmark start")
+            self.logger.exception(
+                "Could not retrieve cluster info on benchmark start")
             return None
 
     def prepare_benchmark(self, t):
         self.workload = t
         self.test_procedure = select_test_procedure(self.config, self.workload)
-        self.quiet = self.config.opts("system", "quiet.mode", mandatory=False, default_value=False)
+        self.quiet = self.config.opts(
+            "system", "quiet.mode", mandatory=False, default_value=False)
         downsample_factor = int(self.config.opts(
             "results_publishing", "metrics.request.downsample.factor",
             mandatory=False, default_value=1))
@@ -623,15 +667,20 @@ def prepare_benchmark(self, t):
 
         os_clients = self.create_os_clients()
 
-        skip_rest_api_check = self.config.opts("builder", "skip.rest.api.check")
-        uses_static_responses = self.config.opts("client", "options").uses_static_responses
+        skip_rest_api_check = self.config.opts(
+            "builder", "skip.rest.api.check")
+        uses_static_responses = self.config.opts(
+            "client", "options").uses_static_responses
         if skip_rest_api_check:
-            self.logger.info("Skipping REST API check as requested explicitly.")
+            self.logger.info(
+                "Skipping REST API check as requested explicitly.")
         elif uses_static_responses:
-            self.logger.info("Skipping REST API check as static responses are used.")
+            self.logger.info(
+                "Skipping REST API check as static responses are used.")
         else:
             self.wait_for_rest_api(os_clients)
-            self.target.on_cluster_details_retrieved(self.retrieve_cluster_info(os_clients))
+            self.target.on_cluster_details_retrieved(
+                self.retrieve_cluster_info(os_clients))
 
         # Avoid issuing any requests to the target cluster when static responses are enabled. The results
         # are not useful and attempts to connect to a non-existing cluster just lead to exception traces in logs.
@@ -649,7 +698,8 @@ def prepare_benchmark(self, t):
 
             self.load_worker_coordinator_hosts.append(host_config)
 
-        self.target.prepare_workload([h["host"] for h in self.load_worker_coordinator_hosts], self.config, self.workload)
+        self.target.prepare_workload(
+            [h["host"] for h in self.load_worker_coordinator_hosts], self.config, self.workload)
 
     def start_benchmark(self):
         self.logger.info("Benchmark is about to start.")
@@ -660,29 +710,34 @@ def start_benchmark(self):
         self.logger.info("Cluster-level telemetry devices are now attached.")
         allocator = Allocator(self.test_procedure.schedule)
         self.allocations = allocator.allocations
-        self.number_of_steps = len(allocator.join_points) - 1 ## 1
+        self.number_of_steps = len(allocator.join_points) - 1  # 1
         self.tasks_per_join_point = allocator.tasks_per_joinpoint
         self.logger.info("Benchmark consists of [%d] steps executed by [%d] clients.",
                          self.number_of_steps, len(self.allocations))
         # avoid flooding the log if there are too many clients
         if allocator.clients < 128:
-            self.logger.info("Allocation matrix:\n%s", "\n".join([str(a) for a in self.allocations]))
+            self.logger.info("Allocation matrix:\n%s", "\n".join(
+                [str(a) for a in self.allocations]))
 
-        worker_assignments = calculate_worker_assignments(self.load_worker_coordinator_hosts, allocator.clients)
+        worker_assignments = calculate_worker_assignments(
+            self.load_worker_coordinator_hosts, allocator.clients)
         worker_id = 0
         for assignment in worker_assignments:
-            host = assignment["host"] #localhost
-            for clients in assignment["workers"]: # cpu cores [0] [1] [2] [3]
+            host = assignment["host"]  # localhost
+            for clients in assignment["workers"]:  # cpu cores [0] [1] [2] [3]
                 # don't assign workers without any clients
                 if len(clients) > 0:
-                    self.logger.info("Allocating worker [%d] on [%s] with [%d] clients.", worker_id, host, len(clients))
+                    self.logger.info(
+                        "Allocating worker [%d] on [%s] with [%d] clients.", worker_id, host, len(clients))
                     worker = self.target.create_client(host)
 
                     client_allocations = ClientAllocations()
                     for client_id in clients:
-                        client_allocations.add(client_id, self.allocations[client_id])
+                        client_allocations.add(
+                            client_id, self.allocations[client_id])
                         self.clients_per_worker[client_id] = worker_id
-                    self.target.start_worker(worker, worker_id, self.config, self.workload, client_allocations)
+                    self.target.start_worker(
+                        worker, worker_id, self.config, self.workload, client_allocations)
                     self.workers.append(worker)
                     worker_id += 1
 
@@ -690,11 +745,13 @@ def start_benchmark(self):
 
     def joinpoint_reached(self, worker_id, worker_local_timestamp, task_allocations):
         self.currently_completed += 1
-        self.workers_completed_current_step[worker_id] = (worker_local_timestamp, time.perf_counter())
+        self.workers_completed_current_step[worker_id] = (
+            worker_local_timestamp, time.perf_counter())
         self.logger.info("[%d/%d] workers reached join point [%d/%d].",
                          self.currently_completed, len(self.workers), self.current_step + 1, self.number_of_steps)
         if self.currently_completed == len(self.workers):
-            self.logger.info("All workers completed their tasks until join point [%d/%d].", self.current_step + 1, self.number_of_steps)
+            self.logger.info(
+                "All workers completed their tasks until join point [%d/%d].", self.current_step + 1, self.number_of_steps)
             # we can go on to the next step
             self.currently_completed = 0
             self.complete_current_task_sent = False
@@ -746,13 +803,15 @@ def move_to_next_task(self, workers_curr_step):
         start_next_task = time.perf_counter() + waiting_period
         for worker_id, worker in enumerate(self.workers):
             worker_ended_task_at, master_received_msg_at = workers_curr_step[worker_id]
-            worker_start_timestamp = worker_ended_task_at + (start_next_task - master_received_msg_at)
+            worker_start_timestamp = worker_ended_task_at + \
+                (start_next_task - master_received_msg_at)
             self.logger.info("Scheduling next task for worker id [%d] at their timestamp [%f] (master timestamp [%f])",
                              worker_id, worker_start_timestamp, start_next_task)
             self.target.drive_at(worker, worker_start_timestamp)
 
     def may_complete_current_task(self, task_allocations):
-        joinpoints_completing_parent = [a for a in task_allocations if a.task.preceding_task_completes_parent]
+        joinpoints_completing_parent = [
+            a for a in task_allocations if a.task.preceding_task_completes_parent]
         # we need to actively send CompleteCurrentTask messages to all remaining workers.
         if len(joinpoints_completing_parent) > 0 and not self.complete_current_task_sent:
             # while this list could contain multiple items, it should always be the same task (but multiple
@@ -774,14 +833,17 @@ def may_complete_current_task(self, task_allocations):
                 # As we are waiting for other clients to finish, we would send this message over and over again.
                 # Hence we need to memorize whether we have already sent it for the current step.
                 self.complete_current_task_sent = True
-                self.logger.info("All affected clients have finished. Notifying all clients to complete their current tasks.")
+                self.logger.info(
+                    "All affected clients have finished. Notifying all clients to complete their current tasks.")
                 for worker in self.workers:
                     self.target.complete_current_task(worker)
             else:
                 if len(pending_client_ids) > 32:
-                    self.logger.info("[%d] clients did not yet finish.", len(pending_client_ids))
+                    self.logger.info(
+                        "[%d] clients did not yet finish.", len(pending_client_ids))
                 else:
-                    self.logger.info("Client id(s) [%s] did not yet finish.", ",".join(map(str, pending_client_ids)))
+                    self.logger.info("Client id(s) [%s] did not yet finish.", ",".join(
+                        map(str, pending_client_ids)))
 
     def reset_relative_time(self):
         self.logger.debug("Resetting relative time of request metrics store.")
@@ -804,7 +866,8 @@ def update_samples(self, samples):
 
     def update_progress_message(self, task_finished=False):
         if not self.quiet and self.current_step >= 0:
-            tasks = ",".join([t.name for t in self.tasks_per_join_point[self.current_step]])
+            tasks = ",".join(
+                [t.name for t in self.tasks_per_join_point[self.current_step]])
 
             if task_finished:
                 total_progress = 1.0
@@ -817,7 +880,8 @@ def update_progress_message(self, task_finished=False):
 
                 num_clients = max(len(progress_per_client), 1)
                 total_progress = sum(progress_per_client) / num_clients
-            self.progress_results_publisher.print("Running %s" % tasks, "[%3d%% done]" % (round(total_progress * 100)))
+            self.progress_results_publisher.print(
+                "Running %s" % tasks, "[%3d%% done]" % (round(total_progress * 100)))
             if task_finished:
                 self.progress_results_publisher.finish()
 
@@ -904,7 +968,8 @@ def __call__(self, raw_samples):
                                                            relative_time=sample.relative_time, meta_data=meta_data)
 
                 self.metrics_store.put_value_cluster_level(name="client_processing_time",
-                                                           value=convert.seconds_to_ms(sample.client_processing_time),
+                                                           value=convert.seconds_to_ms(
+                                                               sample.client_processing_time),
                                                            unit="ms", task=sample.task.name,
                                                            operation=sample.operation_name, operation_type=sample.operation_type,
                                                            sample_type=sample.sample_type, absolute_time=sample.absolute_time,
@@ -924,11 +989,13 @@ def __call__(self, raw_samples):
                                                                relative_time=timing.relative_time, meta_data=meta_data)
 
         end = time.perf_counter()
-        self.logger.debug("Storing latency and service time took [%f] seconds.", (end - start))
+        self.logger.debug(
+            "Storing latency and service time took [%f] seconds.", (end - start))
         start = end
         aggregates = self.throughput_calculator.calculate(raw_samples)
         end = time.perf_counter()
-        self.logger.debug("Calculating throughput took [%f] seconds.", (end - start))
+        self.logger.debug(
+            "Calculating throughput took [%f] seconds.", (end - start))
         start = end
         for task, samples in aggregates.items():
             meta_data = self.merge(
@@ -943,7 +1010,8 @@ def __call__(self, raw_samples):
                                                            sample_type=sample_type, absolute_time=absolute_time,
                                                            relative_time=relative_time, meta_data=meta_data)
         end = time.perf_counter()
-        self.logger.debug("Storing throughput took [%f] seconds.", (end - start))
+        self.logger.debug(
+            "Storing throughput took [%f] seconds.", (end - start))
         start = end
         # this will be a noop for the in-memory metrics store. If we use an ES metrics store however, this will ensure that we already send
         # the data and also clear the in-memory buffer. This allows users to see data already while running the benchmark. In cases where
@@ -953,7 +1021,8 @@ def __call__(self, raw_samples):
         # no need for frequent refreshes.
         self.metrics_store.flush(refresh=False)
         end = time.perf_counter()
-        self.logger.debug("Flushing the metrics store took [%f] seconds.", (end - start))
+        self.logger.debug(
+            "Flushing the metrics store took [%f] seconds.", (end - start))
         self.logger.debug("Postprocessing [%d] raw samples (downsampled to [%d] samples) took [%f] seconds in total.",
                           len(raw_samples), final_sample_count, (end - total_start))
 
@@ -1011,7 +1080,8 @@ def calculate_worker_assignments(host_configs, client_count):
     return assignments
 
 
-ClientAllocation = collections.namedtuple("ClientAllocation", ["client_id", "task"])
+ClientAllocation = collections.namedtuple(
+    "ClientAllocation", ["client_id", "task"])
 
 
 class ClientAllocations:
@@ -1032,7 +1102,8 @@ def tasks(self, task_index, remove_empty=True):
         for allocation in self.allocations:
             tasks_at_index = allocation["tasks"][task_index]
             if remove_empty and tasks_at_index is not None:
-                current_tasks.append(ClientAllocation(allocation["client_id"], tasks_at_index))
+                current_tasks.append(ClientAllocation(
+                    allocation["client_id"], tasks_at_index))
         return current_tasks
 
 
@@ -1074,7 +1145,8 @@ def receiveMsg_StartWorker(self, msg, sender):
         self.worker_id = msg.worker_id
         self.config = load_local_config(msg.config)
         self.on_error = self.config.opts("worker_coordinator", "on.error")
-        self.sample_queue_size = int(self.config.opts("results_publishing", "sample.queue.size", mandatory=False, default_value=1 << 20))
+        self.sample_queue_size = int(self.config.opts(
+            "results_publishing", "sample.queue.size", mandatory=False, default_value=1 << 20))
         self.workload = msg.workload
         workload.set_absolute_data_path(self.config, self.workload)
         self.client_allocations = msg.client_allocations
@@ -1085,12 +1157,14 @@ def receiveMsg_StartWorker(self, msg, sender):
             self.wakeup_interval = 0.5
         runner.register_default_runners()
         if self.workload.has_plugins:
-            workload.load_workload_plugins(self.config, self.workload.name, runner.register_runner, scheduler.register_scheduler)
+            workload.load_workload_plugins(
+                self.config, self.workload.name, runner.register_runner, scheduler.register_scheduler)
         self.drive()
 
     @actor.no_retry("worker")  # pylint: disable=no-value-for-parameter
     def receiveMsg_Drive(self, msg, sender):
-        sleep_time = datetime.timedelta(seconds=msg.client_start_timestamp - time.perf_counter())
+        sleep_time = datetime.timedelta(
+            seconds=msg.client_start_timestamp - time.perf_counter())
         self.logger.info("Worker[%d] is continuing its work at task index [%d] on [%f], that is in [%s].",
                          self.worker_id, self.current_task_index, msg.client_start_timestamp, sleep_time)
         self.start_driving = True
@@ -1127,9 +1201,11 @@ def receiveMsg_WakeupMessage(self, msg, sender):
                                           str(self.worker_id), exc_info=e)
                     # the exception might be user-defined and not be on the load path of the master worker_coordinator. Hence, it cannot be
                     # deserialized on the receiver so we convert it here to a plain string.
-                    self.send(self.master, actor.BenchmarkFailure("Error in load generator [{}]".format(self.worker_id), str(e)))
+                    self.send(self.master, actor.BenchmarkFailure(
+                        "Error in load generator [{}]".format(self.worker_id), str(e)))
                 else:
-                    self.logger.info("Worker[%s] is ready for the next task.", str(self.worker_id))
+                    self.logger.info(
+                        "Worker[%s] is ready for the next task.", str(self.worker_id))
                     self.executor_future = None
                     self.drive()
             else:
@@ -1143,22 +1219,27 @@ def receiveMsg_WakeupMessage(self, msg, sender):
                         self.logger.debug("Worker[%s] is executing [%s] (dependent eternal task).",
                                           str(self.worker_id), most_recent_sample.task)
                 else:
-                    self.logger.debug("Worker[%s] is executing (no samples).", str(self.worker_id))
-                self.wakeupAfter(datetime.timedelta(seconds=self.wakeup_interval))
+                    self.logger.debug(
+                        "Worker[%s] is executing (no samples).", str(self.worker_id))
+                self.wakeupAfter(datetime.timedelta(
+                    seconds=self.wakeup_interval))
 
     def receiveMsg_ActorExitRequest(self, msg, sender):
-        self.logger.info("Worker[%s] has received ActorExitRequest.", str(self.worker_id))
+        self.logger.info(
+            "Worker[%s] has received ActorExitRequest.", str(self.worker_id))
         if self.executor_future is not None and self.executor_future.running():
             self.cancel.set()
         self.pool.shutdown()
-        self.logger.info("Worker[%s] is exiting due to ActorExitRequest.", str(self.worker_id))
+        self.logger.info(
+            "Worker[%s] is exiting due to ActorExitRequest.", str(self.worker_id))
 
     def receiveMsg_BenchmarkFailure(self, msg, sender):
         # sent by our no_retry infrastructure; forward to master
         self.send(self.master, msg)
 
     def receiveUnrecognizedMessage(self, msg, sender):
-        self.logger.info("Worker[%d] received unknown message [%s] (ignoring).", self.worker_id, str(msg))
+        self.logger.info(
+            "Worker[%d] received unknown message [%s] (ignoring).", self.worker_id, str(msg))
 
     def drive(self):
         task_allocations = self.current_tasks_and_advance()
@@ -1167,7 +1248,8 @@ def drive(self):
             task_allocations = self.current_tasks_and_advance()
 
         if self.at_joinpoint():
-            self.logger.info("Worker[%d] reached join point at index [%d].", self.worker_id, self.current_task_index)
+            self.logger.info(
+                "Worker[%d] reached join point at index [%d].", self.worker_id, self.current_task_index)
             # clients that don't execute tasks don't need to care about waiting
             if self.executor_future is not None:
                 self.executor_future.result()
@@ -1176,7 +1258,8 @@ def drive(self):
             self.complete.clear()
             self.executor_future = None
             self.sampler = None
-            self.send(self.master, JoinPointReached(self.worker_id, task_allocations))
+            self.send(self.master, JoinPointReached(
+                self.worker_id, task_allocations))
         else:
             # There may be a situation where there are more (parallel) tasks than workers. If we were asked to complete all tasks, we not
             # only need to complete actively running tasks but actually all scheduled tasks until we reach the next join point.
@@ -1184,13 +1267,16 @@ def drive(self):
                 self.logger.info("Worker[%d] skips tasks at index [%d] because it has been asked to complete all "
                                  "tasks until next join point.", self.worker_id, self.current_task_index)
             else:
-                self.logger.info("Worker[%d] is executing tasks at index [%d].", self.worker_id, self.current_task_index)
-                self.sampler = Sampler(start_timestamp=time.perf_counter(), buffer_size=self.sample_queue_size)
+                self.logger.info(
+                    "Worker[%d] is executing tasks at index [%d].", self.worker_id, self.current_task_index)
+                self.sampler = Sampler(
+                    start_timestamp=time.perf_counter(), buffer_size=self.sample_queue_size)
                 executor = AsyncIoAdapter(self.config, self.workload, task_allocations, self.sampler,
                                           self.cancel, self.complete, self.on_error)
 
                 self.executor_future = self.pool.submit(executor)
-                self.wakeupAfter(datetime.timedelta(seconds=self.wakeup_interval))
+                self.wakeupAfter(datetime.timedelta(
+                    seconds=self.wakeup_interval))
 
     def at_joinpoint(self):
         return self.client_allocations.is_joinpoint(self.current_task_index)
@@ -1199,7 +1285,8 @@ def current_tasks_and_advance(self):
         self.current_task_index = self.next_task_index
         current = self.client_allocations.tasks(self.current_task_index)
         self.next_task_index += 1
-        self.logger.info("Worker[%d] is at task index [%d].", self.worker_id, self.current_task_index)
+        self.logger.info("Worker[%d] is at task index [%d].",
+                         self.worker_id, self.current_task_index)
         return current
 
     def send_samples(self):
@@ -1230,7 +1317,8 @@ def add(self, task, client_id, sample_type, meta_data, absolute_time, request_st
                        latency, service_time, client_processing_time, processing_time, throughput, ops, ops_unit, time_period,
                        percent_completed, dependent_timing))
         except queue.Full:
-            self.logger.warning("Dropping sample for [%s] due to a full sampling queue.", task.operation.name)
+            self.logger.warning(
+                "Dropping sample for [%s] due to a full sampling queue.", task.operation.name)
 
     @property
     def samples(self):
@@ -1289,7 +1377,8 @@ def dependent_timings(self):
         if self._dependent_timing:
             for t in self._dependent_timing:
                 yield Sample(self.client_id, t["absolute_time"], t["request_start"], self.task_start, self.task,
-                             self.sample_type, self.request_meta_data, 0, t["service_time"], 0, 0, 0, self.total_ops,
+                             self.sample_type, self.request_meta_data, 0, t[
+                                 "service_time"], 0, 0, 0, self.total_ops,
                              self.total_ops_unit, self.time_period, self.percent_completed, None,
                              t["operation"], t["operation-type"])
 
@@ -1301,7 +1390,8 @@ def __repr__(self, *args, **kwargs):
 
 def select_test_procedure(config, t):
     test_procedure_name = config.opts("workload", "test_procedure.name")
-    selected_test_procedure = t.find_test_procedure_or_default(test_procedure_name)
+    selected_test_procedure = t.find_test_procedure_or_default(
+        test_procedure_name)
 
     if not selected_test_procedure:
         raise exceptions.SystemSetupError("Unknown test_procedure [%s] for workload [%s]. You can list the available workloads and their "
@@ -1314,6 +1404,7 @@ class TaskStats:
         """
         Stores per task numbers needed for throughput calculation in between multiple calculations.
         """
+
         def __init__(self, bucket_interval, sample_type, start_time):
             self.unprocessed = []
             self.total_count = 0
@@ -1336,7 +1427,8 @@ def maybe_update_sample_type(self, current_sample_type):
                 self.has_samples_in_sample_type = False
 
         def update_interval(self, absolute_sample_time):
-            self.interval = max(absolute_sample_time - self.start_time, self.interval)
+            self.interval = max(absolute_sample_time -
+                                self.start_time, self.interval)
 
         def can_calculate_throughput(self):
             return self.interval > 0 and self.interval >= self.bucket
@@ -1388,7 +1480,8 @@ def calculate(self, samples, bucket_interval_secs=1):
             # only transform the values into the expected structure.
             first_sample = current_samples[0]
             if first_sample.throughput is None:
-                task_throughput = self.calculate_task_throughput(task, current_samples, bucket_interval_secs)
+                task_throughput = self.calculate_task_throughput(
+                    task, current_samples, bucket_interval_secs)
             else:
                 task_throughput = self.map_task_throughput(current_samples)
             global_throughput[task].extend(task_throughput)
@@ -1464,9 +1557,12 @@ def __init__(self, cfg, workload, task_allocations, sampler, cancel, complete, a
         self.cancel = cancel
         self.complete = complete
         self.abort_on_error = abort_on_error
-        self.profiling_enabled = self.cfg.opts("worker_coordinator", "profiling")
-        self.assertions_enabled = self.cfg.opts("worker_coordinator", "assertions")
-        self.debug_event_loop = self.cfg.opts("system", "async.debug", mandatory=False, default_value=False)
+        self.profiling_enabled = self.cfg.opts(
+            "worker_coordinator", "profiling")
+        self.assertions_enabled = self.cfg.opts(
+            "worker_coordinator", "assertions")
+        self.debug_event_loop = self.cfg.opts(
+            "system", "async.debug", mandatory=False, default_value=False)
         self.logger = logging.getLogger(__name__)
 
     def __call__(self, *args, **kwargs):
@@ -1492,16 +1588,18 @@ async def run(self):
         def os_clients(all_hosts, all_client_options):
             opensearch = {}
             for cluster_name, cluster_hosts in all_hosts.items():
-                opensearch[cluster_name] = client.OsClientFactory(cluster_hosts, all_client_options[cluster_name]).create_async()
+                opensearch[cluster_name] = client.OsClientFactory(
+                    cluster_hosts, all_client_options[cluster_name]).create_async()
             return opensearch
 
         # Properly size the internal connection pool to match the number of expected clients but allow the user
         # to override it if needed.
         client_count = len(self.task_allocations)
         opensearch = os_clients(self.cfg.opts("client", "hosts").all_hosts,
-                        self.cfg.opts("client", "options").with_max_connections(client_count))
+                                self.cfg.opts("client", "options").with_max_connections(client_count))
 
-        self.logger.info("Task assertions enabled: %s", str(self.assertions_enabled))
+        self.logger.info("Task assertions enabled: %s",
+                         str(self.assertions_enabled))
         runner.enable_assertions(self.assertions_enabled)
 
         aws = []
@@ -1510,7 +1608,8 @@ def os_clients(all_hosts, all_client_options):
         for client_id, task_allocation in self.task_allocations:
             task = task_allocation.task
             if task not in params_per_task:
-                param_source = workload.operation_parameters(self.workload, task)
+                param_source = workload.operation_parameters(
+                    self.workload, task)
                 params_per_task[task] = param_source
             # We cannot use the global client index here because we need to support parallel execution of tasks
             # with multiple clients. Consider the following scenario:
@@ -1524,21 +1623,25 @@ def os_clients(all_hosts, all_client_options):
             async_executor = AsyncExecutor(
                 client_id, task, schedule, opensearch, self.sampler, self.cancel, self.complete,
                 task.error_behavior(self.abort_on_error), self.cfg)
-            final_executor = AsyncProfiler(async_executor) if self.profiling_enabled else async_executor
+            final_executor = AsyncProfiler(
+                async_executor) if self.profiling_enabled else async_executor
             aws.append(final_executor())
         run_start = time.perf_counter()
         try:
             _ = await asyncio.gather(*aws)
         finally:
             run_end = time.perf_counter()
-            self.logger.info("Total run duration: %f seconds.", (run_end - run_start))
+            self.logger.info("Total run duration: %f seconds.",
+                             (run_end - run_start))
             await asyncio.get_event_loop().shutdown_asyncgens()
             shutdown_asyncgens_end = time.perf_counter()
-            self.logger.info("Total time to shutdown asyncgens: %f seconds.", (shutdown_asyncgens_end - run_end))
+            self.logger.info(
+                "Total time to shutdown asyncgens: %f seconds.", (shutdown_asyncgens_end - run_end))
             for s in opensearch.values():
                 await s.transport.close()
             transport_close_end = time.perf_counter()
-            self.logger.info("Total time to close transports: %f seconds.", (shutdown_asyncgens_end - transport_close_end))
+            self.logger.info("Total time to close transports: %f seconds.",
+                             (shutdown_asyncgens_end - transport_close_end))
 
 
 class AsyncProfiler:
@@ -1603,18 +1706,21 @@ async def __call__(self, *args, **kwargs):
         task_completes_parent = self.task.completes_parent
         total_start = time.perf_counter()
         # lazily initialize the schedule
-        self.logger.debug("Initializing schedule for client id [%s].", self.client_id)
+        self.logger.debug(
+            "Initializing schedule for client id [%s].", self.client_id)
         schedule = self.schedule_handle()
         self.schedule_handle.start()
         rampup_wait_time = self.schedule_handle.ramp_up_wait_time
         if rampup_wait_time:
-            self.logger.info("client id [%s] waiting [%.2f]s for ramp-up.", self.client_id, rampup_wait_time)
+            self.logger.info(
+                "client id [%s] waiting [%.2f]s for ramp-up.", self.client_id, rampup_wait_time)
             await asyncio.sleep(rampup_wait_time)
-        
+
         if rampup_wait_time:
             console.println(f" Client id {self.client_id} is running now.")
 
-        self.logger.debug("Entering main loop for client id [%s].", self.client_id)
+        self.logger.debug(
+            "Entering main loop for client id [%s].", self.client_id)
         # noinspection PyBroadException
         try:
             async for expected_scheduled_time, sample_type, percent_completed, runner, params in schedule:
@@ -1637,8 +1743,9 @@ async def __call__(self, *args, **kwargs):
                     if params:
                         if params.get("operation-type") == "vector-search":
                             available_cores = int(self.cfg.opts("system", "available.cores", mandatory=False,
-                                default_value=multiprocessing.cpu_count()))
-                            params.update({"num_clients": self.task.clients, "num_cores": available_cores})
+                                                                default_value=multiprocessing.cpu_count()))
+                            params.update(
+                                {"num_clients": self.task.clients, "num_cores": available_cores})
 
                     total_ops, total_ops_unit, request_meta_data = await execute_single(runner, self.opensearch, params, self.on_error)
                     request_start = request_context.request_start
@@ -1648,10 +1755,12 @@ async def __call__(self, *args, **kwargs):
 
                 processing_end = time.perf_counter()
                 service_time = request_end - request_start
-                client_processing_time = (client_request_end - client_request_start) - service_time
+                client_processing_time = (
+                    client_request_end - client_request_start) - service_time
                 processing_time = processing_end - processing_start
                 time_period = request_end - total_start
-                self.schedule_handle.after_request(processing_end, total_ops, total_ops_unit, request_meta_data)
+                self.schedule_handle.after_request(
+                    processing_end, total_ops, total_ops_unit, request_meta_data)
                 # Allow runners to override the throughput calculation in very specific circumstances. Usually, Benchmark
                 # assumes that throughput is the "amount of work" (determined by the "weight") per unit of time
                 # (determined by the elapsed time period). However, in certain cases (e.g. shard recovery or other
@@ -1664,7 +1773,8 @@ async def __call__(self, *args, **kwargs):
                 #
                 throughput = request_meta_data.pop("throughput", None)
                 # Do not calculate latency separately when we run unthrottled. This metric is just confusing then.
-                latency = request_end - absolute_expected_schedule_time if throughput_throttled else service_time
+                latency = request_end - \
+                    absolute_expected_schedule_time if throughput_throttled else service_time
                 # If this task completes the parent task we should *not* check for completion by another client but
                 # instead continue until our own runner has completed. We need to do this because the current
                 # worker (process) could run multiple clients that execute the same task. We do not want all clients to
@@ -1688,11 +1798,13 @@ async def __call__(self, *args, **kwargs):
                                  time_period, progress, request_meta_data.pop("dependent_timing", None))
 
                 if completed:
-                    self.logger.info("Task [%s] is considered completed due to external event.", self.task)
+                    self.logger.info(
+                        "Task [%s] is considered completed due to external event.", self.task)
                     break
         except BaseException as e:
             self.logger.exception("Could not execute schedule")
-            raise exceptions.BenchmarkError(f"Cannot run task [{self.task}]: {e}") from None
+            raise exceptions.BenchmarkError(
+                f"Cannot run task [{self.task}]: {e}") from None
         finally:
             # Actively set it if this task completes its parent
             if task_completes_parent:
@@ -1758,14 +1870,17 @@ async def execute_single(runner, opensearch, params, on_error):
             request_meta_data["error-description"] = error_description
     except KeyError as e:
         request_context_holder.on_client_request_end()
-        logging.getLogger(__name__).exception("Cannot execute runner [%s]; most likely due to missing parameters.", str(runner))
-        msg = "Cannot execute [%s]. Provided parameters are: %s. Error: [%s]." % (str(runner), list(params.keys()), str(e))
+        logging.getLogger(__name__).exception(
+            "Cannot execute runner [%s]; most likely due to missing parameters.", str(runner))
+        msg = "Cannot execute [%s]. Provided parameters are: %s. Error: [%s]." % (
+            str(runner), list(params.keys()), str(e))
         console.error(msg)
         raise exceptions.SystemSetupError(msg)
 
     if not request_meta_data["success"]:
         if on_error == "abort" or fatal_error:
-            msg = "Request returned an error. Error type: %s" % request_meta_data.get("error-type", "Unknown")
+            msg = "Request returned an error. Error type: %s" % request_meta_data.get(
+                "error-type", "Unknown")
             description = request_meta_data.get("error-description")
             if description:
                 msg += ", Description: %s" % description
@@ -1774,7 +1889,8 @@ async def execute_single(runner, opensearch, params, on_error):
 
         if 'error-description' in request_meta_data:
             try:
-                error_metadata = json.loads(request_meta_data["error-description"])
+                error_metadata = json.loads(
+                    request_meta_data["error-description"])
                 # parse error-description metadata
                 opensearch_operation_error = parse_error(error_metadata)
                 console.error(opensearch_operation_error.get_error_message())
@@ -1782,7 +1898,8 @@ async def execute_single(runner, opensearch, params, on_error):
                 # error-description is not a valid json so we just print it
                 console.error(request_meta_data["error-description"])
 
-            logging.getLogger(__name__).error(request_meta_data["error-description"])
+            logging.getLogger(__name__).error(
+                request_meta_data["error-description"])
 
     return total_ops, total_ops_unit, request_meta_data
 
@@ -1799,7 +1916,8 @@ def __init__(self, id, clients_executing_completing_task=None):
             clients_executing_completing_task = []
         self.id = id
         self.clients_executing_completing_task = clients_executing_completing_task
-        self.num_clients_executing_completing_task = len(clients_executing_completing_task)
+        self.num_clients_executing_completing_task = len(
+            clients_executing_completing_task)
         self.preceding_task_completes_parent = self.num_clients_executing_completing_task > 0
 
     def __hash__(self):
@@ -1871,14 +1989,15 @@ def allocations(self):
                     # more tasks than actually available clients)
                     physical_client_index = client_index % max_clients
                     if sub_task.completes_parent:
-                        clients_executing_completing_task.append(physical_client_index)
+                        clients_executing_completing_task.append(
+                            physical_client_index)
                     ta = TaskAllocation(task=sub_task,
                                         client_index_in_task=client_index - start_client_index,
                                         global_client_index=client_index,
                                         # if task represents a parallel structure this is the total number of clients
                                         # executing sub-tasks concurrently.
                                         total_clients=task.clients)
-                    
+
                     allocations[physical_client_index].append(ta)
                 start_client_index += sub_task.clients
 
@@ -1891,7 +2010,8 @@ def allocations(self):
                     allocations[client_index].append(None)
 
             # let all clients join after each task, then we go on
-            next_join_point = JoinPoint(join_point_id, clients_executing_completing_task)
+            next_join_point = JoinPoint(
+                join_point_id, clients_executing_completing_task)
             for client_index in range(max_clients):
                 allocations[client_index].append(next_join_point)
             join_point_id += 1
@@ -1979,7 +2099,8 @@ def schedule_for(task_allocation, parameter_source):
     params_for_op = parameter_source.partition(client_index, task.clients)
     if hasattr(sched, "parameter_source"):
         if client_index == 0:
-            logger.debug("Setting parameter source [%s] for scheduler [%s]", params_for_op, sched)
+            logger.debug(
+                "Setting parameter source [%s] for scheduler [%s]", params_for_op, sched)
         sched.parameter_source = params_for_op
 
     if requires_time_period_schedule(task, runner_for_op, params_for_op):
@@ -2005,9 +2126,11 @@ def schedule_for(task_allocation, parameter_source):
 
     if client_index == 0:
         if loop_control.infinite:
-            logger.info("Parameter source will determine when the schedule for [%s] terminates.", task.name)
+            logger.info(
+                "Parameter source will determine when the schedule for [%s] terminates.", task.name)
         else:
-            logger.info("%s schedule will determine when the schedule for [%s] terminates.", str(loop_control), task.name)
+            logger.info("%s schedule will determine when the schedule for [%s] terminates.", str(
+                loop_control), task.name)
 
     return ScheduleHandle(task_allocation, sched, loop_control, runner_for_op, params_for_op)
 
@@ -2043,11 +2166,11 @@ def __init__(self, task_allocation, sched, task_progress_control, runner, params
         self.runner = runner
         self.params = params
         # TODO: Can we offload the parameter source execution to a different thread / process? Is this too heavy-weight?
-        #from concurrent.futures import ThreadPoolExecutor
-        #import asyncio
-        #self.io_pool_exc = ThreadPoolExecutor(max_workers=1)
-        #self.loop = asyncio.get_event_loop()
-    
+        # from concurrent.futures import ThreadPoolExecutor
+        # import asyncio
+        # self.io_pool_exc = ThreadPoolExecutor(max_workers=1)
+        # self.loop = asyncio.get_event_loop()
+
     @property
     def ramp_up_wait_time(self):
         """
@@ -2058,7 +2181,7 @@ def ramp_up_wait_time(self):
             return ramp_up_time_period * (self.task_allocation.global_client_index / self.task_allocation.total_clients)
         else:
             return 0
-    
+
     def start(self):
         self.task_progress_control.start()
 
@@ -2071,13 +2194,14 @@ def after_request(self, now, weight, unit, request_meta_data):
     async def __call__(self):
         next_scheduled = 0
         if self.task_progress_control.infinite:
-            param_source_knows_progress = hasattr(self.params, "percent_completed")
+            param_source_knows_progress = hasattr(
+                self.params, "percent_completed")
             while True:
                 try:
                     next_scheduled = self.sched.next(next_scheduled)
                     # does not contribute at all to completion. Hence, we cannot define completion.
                     percent_completed = self.params.percent_completed if param_source_knows_progress else None
-                    #current_params = await self.loop.run_in_executor(self.io_pool_exc, self.params.params)
+                    # current_params = await self.loop.run_in_executor(self.io_pool_exc, self.params.params)
                     yield (next_scheduled, self.task_progress_control.sample_type, percent_completed, self.runner,
                            self.params.params())
                     self.task_progress_control.next()
@@ -2087,7 +2211,7 @@ async def __call__(self):
             while not self.task_progress_control.completed:
                 try:
                     next_scheduled = self.sched.next(next_scheduled)
-                    #current_params = await self.loop.run_in_executor(self.io_pool_exc, self.params.params)
+                    # current_params = await self.loop.run_in_executor(self.io_pool_exc, self.params.params)
                     yield (next_scheduled,
                            self.task_progress_control.sample_type,
                            self.task_progress_control.percent_completed,
@@ -2147,7 +2271,8 @@ def __init__(self, warmup_iterations, iterations):
         if warmup_iterations is not None and iterations is not None:
             self._total_iterations = self._warmup_iterations + self._iterations
             if self._total_iterations == 0:
-                raise exceptions.BenchmarkAssertionError("Operation must run at least for one iteration.")
+                raise exceptions.BenchmarkAssertionError(
+                    "Operation must run at least for one iteration.")
         else:
             self._total_iterations = None
         self._it = None
diff --git a/osbenchmark/workload/loader.py b/osbenchmark/workload/loader.py
index 8905c6fc..2bd7bf39 100644
--- a/osbenchmark/workload/loader.py
+++ b/osbenchmark/workload/loader.py
@@ -13,7 +13,7 @@
 # not use this file except in compliance with the License.
 # You may obtain a copy of the License at
 #
-#	http://www.apache.org/licenses/LICENSE-2.0
+# http://www.apache.org/licenses/LICENSE-2.0
 #
 # Unless required by applicable law or agreed to in writing,
 # software distributed under the License is distributed on an
@@ -76,10 +76,12 @@ def on_prepare_workload(self, workload, data_root_dir):
 
 class WorkloadProcessorRegistry:
     def __init__(self, cfg):
-        self.required_processors = [TaskFilterWorkloadProcessor(cfg), TestModeWorkloadProcessor(cfg), QueryRandomizerWorkloadProcessor(cfg)]
+        self.required_processors = [TaskFilterWorkloadProcessor(
+            cfg), TestModeWorkloadProcessor(cfg), QueryRandomizerWorkloadProcessor(cfg)]
         self.workload_processors = []
         self.offline = cfg.opts("system", "offline.mode")
-        self.test_mode = cfg.opts("workload", "test.mode.enabled", mandatory=False, default_value=False)
+        self.test_mode = cfg.opts(
+            "workload", "test.mode.enabled", mandatory=False, default_value=False)
         self.base_config = cfg
         self.custom_configuration = False
 
@@ -99,7 +101,8 @@ def register_workload_processor(self, processor):
     @property
     def processors(self):
         if not self.custom_configuration:
-            self.register_workload_processor(DefaultWorkloadPreparator(self.base_config))
+            self.register_workload_processor(
+                DefaultWorkloadPreparator(self.base_config))
         return [*self.required_processors, *self.workload_processors]
 
 
@@ -118,7 +121,8 @@ def workloads(cfg):
 
 def list_workloads(cfg):
     available_workloads = workloads(cfg)
-    only_auto_generated_test_procedures = all(t.default_test_procedure.auto_generated for t in available_workloads)
+    only_auto_generated_test_procedures = all(
+        t.default_test_procedure.auto_generated for t in available_workloads)
 
     data = []
     for t in available_workloads:
@@ -130,7 +134,8 @@ def list_workloads(cfg):
             line.append(",".join(map(str, t.test_procedures)))
         data.append(line)
 
-    headers = ["Name", "Description", "Documents", "Compressed Size", "Uncompressed Size"]
+    headers = ["Name", "Description", "Documents",
+               "Compressed Size", "Uncompressed Size"]
     if not only_auto_generated_test_procedures:
         headers.append("Default TestProcedure")
         headers.append("All TestProcedures")
@@ -160,9 +165,11 @@ def test_procedure_info(c):
         console.println("")
         for num, task in enumerate(c.schedule, start=1):
             if task.nested:
-                console.println(format_task(task, suffix=":", num="{}. ".format(num)))
+                console.println(format_task(
+                    task, suffix=":", num="{}. ".format(num)))
                 for leaf_num, leaf_task in enumerate(task, start=1):
-                    console.println(format_task(leaf_task, indent="\t", num="{}.{} ".format(num, leaf_num)))
+                    console.println(format_task(
+                        leaf_task, indent="\t", num="{}.{} ".format(num, leaf_num)))
             else:
                 console.println(format_task(task, num="{}. ".format(num)))
 
@@ -170,9 +177,12 @@ def test_procedure_info(c):
     console.println("Showing details for workload [{}]:\n".format(t.name))
     console.println("* Description: {}".format(t.description))
     if t.number_of_documents:
-        console.println("* Documents: {}".format(convert.number_to_human_string(t.number_of_documents)))
-        console.println("* Compressed Size: {}".format(convert.bytes_to_human_string(t.compressed_size_in_bytes)))
-        console.println("* Uncompressed Size: {}".format(convert.bytes_to_human_string(t.uncompressed_size_in_bytes)))
+        console.println(
+            "* Documents: {}".format(convert.number_to_human_string(t.number_of_documents)))
+        console.println(
+            "* Compressed Size: {}".format(convert.bytes_to_human_string(t.compressed_size_in_bytes)))
+        console.println("* Uncompressed Size: {}".format(
+            convert.bytes_to_human_string(t.uncompressed_size_in_bytes)))
     console.println("")
 
     if t.selected_test_procedure:
@@ -199,28 +209,32 @@ def _load_single_workload(cfg, workload_repository, workload_name):
     try:
         workload_dir = workload_repository.workload_dir(workload_name)
         reader = WorkloadFileReader(cfg)
-        current_workload = reader.read(workload_name, workload_repository.workload_file(workload_name), workload_dir)
+        current_workload = reader.read(
+            workload_name, workload_repository.workload_file(workload_name), workload_dir)
         tpr = WorkloadProcessorRegistry(cfg)
-        has_plugins = load_workload_plugins(cfg, workload_name, register_workload_processor=tpr.register_workload_processor)
+        has_plugins = load_workload_plugins(
+            cfg, workload_name, register_workload_processor=tpr.register_workload_processor)
         current_workload.has_plugins = has_plugins
         for processor in tpr.processors:
             processor.on_after_load_workload(current_workload)
         return current_workload
     except FileNotFoundError as e:
-        logging.getLogger(__name__).exception("Cannot load workload [%s]", workload_name)
+        logging.getLogger(__name__).exception(
+            "Cannot load workload [%s]", workload_name)
         raise exceptions.SystemSetupError(f"Cannot load workload [{workload_name}]. "
                                           f"List the available workloads with [{PROGRAM_NAME} list workloads].") from e
     except BaseException:
-        logging.getLogger(__name__).exception("Cannot load workload [%s]", workload_name)
+        logging.getLogger(__name__).exception(
+            "Cannot load workload [%s]", workload_name)
         raise
 
 
 def load_workload_plugins(cfg,
-                       workload_name,
-                       register_runner=None,
-                       register_scheduler=None,
-                       register_workload_processor=None,
-                       force_update=False):
+                          workload_name,
+                          register_runner=None,
+                          register_scheduler=None,
+                          register_workload_processor=None,
+                          force_update=False):
     """
     Loads plugins that are defined for the current workload (as specified by the configuration).
 
@@ -235,8 +249,10 @@ def load_workload_plugins(cfg,
     """
     repo = workload_repo(cfg, fetch=force_update, update=force_update)
     workload_plugin_path = repo.workload_dir(workload_name)
-    logging.getLogger(__name__).debug("Invoking plugin_reader with name [%s] resolved to path [%s]", workload_name, workload_plugin_path)
-    plugin_reader = WorkloadPluginReader(workload_plugin_path, register_runner, register_scheduler, register_workload_processor)
+    logging.getLogger(__name__).debug(
+        "Invoking plugin_reader with name [%s] resolved to path [%s]", workload_name, workload_plugin_path)
+    plugin_reader = WorkloadPluginReader(
+        workload_plugin_path, register_runner, register_scheduler, register_workload_processor)
 
     if plugin_reader.can_load():
         plugin_reader.load()
@@ -268,9 +284,11 @@ def first_existing(root_dirs, f):
         for document_set in corpus.documents:
             # At this point we can assume that the file is available locally. Check which path exists and set it.
             if document_set.document_archive:
-                document_set.document_archive = first_existing(data_root, document_set.document_archive)
+                document_set.document_archive = first_existing(
+                    data_root, document_set.document_archive)
             if document_set.document_file:
-                document_set.document_file = first_existing(data_root, document_set.document_file)
+                document_set.document_file = first_existing(
+                    data_root, document_set.document_file)
 
 
 def is_simple_workload_mode(cfg):
@@ -301,7 +319,8 @@ def data_dir(cfg, workload_name, corpus_name):
     :param corpus_name: Name of the current corpus.
     :return: A list containing either one or two elements. Each element contains a path to a directory which may contain document files.
     """
-    corpus_dir = os.path.join(cfg.opts("benchmarks", "local.dataset.cache"), corpus_name)
+    corpus_dir = os.path.join(
+        cfg.opts("benchmarks", "local.dataset.cache"), corpus_name)
     if is_simple_workload_mode(cfg):
         workload_path = cfg.opts("workload", "workload.path")
         r = SimpleWorkloadRepository(workload_path)
@@ -315,23 +334,30 @@ def data_dir(cfg, workload_name, corpus_name):
 class GitWorkloadRepository:
     def __init__(self, cfg, fetch, update, repo_class=repo.BenchmarkRepository):
         # current workload name (if any)
-        self.workload_name = cfg.opts("workload", "workload.name", mandatory=False)
-        distribution_version = cfg.opts("builder", "distribution.version", mandatory=False)
+        self.workload_name = cfg.opts(
+            "workload", "workload.name", mandatory=False)
+        distribution_version = cfg.opts(
+            "builder", "distribution.version", mandatory=False)
         repo_name = cfg.opts("workload", "repository.name")
-        repo_revision = cfg.opts("workload", "repository.revision", mandatory=False)
+        repo_revision = cfg.opts(
+            "workload", "repository.revision", mandatory=False)
         offline = cfg.opts("system", "offline.mode")
-        remote_url = cfg.opts("workloads", "%s.url" % repo_name, mandatory=False)
+        remote_url = cfg.opts("workloads", "%s.url" %
+                              repo_name, mandatory=False)
         root = cfg.opts("node", "root.dir")
-        workload_repositories = cfg.opts("benchmarks", "workload.repository.dir")
+        workload_repositories = cfg.opts(
+            "benchmarks", "workload.repository.dir")
         workloads_dir = os.path.join(root, workload_repositories)
 
-        self.repo = repo_class(remote_url, workloads_dir, repo_name, "workloads", offline, fetch)
+        self.repo = repo_class(remote_url, workloads_dir,
+                               repo_name, "workloads", offline, fetch)
         if update:
             if repo_revision:
                 self.repo.checkout(repo_revision)
             else:
                 self.repo.update(distribution_version)
-                cfg.add(config.Scope.applicationOverride, "workload", "repository.revision", self.repo.revision)
+                cfg.add(config.Scope.applicationOverride, "workload",
+                        "repository.revision", self.repo.revision)
 
     @property
     def workload_names(self):
@@ -347,30 +373,35 @@ def workload_file(self, workload_name):
 class SimpleWorkloadRepository:
     def __init__(self, workload_path):
         if not os.path.exists(workload_path):
-            raise exceptions.SystemSetupError("Workload path %s does not exist" % workload_path)
+            raise exceptions.SystemSetupError(
+                "Workload path %s does not exist" % workload_path)
 
         if os.path.isdir(workload_path):
             self.workload_name = io.basename(workload_path)
             self._workload_dir = workload_path
             self._workload_file = os.path.join(workload_path, "workload.json")
             if not os.path.exists(self._workload_file):
-                raise exceptions.SystemSetupError("Could not find workload.json in %s" % workload_path)
+                raise exceptions.SystemSetupError(
+                    "Could not find workload.json in %s" % workload_path)
         elif os.path.isfile(workload_path):
             if io.has_extension(workload_path, ".json"):
                 self._workload_dir = io.dirname(workload_path)
                 self._workload_file = workload_path
                 self.workload_name = io.splitext(io.basename(workload_path))[0]
             else:
-                raise exceptions.SystemSetupError("%s has to be a JSON file" % workload_path)
+                raise exceptions.SystemSetupError(
+                    "%s has to be a JSON file" % workload_path)
         else:
-            raise exceptions.SystemSetupError("%s is neither a file nor a directory" % workload_path)
+            raise exceptions.SystemSetupError(
+                "%s is neither a file nor a directory" % workload_path)
 
     @property
     def workload_names(self):
         return [self.workload_name]
 
     def workload_dir(self, workload_name):
-        assert workload_name == self.workload_name, "Expect provided workload name [%s] to match [%s]" % (workload_name, self.workload_name)
+        assert workload_name == self.workload_name, "Expect provided workload name [%s] to match [%s]" % (
+            workload_name, self.workload_name)
         return self._workload_dir
 
     def workload_file(self, workload_name):
@@ -423,7 +454,8 @@ def prepare_docs(cfg, workload, corpus, preparator):
                     preparator.prepare_document_set(document_set, data_root[1])
 
     def on_prepare_workload(self, workload, data_root_dir):
-        prep = DocumentSetPreparator(workload.name, self.downloader, self.decompressor)
+        prep = DocumentSetPreparator(
+            workload.name, self.downloader, self.decompressor)
         for corpus in used_corpora(workload):
             params = {
                 "cfg": self.cfg,
@@ -469,9 +501,11 @@ def download(self, base_url, source_url, target_path, size_in_bytes):
         file_name = os.path.basename(target_path)
 
         if not base_url:
-            raise exceptions.DataError("Cannot download data because no base URL is provided.")
+            raise exceptions.DataError(
+                "Cannot download data because no base URL is provided.")
         if self.offline:
-            raise exceptions.SystemSetupError(f"Cannot find [{target_path}]. Please disable offline mode and retry.")
+            raise exceptions.SystemSetupError(
+                f"Cannot find [{target_path}]. Please disable offline mode and retry.")
 
         if source_url:
             data_url = source_url
@@ -486,16 +520,20 @@ def download(self, base_url, source_url, target_path, size_in_bytes):
             io.ensure_dir(os.path.dirname(target_path))
             if size_in_bytes:
                 size_in_mb = round(convert.bytes_to_mb(size_in_bytes))
-                self.logger.info("Downloading data from [%s] (%s MB) to [%s].", data_url, size_in_mb, target_path)
+                self.logger.info(
+                    "Downloading data from [%s] (%s MB) to [%s].", data_url, size_in_mb, target_path)
             else:
-                self.logger.info("Downloading data from [%s] to [%s].", data_url, target_path)
+                self.logger.info(
+                    "Downloading data from [%s] to [%s].", data_url, target_path)
 
             # we want to have a bit more accurate download progress as these files are typically very large
             progress = net.Progress("[INFO] Downloading workload data file: " + os.path.basename(target_path),
                                     accuracy=1)
-            net.download(data_url, target_path, size_in_bytes, progress_indicator=progress)
+            net.download(data_url, target_path, size_in_bytes,
+                         progress_indicator=progress)
             progress.finish()
-            self.logger.info("Downloaded data from [%s] to [%s].", data_url, target_path)
+            self.logger.info(
+                "Downloaded data from [%s] to [%s].", data_url, target_path)
         except urllib.error.HTTPError as e:
             if e.code == 404 and self.test_mode:
                 raise exceptions.DataError("This workload does not support test mode. Ask the workload author to add it or"
@@ -508,7 +546,8 @@ def download(self, base_url, source_url, target_path, size_in_bytes):
                     msg += f" (HTTP status: {e.code})"
                 raise exceptions.DataError(msg, e) from None
         except urllib.error.URLError as e:
-            raise exceptions.DataError(f"Could not download [{data_url}] to [{target_path}].") from e
+            raise exceptions.DataError(
+                f"Could not download [{data_url}] to [{target_path}].") from e
 
         if not os.path.isfile(target_path):
             raise exceptions.SystemSetupError(f"Could not download [{data_url}] to [{target_path}]. Verify data "
@@ -535,7 +574,8 @@ def has_expected_size(self, file_name, expected_size):
 
     def create_file_offset_table(self, document_file_path, base_url, source_url, expected_number_of_lines):
         # just rebuild the file every time for the time being. Later on, we might check the data file fingerprint to avoid it
-        lines_read = io.prepare_file_offset_table(document_file_path, base_url, source_url, self.downloader)
+        lines_read = io.prepare_file_offset_table(
+            document_file_path, base_url, source_url, self.downloader)
         if lines_read and lines_read != expected_number_of_lines:
             io.remove_file_offset_table(document_file_path)
             raise exceptions.DataError(f"Data in [{document_file_path}] for workload [{self.workload_name}] are invalid. "
@@ -558,7 +598,8 @@ def prepare_document_set(self, document_set, data_root):
         :param data_root: The data root directory for this document set.
         """
         doc_path = os.path.join(data_root, document_set.document_file)
-        archive_path = os.path.join(data_root, document_set.document_archive) if document_set.has_compressed_corpus() else None
+        archive_path = os.path.join(
+            data_root, document_set.document_archive) if document_set.has_compressed_corpus() else None
         while True:
             if self.is_locally_available(doc_path) and \
                     self.has_expected_size(doc_path, document_set.uncompressed_size_in_bytes):
@@ -566,7 +607,8 @@ def prepare_document_set(self, document_set, data_root):
             if document_set.has_compressed_corpus() and \
                     self.is_locally_available(archive_path) and \
                     self.has_expected_size(archive_path, document_set.compressed_size_in_bytes):
-                self.decompressor.decompress(archive_path, doc_path, document_set.uncompressed_size_in_bytes)
+                self.decompressor.decompress(
+                    archive_path, doc_path, document_set.uncompressed_size_in_bytes)
             else:
                 if document_set.has_compressed_corpus():
                     target_path = archive_path
@@ -576,25 +618,30 @@ def prepare_document_set(self, document_set, data_root):
                     expected_size = document_set.uncompressed_size_in_bytes
                 else:
                     # this should not happen in practice as the JSON schema should take care of this
-                    raise exceptions.BenchmarkAssertionError(f"Workload {self.workload_name} specifies documents but no corpus")
+                    raise exceptions.BenchmarkAssertionError(
+                        f"Workload {self.workload_name} specifies documents but no corpus")
 
                 try:
                     if document_set.document_file_parts:
                         for part in document_set.document_file_parts:
-                            self.downloader.download(document_set.base_url, None, os.path.join(data_root, part["name"]), part["size"])
+                            self.downloader.download(document_set.base_url, None, os.path.join(
+                                data_root, part["name"]), part["size"])
                         try:
                             with open(target_path, "wb") as outfile:
                                 console.info(f"Concatenating file parts {', '.join([p['name'] for p in document_set.document_file_parts])}"
                                              f" into {os.path.basename(target_path)}", flush=True, logger=self.logger)
                                 for part in document_set.document_file_parts:
-                                    part_name = os.path.join(data_root, part["name"])
+                                    part_name = os.path.join(
+                                        data_root, part["name"])
                                     with open(part_name, "rb") as infile:
                                         shutil.copyfileobj(infile, outfile)
                                         os.remove(part_name)
                         except Exception as e:
-                            raise exceptions.DataError(f"Encountered exception {repr(e)} when building corpus file from parts")
+                            raise exceptions.DataError(
+                                f"Encountered exception {repr(e)} when building corpus file from parts")
                     else:
-                        self.downloader.download(document_set.base_url, document_set.source_url, target_path, expected_size)
+                        self.downloader.download(
+                            document_set.base_url, document_set.source_url, target_path, expected_size)
                 except exceptions.DataError as e:
                     if e.message == "Cannot download data because no base URL is provided." and \
                        self.is_locally_available(target_path):
@@ -604,7 +651,8 @@ def prepare_document_set(self, document_set, data_root):
                     else:
                         raise
         if document_set.support_file_offset_table:
-            self.create_file_offset_table(doc_path, document_set.base_url, document_set.source_url, document_set.number_of_lines)
+            self.create_file_offset_table(
+                doc_path, document_set.base_url, document_set.source_url, document_set.number_of_lines)
 
     def prepare_bundled_document_set(self, document_set, data_root):
         """
@@ -626,12 +674,14 @@ def prepare_bundled_document_set(self, document_set, data_root):
         :return: See postcondition.
         """
         doc_path = os.path.join(data_root, document_set.document_file)
-        archive_path = os.path.join(data_root, document_set.document_archive) if document_set.has_compressed_corpus() else None
+        archive_path = os.path.join(
+            data_root, document_set.document_archive) if document_set.has_compressed_corpus() else None
 
         while True:
             if self.is_locally_available(doc_path):
                 if self.has_expected_size(doc_path, document_set.uncompressed_size_in_bytes):
-                    self.create_file_offset_table(doc_path, document_set.base_url, document_set.source_url, document_set.number_of_lines)
+                    self.create_file_offset_table(
+                        doc_path, document_set.base_url, document_set.source_url, document_set.number_of_lines)
                     return True
                 else:
                     raise exceptions.DataError(f"[{doc_path}] is present but does not have the expected size "
@@ -639,7 +689,8 @@ def prepare_bundled_document_set(self, document_set, data_root):
 
             if document_set.has_compressed_corpus() and self.is_locally_available(archive_path):
                 if self.has_expected_size(archive_path, document_set.compressed_size_in_bytes):
-                    self.decompressor.decompress(archive_path, doc_path, document_set.uncompressed_size_in_bytes)
+                    self.decompressor.decompress(
+                        archive_path, doc_path, document_set.uncompressed_size_in_bytes)
                 else:
                     # treat this is an error because if the file is present but the size does not match, something is
                     # really fishy. It is likely that the user is currently creating a new workload and did not specify
@@ -657,7 +708,8 @@ class TemplateSource:
     benchmark.collect(parts=...
     """
 
-    collect_parts_re = re.compile(r"{{\ +?benchmark\.collect\(parts=\"(.+?(?=\"))\"\)\ +?}}")
+    collect_parts_re = re.compile(
+        r"{{\ +?benchmark\.collect\(parts=\"(.+?(?=\"))\"\)\ +?}}")
 
     def __init__(self, base_path, template_file_name, source=io.FileSource, fileglobber=glob.glob):
         self.base_path = base_path
@@ -674,12 +726,16 @@ def load_template_from_file(self):
                 autoescape=select_autoescape(['html', 'xml'])),
                 self.template_file_name)
         except jinja2.TemplateNotFound:
-            self.logger.exception("Could not load workload from [%s].", self.template_file_name)
-            raise WorkloadSyntaxError("Could not load workload from '{}'".format(self.template_file_name))
-        self.assembled_source = self.replace_includes(self.base_path, base_workload[0])
+            self.logger.exception(
+                "Could not load workload from [%s].", self.template_file_name)
+            raise WorkloadSyntaxError(
+                "Could not load workload from '{}'".format(self.template_file_name))
+        self.assembled_source = self.replace_includes(
+            self.base_path, base_workload[0])
 
     def load_template_from_string(self, template_source):
-        self.assembled_source = self.replace_includes(self.base_path, template_source)
+        self.assembled_source = self.replace_includes(
+            self.base_path, template_source)
 
     def replace_includes(self, base_path, workload_fragment):
         match = TemplateSource.collect_parts_re.findall(workload_fragment)
@@ -689,7 +745,8 @@ def replace_includes(self, base_path, workload_fragment):
             for glob_pattern in match:
                 full_glob_path = os.path.join(base_path, glob_pattern)
                 sub_source = self.read_glob_files(full_glob_path)
-                repl[glob_pattern] = self.replace_includes(base_path=io.dirname(full_glob_path), workload_fragment=sub_source)
+                repl[glob_pattern] = self.replace_includes(
+                    base_path=io.dirname(full_glob_path), workload_fragment=sub_source)
 
             def replstring(matchobj):
                 # matchobj.groups() is a tuple and first element contains the matched group id
@@ -803,9 +860,11 @@ def relative_glob(start, f):
             return []
 
     base_path = io.dirname(template_file_name)
-    template_source = TemplateSource(base_path, io.basename(template_file_name))
+    template_source = TemplateSource(
+        base_path, io.basename(template_file_name))
     template_source.load_template_from_file()
-    register_all_params_in_workload(template_source.assembled_source, complete_workload_params)
+    register_all_params_in_workload(
+        template_source.assembled_source, complete_workload_params)
 
     return render_template(loader=jinja2.FileSystemLoader(base_path),
                            template_source=template_source.assembled_source,
@@ -843,7 +902,8 @@ def _filters_from_filtered_tasks(self, filtered_tasks):
                         raise exceptions.SystemSetupError(f"Invalid format for filtered tasks: [{t}]. "
                                                           f"Expected [type] but got [{spec[0]}].")
                 else:
-                    raise exceptions.SystemSetupError(f"Invalid format for filtered tasks: [{t}]")
+                    raise exceptions.SystemSetupError(
+                        f"Invalid format for filtered tasks: [{t}]")
         return filters
 
     def _filter_out_match(self, task):
@@ -874,7 +934,8 @@ def on_after_load_workload(self, input_workload, **kwargs):
                                          leaf_task, test_procedure)
                         task.remove_task(leaf_task)
             for task in tasks_to_remove:
-                self.logger.info("Removing task [%s] from test_procedure [%s] due to task filter.", task, test_procedure)
+                self.logger.info(
+                    "Removing task [%s] from test_procedure [%s] due to task filter.", task, test_procedure)
                 test_procedure.remove_task(task)
 
         return input_workload
@@ -882,16 +943,19 @@ def on_after_load_workload(self, input_workload, **kwargs):
 
 class TestModeWorkloadProcessor(WorkloadProcessor):
     def __init__(self, cfg):
-        self.test_mode_enabled = cfg.opts("workload", "test.mode.enabled", mandatory=False, default_value=False)
+        self.test_mode_enabled = cfg.opts(
+            "workload", "test.mode.enabled", mandatory=False, default_value=False)
         self.logger = logging.getLogger(__name__)
 
     def on_after_load_workload(self, input_workload, **kwargs):
         if not self.test_mode_enabled:
             return input_workload
-        self.logger.info("Preparing workload [%s] for test mode.", str(input_workload))
+        self.logger.info(
+            "Preparing workload [%s] for test mode.", str(input_workload))
         for corpus in input_workload.corpora:
             if self.logger.isEnabledFor(logging.DEBUG):
-                self.logger.debug("Reducing corpus size to 1000 documents for [%s]", corpus.name)
+                self.logger.debug(
+                    "Reducing corpus size to 1000 documents for [%s]", corpus.name)
             for document_set in corpus.documents:
                 # TODO #341: Should we allow this for snapshots too?
                 if document_set.is_bulk:
@@ -908,7 +972,7 @@ def on_after_load_workload(self, input_workload, **kwargs):
                         document_set.document_file = f"{path}-1k{ext}"
                     else:
                         raise exceptions.BenchmarkAssertionError(f"Document corpus [{corpus.name}] has neither compressed "
-                                                             f"nor uncompressed corpus.")
+                                                                 f"nor uncompressed corpus.")
 
                     # we don't want to check sizes
                     document_set.compressed_size_in_bytes = None
@@ -923,12 +987,14 @@ def on_after_load_workload(self, input_workload, **kwargs):
                     if leaf_task.warmup_iterations is not None and leaf_task.warmup_iterations > leaf_task.clients:
                         count = leaf_task.clients
                         if self.logger.isEnabledFor(logging.DEBUG):
-                            self.logger.debug("Resetting warmup iterations to %d for [%s]", count, str(leaf_task))
+                            self.logger.debug(
+                                "Resetting warmup iterations to %d for [%s]", count, str(leaf_task))
                         leaf_task.warmup_iterations = count
                     if leaf_task.iterations is not None and leaf_task.iterations > leaf_task.clients:
                         count = leaf_task.clients
                         if self.logger.isEnabledFor(logging.DEBUG):
-                            self.logger.debug("Resetting measurement iterations to %d for [%s]", count, str(leaf_task))
+                            self.logger.debug(
+                                "Resetting measurement iterations to %d for [%s]", count, str(leaf_task))
                         leaf_task.iterations = count
                     if leaf_task.warmup_time_period is not None and leaf_task.warmup_time_period > 0:
                         leaf_task.warmup_time_period = 0
@@ -950,16 +1016,22 @@ def on_after_load_workload(self, input_workload, **kwargs):
 
         return input_workload
 
+
 class QueryRandomizerWorkloadProcessor(WorkloadProcessor):
     DEFAULT_RF = 0.3
     DEFAULT_N = 5000
     DEFAULT_ALPHA = 1
+
     def __init__(self, cfg):
-        self.randomization_enabled = cfg.opts("workload", "randomization.enabled", mandatory=False, default_value=False)
-        self.rf = float(cfg.opts("workload", "randomization.repeat_frequency", mandatory=False, default_value=self.DEFAULT_RF))
+        self.randomization_enabled = cfg.opts(
+            "workload", "randomization.enabled", mandatory=False, default_value=False)
+        self.rf = float(cfg.opts("workload", "randomization.repeat_frequency",
+                        mandatory=False, default_value=self.DEFAULT_RF))
         self.logger = logging.getLogger(__name__)
-        self.N = int(cfg.opts("workload", "randomization.n", mandatory=False, default_value=self.DEFAULT_N))
-        self.zipf_alpha = float(cfg.opts("workload", "randomization.alpha", mandatory=False, default_value=self.DEFAULT_ALPHA))
+        self.N = int(cfg.opts("workload", "randomization.n",
+                     mandatory=False, default_value=self.DEFAULT_N))
+        self.zipf_alpha = float(cfg.opts(
+            "workload", "randomization.alpha", mandatory=False, default_value=self.DEFAULT_ALPHA))
         self.H_list = self.precompute_H(self.N, self.zipf_alpha)
 
     # Helper functions for computing Zipf distribution
@@ -1001,7 +1073,7 @@ def get_dict_from_previous_path(self, root, current_path):
     def extract_fields_helper(self, root, current_path):
         # Recursively called to find the location of ranges in an OpenSearch range query.
         # Return the field and the current path if we're currently scanning the field name in a range query, otherwise return an empty list.
-        fields = [] # pairs of (field, path_to_field)
+        fields = []  # pairs of (field, path_to_field)
         curr = self.get_dict_from_previous_path(root, current_path)
         if isinstance(curr, dict) and curr != {}:
             if len(current_path) > 0 and current_path[-1] == "range":
@@ -1012,7 +1084,8 @@ def extract_fields_helper(self, root, current_path):
                 return fields
             else:
                 for key in curr.keys():
-                    fields += self.extract_fields_helper(root, current_path + [key])
+                    fields += self.extract_fields_helper(
+                        root, current_path + [key])
                 return fields
         elif isinstance(curr, list) and curr != []:
             for i in range(len(curr)):
@@ -1041,7 +1114,8 @@ def set_range(self, params, fields_and_paths, new_values):
         for field_and_path, new_value in zip(fields_and_paths, new_values):
             field = field_and_path[0]
             path = field_and_path[1]
-            range_section = self.get_dict_from_previous_path(params["body"]["query"], path)[field]
+            range_section = self.get_dict_from_previous_path(
+                params["body"]["query"], path)[field]
             # get the section of the query corresponding to the field name
             for greater_than in ["gte", "gt"]:
                 if greater_than in range_section:
@@ -1059,26 +1133,32 @@ def get_repeated_value_index(self):
 
     def get_randomized_values(self, input_workload, input_params,
                               get_standard_value=params.get_standard_value,
-                              get_standard_value_source=params.get_standard_value_source, # Made these configurable for simpler unit tests
+                              # Made these configurable for simpler unit tests
+                              get_standard_value_source=params.get_standard_value_source,
                               **kwargs):
 
         # The queries as listed in operations/default.json don't have the index param,
         # unlike the custom ones you would specify in workload.py, so we have to add them ourselves
         if not "index" in input_params:
-            input_params["index"] = params.get_target(input_workload, input_params)
+            input_params["index"] = params.get_target(
+                input_workload, input_params)
 
         fields_and_paths = self.extract_fields_and_paths(input_params)
 
         if random.random() < self.rf:
             # Draw a potentially repeated value from the saved standard values
             index = self.get_repeated_value_index()
-            new_values = [get_standard_value(kwargs["op_name"], field_and_path[0], index) for field_and_path in fields_and_paths]
+            new_values = [get_standard_value(
+                kwargs["op_name"], field_and_path[0], index) for field_and_path in fields_and_paths]
             # Use the same index for all fields in one query, otherwise the probability of repeats in a multi-field query would be very low
-            input_params = self.set_range(input_params, fields_and_paths, new_values)
+            input_params = self.set_range(
+                input_params, fields_and_paths, new_values)
         else:
             # Generate a new random value, from the standard value source function. This will be new (a cache miss)
-            new_values = [get_standard_value_source(kwargs["op_name"], field_and_path[0])() for field_and_path in fields_and_paths]
-            input_params = self.set_range(input_params, fields_and_paths, new_values)
+            new_values = [get_standard_value_source(
+                kwargs["op_name"], field_and_path[0])() for field_and_path in fields_and_paths]
+            input_params = self.set_range(
+                input_params, fields_and_paths, new_values)
         return input_params
 
     def create_param_source_lambda(self, op_name, get_standard_value, get_standard_value_source):
@@ -1091,7 +1171,8 @@ def on_after_load_workload(self, input_workload, **kwargs):
         if not self.randomization_enabled:
             self.logger.info("Query randomization is disabled.")
             return input_workload
-        self.logger.info("Query randomization is enabled, with repeat frequency = %d, n = %d",self.rf, self.N)
+        self.logger.info(
+            "Query randomization is enabled, with repeat frequency = %d, n = %d", self.rf, self.N)
 
         # By default, use params for standard values and generate new standard values the first time an op/field is seen.
         # In unit tests, we should be able to supply our own sources independent of params.
@@ -1113,7 +1194,8 @@ def on_after_load_workload(self, input_workload, **kwargs):
         for task in default_test_procedure.schedule:
             for leaf_task in task:
                 try:
-                    op_type = workload.OperationType.from_hyphenated_string(leaf_task.operation.type)
+                    op_type = workload.OperationType.from_hyphenated_string(
+                        leaf_task.operation.type)
                 except KeyError:
                     op_type = None
                     self.logger.info(
@@ -1130,9 +1212,11 @@ def on_after_load_workload(self, input_workload, **kwargs):
                     # Generate the right number of standard values for this field, if not already present
                     for field_and_path in self.extract_fields_and_paths(leaf_task.operation.params):
                         if generate_new_standard_values:
-                            params.generate_standard_values_if_absent(op_name, field_and_path[0], self.N)
+                            params.generate_standard_values_if_absent(
+                                op_name, field_and_path[0], self.N)
         return input_workload
 
+
 class CompleteWorkloadParams:
     def __init__(self, user_specified_workload_params=None):
         self.workload_defined_params = set()
@@ -1169,15 +1253,18 @@ class WorkloadFileReader:
     """
 
     def __init__(self, cfg):
-        workload_schema_file = os.path.join(cfg.opts("node", "benchmark.root"), "resources", "workload-schema.json")
+        workload_schema_file = os.path.join(
+            cfg.opts("node", "benchmark.root"), "resources", "workload-schema.json")
         with open(workload_schema_file, mode="rt", encoding="utf-8") as f:
             self.workload_schema = json.loads(f.read())
         self.workload_params = cfg.opts("workload", "params", mandatory=False)
-        self.complete_workload_params = CompleteWorkloadParams(user_specified_workload_params=self.workload_params)
+        self.complete_workload_params = CompleteWorkloadParams(
+            user_specified_workload_params=self.workload_params)
         self.read_workload = WorkloadSpecificationReader(
             workload_params=self.workload_params,
             complete_workload_params=self.complete_workload_params,
-            selected_test_procedure=cfg.opts("workload", "test_procedure.name", mandatory=False)
+            selected_test_procedure=cfg.opts(
+                "workload", "test_procedure.name", mandatory=False)
         )
         self.logger = logging.getLogger(__name__)
 
@@ -1191,7 +1278,8 @@ def read(self, workload_name, workload_spec_file, mapping_dir):
         :return: A corresponding workload instance if the workload file is valid.
         """
 
-        self.logger.info("Reading workload specification file [%s].", workload_spec_file)
+        self.logger.info(
+            "Reading workload specification file [%s].", workload_spec_file)
         # render the workload to a temporary file instead of dumping it into the logs. It is easier to check for error messages
         # involving lines numbers and it also does not bloat Benchmark's log file so much.
         tmp = tempfile.NamedTemporaryFile(delete=False, suffix=".json")
@@ -1201,12 +1289,14 @@ def read(self, workload_name, workload_spec_file, mapping_dir):
                 complete_workload_params=self.complete_workload_params)
             with open(tmp.name, "wt", encoding="utf-8") as f:
                 f.write(rendered)
-            self.logger.info("Final rendered workload for '%s' has been written to '%s'.", workload_spec_file, tmp.name)
+            self.logger.info(
+                "Final rendered workload for '%s' has been written to '%s'.", workload_spec_file, tmp.name)
             workload_spec = json.loads(rendered)
 
         except jinja2.exceptions.TemplateNotFound:
             self.logger.exception("Could not load [%s]", workload_spec_file)
-            raise exceptions.SystemSetupError("Workload {} does not exist".format(workload_name))
+            raise exceptions.SystemSetupError(
+                "Workload {} does not exist".format(workload_name))
 
         except jinja2.exceptions.TemplateSyntaxError as e:
             exception_message = f"Jinja2 Exception TemplateSyntaxError: {e}\n"
@@ -1220,7 +1310,6 @@ def read(self, workload_name, workload_spec_file, mapping_dir):
 
             raise exceptions.SystemSetupError(exception_message)
 
-
         except json.JSONDecodeError as e:
             self.logger.exception("Could not load [%s].", workload_spec_file)
             msg = "Could not load '{}': {}.".format(workload_spec_file, str(e))
@@ -1231,9 +1320,12 @@ def read(self, workload_name, workload_spec_file, mapping_dir):
                 ctx_start = max(0, line_idx - ctx_line_count)
                 ctx_end = min(line_idx + ctx_line_count, len(lines))
                 erroneous_lines = lines[ctx_start:ctx_end]
-                erroneous_lines.insert(line_idx - ctx_start + 1, "-" * (e.colno - 1) + "^ Error is here")
-                msg += " Lines containing the error:\n\n{}\n\n".format("\n".join(erroneous_lines))
-            msg += "The complete workload has been written to '{}' for diagnosis. \n\n".format(tmp.name)
+                erroneous_lines.insert(
+                    line_idx - ctx_start + 1, "-" * (e.colno - 1) + "^ Error is here")
+                msg += " Lines containing the error:\n\n{}\n\n".format(
+                    "\n".join(erroneous_lines))
+            msg += "The complete workload has been written to '{}' for diagnosis. \n\n".format(
+                tmp.name)
             console_message = f"Suggestion: Verify that [{workload_name}] workload has correctly formatted JSON files and " + \
                 "Jinja Templates. For Jinja2 errors, consider using a live Jinja2 parser. " + \
                 f"See common workload formatting errors:{WorkloadFileReader.COMMON_WORKLOAD_FORMAT_ERRORS}"
@@ -1252,7 +1344,8 @@ def read(self, workload_name, workload_spec_file, mapping_dir):
             # Convert to string early on to avoid serialization errors with Jinja exceptions.
             raise WorkloadSyntaxError(msg, str(e))
         # check the workload version before even attempting to validate the JSON format to avoid bogus errors.
-        raw_version = workload_spec.get("version", WorkloadFileReader.MAXIMUM_SUPPORTED_TRACK_VERSION)
+        raw_version = workload_spec.get(
+            "version", WorkloadFileReader.MAXIMUM_SUPPORTED_TRACK_VERSION)
         try:
             workload_version = int(raw_version)
         except ValueError:
@@ -1260,15 +1353,15 @@ def read(self, workload_name, workload_spec_file, mapping_dir):
                 workload_name, str(raw_version)))
         if WorkloadFileReader.MINIMUM_SUPPORTED_TRACK_VERSION > workload_version:
             raise exceptions.BenchmarkError("Workload {} is on version {} but needs to be updated at least to version {} to work with the "
-                                        "current version of Benchmark.".format(workload_name, workload_version,
-                                                                           WorkloadFileReader.MINIMUM_SUPPORTED_TRACK_VERSION))
+                                            "current version of Benchmark.".format(workload_name, workload_version,
+                                                                                   WorkloadFileReader.MINIMUM_SUPPORTED_TRACK_VERSION))
         if WorkloadFileReader.MAXIMUM_SUPPORTED_TRACK_VERSION < workload_version:
             raise exceptions.BenchmarkError("Workload {} requires a newer version of Benchmark. "
-                        "Please upgrade Benchmark (supported workload version: {}, "
-                                        "required workload version: {}).".format(
-                                            workload_name,
-                                            WorkloadFileReader.MAXIMUM_SUPPORTED_TRACK_VERSION,
-                                                                              workload_version))
+                                            "Please upgrade Benchmark (supported workload version: {}, "
+                                            "required workload version: {}).".format(
+                                                workload_name,
+                                                WorkloadFileReader.MAXIMUM_SUPPORTED_TRACK_VERSION,
+                                                workload_version))
         try:
             jsonschema.validate(workload_spec, self.workload_schema)
         except jsonschema.exceptions.ValidationError as ve:
@@ -1276,10 +1369,11 @@ def read(self, workload_name, workload_spec_file, mapping_dir):
                 "Workload '{}' is invalid.\n\nError details: {}\nInstance: {}\nPath: {}\nSchema path: {}".format(
                     workload_name, ve.message, json.dumps(
                         ve.instance, indent=4, sort_keys=True),
-                        ve.absolute_path, ve.absolute_schema_path))
+                    ve.absolute_path, ve.absolute_schema_path))
 
         try:
-            current_workload = self.read_workload(workload_name, workload_spec, mapping_dir)
+            current_workload = self.read_workload(
+                workload_name, workload_spec, mapping_dir)
         except Exception as e:
             console.error(e)
             raise
@@ -1292,19 +1386,22 @@ def read(self, workload_name, workload_spec_file, mapping_dir):
                 "{}\n\n"
                 "All parameters exposed by this workload:\n"
                 "{}".format(
-                    ",".join(opts.double_quoted_list_of(sorted(unused_user_defined_workload_params))),
+                    ",".join(opts.double_quoted_list_of(
+                        sorted(unused_user_defined_workload_params))),
                     ",".join(opts.double_quoted_list_of(sorted(opts.make_list_of_close_matches(
                         unused_user_defined_workload_params,
                         self.complete_workload_params.workload_defined_params
                     )))),
-                    "\n".join(opts.bulleted_list_of(sorted(list(self.workload_params.keys())))),
+                    "\n".join(opts.bulleted_list_of(
+                        sorted(list(self.workload_params.keys())))),
                     "\n".join(opts.bulleted_list_of(self.complete_workload_params.sorted_workload_defined_params))))
 
             self.logger.critical(err_msg)
             # also dump the message on the console
             console.println(err_msg)
             raise exceptions.WorkloadConfigError(
-                "Unused workload parameters {}.".format(sorted(unused_user_defined_workload_params))
+                "Unused workload parameters {}.".format(
+                    sorted(unused_user_defined_workload_params))
             )
         return current_workload
 
@@ -1318,7 +1415,8 @@ def __init__(self, workload_plugin_path, runner_registry=None, scheduler_registr
         self.runner_registry = runner_registry
         self.scheduler_registry = scheduler_registry
         self.workload_processor_registry = workload_processor_registry
-        self.loader = modules.ComponentLoader(root_path=workload_plugin_path, component_entry_point="workload")
+        self.loader = modules.ComponentLoader(
+            root_path=workload_plugin_path, component_entry_point="workload")
 
     def can_load(self):
         return self.loader.can_load()
@@ -1350,7 +1448,8 @@ def register_workload_processor(self, workload_processor):
 
     def register_standard_value_source(self, op_name, field_name, standard_value_source):
         # Define a value source for parameters for a given operation name and field name, for use in randomization
-        params.register_standard_value_source(op_name, field_name, standard_value_source)
+        params.register_standard_value_source(
+            op_name, field_name, standard_value_source)
 
     @property
     def meta_data(self):
@@ -1375,7 +1474,8 @@ def __init__(self, workload_params=None, complete_workload_params=None, selected
 
     def __call__(self, workload_name, workload_specification, mapping_dir):
         self.name = workload_name
-        description = self._r(workload_specification, "description", mandatory=False, default_value="")
+        description = self._r(workload_specification,
+                              "description", mandatory=False, default_value="")
 
         meta_data = self._r(workload_specification, "meta", mandatory=False)
         indices = [self._create_index(idx, mapping_dir)
@@ -1384,25 +1484,27 @@ def __call__(self, workload_name, workload_specification, mapping_dir):
                         for idx in self._r(workload_specification, "data-streams", mandatory=False, default_value=[])]
         if len(indices) > 0 and len(data_streams) > 0:
             # we guard against this early and support either or
-            raise WorkloadSyntaxError("indices and data-streams cannot both be specified")
+            raise WorkloadSyntaxError(
+                "indices and data-streams cannot both be specified")
         templates = [self._create_index_template(tpl, mapping_dir)
                      for tpl in self._r(workload_specification, "templates", mandatory=False, default_value=[])]
         composable_templates = [self._create_index_template(tpl, mapping_dir)
-                     for tpl in self._r(workload_specification, "composable-templates", mandatory=False, default_value=[])]
+                                for tpl in self._r(workload_specification, "composable-templates", mandatory=False, default_value=[])]
         component_templates = [self._create_component_template(tpl, mapping_dir)
-                     for tpl in self._r(workload_specification, "component-templates", mandatory=False, default_value=[])]
+                               for tpl in self._r(workload_specification, "component-templates", mandatory=False, default_value=[])]
         corpora = self._create_corpora(self._r(workload_specification, "corpora", mandatory=False, default_value=[]),
                                        indices, data_streams)
         test_procedures = self._create_test_procedures(workload_specification)
         # at this point, *all* workload params must have been referenced in the templates
         return workload.Workload(name=self.name, meta_data=meta_data,
-        description=description, test_procedures=test_procedures,
-        indices=indices,
-                           data_streams=data_streams, templates=templates, composable_templates=composable_templates,
-                           component_templates=component_templates, corpora=corpora)
+                                 description=description, test_procedures=test_procedures,
+                                 indices=indices,
+                                 data_streams=data_streams, templates=templates, composable_templates=composable_templates,
+                                 component_templates=component_templates, corpora=corpora)
 
     def _error(self, msg):
-        raise WorkloadSyntaxError("Workload '%s' is invalid. %s" % (self.name, msg))
+        raise WorkloadSyntaxError(
+            "Workload '%s' is invalid. %s" % (self.name, msg))
 
     def _r(self, root, path, error_ctx=None, mandatory=True, default_value=None):
         if isinstance(path, str):
@@ -1416,9 +1518,11 @@ def _r(self, root, path, error_ctx=None, mandatory=True, default_value=None):
         except KeyError:
             if mandatory:
                 if error_ctx:
-                    self._error("Mandatory element '%s' is missing in '%s'." % (".".join(path), error_ctx))
+                    self._error("Mandatory element '%s' is missing in '%s'." % (
+                        ".".join(path), error_ctx))
                 else:
-                    self._error("Mandatory element '%s' is missing." % ".".join(path))
+                    self._error("Mandatory element '%s' is missing." %
+                                ".".join(path))
             else:
                 return default_value
 
@@ -1426,7 +1530,8 @@ def _create_index(self, index_spec, mapping_dir):
         index_name = self._r(index_spec, "name")
         body_file = self._r(index_spec, "body", mandatory=False)
         if body_file:
-            idx_body_tmpl_src = TemplateSource(mapping_dir, body_file, self.source)
+            idx_body_tmpl_src = TemplateSource(
+                mapping_dir, body_file, self.source)
             with self.source(os.path.join(mapping_dir, body_file), "rt") as f:
                 idx_body_tmpl_src.load_template_from_string(f.read())
                 body = self._load_template(
@@ -1456,7 +1561,8 @@ def _create_index_template(self, tpl_spec, mapping_dir):
         name = self._r(tpl_spec, "name")
         template_file = self._r(tpl_spec, "template")
         index_pattern = self._r(tpl_spec, "index-pattern")
-        delete_matching_indices = self._r(tpl_spec, "delete-matching-indices", mandatory=False, default_value=True)
+        delete_matching_indices = self._r(
+            tpl_spec, "delete-matching-indices", mandatory=False, default_value=True)
         template_file = os.path.join(mapping_dir, template_file)
         idx_tmpl_src = TemplateSource(mapping_dir, template_file, self.source)
         with self.source(template_file, "rt") as f:
@@ -1468,18 +1574,22 @@ def _create_index_template(self, tpl_spec, mapping_dir):
 
     def _load_template(self, contents, description):
         self.logger.info("Loading template [%s].", description)
-        register_all_params_in_workload(contents, self.complete_workload_params)
+        register_all_params_in_workload(
+            contents, self.complete_workload_params)
         try:
             rendered = render_template(template_source=contents,
                                        template_vars=self.workload_params)
             return json.loads(rendered)
         except Exception as e:
-            self.logger.exception("Could not load file template for %s.", description)
-            raise WorkloadSyntaxError("Could not load file template for '%s'" % description, str(e))
+            self.logger.exception(
+                "Could not load file template for %s.", description)
+            raise WorkloadSyntaxError(
+                "Could not load file template for '%s'" % description, str(e))
 
     def _create_corpora(self, corpora_specs, indices, data_streams):
         if len(indices) > 0 and len(data_streams) > 0:
-            raise WorkloadSyntaxError("indices and data-streams cannot both be specified")
+            raise WorkloadSyntaxError(
+                "indices and data-streams cannot both be specified")
         document_corpora = []
         known_corpora_names = set()
         for corpus_spec in corpora_specs:
@@ -1489,10 +1599,12 @@ def _create_corpora(self, corpora_specs, indices, data_streams):
                 self._error("Duplicate document corpus name [%s]." % name)
             known_corpora_names.add(name)
 
-            meta_data = self._r(corpus_spec, "meta", error_ctx=name, mandatory=False)
+            meta_data = self._r(corpus_spec, "meta",
+                                error_ctx=name, mandatory=False)
             corpus = workload.DocumentCorpus(name=name, meta_data=meta_data)
             # defaults on corpus level
-            default_base_url = self._r(corpus_spec, "base-url", mandatory=False, default_value=None)
+            default_base_url = self._r(
+                corpus_spec, "base-url", mandatory=False, default_value=None)
             default_source_format = self._r(corpus_spec, "source-format", mandatory=False,
                                             default_value=workload.Documents.SOURCE_FORMAT_BULK)
             default_action_and_meta_data = self._r(corpus_spec, "includes-action-and-meta-data", mandatory=False,
@@ -1502,32 +1614,40 @@ def _create_corpora(self, corpora_specs, indices, data_streams):
             corpus_target_type = None
 
             if len(indices) == 1:
-                corpus_target_idx = self._r(corpus_spec, "target-index", mandatory=False, default_value=indices[0].name)
+                corpus_target_idx = self._r(
+                    corpus_spec, "target-index", mandatory=False, default_value=indices[0].name)
             elif len(indices) > 0:
-                corpus_target_idx = self._r(corpus_spec, "target-index", mandatory=False)
+                corpus_target_idx = self._r(
+                    corpus_spec, "target-index", mandatory=False)
 
             if len(data_streams) == 1:
                 corpus_target_ds = self._r(corpus_spec, "target-data-stream", mandatory=False,
                                            default_value=data_streams[0].name)
             elif len(data_streams) > 0:
-                corpus_target_ds = self._r(corpus_spec, "target-data-stream", mandatory=False)
+                corpus_target_ds = self._r(
+                    corpus_spec, "target-data-stream", mandatory=False)
 
             if len(indices) == 1 and len(indices[0].types) == 1:
                 corpus_target_type = self._r(corpus_spec, "target-type", mandatory=False,
                                              default_value=indices[0].types[0])
             elif len(indices) > 0:
-                corpus_target_type = self._r(corpus_spec, "target-type", mandatory=False)
+                corpus_target_type = self._r(
+                    corpus_spec, "target-type", mandatory=False)
 
             for doc_spec in self._r(corpus_spec, "documents"):
-                base_url = self._r(doc_spec, "base-url", mandatory=False, default_value=default_base_url)
-                source_format = self._r(doc_spec, "source-format", mandatory=False, default_value=default_source_format)
+                base_url = self._r(
+                    doc_spec, "base-url", mandatory=False, default_value=default_base_url)
+                source_format = self._r(
+                    doc_spec, "source-format", mandatory=False, default_value=default_source_format)
 
                 if source_format in workload.Documents.SUPPORTED_SOURCE_FORMAT:
-                    source_url = self._r(doc_spec, "source-url", mandatory=False)
+                    source_url = self._r(
+                        doc_spec, "source-url", mandatory=False)
                     docs = self._r(doc_spec, "source-file")
                     document_file_parts = list()
                     for parts in self._r(doc_spec, "source-file-parts", mandatory=False, default_value=[]):
-                        document_file_parts.append( { "name": self._r(parts, "name"), "size": self._r(parts, "size") } )
+                        document_file_parts.append(
+                            {"name": self._r(parts, "name"), "size": self._r(parts, "size")})
                     if io.is_archive(docs):
                         document_archive = docs
                         document_file = io.splitext(docs)[0]
@@ -1535,9 +1655,12 @@ def _create_corpora(self, corpora_specs, indices, data_streams):
                         document_archive = None
                         document_file = docs
                     num_docs = self._r(doc_spec, "document-count")
-                    compressed_bytes = self._r(doc_spec, "compressed-bytes", mandatory=False)
-                    uncompressed_bytes = self._r(doc_spec, "uncompressed-bytes", mandatory=False)
-                    doc_meta_data = self._r(doc_spec, "meta", error_ctx=name, mandatory=False)
+                    compressed_bytes = self._r(
+                        doc_spec, "compressed-bytes", mandatory=False)
+                    uncompressed_bytes = self._r(
+                        doc_spec, "uncompressed-bytes", mandatory=False)
+                    doc_meta_data = self._r(
+                        doc_spec, "meta", error_ctx=name, mandatory=False)
 
                     includes_action_and_meta_data = self._r(doc_spec, "includes-action-and-meta-data", mandatory=False,
                                                             default_value=default_action_and_meta_data)
@@ -1551,64 +1674,79 @@ def _create_corpora(self, corpora_specs, indices, data_streams):
 
                         # require to be specified if we're using data streams and we have no default
                         target_ds = self._r(doc_spec, "target-data-stream",
-                                            mandatory=len(data_streams) > 0 and corpus_target_ds is None,
+                                            mandatory=len(
+                                                data_streams) > 0 and corpus_target_ds is None,
                                             default_value=corpus_target_ds,
                                             error_ctx=docs)
                         if target_ds and len(indices) > 0:
                             # if indices are in use we error
-                            raise WorkloadSyntaxError("target-data-stream cannot be used when using indices")
+                            raise WorkloadSyntaxError(
+                                "target-data-stream cannot be used when using indices")
                         elif target_ds and target_type:
-                            raise WorkloadSyntaxError("target-type cannot be used when using data-streams")
+                            raise WorkloadSyntaxError(
+                                "target-type cannot be used when using data-streams")
 
                         # need an index if we're using indices and no meta-data are present and we don't have a default
                         target_idx = self._r(doc_spec, "target-index",
-                                             mandatory=len(indices) > 0 and corpus_target_idx is None,
+                                             mandatory=len(
+                                                 indices) > 0 and corpus_target_idx is None,
                                              default_value=corpus_target_idx,
                                              error_ctx=docs)
                         # either target_idx or target_ds
                         if target_idx and len(data_streams) > 0:
                             # if data streams are in use we error
-                            raise WorkloadSyntaxError("target-index cannot be used when using data-streams")
+                            raise WorkloadSyntaxError(
+                                "target-index cannot be used when using data-streams")
 
                         # we need one or the other
                         if target_idx is None and target_ds is None:
                             raise WorkloadSyntaxError(f"a {'target-index' if len(indices) > 0 else 'target-data-stream'} "
-                                                   f"is required for {docs}" )
+                                                      f"is required for {docs}")
 
                     docs = workload.Documents(source_format=source_format,
-                                           document_file=document_file,
-                                           document_file_parts=document_file_parts,
-                                           document_archive=document_archive,
-                                           base_url=base_url,
-                                           source_url=source_url,
-                                           includes_action_and_meta_data=includes_action_and_meta_data,
-                                           number_of_documents=num_docs,
-                                           compressed_size_in_bytes=compressed_bytes,
-                                           uncompressed_size_in_bytes=uncompressed_bytes,
-                                           target_index=target_idx, target_type=target_type,
-                                           target_data_stream=target_ds, meta_data=doc_meta_data)
+                                              document_file=document_file,
+                                              document_file_parts=document_file_parts,
+                                              document_archive=document_archive,
+                                              base_url=base_url,
+                                              source_url=source_url,
+                                              includes_action_and_meta_data=includes_action_and_meta_data,
+                                              number_of_documents=num_docs,
+                                              compressed_size_in_bytes=compressed_bytes,
+                                              uncompressed_size_in_bytes=uncompressed_bytes,
+                                              target_index=target_idx, target_type=target_type,
+                                              target_data_stream=target_ds, meta_data=doc_meta_data)
                     corpus.documents.append(docs)
                 else:
-                    self._error("Unknown source-format [%s] in document corpus [%s]." % (source_format, name))
+                    self._error(
+                        "Unknown source-format [%s] in document corpus [%s]." % (source_format, name))
             document_corpora.append(corpus)
         return document_corpora
 
     def _create_test_procedures(self, workload_spec):
-        ops = self.parse_operations(self._r(workload_spec, "operations", mandatory=False, default_value=[]))
-        workload_params = self._r(workload_spec, "parameters", mandatory=False, default_value={})
+        ops = self.parse_operations(
+            self._r(workload_spec, "operations", mandatory=False, default_value=[]))
+        workload_params = self._r(
+            workload_spec, "parameters", mandatory=False, default_value={})
         test_procedures = []
         known_test_procedure_names = set()
         default_test_procedure = None
-        test_procedure_specs, auto_generated = self._get_test_procedure_specs(workload_spec)
+        test_procedure_specs, auto_generated = self._get_test_procedure_specs(
+            workload_spec)
         number_of_test_procedures = len(test_procedure_specs)
         for test_procedure_spec in test_procedure_specs:
-            name = self._r(test_procedure_spec, "name", error_ctx="test_procedures")
-            description = self._r(test_procedure_spec, "description", error_ctx=name, mandatory=False)
-            user_info = self._r(test_procedure_spec, "user-info", error_ctx=name, mandatory=False)
-            test_procedure_params = self._r(test_procedure_spec, "parameters", error_ctx=name, mandatory=False, default_value={})
-            meta_data = self._r(test_procedure_spec, "meta", error_ctx=name, mandatory=False)
+            name = self._r(test_procedure_spec, "name",
+                           error_ctx="test_procedures")
+            description = self._r(
+                test_procedure_spec, "description", error_ctx=name, mandatory=False)
+            user_info = self._r(test_procedure_spec,
+                                "user-info", error_ctx=name, mandatory=False)
+            test_procedure_params = self._r(
+                test_procedure_spec, "parameters", error_ctx=name, mandatory=False, default_value={})
+            meta_data = self._r(test_procedure_spec, "meta",
+                                error_ctx=name, mandatory=False)
             # if we only have one test_procedure it is treated as default test_procedure, no matter what the user has specified
-            default = number_of_test_procedures == 1 or self._r(test_procedure_spec, "default", error_ctx=name, mandatory=False)
+            default = number_of_test_procedures == 1 or self._r(
+                test_procedure_spec, "default", error_ctx=name, mandatory=False)
             selected = number_of_test_procedures == 1 or self.selected_test_procedure == name
             if default and default_test_procedure is not None:
                 self._error("Both '%s' and '%s' are defined as default test_procedures. Please define only one of them as default."
@@ -1621,12 +1759,13 @@ def _create_test_procedures(self, workload_spec):
 
             for op in self._r(test_procedure_spec, "schedule", error_ctx=name):
                 if "clients_list" in op:
-                    self.logger.info("Clients list specified: %s. Running multiple search tasks, "\
+                    self.logger.info("Clients list specified: %s. Running multiple search tasks, "
                                      "each scheduled with the corresponding number of clients from the list.", op["clients_list"])
                     for num_clients in op["clients_list"]:
                         op["clients"] = num_clients
 
-                        new_name = self._rename_task_based_on_num_clients(name, num_clients)
+                        new_name = self._rename_task_based_on_num_clients(
+                            name, num_clients)
 
                         new_name = name + "_" + str(num_clients) + "_clients"
                         new_task = self.parse_task(op, ops, new_name)
@@ -1651,17 +1790,18 @@ def _create_test_procedures(self, workload_spec):
                         known_task_names.add(sub_task.name)
 
             # merge params
-            final_test_procedure_params = dict(collections.merge_dicts(workload_params, test_procedure_params))
+            final_test_procedure_params = dict(
+                collections.merge_dicts(workload_params, test_procedure_params))
 
             test_procedure = workload.TestProcedure(name=name,
-                                        parameters=final_test_procedure_params,
-                                        meta_data=meta_data,
-                                        description=description,
-                                        user_info=user_info,
-                                        default=default,
-                                        selected=selected,
-                                        auto_generated=auto_generated,
-                                        schedule=schedule)
+                                                    parameters=final_test_procedure_params,
+                                                    meta_data=meta_data,
+                                                    description=description,
+                                                    user_info=user_info,
+                                                    default=default,
+                                                    selected=selected,
+                                                    auto_generated=auto_generated,
+                                                    schedule=schedule)
             if default:
                 default_test_procedure = test_procedure
 
@@ -1670,14 +1810,14 @@ def _create_test_procedures(self, workload_spec):
         if test_procedures and default_test_procedure is None:
             self._error(
                 "No default test_procedure specified. Please edit the workload and add \"default\": true to one of the test_procedures %s."
-                        % ", ".join([c.name for c in test_procedures]))
+                % ", ".join([c.name for c in test_procedures]))
         return test_procedures
 
     def _rename_task_based_on_num_clients(self, name: str, num_clients: int) -> str:
         has_underscore = "_" in name
         has_hyphen = "-" in name
         if has_underscore and has_hyphen:
-            self.logger.warning("The test procedure name %s contains a mix of _ and -. "\
+            self.logger.warning("The test procedure name %s contains a mix of _ and -. "
                                 "Consider changing the name to avoid frustrating bugs in the future.", name)
             return name + "_" + str(num_clients) + "_clients"
         elif has_hyphen:
@@ -1687,15 +1827,20 @@ def _rename_task_based_on_num_clients(self, name: str, num_clients: int) -> str:
 
     def _get_test_procedure_specs(self, workload_spec):
         schedule = self._r(workload_spec, "schedule", mandatory=False)
-        test_procedure = self._r(workload_spec, "test_procedure", mandatory=False)
-        test_procedures = self._r(workload_spec, "test_procedures", mandatory=False)
+        test_procedure = self._r(
+            workload_spec, "test_procedure", mandatory=False)
+        test_procedures = self._r(
+            workload_spec, "test_procedures", mandatory=False)
 
-        count_defined = len(list(filter(lambda e: e is not None, [schedule, test_procedure, test_procedures])))
+        count_defined = len(list(filter(lambda e: e is not None, [
+                            schedule, test_procedure, test_procedures])))
 
         if count_defined == 0:
-            self._error("You must define 'test_procedure', 'test_procedures' or 'schedule' but none is specified.")
+            self._error(
+                "You must define 'test_procedure', 'test_procedures' or 'schedule' but none is specified.")
         elif count_defined > 1:
-            self._error("Multiple out of 'test_procedure', 'test_procedures' or 'schedule' are defined but only one of them is allowed.")
+            self._error(
+                "Multiple out of 'test_procedure', 'test_procedures' or 'schedule' are defined but only one of them is allowed.")
         elif test_procedure is not None:
             return [test_procedure], False
         elif test_procedures is not None:
@@ -1712,30 +1857,37 @@ def _get_test_procedure_specs(self, workload_spec):
 
     def parse_parallel(self, ops_spec, ops, test_procedure_name):
         # use same default values as #parseTask() in case the 'parallel' element did not specify anything
-        default_warmup_iterations = self._r(ops_spec, "warmup-iterations", error_ctx="parallel", mandatory=False)
-        default_iterations = self._r(ops_spec, "iterations", error_ctx="parallel", mandatory=False)
-        default_warmup_time_period = self._r(ops_spec, "warmup-time-period", error_ctx="parallel", mandatory=False)
-        default_time_period = self._r(ops_spec, "time-period", error_ctx="parallel", mandatory=False)
-        default_ramp_up_time_period = self._r(ops_spec, "ramp-up-time-period", error_ctx="parallel", mandatory=False)
-        clients = self._r(ops_spec, "clients", error_ctx="parallel", mandatory=False)
-        completed_by = self._r(ops_spec, "completed-by", error_ctx="parallel", mandatory=False)
+        default_warmup_iterations = self._r(
+            ops_spec, "warmup-iterations", error_ctx="parallel", mandatory=False)
+        default_iterations = self._r(
+            ops_spec, "iterations", error_ctx="parallel", mandatory=False)
+        default_warmup_time_period = self._r(
+            ops_spec, "warmup-time-period", error_ctx="parallel", mandatory=False)
+        default_time_period = self._r(
+            ops_spec, "time-period", error_ctx="parallel", mandatory=False)
+        default_ramp_up_time_period = self._r(
+            ops_spec, "ramp-up-time-period", error_ctx="parallel", mandatory=False)
+        clients = self._r(ops_spec, "clients",
+                          error_ctx="parallel", mandatory=False)
+        completed_by = self._r(ops_spec, "completed-by",
+                               error_ctx="parallel", mandatory=False)
 
         # now descent to each operation
         tasks = []
         for task in self._r(ops_spec, "tasks", error_ctx="parallel"):
             tasks.append(self.parse_task(task, ops, test_procedure_name, default_warmup_iterations, default_iterations,
-                                         default_warmup_time_period, default_time_period, default_ramp_up_time_period, 
+                                         default_warmup_time_period, default_time_period, default_ramp_up_time_period,
                                          completed_by))
-            
+
         for task in tasks:
             if task.ramp_up_time_period != default_ramp_up_time_period:
-                 if default_ramp_up_time_period is None:
-                     self._error(f"task '{task.name}' in 'parallel' element of test-procedure '{test_procedure_name}' specifies "
+                if default_ramp_up_time_period is None:
+                    self._error(f"task '{task.name}' in 'parallel' element of test-procedure '{test_procedure_name}' specifies "
                                 f"a ramp-up-time-period but it is only allowed on the 'parallel' element.")
-                 else:
-                     self._error(f"task '{task.name}' specifies a different ramp-up-time-period than its enclosing "
+                else:
+                    self._error(f"task '{task.name}' specifies a different ramp-up-time-period than its enclosing "
                                 f"'parallel' element in test-procedure '{test_procedure_name}'.")
-                     
+
         if completed_by:
             completion_task = None
             for task in tasks:
@@ -1744,7 +1896,7 @@ def parse_parallel(self, ops_spec, ops, test_procedure_name):
                 elif task.completes_parent:
                     self._error(
                         "'parallel' element for test_procedure '%s' contains multiple tasks with the name '%s' which are marked with "
-                                "'completed-by' but only task is allowed to match." % (test_procedure_name, completed_by))
+                        "'completed-by' but only task is allowed to match." % (test_procedure_name, completed_by))
             if not completion_task:
                 self._error("'parallel' element for test_procedure '%s' is marked with 'completed-by' with task name '%s' but no task with "
                             "this name exists." % (test_procedure_name, completed_by))
@@ -1758,43 +1910,50 @@ def parse_task(self, task_spec, ops, test_procedure_name, default_warmup_iterati
             op = ops[op_spec]
         else:
             # may as well an inline operation
-            op = self.parse_operation(op_spec, error_ctx="inline operation in test_procedure %s" % test_procedure_name)
+            op = self.parse_operation(
+                op_spec, error_ctx="inline operation in test_procedure %s" % test_procedure_name)
 
-        schedule = self._r(task_spec, "schedule", error_ctx=op.name, mandatory=False)
-        task_name = self._r(task_spec, "name", error_ctx=op.name, mandatory=False, default_value=op.name)
+        schedule = self._r(task_spec, "schedule",
+                           error_ctx=op.name, mandatory=False)
+        task_name = self._r(task_spec, "name", error_ctx=op.name,
+                            mandatory=False, default_value=op.name)
         task = workload.Task(name=task_name,
-                          operation=op,
-                          tags=self._r(task_spec, "tags", error_ctx=op.name, mandatory=False),
-                          meta_data=self._r(task_spec, "meta", error_ctx=op.name, mandatory=False),
-                          warmup_iterations=self._r(task_spec, "warmup-iterations", error_ctx=op.name, mandatory=False,
-                                                    default_value=default_warmup_iterations),
-                          iterations=self._r(task_spec, "iterations", error_ctx=op.name, mandatory=False, default_value=default_iterations),
-                          warmup_time_period=self._r(task_spec, "warmup-time-period", error_ctx=op.name,
-                                                     mandatory=False,
-                                                     default_value=default_warmup_time_period),
-                          time_period=self._r(task_spec, "time-period", error_ctx=op.name, mandatory=False,
-                                              default_value=default_time_period),
-                          ramp_up_time_period=self._r(task_spec, "ramp-up-time-period", error_ctx=op.name,
-                                                      mandatory=False, default_value=default_ramp_up_time_period),
-                          clients=self._r(task_spec, "clients", error_ctx=op.name, mandatory=False, default_value=1),
-                          completes_parent=(task_name == completed_by_name),
-                          schedule=schedule,
-                          # this is to provide scheduler-specific parameters for custom schedulers.
-                          params=task_spec)
+                             operation=op,
+                             tags=self._r(task_spec, "tags",
+                                          error_ctx=op.name, mandatory=False),
+                             meta_data=self._r(
+                                 task_spec, "meta", error_ctx=op.name, mandatory=False),
+                             warmup_iterations=self._r(task_spec, "warmup-iterations", error_ctx=op.name, mandatory=False,
+                                                       default_value=default_warmup_iterations),
+                             iterations=self._r(
+                                 task_spec, "iterations", error_ctx=op.name, mandatory=False, default_value=default_iterations),
+                             warmup_time_period=self._r(task_spec, "warmup-time-period", error_ctx=op.name,
+                                                        mandatory=False,
+                                                        default_value=default_warmup_time_period),
+                             time_period=self._r(task_spec, "time-period", error_ctx=op.name, mandatory=False,
+                                                 default_value=default_time_period),
+                             ramp_up_time_period=self._r(task_spec, "ramp-up-time-period", error_ctx=op.name,
+                                                         mandatory=False, default_value=default_ramp_up_time_period),
+                             clients=self._r(
+                                 task_spec, "clients", error_ctx=op.name, mandatory=False, default_value=1),
+                             completes_parent=(task_name == completed_by_name),
+                             schedule=schedule,
+                             # this is to provide scheduler-specific parameters for custom schedulers.
+                             params=task_spec)
         if task.warmup_iterations is not None and task.time_period is not None:
             self._error(
                 "Operation '%s' in test_procedure '%s' defines '%d' warmup iterations and a time period of '%d' seconds. Please do not "
-                        "mix time periods and iterations." % (op.name, test_procedure_name, task.warmup_iterations, task.time_period))
+                "mix time periods and iterations." % (op.name, test_procedure_name, task.warmup_iterations, task.time_period))
         elif task.warmup_time_period is not None and task.iterations is not None:
             self._error(
                 "Operation '%s' in test_procedure '%s' defines a warmup time period of '%d' seconds and '%d' iterations. Please do not "
-                        "mix time periods and iterations." % (op.name, test_procedure_name, task.warmup_time_period, task.iterations))
-        
+                "mix time periods and iterations." % (op.name, test_procedure_name, task.warmup_time_period, task.iterations))
+
         if (task.warmup_iterations is not None or task.iterations is not None) and task.ramp_up_time_period is not None:
             self._error(f"Operation '{op.name}' in test_procedure '{test_procedure_name}' defines a ramp-up time period of "
                         f"{task.ramp_up_time_period} seconds as well as {task.warmup_iterations} warmup iterations and "
                         f"{task.iterations} iterations but mixing time periods and iterations is not allowed.")
-        
+
         if task.ramp_up_time_period is not None:
             if task.warmup_time_period is None:
                 self._error(f"Operation '{op.name}' in test_procedure '{test_procedure_name}' defines a ramp-up time period of "
@@ -1827,12 +1986,16 @@ def parse_operation(self, op_spec, error_ctx="operations"):
             # Cannot have parameters here
             params = {}
         else:
-            meta_data = self._r(op_spec, "meta", error_ctx=error_ctx, mandatory=False)
+            meta_data = self._r(
+                op_spec, "meta", error_ctx=error_ctx, mandatory=False)
             # Benchmark's core operations will still use enums then but we'll allow users to define arbitrary operations
-            op_type_name = self._r(op_spec, "operation-type", error_ctx=error_ctx)
+            op_type_name = self._r(
+                op_spec, "operation-type", error_ctx=error_ctx)
             # fallback to use the operation type as the operation name
-            op_name = self._r(op_spec, "name", error_ctx=error_ctx, mandatory=False, default_value=op_type_name)
-            param_source = self._r(op_spec, "param-source", error_ctx=error_ctx, mandatory=False)
+            op_name = self._r(op_spec, "name", error_ctx=error_ctx,
+                              mandatory=False, default_value=op_type_name)
+            param_source = self._r(
+                op_spec, "param-source", error_ctx=error_ctx, mandatory=False)
             # just pass-through all parameters by default
             params = op_spec
 
@@ -1840,13 +2003,16 @@ def parse_operation(self, op_spec, error_ctx="operations"):
             op = workload.OperationType.from_hyphenated_string(op_type_name)
             if "include-in-results_publishing" not in params:
                 params["include-in-results_publishing"] = not op.admin_op
-            self.logger.debug("Using built-in operation type [%s] for operation [%s].", op_type_name, op_name)
+            self.logger.debug(
+                "Using built-in operation type [%s] for operation [%s].", op_type_name, op_name)
         except KeyError:
-            self.logger.info("Using user-provided operation type [%s] for operation [%s].", op_type_name, op_name)
+            self.logger.info(
+                "Using user-provided operation type [%s] for operation [%s].", op_type_name, op_name)
 
         try:
             return workload.Operation(name=op_name, meta_data=meta_data,
-            operation_type=op_type_name, params=params,
-            param_source=param_source)
+                                      operation_type=op_type_name, params=params,
+                                      param_source=param_source)
         except exceptions.InvalidSyntax as e:
-            raise WorkloadSyntaxError("Invalid operation [%s]: %s" % (op_name, str(e)))
+            raise WorkloadSyntaxError(
+                "Invalid operation [%s]: %s" % (op_name, str(e)))
diff --git a/tests/aggregator_test.py b/tests/aggregator_test.py
index 32be06cb..d963de60 100644
--- a/tests/aggregator_test.py
+++ b/tests/aggregator_test.py
@@ -50,6 +50,7 @@ def test_count_iterations_for_each_op(aggregator):
     mock_test_procedure.schedule = mock_schedule
     mock_workload.test_procedures = [mock_test_procedure]
 
+    mock_workload.find_test_procedure_or_default = Mock(return_value=mock_test_procedure)
     mock_test_execution = Mock(test_execution_id="test1", workload_params={})
 
     aggregator.loaded_workload = mock_workload
diff --git a/tests/worker_coordinator/worker_coordinator_test.py b/tests/worker_coordinator/worker_coordinator_test.py
index ab7eba63..02626238 100644
--- a/tests/worker_coordinator/worker_coordinator_test.py
+++ b/tests/worker_coordinator/worker_coordinator_test.py
@@ -13,7 +13,7 @@
 # not use this file except in compliance with the License.
 # You may obtain a copy of the License at
 #
-#	http://www.apache.org/licenses/LICENSE-2.0
+# http://www.apache.org/licenses/LICENSE-2.0
 #
 # Unless required by applicable law or agreed to in writing,
 # software distributed under the License is distributed on an
@@ -82,7 +82,8 @@ class StaticClientFactory:
         PATCHER = None
 
         def __init__(self, *args, **kwargs):
-            WorkerCoordinatorTests.StaticClientFactory.PATCHER = mock.patch("opensearchpy.OpenSearch")
+            WorkerCoordinatorTests.StaticClientFactory.PATCHER = mock.patch(
+                "opensearchpy.OpenSearch")
             self.opensearch = WorkerCoordinatorTests.StaticClientFactory.PATCHER.start()
             self.opensearch.indices.stats.return_value = {"mocked": True}
 
@@ -95,26 +96,38 @@ def close(cls):
 
     def setUp(self):
         self.cfg = config.Config()
-        self.cfg.add(config.Scope.application, "system", "env.name", "unittest")
-        self.cfg.add(config.Scope.application, "system", "time.start", datetime(year=2017, month=8, day=20, hour=1, minute=0, second=0))
-        self.cfg.add(config.Scope.application, "system", "test_execution.id", "6ebc6e53-ee20-4b0c-99b4-09697987e9f4")
+        self.cfg.add(config.Scope.application,
+                     "system", "env.name", "unittest")
+        self.cfg.add(config.Scope.application, "system", "time.start", datetime(
+            year=2017, month=8, day=20, hour=1, minute=0, second=0))
+        self.cfg.add(config.Scope.application, "system",
+                     "test_execution.id", "6ebc6e53-ee20-4b0c-99b4-09697987e9f4")
         self.cfg.add(config.Scope.application, "system", "available.cores", 8)
         self.cfg.add(config.Scope.application, "node", "root.dir", "/tmp")
-        self.cfg.add(config.Scope.application, "workload", "test_procedure.name", "default")
+        self.cfg.add(config.Scope.application, "workload",
+                     "test_procedure.name", "default")
         self.cfg.add(config.Scope.application, "workload", "params", {})
-        self.cfg.add(config.Scope.application, "workload", "test.mode.enabled", True)
+        self.cfg.add(config.Scope.application, "workload",
+                     "test.mode.enabled", True)
         self.cfg.add(config.Scope.application, "telemetry", "devices", [])
-        self.cfg.add(config.Scope.application, "telemetry", "params", {"ccr-stats-indices": {"default": ["leader_index"]}})
-        self.cfg.add(config.Scope.application, "builder", "provision_config_instance.names", ["default"])
-        self.cfg.add(config.Scope.application, "builder", "skip.rest.api.check", True)
+        self.cfg.add(config.Scope.application, "telemetry", "params", {
+                     "ccr-stats-indices": {"default": ["leader_index"]}})
+        self.cfg.add(config.Scope.application, "builder",
+                     "provision_config_instance.names", ["default"])
+        self.cfg.add(config.Scope.application, "builder",
+                     "skip.rest.api.check", True)
         self.cfg.add(config.Scope.application, "client", "hosts",
                      WorkerCoordinatorTests.Holder(all_hosts={"default": ["localhost:9200"]}))
-        self.cfg.add(config.Scope.application, "client", "options", WorkerCoordinatorTests.Holder(all_client_options={"default": {}}))
-        self.cfg.add(config.Scope.application, "worker_coordinator", "load_worker_coordinator_hosts", ["localhost"])
-        self.cfg.add(config.Scope.application, "results_publishing", "datastore.type", "in-memory")
+        self.cfg.add(config.Scope.application, "client", "options",
+                     WorkerCoordinatorTests.Holder(all_client_options={"default": {}}))
+        self.cfg.add(config.Scope.application, "worker_coordinator",
+                     "load_worker_coordinator_hosts", ["localhost"])
+        self.cfg.add(config.Scope.application, "results_publishing",
+                     "datastore.type", "in-memory")
 
         default_test_procedure = workload.TestProcedure("default", default=True, schedule=[
-            workload.Task(name="index", operation=workload.Operation("index", operation_type=workload.OperationType.Bulk), clients=4)
+            workload.Task(name="index", operation=workload.Operation(
+                "index", operation_type=workload.OperationType.Bulk), clients=4)
         ])
         another_test_procedure = workload.TestProcedure("other", default=False)
         self.workload = workload.Workload(
@@ -135,14 +148,17 @@ def create_test_worker_coordinator_target(self):
     @mock.patch("osbenchmark.utils.net.resolve")
     def test_start_benchmark_and_prepare_workload(self, resolve):
         # override load worker_coordinator host
-        self.cfg.add(config.Scope.applicationOverride, "worker_coordinator", "load_worker_coordinator_hosts", ["10.5.5.1", "10.5.5.2"])
+        self.cfg.add(config.Scope.applicationOverride, "worker_coordinator",
+                     "load_worker_coordinator_hosts", ["10.5.5.1", "10.5.5.2"])
         resolve.side_effect = ["10.5.5.1", "10.5.5.2"]
 
         target = self.create_test_worker_coordinator_target()
-        d = worker_coordinator.WorkerCoordinator(target, self.cfg, os_client_factory_class=WorkerCoordinatorTests.StaticClientFactory)
+        d = worker_coordinator.WorkerCoordinator(
+            target, self.cfg, os_client_factory_class=WorkerCoordinatorTests.StaticClientFactory)
         d.prepare_benchmark(t=self.workload)
 
-        target.prepare_workload.assert_called_once_with(["10.5.5.1", "10.5.5.2"], self.cfg, self.workload)
+        target.prepare_workload.assert_called_once_with(
+            ["10.5.5.1", "10.5.5.2"], self.cfg, self.workload)
         d.start_benchmark()
 
         target.create_client.assert_has_calls(calls=[
@@ -157,11 +173,13 @@ def test_start_benchmark_and_prepare_workload(self, resolve):
 
     def test_assign_worker_coordinators_round_robin(self):
         target = self.create_test_worker_coordinator_target()
-        d = worker_coordinator.WorkerCoordinator(target, self.cfg, os_client_factory_class=WorkerCoordinatorTests.StaticClientFactory)
+        d = worker_coordinator.WorkerCoordinator(
+            target, self.cfg, os_client_factory_class=WorkerCoordinatorTests.StaticClientFactory)
 
         d.prepare_benchmark(t=self.workload)
 
-        target.prepare_workload.assert_called_once_with(["localhost"], self.cfg, self.workload)
+        target.prepare_workload.assert_called_once_with(
+            ["localhost"], self.cfg, self.workload)
 
         d.start_benchmark()
 
@@ -177,7 +195,8 @@ def test_assign_worker_coordinators_round_robin(self):
 
     def test_client_reaches_join_point_others_still_executing(self):
         target = self.create_test_worker_coordinator_target()
-        d = worker_coordinator.WorkerCoordinator(target, self.cfg, os_client_factory_class=WorkerCoordinatorTests.StaticClientFactory)
+        d = worker_coordinator.WorkerCoordinator(
+            target, self.cfg, os_client_factory_class=WorkerCoordinatorTests.StaticClientFactory)
 
         d.prepare_benchmark(t=self.workload)
         d.start_benchmark()
@@ -195,7 +214,8 @@ def test_client_reaches_join_point_others_still_executing(self):
 
     def test_client_reaches_join_point_which_completes_parent(self):
         target = self.create_test_worker_coordinator_target()
-        d = worker_coordinator.WorkerCoordinator(target, self.cfg, os_client_factory_class=WorkerCoordinatorTests.StaticClientFactory)
+        d = worker_coordinator.WorkerCoordinator(
+            target, self.cfg, os_client_factory_class=WorkerCoordinatorTests.StaticClientFactory)
 
         d.prepare_benchmark(t=self.workload)
         d.start_benchmark()
@@ -206,8 +226,8 @@ def test_client_reaches_join_point_which_completes_parent(self):
                             worker_local_timestamp=10,
                             task_allocations=[
                                 worker_coordinator.ClientAllocation(client_id=0,
-                                                        task=worker_coordinator.JoinPoint(id=0,
-                                                                              clients_executing_completing_task=[0]))])
+                                                                    task=worker_coordinator.JoinPoint(id=0,
+                                                                                                      clients_executing_completing_task=[0]))])
 
         self.assertEqual(-1, d.current_step)
         self.assertEqual(1, len(d.workers_completed_current_step))
@@ -219,8 +239,8 @@ def test_client_reaches_join_point_which_completes_parent(self):
                             worker_local_timestamp=11,
                             task_allocations=[
                                 worker_coordinator.ClientAllocation(client_id=1,
-                                                        task=worker_coordinator.JoinPoint(id=0,
-                                                                              clients_executing_completing_task=[0]))])
+                                                                    task=worker_coordinator.JoinPoint(id=0,
+                                                                                                      clients_executing_completing_task=[0]))])
 
         self.assertEqual(-1, d.current_step)
         self.assertEqual(2, len(d.workers_completed_current_step))
@@ -229,8 +249,8 @@ def test_client_reaches_join_point_which_completes_parent(self):
                             worker_local_timestamp=12,
                             task_allocations=[
                                 worker_coordinator.ClientAllocation(client_id=2,
-                                                        task=worker_coordinator.JoinPoint(id=0,
-                                                                              clients_executing_completing_task=[0]))])
+                                                                    task=worker_coordinator.JoinPoint(id=0,
+                                                                                                      clients_executing_completing_task=[0]))])
         self.assertEqual(-1, d.current_step)
         self.assertEqual(3, len(d.workers_completed_current_step))
 
@@ -238,8 +258,8 @@ def test_client_reaches_join_point_which_completes_parent(self):
                             worker_local_timestamp=13,
                             task_allocations=[
                                 worker_coordinator.ClientAllocation(client_id=3,
-                                                        task=worker_coordinator.JoinPoint(id=0,
-                                                                              clients_executing_completing_task=[0]))])
+                                                                    task=worker_coordinator.JoinPoint(id=0,
+                                                                                                      clients_executing_completing_task=[0]))])
 
         # by now the previous step should be considered completed and we are at the next one
         self.assertEqual(0, d.current_step)
@@ -295,11 +315,12 @@ def request_metric(self, absolute_time, relative_time, name, value):
     @mock.patch("osbenchmark.metrics.MetricsStore")
     def test_all_samples(self, metrics_store):
         post_process = worker_coordinator.SamplePostprocessor(metrics_store,
-                                                  downsample_factor=1,
-                                                  workload_meta_data={},
-                                                  test_procedure_meta_data={})
+                                                              downsample_factor=1,
+                                                              workload_meta_data={},
+                                                              test_procedure_meta_data={})
 
-        task = workload.Task("index", workload.Operation("index-op", "bulk", param_source="worker-coordinator-test-param-source"))
+        task = workload.Task("index", workload.Operation(
+            "index-op", "bulk", param_source="worker-coordinator-test-param-source"))
         samples = [
             worker_coordinator.Sample(
                 0, 38598, 24, 0, task, metrics.SampleType.Normal,
@@ -313,9 +334,11 @@ def test_all_samples(self, metrics_store):
 
         calls = [
             self.latency(38598, 24, 10.0), self.service_time(38598, 24, 7.0),
-            self.client_processing_time(38598, 24, 0.7), self.processing_time(38598, 24, 9.0),
+            self.client_processing_time(
+                38598, 24, 0.7), self.processing_time(38598, 24, 9.0),
             self.latency(38599, 25, 10.0), self.service_time(38599, 25, 7.0),
-            self.client_processing_time(38599, 25, 0.7), self.processing_time(38599, 25, 9.0),
+            self.client_processing_time(
+                38599, 25, 0.7), self.processing_time(38599, 25, 9.0),
             self.throughput(38598, 24, 5000),
             self.throughput(38599, 25, 5000),
         ]
@@ -324,11 +347,12 @@ def test_all_samples(self, metrics_store):
     @mock.patch("osbenchmark.metrics.MetricsStore")
     def test_downsamples(self, metrics_store):
         post_process = worker_coordinator.SamplePostprocessor(metrics_store,
-                                                  downsample_factor=2,
-                                                  workload_meta_data={},
-                                                  test_procedure_meta_data={})
+                                                              downsample_factor=2,
+                                                              workload_meta_data={},
+                                                              test_procedure_meta_data={})
 
-        task = workload.Task("index", workload.Operation("index-op", "bulk", param_source="worker-coordinator-test-param-source"))
+        task = workload.Task("index", workload.Operation(
+            "index-op", "bulk", param_source="worker-coordinator-test-param-source"))
 
         samples = [
             worker_coordinator.Sample(
@@ -344,7 +368,8 @@ def test_downsamples(self, metrics_store):
         calls = [
             # only the first out of two request samples is included, throughput metrics are still complete
             self.latency(38598, 24, 10.0), self.service_time(38598, 24, 7.0),
-            self.client_processing_time(38598, 24, 0.7), self.processing_time(38598, 24, 9.0),
+            self.client_processing_time(
+                38598, 24, 0.7), self.processing_time(38598, 24, 9.0),
             self.throughput(38598, 24, 5000),
             self.throughput(38599, 25, 5000),
         ]
@@ -353,38 +378,40 @@ def test_downsamples(self, metrics_store):
     @mock.patch("osbenchmark.metrics.MetricsStore")
     def test_dependent_samples(self, metrics_store):
         post_process = worker_coordinator.SamplePostprocessor(metrics_store,
-                                                  downsample_factor=1,
-                                                  workload_meta_data={},
-                                                  test_procedure_meta_data={})
+                                                              downsample_factor=1,
+                                                              workload_meta_data={},
+                                                              test_procedure_meta_data={})
 
-        task = workload.Task("index", workload.Operation("index-op", "bulk", param_source="worker-coordinator-test-param-source"))
+        task = workload.Task("index", workload.Operation(
+            "index-op", "bulk", param_source="worker-coordinator-test-param-source"))
         samples = [
             worker_coordinator.Sample(
                 0, 38598, 24, 0, task, metrics.SampleType.Normal,
                 None, 0.01, 0.007, 0.0007, 0.009, None, 5000, "docs", 1, 1 / 2,
-                          dependent_timing=[
-                              {
-                                  "absolute_time": 38601,
-                                  "request_start": 25,
-                                  "service_time": 0.05,
-                                  "operation": "index-op",
-                                  "operation-type": "bulk"
-                              },
-                              {
-                                  "absolute_time": 38602,
-                                  "request_start": 26,
-                                  "service_time": 0.08,
-                                  "operation": "index-op",
-                                  "operation-type": "bulk"
-                              }
-                          ]),
+                dependent_timing=[
+                    {
+                        "absolute_time": 38601,
+                        "request_start": 25,
+                        "service_time": 0.05,
+                        "operation": "index-op",
+                        "operation-type": "bulk"
+                    },
+                    {
+                        "absolute_time": 38602,
+                        "request_start": 26,
+                        "service_time": 0.08,
+                        "operation": "index-op",
+                        "operation-type": "bulk"
+                    }
+                ]),
         ]
 
         post_process(samples)
 
         calls = [
             self.latency(38598, 24, 10.0), self.service_time(38598, 24, 7.0),
-            self.client_processing_time(38598, 24, 0.7), self.processing_time(38598, 24, 9.0),
+            self.client_processing_time(
+                38598, 24, 0.7), self.processing_time(38598, 24, 9.0),
             # dependent timings
             self.service_time(38601, 25, 50.0),
             self.service_time(38602, 26, 80.0),
@@ -400,7 +427,8 @@ def test_single_host_assignment_clients_matches_cores(self):
             "cores": 4
         }]
 
-        assignments = worker_coordinator.calculate_worker_assignments(host_configs, client_count=4)
+        assignments = worker_coordinator.calculate_worker_assignments(
+            host_configs, client_count=4)
 
         self.assertEqual([
             {
@@ -420,7 +448,8 @@ def test_single_host_assignment_more_clients_than_cores(self):
             "cores": 4
         }]
 
-        assignments = worker_coordinator.calculate_worker_assignments(host_configs, client_count=6)
+        assignments = worker_coordinator.calculate_worker_assignments(
+            host_configs, client_count=6)
 
         self.assertEqual([
             {
@@ -440,7 +469,8 @@ def test_single_host_assignment_less_clients_than_cores(self):
             "cores": 4
         }]
 
-        assignments = worker_coordinator.calculate_worker_assignments(host_configs, client_count=2)
+        assignments = worker_coordinator.calculate_worker_assignments(
+            host_configs, client_count=2)
 
         self.assertEqual([
             {
@@ -466,7 +496,8 @@ def test_multiple_host_assignment_more_clients_than_cores(self):
             }
         ]
 
-        assignments = worker_coordinator.calculate_worker_assignments(host_configs, client_count=16)
+        assignments = worker_coordinator.calculate_worker_assignments(
+            host_configs, client_count=16)
 
         self.assertEqual([
             {
@@ -501,7 +532,8 @@ def test_multiple_host_assignment_less_clients_than_cores(self):
             }
         ]
 
-        assignments = worker_coordinator.calculate_worker_assignments(host_configs, client_count=4)
+        assignments = worker_coordinator.calculate_worker_assignments(
+            host_configs, client_count=4)
 
         self.assertEqual([
             {
@@ -540,7 +572,8 @@ def test_uneven_assignment_across_hosts(self):
             }
         ]
 
-        assignments = worker_coordinator.calculate_worker_assignments(host_configs, client_count=17)
+        assignments = worker_coordinator.calculate_worker_assignments(
+            host_configs, client_count=17)
 
         self.assertEqual([
             {
@@ -575,10 +608,11 @@ def test_uneven_assignment_across_hosts(self):
 
 class AllocatorTests(TestCase):
     def setUp(self):
-        params.register_param_source_for_name("worker-coordinator-test-param-source", WorkerCoordinatorTestParamSource)
+        params.register_param_source_for_name(
+            "worker-coordinator-test-param-source", WorkerCoordinatorTestParamSource)
 
     def ta(self, task, client_index_in_task, global_client_index=None, total_clients=None):
-        return worker_coordinator.TaskAllocation(task, client_index_in_task, 
+        return worker_coordinator.TaskAllocation(task, client_index_in_task,
                                                  client_index_in_task if global_client_index is None else global_client_index,
                                                  task.clients if total_clients is None else total_clients)
 
@@ -606,7 +640,8 @@ def test_allocates_two_serial_tasks(self):
     def test_allocates_two_parallel_tasks(self):
         task = workload.Task("index", op("index", workload.OperationType.Bulk))
 
-        allocator = worker_coordinator.Allocator([workload.Parallel([task, task])])
+        allocator = worker_coordinator.Allocator(
+            [workload.Parallel([task, task])])
 
         self.assertEqual(2, allocator.clients)
         self.assertEqual(3, len(allocator.allocations[0]))
@@ -615,13 +650,17 @@ def test_allocates_two_parallel_tasks(self):
         self.assertEqual([{task}], allocator.tasks_per_joinpoint)
         for join_point in allocator.join_points:
             self.assertFalse(join_point.preceding_task_completes_parent)
-            self.assertEqual(0, join_point.num_clients_executing_completing_task)
+            self.assertEqual(
+                0, join_point.num_clients_executing_completing_task)
 
     def test_a_task_completes_the_parallel_structure(self):
-        taskA = workload.Task("index-completing", op("index", workload.OperationType.Bulk), completes_parent=True)
-        taskB = workload.Task("index-non-completing", op("index", workload.OperationType.Bulk))
+        taskA = workload.Task("index-completing", op("index",
+                              workload.OperationType.Bulk), completes_parent=True)
+        taskB = workload.Task("index-non-completing",
+                              op("index", workload.OperationType.Bulk))
 
-        allocator = worker_coordinator.Allocator([workload.Parallel([taskA, taskB])])
+        allocator = worker_coordinator.Allocator(
+            [workload.Parallel([taskA, taskB])])
 
         self.assertEqual(2, allocator.clients)
         self.assertEqual(3, len(allocator.allocations[0]))
@@ -630,19 +669,25 @@ def test_a_task_completes_the_parallel_structure(self):
         self.assertEqual([{taskA, taskB}], allocator.tasks_per_joinpoint)
         final_join_point = allocator.join_points[1]
         self.assertTrue(final_join_point.preceding_task_completes_parent)
-        self.assertEqual(1, final_join_point.num_clients_executing_completing_task)
-        self.assertEqual([0], final_join_point.clients_executing_completing_task)
+        self.assertEqual(
+            1, final_join_point.num_clients_executing_completing_task)
+        self.assertEqual(
+            [0], final_join_point.clients_executing_completing_task)
 
     def test_allocates_mixed_tasks(self):
-        index = workload.Task("index", op("index", workload.OperationType.Bulk))
-        stats = workload.Task("stats", op("stats", workload.OperationType.IndexStats))
-        search = workload.Task("search", op("search", workload.OperationType.Search))
+        index = workload.Task("index", op(
+            "index", workload.OperationType.Bulk))
+        stats = workload.Task("stats", op(
+            "stats", workload.OperationType.IndexStats))
+        search = workload.Task("search", op(
+            "search", workload.OperationType.Search))
 
         allocator = worker_coordinator.Allocator([index,
-                                      workload.Parallel([index, stats, stats]),
-                                      index,
-                                      index,
-                                      workload.Parallel([search, search, search])])
+                                                  workload.Parallel(
+                                                      [index, stats, stats]),
+                                                  index,
+                                                  index,
+                                                  workload.Parallel([search, search, search])])
 
         self.assertEqual(3, allocator.clients)
 
@@ -651,19 +696,27 @@ def test_allocates_mixed_tasks(self):
         self.assertEqual(11, len(allocator.allocations[1]))
         self.assertEqual(11, len(allocator.allocations[2]))
         self.assertEqual(6, len(allocator.join_points))
-        self.assertEqual([{index}, {index, stats}, {index}, {index}, {search}], allocator.tasks_per_joinpoint)
+        self.assertEqual([{index}, {index, stats}, {index}, {index}, {
+                         search}], allocator.tasks_per_joinpoint)
         for join_point in allocator.join_points:
             self.assertFalse(join_point.preceding_task_completes_parent)
-            self.assertEqual(0, join_point.num_clients_executing_completing_task)
+            self.assertEqual(
+                0, join_point.num_clients_executing_completing_task)
 
     def test_allocates_more_tasks_than_clients(self):
-        index_a = workload.Task("index-a", op("index-a", workload.OperationType.Bulk))
-        index_b = workload.Task("index-b", op("index-b", workload.OperationType.Bulk), completes_parent=True)
-        index_c = workload.Task("index-c", op("index-c", workload.OperationType.Bulk))
-        index_d = workload.Task("index-d", op("index-d", workload.OperationType.Bulk))
-        index_e = workload.Task("index-e", op("index-e", workload.OperationType.Bulk))
-
-        allocator = worker_coordinator.Allocator([workload.Parallel(tasks=[index_a, index_b, index_c, index_d, index_e], clients=2)])
+        index_a = workload.Task(
+            "index-a", op("index-a", workload.OperationType.Bulk))
+        index_b = workload.Task(
+            "index-b", op("index-b", workload.OperationType.Bulk), completes_parent=True)
+        index_c = workload.Task(
+            "index-c", op("index-c", workload.OperationType.Bulk))
+        index_d = workload.Task(
+            "index-d", op("index-d", workload.OperationType.Bulk))
+        index_e = workload.Task(
+            "index-e", op("index-e", workload.OperationType.Bulk))
+
+        allocator = worker_coordinator.Allocator([workload.Parallel(
+            tasks=[index_a, index_b, index_c, index_d, index_e], clients=2)])
 
         self.assertEqual(2, allocator.clients)
 
@@ -673,33 +726,45 @@ def test_allocates_more_tasks_than_clients(self):
         # join_point, index_a, index_c, index_e, join_point
         self.assertEqual(5, len(allocations[0]))
         # we really have no chance to extract the join point so we just take what is there...
-        self.assertEqual([allocations[0][0], 
-                          self.ta(index_a, client_index_in_task=0, global_client_index=0, total_clients=2), 
-                          self.ta(index_c, client_index_in_task=0, global_client_index=2, total_clients=2), 
-                          self.ta(index_e, client_index_in_task=0, global_client_index=4, total_clients=2), 
+        self.assertEqual([allocations[0][0],
+                          self.ta(index_a, client_index_in_task=0,
+                                  global_client_index=0, total_clients=2),
+                          self.ta(index_c, client_index_in_task=0,
+                                  global_client_index=2, total_clients=2),
+                          self.ta(index_e, client_index_in_task=0,
+                                  global_client_index=4, total_clients=2),
                           allocations[0][4]],
                          allocations[0])
         # join_point, index_a, index_c, None, join_point
         self.assertEqual(5, len(allocator.allocations[1]))
-        self.assertEqual([allocations[1][0], 
-                          self.ta(index_b, client_index_in_task=0, global_client_index=1, total_clients=2), 
-                          self.ta(index_d, client_index_in_task=0, global_client_index=3, total_clients=2), 
-                          None, allocations[1][4]], 
-                          allocations[1])
+        self.assertEqual([allocations[1][0],
+                          self.ta(index_b, client_index_in_task=0,
+                                  global_client_index=1, total_clients=2),
+                          self.ta(index_d, client_index_in_task=0,
+                                  global_client_index=3, total_clients=2),
+                          None, allocations[1][4]],
+                         allocations[1])
 
-        self.assertEqual([{index_a, index_b, index_c, index_d, index_e}], allocator.tasks_per_joinpoint)
+        self.assertEqual(
+            [{index_a, index_b, index_c, index_d, index_e}], allocator.tasks_per_joinpoint)
         self.assertEqual(2, len(allocator.join_points))
         final_join_point = allocator.join_points[1]
         self.assertTrue(final_join_point.preceding_task_completes_parent)
-        self.assertEqual(1, final_join_point.num_clients_executing_completing_task)
-        self.assertEqual([1], final_join_point.clients_executing_completing_task)
+        self.assertEqual(
+            1, final_join_point.num_clients_executing_completing_task)
+        self.assertEqual(
+            [1], final_join_point.clients_executing_completing_task)
 
     def test_considers_number_of_clients_per_subtask(self):
-        index_a = workload.Task("index-a", op("index-a", workload.OperationType.Bulk))
-        index_b = workload.Task("index-b", op("index-b", workload.OperationType.Bulk))
-        index_c = workload.Task("index-c", op("index-c", workload.OperationType.Bulk), clients=2, completes_parent=True)
+        index_a = workload.Task(
+            "index-a", op("index-a", workload.OperationType.Bulk))
+        index_b = workload.Task(
+            "index-b", op("index-b", workload.OperationType.Bulk))
+        index_c = workload.Task(
+            "index-c", op("index-c", workload.OperationType.Bulk), clients=2, completes_parent=True)
 
-        allocator = worker_coordinator.Allocator([workload.Parallel(tasks=[index_a, index_b, index_c], clients=3)])
+        allocator = worker_coordinator.Allocator(
+            [workload.Parallel(tasks=[index_a, index_b, index_c], clients=3)])
 
         self.assertEqual(3, allocator.clients)
 
@@ -712,45 +777,54 @@ def test_considers_number_of_clients_per_subtask(self):
         # join_point, index_a, index_c, join_point
         self.assertEqual(4, len(allocations[0]))
         # we really have no chance to extract the join point so we just take what is there...
-        self.assertEqual([allocations[0][0], 
-                          self.ta(index_a, client_index_in_task=0, global_client_index=0, total_clients=3), 
-                          self.ta(index_c, client_index_in_task=1, global_client_index=3, total_clients=3), 
-                          allocations[0][3]], 
-                          allocations[0])
+        self.assertEqual([allocations[0][0],
+                          self.ta(index_a, client_index_in_task=0,
+                                  global_client_index=0, total_clients=3),
+                          self.ta(index_c, client_index_in_task=1,
+                                  global_client_index=3, total_clients=3),
+                          allocations[0][3]],
+                         allocations[0])
 
         # task that client 1 will execute:
         # join_point, index_b, None, join_point
         self.assertEqual(4, len(allocator.allocations[1]))
-        self.assertEqual([allocations[1][0], 
-                          self.ta(index_b, client_index_in_task=0, global_client_index=1, total_clients=3), 
-                          None, 
-                          allocations[1][3]], 
-                          allocations[1])
+        self.assertEqual([allocations[1][0],
+                          self.ta(index_b, client_index_in_task=0,
+                                  global_client_index=1, total_clients=3),
+                          None,
+                          allocations[1][3]],
+                         allocations[1])
 
         # tasks that client 2 will execute:
         self.assertEqual(4, len(allocator.allocations[2]))
-        self.assertEqual([allocations[2][0], 
-                          self.ta(index_c, client_index_in_task=0, global_client_index=2, total_clients=3), 
-                          None, 
-                          allocations[2][3]], 
-                          allocations[2])
+        self.assertEqual([allocations[2][0],
+                          self.ta(index_c, client_index_in_task=0,
+                                  global_client_index=2, total_clients=3),
+                          None,
+                          allocations[2][3]],
+                         allocations[2])
 
-        self.assertEqual([{index_a, index_b, index_c}], allocator.tasks_per_joinpoint)
+        self.assertEqual([{index_a, index_b, index_c}],
+                         allocator.tasks_per_joinpoint)
 
         self.assertEqual(2, len(allocator.join_points))
         final_join_point = allocator.join_points[1]
         self.assertTrue(final_join_point.preceding_task_completes_parent)
         # task index_c has two clients, hence we have to wait for two clients to finish
-        self.assertEqual(2, final_join_point.num_clients_executing_completing_task)
-        self.assertEqual([2, 0], final_join_point.clients_executing_completing_task)
+        self.assertEqual(
+            2, final_join_point.num_clients_executing_completing_task)
+        self.assertEqual(
+            [2, 0], final_join_point.clients_executing_completing_task)
 
 
 class MetricsAggregationTests(TestCase):
     def setUp(self):
-        params.register_param_source_for_name("worker-coordinator-test-param-source", WorkerCoordinatorTestParamSource)
+        params.register_param_source_for_name(
+            "worker-coordinator-test-param-source", WorkerCoordinatorTestParamSource)
 
     def test_different_sample_types(self):
-        op = workload.Operation("index", workload.OperationType.Bulk, param_source="worker-coordinator-test-param-source")
+        op = workload.Operation("index", workload.OperationType.Bulk,
+                                param_source="worker-coordinator-test-param-source")
 
         samples = [
             worker_coordinator.Sample(0, 1470838595, 21, 0, op, metrics.SampleType.Warmup,
@@ -766,19 +840,28 @@ def test_different_sample_types(self):
 
         throughput = aggregated[op]
         self.assertEqual(2, len(throughput))
-        self.assertEqual((1470838595, 21, metrics.SampleType.Warmup, 3000, "docs/s"), throughput[0])
-        self.assertEqual((1470838595.5, 21.5, metrics.SampleType.Normal, 3666.6666666666665, "docs/s"), throughput[1])
+        self.assertEqual(
+            (1470838595, 21, metrics.SampleType.Warmup, 3000, "docs/s"), throughput[0])
+        self.assertEqual((1470838595.5, 21.5, metrics.SampleType.Normal,
+                         3666.6666666666665, "docs/s"), throughput[1])
 
     def test_single_metrics_aggregation(self):
-        op = workload.Operation("index", workload.OperationType.Bulk, param_source="worker-coordinator-test-param-source")
+        op = workload.Operation("index", workload.OperationType.Bulk,
+                                param_source="worker-coordinator-test-param-source")
 
         samples = [
-            worker_coordinator.Sample(0, 38595, 21, 0, op, metrics.SampleType.Normal, None, -1, -1, -1, -1, None, 5000, "docs", 1, 1 / 9),
-            worker_coordinator.Sample(0, 38596, 22, 0, op, metrics.SampleType.Normal, None, -1, -1, -1, -1, None, 5000, "docs", 2, 2 / 9),
-            worker_coordinator.Sample(0, 38597, 23, 0, op, metrics.SampleType.Normal, None, -1, -1, -1, -1, None, 5000, "docs", 3, 3 / 9),
-            worker_coordinator.Sample(0, 38598, 24, 0, op, metrics.SampleType.Normal, None, -1, -1, -1, -1, None, 5000, "docs", 4, 4 / 9),
-            worker_coordinator.Sample(0, 38599, 25, 0, op, metrics.SampleType.Normal, None, -1, -1, -1, -1, None, 5000, "docs", 5, 5 / 9),
-            worker_coordinator.Sample(0, 38600, 26, 0, op, metrics.SampleType.Normal, None, -1, -1, -1, -1, None, 5000, "docs", 6, 6 / 9),
+            worker_coordinator.Sample(0, 38595, 21, 0, op, metrics.SampleType.Normal,
+                                      None, -1, -1, -1, -1, None, 5000, "docs", 1, 1 / 9),
+            worker_coordinator.Sample(0, 38596, 22, 0, op, metrics.SampleType.Normal,
+                                      None, -1, -1, -1, -1, None, 5000, "docs", 2, 2 / 9),
+            worker_coordinator.Sample(0, 38597, 23, 0, op, metrics.SampleType.Normal,
+                                      None, -1, -1, -1, -1, None, 5000, "docs", 3, 3 / 9),
+            worker_coordinator.Sample(0, 38598, 24, 0, op, metrics.SampleType.Normal,
+                                      None, -1, -1, -1, -1, None, 5000, "docs", 4, 4 / 9),
+            worker_coordinator.Sample(0, 38599, 25, 0, op, metrics.SampleType.Normal,
+                                      None, -1, -1, -1, -1, None, 5000, "docs", 5, 5 / 9),
+            worker_coordinator.Sample(0, 38600, 26, 0, op, metrics.SampleType.Normal,
+                                      None, -1, -1, -1, -1, None, 5000, "docs", 6, 6 / 9),
             worker_coordinator.Sample(1, 38598.5, 24.5, 0, op, metrics.SampleType.Normal,
                                       None, -1, -1, -1, -1, None, 5000, "docs", 4.5, 7 / 9),
             worker_coordinator.Sample(1, 38599.5, 25.5, 0, op, metrics.SampleType.Normal,
@@ -794,22 +877,31 @@ def test_single_metrics_aggregation(self):
 
         throughput = aggregated[op]
         self.assertEqual(6, len(throughput))
-        self.assertEqual((38595, 21, metrics.SampleType.Normal, 5000, "docs/s"), throughput[0])
-        self.assertEqual((38596, 22, metrics.SampleType.Normal, 5000, "docs/s"), throughput[1])
-        self.assertEqual((38597, 23, metrics.SampleType.Normal, 5000, "docs/s"), throughput[2])
-        self.assertEqual((38598, 24, metrics.SampleType.Normal, 5000, "docs/s"), throughput[3])
-        self.assertEqual((38599, 25, metrics.SampleType.Normal, 6000, "docs/s"), throughput[4])
-        self.assertEqual((38600, 26, metrics.SampleType.Normal, 6666.666666666667, "docs/s"), throughput[5])
+        self.assertEqual((38595, 21, metrics.SampleType.Normal,
+                         5000, "docs/s"), throughput[0])
+        self.assertEqual((38596, 22, metrics.SampleType.Normal,
+                         5000, "docs/s"), throughput[1])
+        self.assertEqual((38597, 23, metrics.SampleType.Normal,
+                         5000, "docs/s"), throughput[2])
+        self.assertEqual((38598, 24, metrics.SampleType.Normal,
+                         5000, "docs/s"), throughput[3])
+        self.assertEqual((38599, 25, metrics.SampleType.Normal,
+                         6000, "docs/s"), throughput[4])
+        self.assertEqual((38600, 26, metrics.SampleType.Normal,
+                         6666.666666666667, "docs/s"), throughput[5])
         # self.assertEqual((1470838600.5, 26.5, metrics.SampleType.Normal, 10000), throughput[6])
 
     def test_use_provided_throughput(self):
         op = workload.Operation("index-recovery", workload.OperationType.WaitForRecovery,
-                             param_source="worker-coordinator-test-param-source")
+                                param_source="worker-coordinator-test-param-source")
 
         samples = [
-            worker_coordinator.Sample(0, 38595, 21, 0, op, metrics.SampleType.Normal, None, -1, -1, -1, -1, 8000, 5000, "byte", 1, 1 / 3),
-            worker_coordinator.Sample(0, 38596, 22, 0, op, metrics.SampleType.Normal, None, -1, -1, -1, -1, 8000, 5000, "byte", 2, 2 / 3),
-            worker_coordinator.Sample(0, 38597, 23, 0, op, metrics.SampleType.Normal, None, -1, -1, -1, -1, 8000, 5000, "byte", 3, 3 / 3),
+            worker_coordinator.Sample(0, 38595, 21, 0, op, metrics.SampleType.Normal,
+                                      None, -1, -1, -1, -1, 8000, 5000, "byte", 1, 1 / 3),
+            worker_coordinator.Sample(0, 38596, 22, 0, op, metrics.SampleType.Normal,
+                                      None, -1, -1, -1, -1, 8000, 5000, "byte", 2, 2 / 3),
+            worker_coordinator.Sample(0, 38597, 23, 0, op, metrics.SampleType.Normal,
+                                      None, -1, -1, -1, -1, 8000, 5000, "byte", 3, 3 / 3),
         ]
 
         aggregated = self.calculate_global_throughput(samples)
@@ -819,9 +911,12 @@ def test_use_provided_throughput(self):
 
         throughput = aggregated[op]
         self.assertEqual(3, len(throughput))
-        self.assertEqual((38595, 21, metrics.SampleType.Normal, 8000, "byte/s"), throughput[0])
-        self.assertEqual((38596, 22, metrics.SampleType.Normal, 8000, "byte/s"), throughput[1])
-        self.assertEqual((38597, 23, metrics.SampleType.Normal, 8000, "byte/s"), throughput[2])
+        self.assertEqual((38595, 21, metrics.SampleType.Normal,
+                         8000, "byte/s"), throughput[0])
+        self.assertEqual((38596, 22, metrics.SampleType.Normal,
+                         8000, "byte/s"), throughput[1])
+        self.assertEqual((38597, 23, metrics.SampleType.Normal,
+                         8000, "byte/s"), throughput[2])
 
     def calculate_global_throughput(self, samples):
         return worker_coordinator.ThroughputCalculator().calculate(samples)
@@ -863,10 +958,14 @@ async def assert_schedule(self, expected_schedule, schedule_handle, infinite_sch
         schedule_handle.start()
         async for invocation_time, sample_type, progress_percent, runner, params in schedule_handle():
             schedule_handle.before_request(now=idx)
-            exp_invocation_time, exp_sample_type, exp_progress_percent, exp_params = expected_schedule[idx]
-            self.assertAlmostEqual(exp_invocation_time, invocation_time, msg="Invocation time for sample at index %d does not match" % idx)
-            self.assertEqual(exp_sample_type, sample_type, "Sample type for sample at index %d does not match" % idx)
-            self.assertEqual(exp_progress_percent, progress_percent, "Current progress for sample at index %d does not match" % idx)
+            exp_invocation_time, exp_sample_type, exp_progress_percent, exp_params = expected_schedule[
+                idx]
+            self.assertAlmostEqual(exp_invocation_time, invocation_time,
+                                   msg="Invocation time for sample at index %d does not match" % idx)
+            self.assertEqual(exp_sample_type, sample_type,
+                             "Sample type for sample at index %d does not match" % idx)
+            self.assertEqual(exp_progress_percent, progress_percent,
+                             "Current progress for sample at index %d does not match" % idx)
             self.assertIsNotNone(runner, "runner must be defined")
             self.assertEqual(exp_params, params, "Parameters do not match")
             idx += 1
@@ -874,17 +973,22 @@ async def assert_schedule(self, expected_schedule, schedule_handle, infinite_sch
             if infinite_schedule and idx == len(expected_schedule):
                 break
             # simulate that the request is done - we only support throttling based on request count (ops).
-            schedule_handle.after_request(now=idx, weight=1, unit="ops", request_meta_data=None)
+            schedule_handle.after_request(
+                now=idx, weight=1, unit="ops", request_meta_data=None)
         if not infinite_schedule:
-            self.assertEqual(len(expected_schedule), idx, msg="Number of elements in the schedules do not match")
+            self.assertEqual(len(expected_schedule), idx,
+                             msg="Number of elements in the schedules do not match")
 
     def setUp(self):
         self.test_workload = workload.Workload(name="unittest")
         self.runner_with_progress = SchedulerTests.RunnerWithProgress()
-        params.register_param_source_for_name("worker-coordinator-test-param-source", WorkerCoordinatorTestParamSource)
+        params.register_param_source_for_name(
+            "worker-coordinator-test-param-source", WorkerCoordinatorTestParamSource)
         runner.register_default_runners()
-        runner.register_runner("worker-coordinator-test-runner-with-completion", self.runner_with_progress, async_runner=True)
-        scheduler.register_scheduler("custom-complex-scheduler", SchedulerTests.CustomComplexScheduler)
+        runner.register_runner("worker-coordinator-test-runner-with-completion",
+                               self.runner_with_progress, async_runner=True)
+        scheduler.register_scheduler(
+            "custom-complex-scheduler", SchedulerTests.CustomComplexScheduler)
 
     def tearDown(self):
         runner.remove_runner("worker-coordinator-test-runner-with-completion")
@@ -892,16 +996,16 @@ def tearDown(self):
 
     def test_injects_parameter_source_into_scheduler(self):
         task = workload.Task(name="search",
-                          schedule="custom-complex-scheduler",
-                          operation=workload.Operation(
-                              name="search",
-                              operation_type=workload.OperationType.Search.to_hyphenated_string(),
-                              param_source="worker-coordinator-test-param-source"
-                          ),
-                          clients=4,
-                          params={
-                              "target-throughput": "5000 ops/s"
-                          })
+                             schedule="custom-complex-scheduler",
+                             operation=workload.Operation(
+                                 name="search",
+                                 operation_type=workload.OperationType.Search.to_hyphenated_string(),
+                                 param_source="worker-coordinator-test-param-source"
+                             ),
+                             clients=4,
+                             params={
+                                 "target-throughput": "5000 ops/s"
+                             })
 
         param_source = workload.operation_parameters(self.test_workload, task)
         task_allocation = worker_coordinator.TaskAllocation(
@@ -910,16 +1014,18 @@ def test_injects_parameter_source_into_scheduler(self):
             global_client_index=0,
             total_clients=task.clients
         )
-        schedule = worker_coordinator.schedule_for(task_allocation, param_source)
+        schedule = worker_coordinator.schedule_for(
+            task_allocation, param_source)
 
-        self.assertIsNotNone(schedule.sched.parameter_source, "Parameter source has not been injected into scheduler")
+        self.assertIsNotNone(schedule.sched.parameter_source,
+                             "Parameter source has not been injected into scheduler")
         self.assertEqual(param_source, schedule.sched.parameter_source)
 
     @run_async
     async def test_search_task_one_client(self):
         task = workload.Task("search", workload.Operation("search", workload.OperationType.Search.to_hyphenated_string(),
-                                                    param_source="worker-coordinator-test-param-source"),
-                          warmup_iterations=3, iterations=5, clients=1, params={"target-throughput": 10, "clients": 1})
+                                                          param_source="worker-coordinator-test-param-source"),
+                             warmup_iterations=3, iterations=5, clients=1, params={"target-throughput": 10, "clients": 1})
         param_source = workload.operation_parameters(self.test_workload, task)
         task_allocation = worker_coordinator.TaskAllocation(
             task=task,
@@ -927,7 +1033,8 @@ async def test_search_task_one_client(self):
             global_client_index=0,
             total_clients=task.clients
         )
-        schedule = worker_coordinator.schedule_for(task_allocation, param_source)
+        schedule = worker_coordinator.schedule_for(
+            task_allocation, param_source)
 
         expected_schedule = [
             (0, metrics.SampleType.Warmup, 1 / 8, {}),
@@ -944,8 +1051,8 @@ async def test_search_task_one_client(self):
     @run_async
     async def test_search_task_two_clients(self):
         task = workload.Task("search", workload.Operation("search", workload.OperationType.Search.to_hyphenated_string(),
-                                                    param_source="worker-coordinator-test-param-source"),
-                          warmup_iterations=1, iterations=5, clients=2, params={"target-throughput": 10, "clients": 2})
+                                                          param_source="worker-coordinator-test-param-source"),
+                             warmup_iterations=1, iterations=5, clients=2, params={"target-throughput": 10, "clients": 2})
         param_source = workload.operation_parameters(self.test_workload, task)
         task_allocation = worker_coordinator.TaskAllocation(
             task=task,
@@ -953,7 +1060,8 @@ async def test_search_task_two_clients(self):
             global_client_index=0,
             total_clients=task.clients
         )
-        schedule = worker_coordinator.schedule_for(task_allocation, param_source)
+        schedule = worker_coordinator.schedule_for(
+            task_allocation, param_source)
 
         expected_schedule = [
             (0, metrics.SampleType.Warmup, 1 / 6, {}),
@@ -969,9 +1077,10 @@ async def test_search_task_two_clients(self):
     async def test_schedule_param_source_determines_iterations_no_warmup(self):
         # we neither define any time-period nor any iteration count on the task.
         task = workload.Task("bulk-index", workload.Operation("bulk-index", workload.OperationType.Bulk.to_hyphenated_string(),
-                                                        params={"body": ["a"], "size": 3},
-                                                        param_source="worker-coordinator-test-param-source"),
-                          clients=4, params={"target-throughput": 4})
+                                                              params={
+                                                                  "body": ["a"], "size": 3},
+                                                              param_source="worker-coordinator-test-param-source"),
+                             clients=4, params={"target-throughput": 4})
 
         param_source = workload.operation_parameters(self.test_workload, task)
         task_allocation = worker_coordinator.TaskAllocation(
@@ -980,20 +1089,25 @@ async def test_schedule_param_source_determines_iterations_no_warmup(self):
             global_client_index=0,
             total_clients=task.clients
         )
-        schedule = worker_coordinator.schedule_for(task_allocation, param_source)
+        schedule = worker_coordinator.schedule_for(
+            task_allocation, param_source)
 
         await self.assert_schedule([
-            (0.0, metrics.SampleType.Normal, 1 / 3, {"body": ["a"], "size": 3}),
-            (1.0, metrics.SampleType.Normal, 2 / 3, {"body": ["a"], "size": 3}),
-            (2.0, metrics.SampleType.Normal, 3 / 3, {"body": ["a"], "size": 3}),
+            (0.0, metrics.SampleType.Normal,
+             1 / 3, {"body": ["a"], "size": 3}),
+            (1.0, metrics.SampleType.Normal,
+             2 / 3, {"body": ["a"], "size": 3}),
+            (2.0, metrics.SampleType.Normal,
+             3 / 3, {"body": ["a"], "size": 3}),
         ], schedule)
 
     @run_async
     async def test_schedule_param_source_determines_iterations_including_warmup(self):
         task = workload.Task("bulk-index", workload.Operation("bulk-index", workload.OperationType.Bulk.to_hyphenated_string(),
-                                                        params={"body": ["a"], "size": 5},
-                                                        param_source="worker-coordinator-test-param-source"),
-                          warmup_iterations=2, clients=4, params={"target-throughput": 4})
+                                                              params={
+                                                                  "body": ["a"], "size": 5},
+                                                              param_source="worker-coordinator-test-param-source"),
+                             warmup_iterations=2, clients=4, params={"target-throughput": 4})
 
         param_source = workload.operation_parameters(self.test_workload, task)
         task_allocation = worker_coordinator.TaskAllocation(
@@ -1002,23 +1116,30 @@ async def test_schedule_param_source_determines_iterations_including_warmup(self
             global_client_index=0,
             total_clients=task.clients
         )
-        schedule = worker_coordinator.schedule_for(task_allocation, param_source)
+        schedule = worker_coordinator.schedule_for(
+            task_allocation, param_source)
 
         await self.assert_schedule([
-            (0.0, metrics.SampleType.Warmup, 1 / 5, {"body": ["a"], "size": 5}),
-            (1.0, metrics.SampleType.Warmup, 2 / 5, {"body": ["a"], "size": 5}),
-            (2.0, metrics.SampleType.Normal, 3 / 5, {"body": ["a"], "size": 5}),
-            (3.0, metrics.SampleType.Normal, 4 / 5, {"body": ["a"], "size": 5}),
-            (4.0, metrics.SampleType.Normal, 5 / 5, {"body": ["a"], "size": 5}),
+            (0.0, metrics.SampleType.Warmup,
+             1 / 5, {"body": ["a"], "size": 5}),
+            (1.0, metrics.SampleType.Warmup,
+             2 / 5, {"body": ["a"], "size": 5}),
+            (2.0, metrics.SampleType.Normal,
+             3 / 5, {"body": ["a"], "size": 5}),
+            (3.0, metrics.SampleType.Normal,
+             4 / 5, {"body": ["a"], "size": 5}),
+            (4.0, metrics.SampleType.Normal,
+             5 / 5, {"body": ["a"], "size": 5}),
         ], schedule)
 
     @run_async
     async def test_schedule_defaults_to_iteration_based(self):
         # no time-period and no iterations specified on the task. Also, the parameter source does not define a size.
         task = workload.Task("bulk-index", workload.Operation("bulk-index", workload.OperationType.Bulk.to_hyphenated_string(),
-                                                        params={"body": ["a"]},
-                                                        param_source="worker-coordinator-test-param-source"),
-                          clients=1, params={"target-throughput": 4, "clients": 4})
+                                                              params={
+                                                                  "body": ["a"]},
+                                                              param_source="worker-coordinator-test-param-source"),
+                             clients=1, params={"target-throughput": 4, "clients": 4})
 
         param_source = workload.operation_parameters(self.test_workload, task)
         task_allocation = worker_coordinator.TaskAllocation(
@@ -1027,7 +1148,8 @@ async def test_schedule_defaults_to_iteration_based(self):
             global_client_index=0,
             total_clients=task.clients
         )
-        schedule = worker_coordinator.schedule_for(task_allocation, param_source)
+        schedule = worker_coordinator.schedule_for(
+            task_allocation, param_source)
 
         await self.assert_schedule([
             (0.0, metrics.SampleType.Normal, 1 / 1, {"body": ["a"]}),
@@ -1036,9 +1158,10 @@ async def test_schedule_defaults_to_iteration_based(self):
     @run_async
     async def test_schedule_for_warmup_time_based(self):
         task = workload.Task("time-based", workload.Operation("time-based", workload.OperationType.Bulk.to_hyphenated_string(),
-                                                        params={"body": ["a"], "size": 11},
-                                                        param_source="worker-coordinator-test-param-source"),
-                          warmup_time_period=0, clients=4, params={"target-throughput": 4, "clients": 4})
+                                                              params={
+                                                                  "body": ["a"], "size": 11},
+                                                              param_source="worker-coordinator-test-param-source"),
+                             warmup_time_period=0, clients=4, params={"target-throughput": 4, "clients": 4})
 
         param_source = workload.operation_parameters(self.test_workload, task)
         task_allocation = worker_coordinator.TaskAllocation(
@@ -1047,28 +1170,41 @@ async def test_schedule_for_warmup_time_based(self):
             global_client_index=0,
             total_clients=task.clients
         )
-        schedule = worker_coordinator.schedule_for(task_allocation, param_source)
+        schedule = worker_coordinator.schedule_for(
+            task_allocation, param_source)
 
         await self.assert_schedule([
-            (0.0, metrics.SampleType.Normal, 1 / 11, {"body": ["a"], "size": 11}),
-            (1.0, metrics.SampleType.Normal, 2 / 11, {"body": ["a"], "size": 11}),
-            (2.0, metrics.SampleType.Normal, 3 / 11, {"body": ["a"], "size": 11}),
-            (3.0, metrics.SampleType.Normal, 4 / 11, {"body": ["a"], "size": 11}),
-            (4.0, metrics.SampleType.Normal, 5 / 11, {"body": ["a"], "size": 11}),
-            (5.0, metrics.SampleType.Normal, 6 / 11, {"body": ["a"], "size": 11}),
-            (6.0, metrics.SampleType.Normal, 7 / 11, {"body": ["a"], "size": 11}),
-            (7.0, metrics.SampleType.Normal, 8 / 11, {"body": ["a"], "size": 11}),
-            (8.0, metrics.SampleType.Normal, 9 / 11, {"body": ["a"], "size": 11}),
-            (9.0, metrics.SampleType.Normal, 10 / 11, {"body": ["a"], "size": 11}),
-            (10.0, metrics.SampleType.Normal, 11 / 11, {"body": ["a"], "size": 11}),
+            (0.0, metrics.SampleType.Normal, 1 /
+             11, {"body": ["a"], "size": 11}),
+            (1.0, metrics.SampleType.Normal, 2 /
+             11, {"body": ["a"], "size": 11}),
+            (2.0, metrics.SampleType.Normal, 3 /
+             11, {"body": ["a"], "size": 11}),
+            (3.0, metrics.SampleType.Normal, 4 /
+             11, {"body": ["a"], "size": 11}),
+            (4.0, metrics.SampleType.Normal, 5 /
+             11, {"body": ["a"], "size": 11}),
+            (5.0, metrics.SampleType.Normal, 6 /
+             11, {"body": ["a"], "size": 11}),
+            (6.0, metrics.SampleType.Normal, 7 /
+             11, {"body": ["a"], "size": 11}),
+            (7.0, metrics.SampleType.Normal, 8 /
+             11, {"body": ["a"], "size": 11}),
+            (8.0, metrics.SampleType.Normal, 9 /
+             11, {"body": ["a"], "size": 11}),
+            (9.0, metrics.SampleType.Normal, 10 /
+             11, {"body": ["a"], "size": 11}),
+            (10.0, metrics.SampleType.Normal,
+             11 / 11, {"body": ["a"], "size": 11}),
         ], schedule)
 
     @run_async
     async def test_infinite_schedule_without_progress_indication(self):
         task = workload.Task("time-based", workload.Operation("time-based", workload.OperationType.Bulk.to_hyphenated_string(),
-                                                        params={"body": ["a"]},
-                                                        param_source="worker-coordinator-test-param-source"),
-                          warmup_time_period=0, clients=4, params={"target-throughput": 4, "clients": 4})
+                                                              params={
+                                                                  "body": ["a"]},
+                                                              param_source="worker-coordinator-test-param-source"),
+                             warmup_time_period=0, clients=4, params={"target-throughput": 4, "clients": 4})
 
         param_source = workload.operation_parameters(self.test_workload, task)
         task_allocation = worker_coordinator.TaskAllocation(
@@ -1077,7 +1213,8 @@ async def test_infinite_schedule_without_progress_indication(self):
             global_client_index=0,
             total_clients=task.clients
         )
-        schedule = worker_coordinator.schedule_for(task_allocation, param_source)
+        schedule = worker_coordinator.schedule_for(
+            task_allocation, param_source)
 
         await self.assert_schedule([
             (0.0, metrics.SampleType.Normal, None, {"body": ["a"]}),
@@ -1090,9 +1227,10 @@ async def test_infinite_schedule_without_progress_indication(self):
     @run_async
     async def test_finite_schedule_with_progress_indication(self):
         task = workload.Task("time-based", workload.Operation("time-based", workload.OperationType.Bulk.to_hyphenated_string(),
-                                                        params={"body": ["a"], "size": 5},
-                                                        param_source="worker-coordinator-test-param-source"),
-                          warmup_time_period=0, clients=4, params={"target-throughput": 4, "clients": 4})
+                                                              params={
+                                                                  "body": ["a"], "size": 5},
+                                                              param_source="worker-coordinator-test-param-source"),
+                             warmup_time_period=0, clients=4, params={"target-throughput": 4, "clients": 4})
 
         param_source = workload.operation_parameters(self.test_workload, task)
         task_allocation = worker_coordinator.TaskAllocation(
@@ -1101,23 +1239,30 @@ async def test_finite_schedule_with_progress_indication(self):
             global_client_index=0,
             total_clients=task.clients
         )
-        schedule = worker_coordinator.schedule_for(task_allocation,param_source)
+        schedule = worker_coordinator.schedule_for(
+            task_allocation, param_source)
 
         await self.assert_schedule([
-            (0.0, metrics.SampleType.Normal, 1 / 5, {"body": ["a"], "size": 5}),
-            (1.0, metrics.SampleType.Normal, 2 / 5, {"body": ["a"], "size": 5}),
-            (2.0, metrics.SampleType.Normal, 3 / 5, {"body": ["a"], "size": 5}),
-            (3.0, metrics.SampleType.Normal, 4 / 5, {"body": ["a"], "size": 5}),
-            (4.0, metrics.SampleType.Normal, 5 / 5, {"body": ["a"], "size": 5}),
+            (0.0, metrics.SampleType.Normal,
+             1 / 5, {"body": ["a"], "size": 5}),
+            (1.0, metrics.SampleType.Normal,
+             2 / 5, {"body": ["a"], "size": 5}),
+            (2.0, metrics.SampleType.Normal,
+             3 / 5, {"body": ["a"], "size": 5}),
+            (3.0, metrics.SampleType.Normal,
+             4 / 5, {"body": ["a"], "size": 5}),
+            (4.0, metrics.SampleType.Normal,
+             5 / 5, {"body": ["a"], "size": 5}),
         ], schedule, infinite_schedule=False)
 
     @run_async
     async def test_schedule_with_progress_determined_by_runner(self):
         task = workload.Task("time-based", workload.Operation("time-based", "worker-coordinator-test-runner-with-completion",
-                                                        params={"body": ["a"]},
-                                                        param_source="worker-coordinator-test-param-source"),
-                          clients=1,
-                          params={"target-throughput": 1, "clients": 1})
+                                                              params={
+                                                                  "body": ["a"]},
+                                                              param_source="worker-coordinator-test-param-source"),
+                             clients=1,
+                             params={"target-throughput": 1, "clients": 1})
 
         param_source = workload.operation_parameters(self.test_workload, task)
         task_allocation = worker_coordinator.TaskAllocation(
@@ -1126,7 +1271,8 @@ async def test_schedule_with_progress_determined_by_runner(self):
             global_client_index=0,
             total_clients=task.clients
         )
-        schedule = worker_coordinator.schedule_for(task_allocation, param_source)
+        schedule = worker_coordinator.schedule_for(
+            task_allocation, param_source)
 
         await self.assert_schedule([
             (0.0, metrics.SampleType.Normal, None, {"body": ["a"]}),
@@ -1139,11 +1285,12 @@ async def test_schedule_with_progress_determined_by_runner(self):
     @run_async
     async def test_schedule_for_time_based(self):
         task = workload.Task("time-based", workload.Operation("time-based", workload.OperationType.Bulk.to_hyphenated_string(),
-                                                        params={"body": ["a"], "size": 11},
-                                                        param_source="worker-coordinator-test-param-source"),
-                          warmup_time_period=0.1,
-                          time_period=0.1,
-                          clients=1)
+                                                              params={
+                                                                  "body": ["a"], "size": 11},
+                                                              param_source="worker-coordinator-test-param-source"),
+                             warmup_time_period=0.1,
+                             time_period=0.1,
+                             clients=1)
 
         param_source = workload.operation_parameters(self.test_workload, task)
         task_allocation = worker_coordinator.TaskAllocation(
@@ -1152,7 +1299,8 @@ async def test_schedule_for_time_based(self):
             global_client_index=0,
             total_clients=task.clients
         )
-        schedule_handle = worker_coordinator.schedule_for(task_allocation, param_source)
+        schedule_handle = worker_coordinator.schedule_for(
+            task_allocation, param_source)
         schedule_handle.start()
         self.assertEqual(0.0, schedule_handle.ramp_up_wait_time)
         schedule = schedule_handle()
@@ -1168,8 +1316,10 @@ async def test_schedule_for_time_based(self):
                 self.assertEqual(metrics.SampleType.Normal, sample_type)
             self.assertTrue(last_progress < progress_percent)
             last_progress = progress_percent
-            self.assertTrue(round(progress_percent, 2) >= 0.0, "progress should be >= 0.0 but was [%f]" % progress_percent)
-            self.assertTrue(round(progress_percent, 2) <= 1.0, "progress should be <= 1.0 but was [%f]" % progress_percent)
+            self.assertTrue(round(progress_percent, 2) >= 0.0,
+                            "progress should be >= 0.0 but was [%f]" % progress_percent)
+            self.assertTrue(round(progress_percent, 2) <= 1.0,
+                            "progress should be <= 1.0 but was [%f]" % progress_percent)
             self.assertIsNotNone(runner, "runner must be defined")
             self.assertEqual({"body": ["a"], "size": 11}, params)
 
@@ -1256,8 +1406,10 @@ def setUp(self):
         runner.register_default_runners()
         self.runner_with_progress = AsyncExecutorTests.RunnerWithProgress()
         self.runner_overriding_throughput = AsyncExecutorTests.RunnerOverridingThroughput()
-        runner.register_runner("unit-test-recovery", self.runner_with_progress, async_runner=True)
-        runner.register_runner("override-throughput", self.runner_overriding_throughput, async_runner=True)
+        runner.register_runner("unit-test-recovery",
+                               self.runner_with_progress, async_runner=True)
+        runner.register_runner(
+            "override-throughput", self.runner_overriding_throughput, async_runner=True)
 
     @mock.patch('osbenchmark.client.RequestContextHolder.on_client_request_end')
     @mock.patch('osbenchmark.client.RequestContextHolder.on_client_request_start')
@@ -1265,55 +1417,60 @@ def setUp(self):
     @run_async
     async def test_execute_schedule_in_throughput_mode(self, opensearch, on_client_request_start, on_client_request_end):
         task_start = time.perf_counter()
-        opensearch.new_request_context.return_value = AsyncExecutorTests.StaticRequestTiming(task_start=task_start)
+        opensearch.new_request_context.return_value = AsyncExecutorTests.StaticRequestTiming(
+            task_start=task_start)
 
-        opensearch.bulk.return_value = as_future(io.StringIO('{"errors": false, "took": 8}'))
+        opensearch.bulk.return_value = as_future(
+            io.StringIO('{"errors": false, "took": 8}'))
 
-        params.register_param_source_for_name("worker-coordinator-test-param-source", WorkerCoordinatorTestParamSource)
+        params.register_param_source_for_name(
+            "worker-coordinator-test-param-source", WorkerCoordinatorTestParamSource)
         test_workload = workload.Workload(name="unittest", description="unittest workload",
-                                 indices=None,
-                                 test_procedures=None)
+                                          indices=None,
+                                          test_procedures=None)
 
         task = workload.Task("time-based", workload.Operation("time-based", workload.OperationType.Bulk.to_hyphenated_string(),
-                                                        params={
-                                                            "body": ["action_metadata_line", "index_line"],
-                                                            "action-metadata-present": True,
-                                                            "bulk-size": 1,
-                                                            "unit": "docs",
-                                                            # we need this because WorkerCoordinatorTestParamSource does not know
-                                                            # that we only have one bulk and hence size() returns
-                                                            # incorrect results
-                                                            "size": 1
-                                                        },
-                                                        param_source="worker-coordinator-test-param-source"),
-                          warmup_time_period=0, clients=4)
+                                                              params={
+            "body": ["action_metadata_line", "index_line"],
+            "action-metadata-present": True,
+            "bulk-size": 1,
+            "unit": "docs",
+            # we need this because WorkerCoordinatorTestParamSource does not know
+            # that we only have one bulk and hence size() returns
+            # incorrect results
+            "size": 1
+        },
+            param_source="worker-coordinator-test-param-source"),
+            warmup_time_period=0, clients=4)
         param_source = workload.operation_parameters(test_workload, task)
         task_allocation = worker_coordinator.TaskAllocation(task=task,
-                                                client_index_in_task=0,
-                                                global_client_index=0,
-                                                total_clients=task.clients)
-        schedule = worker_coordinator.schedule_for(task_allocation, param_source)
+                                                            client_index_in_task=0,
+                                                            global_client_index=0,
+                                                            total_clients=task.clients)
+        schedule = worker_coordinator.schedule_for(
+            task_allocation, param_source)
 
         sampler = worker_coordinator.Sampler(start_timestamp=task_start)
         cancel = threading.Event()
         complete = threading.Event()
 
         execute_schedule = worker_coordinator.AsyncExecutor(client_id=2,
-                                                task=task,
-                                                schedule=schedule,
-                                                opensearch={
-                                                    "default": opensearch
-                                                },
-                                                sampler=sampler,
-                                                cancel=cancel,
-                                                complete=complete,
-                                                on_error="continue")
+                                                            task=task,
+                                                            schedule=schedule,
+                                                            opensearch={
+                                                                "default": opensearch
+                                                            },
+                                                            sampler=sampler,
+                                                            cancel=cancel,
+                                                            complete=complete,
+                                                            on_error="continue")
         await execute_schedule()
 
         samples = sampler.samples
 
         self.assertTrue(len(samples) > 0)
-        self.assertFalse(complete.is_set(), "Executor should not auto-complete a normal task")
+        self.assertFalse(complete.is_set(),
+                         "Executor should not auto-complete a normal task")
         previous_absolute_time = -1.0
         previous_relative_time = -1.0
         for sample in samples:
@@ -1334,12 +1491,14 @@ async def test_execute_schedule_in_throughput_mode(self, opensearch, on_client_r
     @run_async
     async def test_execute_schedule_with_progress_determined_by_runner(self, opensearch):
         task_start = time.perf_counter()
-        opensearch.new_request_context.return_value = AsyncExecutorTests.StaticRequestTiming(task_start=task_start)
+        opensearch.new_request_context.return_value = AsyncExecutorTests.StaticRequestTiming(
+            task_start=task_start)
 
-        params.register_param_source_for_name("worker-coordinator-test-param-source", WorkerCoordinatorTestParamSource)
+        params.register_param_source_for_name(
+            "worker-coordinator-test-param-source", WorkerCoordinatorTestParamSource)
         test_workload = workload.Workload(name="unittest", description="unittest workload",
-                                 indices=None,
-                                 test_procedures=None)
+                                          indices=None,
+                                          test_procedures=None)
 
         task = workload.Task("time-based", workload.Operation("time-based", operation_type="unit-test-recovery", params={
             "indices-to-restore": "*",
@@ -1348,25 +1507,26 @@ async def test_execute_schedule_with_progress_determined_by_runner(self, opensea
         }, param_source="worker-coordinator-test-param-source"), warmup_time_period=0, clients=4)
         param_source = workload.operation_parameters(test_workload, task)
         task_allocation = worker_coordinator.TaskAllocation(task=task,
-                                                client_index_in_task=0,
-                                                global_client_index=0,
-                                                total_clients=task.clients)
-        schedule = worker_coordinator.schedule_for(task_allocation, param_source)
+                                                            client_index_in_task=0,
+                                                            global_client_index=0,
+                                                            total_clients=task.clients)
+        schedule = worker_coordinator.schedule_for(
+            task_allocation, param_source)
 
         sampler = worker_coordinator.Sampler(start_timestamp=task_start)
         cancel = threading.Event()
         complete = threading.Event()
 
         execute_schedule = worker_coordinator.AsyncExecutor(client_id=2,
-                                                task=task,
-                                                schedule=schedule,
-                                                opensearch={
-                                                    "default": opensearch
-                                                },
-                                                sampler=sampler,
-                                                cancel=cancel,
-                                                complete=complete,
-                                                on_error="continue")
+                                                            task=task,
+                                                            schedule=schedule,
+                                                            opensearch={
+                                                                "default": opensearch
+                                                            },
+                                                            sampler=sampler,
+                                                            cancel=cancel,
+                                                            complete=complete,
+                                                            on_error="continue")
         await execute_schedule()
 
         samples = sampler.samples
@@ -1374,7 +1534,8 @@ async def test_execute_schedule_with_progress_determined_by_runner(self, opensea
         self.assertEqual(5, len(samples))
         self.assertTrue(self.runner_with_progress.completed)
         self.assertEqual(1.0, self.runner_with_progress.percent_completed)
-        self.assertFalse(complete.is_set(), "Executor should not auto-complete a normal task")
+        self.assertFalse(complete.is_set(),
+                         "Executor should not auto-complete a normal task")
         previous_absolute_time = -1.0
         previous_relative_time = -1.0
         for sample in samples:
@@ -1397,47 +1558,51 @@ async def test_execute_schedule_with_progress_determined_by_runner(self, opensea
     @run_async
     async def test_execute_schedule_runner_overrides_times(self, opensearch):
         task_start = time.perf_counter()
-        opensearch.new_request_context.return_value = AsyncExecutorTests.StaticRequestTiming(task_start=task_start)
+        opensearch.new_request_context.return_value = AsyncExecutorTests.StaticRequestTiming(
+            task_start=task_start)
 
-        params.register_param_source_for_name("worker-coordinator-test-param-source", WorkerCoordinatorTestParamSource)
+        params.register_param_source_for_name(
+            "worker-coordinator-test-param-source", WorkerCoordinatorTestParamSource)
         test_workload = workload.Workload(name="unittest", description="unittest workload",
-                                 indices=None,
-                                 test_procedures=None)
+                                          indices=None,
+                                          test_procedures=None)
 
         task = workload.Task("override-throughput", workload.Operation("override-throughput",
-                                                                 operation_type="override-throughput", params={
-                # we need this because WorkerCoordinatorTestParamSource does not know that we only have one iteration and hence
-                # size() returns incorrect results
-                "size": 1
-            },
-                                                                 param_source="worker-coordinator-test-param-source"),
-                          warmup_iterations=0, iterations=1, clients=1)
+                                                                       operation_type="override-throughput", params={
+                                                                           # we need this because WorkerCoordinatorTestParamSource does not know that we only have one iteration and hence
+                                                                           # size() returns incorrect results
+                                                                           "size": 1
+                                                                       },
+                                                                       param_source="worker-coordinator-test-param-source"),
+                             warmup_iterations=0, iterations=1, clients=1)
         param_source = workload.operation_parameters(test_workload, task)
         task_allocation = worker_coordinator.TaskAllocation(task=task,
-                                                client_index_in_task=0,
-                                                global_client_index=0,
-                                                total_clients=task.clients)
-        schedule = worker_coordinator.schedule_for(task_allocation, param_source)
+                                                            client_index_in_task=0,
+                                                            global_client_index=0,
+                                                            total_clients=task.clients)
+        schedule = worker_coordinator.schedule_for(
+            task_allocation, param_source)
 
         sampler = worker_coordinator.Sampler(start_timestamp=task_start)
         cancel = threading.Event()
         complete = threading.Event()
 
         execute_schedule = worker_coordinator.AsyncExecutor(client_id=0,
-                                                task=task,
-                                                schedule=schedule,
-                                                opensearch={
-                                                    "default": opensearch
-                                                },
-                                                sampler=sampler,
-                                                cancel=cancel,
-                                                complete=complete,
-                                                on_error="continue")
+                                                            task=task,
+                                                            schedule=schedule,
+                                                            opensearch={
+                                                                "default": opensearch
+                                                            },
+                                                            sampler=sampler,
+                                                            cancel=cancel,
+                                                            complete=complete,
+                                                            on_error="continue")
         await execute_schedule()
 
         samples = sampler.samples
 
-        self.assertFalse(complete.is_set(), "Executor should not auto-complete a normal task")
+        self.assertFalse(complete.is_set(),
+                         "Executor should not auto-complete a normal task")
         self.assertEqual(1, len(samples))
         sample = samples[0]
         self.assertEqual(0, sample.client_id)
@@ -1469,27 +1634,29 @@ def perform_request(*args, **kwargs):
         # one has been "consumed".
         opensearch.transport.perform_request.side_effect = perform_request
 
-        params.register_param_source_for_name("worker-coordinator-test-param-source", WorkerCoordinatorTestParamSource)
+        params.register_param_source_for_name(
+            "worker-coordinator-test-param-source", WorkerCoordinatorTestParamSource)
         test_workload = workload.Workload(name="unittest", description="unittest workload",
-                                 indices=None,
-                                 test_procedures=None)
+                                          indices=None,
+                                          test_procedures=None)
 
         # in one second (0.5 warmup + 0.5 measurement) we should get 1000 [ops/s] / 4 [clients] = 250 samples
         for target_throughput, bounds in {10: [2, 4], 100: [24, 26], 1000: [235, 255]}.items():
             task = workload.Task("time-based", workload.Operation("time-based",
-                                                            workload.OperationType.Search.to_hyphenated_string(),
-                                                            params={
-                                                                "index": "_all",
-                                                                "type": None,
-                                                                "body": {"query": {"match_all": {}}},
-                                                                "request-params": {},
-                                                                "cache": False,
-                                                                "response-compression-enabled": True
-                                                            },
-                                                            param_source="worker-coordinator-test-param-source"),
-                              warmup_time_period=0.5, time_period=0.5, clients=4,
-                              params={"target-throughput": target_throughput, "clients": 4},
-                              completes_parent=True)
+                                                                  workload.OperationType.Search.to_hyphenated_string(),
+                                                                  params={
+                                                                      "index": "_all",
+                                                                      "type": None,
+                                                                      "body": {"query": {"match_all": {}}},
+                                                                      "request-params": {},
+                                                                      "cache": False,
+                                                                      "response-compression-enabled": True
+                                                                  },
+                                                                  param_source="worker-coordinator-test-param-source"),
+                                 warmup_time_period=0.5, time_period=0.5, clients=4,
+                                 params={
+                                     "target-throughput": target_throughput, "clients": 4},
+                                 completes_parent=True)
             sampler = worker_coordinator.Sampler(start_timestamp=0)
 
             cancel = threading.Event()
@@ -1497,20 +1664,21 @@ def perform_request(*args, **kwargs):
 
             param_source = workload.operation_parameters(test_workload, task)
             task_allocation = worker_coordinator.TaskAllocation(task=task,
-                                                client_index_in_task=0,
-                                                global_client_index=0,
-                                                total_clients=task.clients)
-            schedule = worker_coordinator.schedule_for(task_allocation, param_source)
+                                                                client_index_in_task=0,
+                                                                global_client_index=0,
+                                                                total_clients=task.clients)
+            schedule = worker_coordinator.schedule_for(
+                task_allocation, param_source)
             execute_schedule = worker_coordinator.AsyncExecutor(client_id=0,
-                                                    task=task,
-                                                    schedule=schedule,
-                                                    opensearch={
-                                                        "default": opensearch
-                                                    },
-                                                    sampler=sampler,
-                                                    cancel=cancel,
-                                                    complete=complete,
-                                                    on_error="continue")
+                                                                task=task,
+                                                                schedule=schedule,
+                                                                opensearch={
+                                                                    "default": opensearch
+                                                                },
+                                                                sampler=sampler,
+                                                                cancel=cancel,
+                                                                complete=complete,
+                                                                on_error="continue")
             await execute_schedule()
 
             samples = sampler.samples
@@ -1520,7 +1688,8 @@ def perform_request(*args, **kwargs):
             upper_bound = bounds[1]
             self.assertTrue(lower_bound <= sample_size <= upper_bound,
                             msg="Expected sample size to be between %d and %d but was %d" % (lower_bound, upper_bound, sample_size))
-            self.assertTrue(complete.is_set(), "Executor should auto-complete a task that terminates its parent")
+            self.assertTrue(complete.is_set(
+            ), "Executor should auto-complete a task that terminates its parent")
 
     @mock.patch("opensearchpy.OpenSearch")
     @run_async
@@ -1531,46 +1700,49 @@ async def test_cancel_execute_schedule(self, opensearch):
             "request_end": 11,
             "client_request_end": 12
         }
-        opensearch.bulk.return_value = as_future(io.StringIO('{"errors": false, "took": 8}'))
+        opensearch.bulk.return_value = as_future(
+            io.StringIO('{"errors": false, "took": 8}'))
 
-        params.register_param_source_for_name("worker-coordinator-test-param-source", WorkerCoordinatorTestParamSource)
+        params.register_param_source_for_name(
+            "worker-coordinator-test-param-source", WorkerCoordinatorTestParamSource)
         test_workload = workload.Workload(name="unittest", description="unittest workload",
-                                 indices=None,
-                                 test_procedures=None)
+                                          indices=None,
+                                          test_procedures=None)
 
         # in one second (0.5 warmup + 0.5 measurement) we should get 1000 [ops/s] / 4 [clients] = 250 samples
         for target_throughput in [10, 100, 1000]:
             task = workload.Task("time-based", workload.Operation("time-based",
-                                                            workload.OperationType.Bulk.to_hyphenated_string(),
-                                                            params={
-                                                                "body": ["action_metadata_line", "index_line"],
-                                                                "action-metadata-present": True,
-                                                                "bulk-size": 1
-                                                            },
-                                                            param_source="worker-coordinator-test-param-source"),
-                              warmup_time_period=0.5, time_period=0.5, clients=4,
-                              params={"target-throughput": target_throughput, "clients": 4})
+                                                                  workload.OperationType.Bulk.to_hyphenated_string(),
+                                                                  params={
+                                                                      "body": ["action_metadata_line", "index_line"],
+                                                                      "action-metadata-present": True,
+                                                                      "bulk-size": 1
+                                                                  },
+                                                                  param_source="worker-coordinator-test-param-source"),
+                                 warmup_time_period=0.5, time_period=0.5, clients=4,
+                                 params={"target-throughput": target_throughput, "clients": 4})
 
             param_source = workload.operation_parameters(test_workload, task)
             task_allocation = worker_coordinator.TaskAllocation(task=task,
-                                                client_index_in_task=0,
-                                                global_client_index=0,
-                                                total_clients=task.clients)
-            schedule = worker_coordinator.schedule_for(task_allocation, param_source)
+                                                                client_index_in_task=0,
+                                                                global_client_index=0,
+                                                                total_clients=task.clients)
+            schedule = worker_coordinator.schedule_for(
+                task_allocation, param_source)
             sampler = worker_coordinator.Sampler(start_timestamp=0)
 
             cancel = threading.Event()
             complete = threading.Event()
             execute_schedule = worker_coordinator.AsyncExecutor(client_id=0,
-                                                    task=task,
-                                                    schedule=schedule,
-                                                    opensearch={
-                                                        "default": opensearch
-                                                    },
-                                                    sampler=sampler,
-                                                    cancel=cancel,
-                                                    complete=complete,
-                                                    on_error="continue")
+                                                                task=task,
+                                                                schedule=schedule,
+                                                                opensearch={
+                                                                    "default": opensearch
+                                                                },
+                                                                sampler=sampler,
+                                                                cancel=cancel,
+                                                                complete=complete,
+                                                                on_error="continue")
 
             cancel.set()
             await execute_schedule()
@@ -1605,29 +1777,30 @@ def start(self):
                 pass
 
             async def __call__(self):
-                invocations = [(0, metrics.SampleType.Warmup, 0, AsyncExecutorTests.context_managed(run), None)]
+                invocations = [(0, metrics.SampleType.Warmup, 0,
+                                AsyncExecutorTests.context_managed(run), None)]
                 for invocation in invocations:
                     yield invocation
 
         task = workload.Task("no-op", workload.Operation("no-op", workload.OperationType.Bulk.to_hyphenated_string(),
-                                                   params={},
-                                                   param_source="worker-coordinator-test-param-source"),
-                          warmup_time_period=0.5, time_period=0.5, clients=4,
-                          params={"clients": 4})
+                                                         params={},
+                                                         param_source="worker-coordinator-test-param-source"),
+                             warmup_time_period=0.5, time_period=0.5, clients=4,
+                             params={"clients": 4})
 
         sampler = worker_coordinator.Sampler(start_timestamp=0)
         cancel = threading.Event()
         complete = threading.Event()
         execute_schedule = worker_coordinator.AsyncExecutor(client_id=2,
-                                                task=task,
-                                                schedule=ScheduleHandle(),
-                                                opensearch={
-                                                    "default": opensearch
-                                                },
-                                                sampler=sampler,
-                                                cancel=cancel,
-                                                complete=complete,
-                                                on_error="continue")
+                                                            task=task,
+                                                            schedule=ScheduleHandle(),
+                                                            opensearch={
+                                                                "default": opensearch
+                                                            },
+                                                            sampler=sampler,
+                                                            cancel=cancel,
+                                                            complete=complete,
+                                                            on_error="continue")
 
         with self.assertRaisesRegex(exceptions.BenchmarkError, r"Cannot run task \[no-op\]: expected unit test exception"):
             await execute_schedule()
@@ -1702,7 +1875,8 @@ async def test_execute_single_with_connection_error_always_aborts(self, on_clien
                 opensearch = None
                 params = None
                 # ES client uses pseudo-status "N/A" in this case...
-                runner = mock.Mock(side_effect=as_future(exception=opensearchpy.ConnectionError("N/A", "no route to host", None)))
+                runner = mock.Mock(side_effect=as_future(
+                    exception=opensearchpy.ConnectionError("N/A", "no route to host", None)))
 
                 with self.assertRaises(exceptions.BenchmarkAssertionError) as ctx:
                     await worker_coordinator.execute_single(self.context_managed(runner), opensearch, params, on_error=on_error)
@@ -1715,8 +1889,8 @@ async def test_execute_single_with_connection_error_always_aborts(self, on_clien
     async def test_execute_single_with_http_400_aborts_when_specified(self, on_client_request_end):
         opensearch = None
         params = None
-        runner = mock.Mock(side_effect=
-                           as_future(exception=opensearchpy.NotFoundError(404, "not found", "the requested document could not be found")))
+        runner = mock.Mock(side_effect=as_future(exception=opensearchpy.NotFoundError(
+            404, "not found", "the requested document could not be found")))
 
         with self.assertRaises(exceptions.BenchmarkAssertionError) as ctx:
             await worker_coordinator.execute_single(self.context_managed(runner), opensearch, params, on_error="abort")
@@ -1729,8 +1903,8 @@ async def test_execute_single_with_http_400_aborts_when_specified(self, on_clien
     async def test_execute_single_with_http_400(self, on_client_request_end):
         opensearch = None
         params = None
-        runner = mock.Mock(side_effect=
-                           as_future(exception=opensearchpy.NotFoundError(404, "not found", "the requested document could not be found")))
+        runner = mock.Mock(side_effect=as_future(exception=opensearchpy.NotFoundError(
+            404, "not found", "the requested document could not be found")))
 
         ops, unit, request_meta_data = await worker_coordinator.execute_single(
             self.context_managed(runner), opensearch, params, on_error="continue")
@@ -1749,8 +1923,8 @@ async def test_execute_single_with_http_400(self, on_client_request_end):
     async def test_execute_single_with_http_413(self, on_client_request_end):
         opensearch = None
         params = None
-        runner = mock.Mock(side_effect=
-                           as_future(exception=opensearchpy.NotFoundError(413, b"", b"")))
+        runner = mock.Mock(side_effect=as_future(
+            exception=opensearchpy.NotFoundError(413, b"", b"")))
 
         ops, unit, request_meta_data = await worker_coordinator.execute_single(
             self.context_managed(runner), opensearch, params, on_error="continue")
@@ -1803,4 +1977,5 @@ async def f(x):
         end = time.perf_counter()
         self.assertEqual(2, return_value)
         duration = end - start
-        self.assertTrue(0.9 <= duration <= 1.2, "Should sleep for roughly 1 second but took [%.2f] seconds." % duration)
+        self.assertTrue(0.9 <= duration <= 1.2,
+                        "Should sleep for roughly 1 second but took [%.2f] seconds." % duration)