Repository: AgnostiqHQ/covalent (language: python)

Issue:
RTD reference to `ct.wait.LONG` must be removed
## Acceptance Criteria

- RTD reference to `ct.wait.LONG` in MNIST Tutorial must be removed


Discussion / hints:
this must be updated on all tutorials... @scottwn  updated me saying that this has been fixed in v 0.178
v0.178 only deconflicts two public "wait" symbols by renaming the wait enum as `WAIT` (I used all caps b/c I thought an enum was basically a constant). According to @scottwn , however, this doesn't quite conform to PEP8 guidelines.

A couple of ways forward:
* Use `ct.WAIT.LONG` in the RTD.
* Choose a different name for the wait enum or the `ct.wait` function, and use that in the RTD.
* Don't expose the wait enum at all, revert the RTD to `wait=True`, and make `wait=True` equivalent in the backend to `wait.EXTREME`; thus would involve just a [minor adjustment here](https://github.com/AgnostiqHQ/covalent/blob/1feddd96a6428482845cc7fe510f9feb3ca82f56/covalent/_results_manager/results_manager.py#L172). This would be consistent with the original intent of `wait=True`, which according to @wjcunningham7  was to make `get_result()` block until the workflow completes. 

I vote for the last point for now, making long the default and we can work out the UX in the next release if we are planning to expose it. @wjcunningham7 

Fix patch:
diff --git a/CHANGELOG.md b/CHANGELOG.md
index b09ab0eea..343412d2a 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -7,6 +7,14 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [UNRELEASED]
 
+### Removed
+
+- Removed `ct.wait.LONG` etc. constants from covalent's init
+
+### Changed
+
+- `wait` in `_get_result_from_dispatcher` will now use `_results_manager.wait.EXTREME` if `True` has been passed to it.
+
 ### Operations
 
 - Prettierified release.yml
diff --git a/covalent/__init__.py b/covalent/__init__.py
index 848952d53..8e6263377 100644
--- a/covalent/__init__.py
+++ b/covalent/__init__.py
@@ -28,7 +28,6 @@
 from ._dispatcher_plugins import local_dispatch as dispatch
 from ._dispatcher_plugins import local_dispatch_sync as dispatch_sync
 from ._file_transfer import strategies as fs_strategies
-from ._results_manager import wait as WAIT
 from ._results_manager.results_manager import cancel, get_result, sync
 from ._shared_files.config import get_config, reload_config, set_config
 from ._shared_files.util_classes import RESULT_STATUS as status
diff --git a/covalent/_results_manager/results_manager.py b/covalent/_results_manager/results_manager.py
index 5b92defae..21cd7807d 100644
--- a/covalent/_results_manager/results_manager.py
+++ b/covalent/_results_manager/results_manager.py
@@ -38,21 +38,21 @@
 from .._data_store.models import Lattice
 from .._shared_files import logger
 from .._shared_files.config import get_config
-from . import wait
 from .result import Result
+from .wait import EXTREME
 from .write_result_to_db import MissingLatticeRecordError, load_file
 
 app_log = logger.app_log
 log_stack_info = logger.log_stack_info
 
 
-def get_result(dispatch_id: str, wait: bool or wait.Wait = False) -> Result:
+def get_result(dispatch_id: str, wait: bool = False) -> Result:
     """
     Get the results of a dispatch from a file.
 
     Args:
         dispatch_id: The dispatch id of the result.
-        wait: Controls how long the method waits for the server to return a result. If False, the method will not wait and will return the current status of the workflow. If True, the method will wait a short amount of time for a result. To wait longer, you may pass `ct.wait.LONG`, `ct.wait.VERY_LONG`, or `ct.wait.EXTREME`. For finer grained control, you may pass, for example, `ct.wait.Wait(50)`, where 50 is the number of times the server will be polled.
+        wait: Controls how long the method waits for the server to return a result. If False, the method will not wait and will return the current status of the workflow. If True, the method will wait for the result to finish and keep retrying for sys.maxsize.
 
     Returns:
         The result from the file.
@@ -148,7 +148,7 @@ def dummy_function(x):
 
 def _get_result_from_dispatcher(
     dispatch_id: str,
-    wait: bool or wait.Wait = False,
+    wait: bool = False,
     dispatcher: str = get_config("dispatcher.address") + ":" + str(get_config("dispatcher.port")),
     status_only: bool = False,
 ) -> Dict:
@@ -158,7 +158,7 @@ def _get_result_from_dispatcher(
 
     Args:
         dispatch_id: The dispatch id of the result.
-        wait: Controls how long the method waits for the server to return a result. If False, the method will not wait and will return the current status of the workflow. If True, the method will wait a short amount of time for a result. To wait longer, you may pass `ct.wait.LONG`, `ct.wait.VERY_LONG`, or `ct.wait.EXTREME`. For finer grained control, you may pass, for example, `ct.wait.Wait(50)`, where 50 is the number of times the server will be polled.
+        wait: Controls how long the method waits for the server to return a result. If False, the method will not wait and will return the current status of the workflow. If True, the method will wait for the result to finish and keep retrying for sys.maxsize.
         status_only: If true, only returns result status, not the full result object, default is False.
         dispatcher: Dispatcher server address, defaults to the address set in covalent.config.
 
@@ -168,9 +168,9 @@ def _get_result_from_dispatcher(
     Raises:
         MissingLatticeRecordError: If the result is not found.
     """
-    retries = 5
-    if wait and int(wait) > retries:
-        retries = int(wait)
+
+    retries = int(EXTREME) if wait else 5
+
     adapter = HTTPAdapter(max_retries=Retry(total=retries, backoff_factor=1))
     http = requests.Session()
     http.mount("http://", adapter)
@@ -255,15 +255,15 @@ def sync(
     """
 
     if isinstance(dispatch_id, str):
-        _get_result_from_dispatcher(dispatch_id, wait=wait.EXTREME, status_only=True)
+        _get_result_from_dispatcher(dispatch_id, wait=True, status_only=True)
     elif isinstance(dispatch_id, list):
         for d in dispatch_id:
-            _get_result_from_dispatcher(d, wait=wait.EXTREME, status_only=True)
+            _get_result_from_dispatcher(d, wait=True, status_only=True)
     else:
         with Session(db.engine) as session:
             rows = session.query(Lattice).all()
         for row in rows:
-            _get_result_from_dispatcher(row.dispatch_id, wait=wait.EXTREME, status_only=True)
+            _get_result_from_dispatcher(row.dispatch_id, wait=True, status_only=True)
 
 
 def cancel(
diff --git a/doc/source/tutorials/machine_learning/Covalent_pennylane_Iris_classification.ipynb b/doc/source/tutorials/machine_learning/Covalent_pennylane_Iris_classification.ipynb
index 45f5f0354..d587093e1 100644
--- a/doc/source/tutorials/machine_learning/Covalent_pennylane_Iris_classification.ipynb
+++ b/doc/source/tutorials/machine_learning/Covalent_pennylane_Iris_classification.ipynb
@@ -279,7 +279,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -291,7 +291,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -303,7 +303,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -553,7 +553,7 @@
    "outputs": [],
    "source": [
     "dispatch_id = ct.dispatch(workflow)(feats_train=feats_train,Y_train=Y_train,feats_val=feats_val,Y_val=Y_val,iterations=80,num_qubits=2,num_layers=6,num_train=num_train,Y=Y)\n",
-    "result = ct.get_result(dispatch_id=dispatch_id,wait=ct.wait.LONG)#,results_dir=\"./\")\n",
+    "result = ct.get_result(dispatch_id=dispatch_id,wait=True)\n",
     "weights,bias,training_steps,cost_steps,accuracy_steps = result.result"
    ]
   },
@@ -573,7 +573,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
diff --git a/doc/source/tutorials/machine_learning/Covalent_pennylane_Parity_classifier.ipynb b/doc/source/tutorials/machine_learning/Covalent_pennylane_Parity_classifier.ipynb
index a2e6213c1..94857fe82 100644
--- a/doc/source/tutorials/machine_learning/Covalent_pennylane_Parity_classifier.ipynb
+++ b/doc/source/tutorials/machine_learning/Covalent_pennylane_Parity_classifier.ipynb
@@ -379,7 +379,7 @@
    "source": [
     "\n",
     "dispatch_id = ct.dispatch(workflow)(X=X,Y=Y,epochs=25,num_layers=2,num_qubits=4)\n",
-    "result = ct.get_result(dispatch_id=dispatch_id,wait=ct.wait.LONG)#,results_dir=\"./\")\n",
+    "result = ct.get_result(dispatch_id=dispatch_id,wait=True)\n",
     "weights,bias,training_steps,cost_steps,accuracy_steps = result.result\n"
    ]
   },
@@ -390,7 +390,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
diff --git a/doc/source/tutorials/machine_learning/Ensemble_pennylane.ipynb b/doc/source/tutorials/machine_learning/Ensemble_pennylane.ipynb
index b562878b2..f46250cf0 100644
--- a/doc/source/tutorials/machine_learning/Ensemble_pennylane.ipynb
+++ b/doc/source/tutorials/machine_learning/Ensemble_pennylane.ipynb
@@ -147,7 +147,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -373,11 +373,11 @@
    },
    "outputs": [],
    "source": [
-    "train_result = ct.get_result(dispatch_id=dispatch_id_train, wait=ct.wait.LONG)\n",
+    "train_result = ct.get_result(dispatch_id=dispatch_id_train, wait=True)\n",
     "p_train, p_train_0, p_train_1, choices_train = train_result.result\n",
     "\n",
     "\n",
-    "test_result = ct.get_result(dispatch_id=dispatch_id_test, wait=ct.wait.LONG)\n",
+    "test_result = ct.get_result(dispatch_id=dispatch_id_test, wait=True)\n",
     "p_test, p_test_0, p_test_1, choices_test = train_result.result\n"
    ]
   },
diff --git a/doc/source/tutorials/machine_learning/Kernel_pennylane.ipynb b/doc/source/tutorials/machine_learning/Kernel_pennylane.ipynb
index 476bfdf7c..d43e94e05 100644
--- a/doc/source/tutorials/machine_learning/Kernel_pennylane.ipynb
+++ b/doc/source/tutorials/machine_learning/Kernel_pennylane.ipynb
@@ -218,7 +218,7 @@
     }
    ],
    "source": [
-    "kernel_result = ct.get_result(dispatch_id=dispatch_id, wait=ct.wait.LONG)\n",
+    "kernel_result = ct.get_result(dispatch_id=dispatch_id, wait=True)\n",
     "kernel_result.result"
    ]
   },
@@ -472,7 +472,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -489,7 +489,7 @@
     "steps = 100\n",
     "\n",
     "dispatch_id = ct.dispatch(variation_circuit)(n_layers, steps, batch_size)\n",
-    "result = ct.get_result(dispatch_id=dispatch_id, wait=ct.wait.LONG)\n",
+    "result = ct.get_result(dispatch_id=dispatch_id, wait=True)\n",
     "loss_history,trained_params, trained_bias, pred_test = result.result\n",
     "\n",
     "#loss_history,trained_params, trained_bias, pred_test = variation_circuit(n_layers, steps, batch_size)\n",
@@ -647,7 +647,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
diff --git a/doc/source/tutorials/machine_learning/autoencoders.ipynb b/doc/source/tutorials/machine_learning/autoencoders.ipynb
index 1670be070..854aca89b 100644
--- a/doc/source/tutorials/machine_learning/autoencoders.ipynb
+++ b/doc/source/tutorials/machine_learning/autoencoders.ipynb
@@ -436,7 +436,7 @@
    "outputs": [],
    "source": [
     "dispatch_id = ct.dispatch(run_experiments)(models=[create_linear_ae(), create_conv_ae()], epochs=50, log_interval=10)\n",
-    "results = ct.get_result(dispatch_id=dispatch_id, wait=ct.wait.LONG)"
+    "results = ct.get_result(dispatch_id=dispatch_id, wait=True)"
    ]
   },
   {
@@ -673,7 +673,7 @@
   "orig_nbformat": 4,
   "vscode": {
    "interpreter": {
-    "hash":""
+    "hash": ""
    }
   }
  },
diff --git a/doc/source/tutorials/machine_learning/classical_quantum_svm.ipynb b/doc/source/tutorials/machine_learning/classical_quantum_svm.ipynb
index 7e2d0b81a..7dbd2de19 100644
--- a/doc/source/tutorials/machine_learning/classical_quantum_svm.ipynb
+++ b/doc/source/tutorials/machine_learning/classical_quantum_svm.ipynb
@@ -247,7 +247,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "result = ct.get_result(dispatch_id=dispatch_id, wait=ct.wait.LONG)\n"
+    "result = ct.get_result(dispatch_id=dispatch_id, wait=True)\n"
    ]
   },
   {
@@ -319,11 +319,8 @@
   }
  ],
  "metadata": {
-  "interpreter": {
-   "hash": "ed521dd8fd373daddae05f3c017fb683255820ac0b02ceb5ac16894af5652dc8"
-  },
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3.8.13 ('cova-qa-2')",
    "language": "python",
    "name": "python3"
   },
diff --git a/doc/source/tutorials/machine_learning/mnist_classifier.ipynb b/doc/source/tutorials/machine_learning/mnist_classifier.ipynb
index 1f3f97c14..6a41b8268 100644
--- a/doc/source/tutorials/machine_learning/mnist_classifier.ipynb
+++ b/doc/source/tutorials/machine_learning/mnist_classifier.ipynb
@@ -519,7 +519,7 @@
    "source": [
     "dispatch_id = ct.dispatch(workflow)(model=NeuralNetwork().to(\"cpu\"))\n",
     "print(f\"Dispatch id: {dispatch_id}\")\n",
-    "result = ct.get_result(dispatch_id=dispatch_id, wait=ct.wait.LONG)\n",
+    "result = ct.get_result(dispatch_id=dispatch_id, wait=True)\n",
     "print(f\"Covalent workflow takes {result.end_time - result.start_time} seconds.\")\n"
    ]
   },
diff --git a/doc/source/tutorials/machine_learning/pennylane_hybrid.ipynb b/doc/source/tutorials/machine_learning/pennylane_hybrid.ipynb
index 714911adf..b1a36839c 100644
--- a/doc/source/tutorials/machine_learning/pennylane_hybrid.ipynb
+++ b/doc/source/tutorials/machine_learning/pennylane_hybrid.ipynb
@@ -188,7 +188,7 @@
    "outputs": [],
    "source": [
     "dispatch_id = ct.dispatch(workflow)([0.01, 0.01], 50)\n",
-    "result = ct.get_result(dispatch_id=dispatch_id, wait=ct.wait.LONG)\n",
+    "result = ct.get_result(dispatch_id=dispatch_id, wait=True)\n",
     "opt_params, traing_steps, cost_steps = result.result"
    ]
   },
diff --git a/doc/source/tutorials/machine_learning/qaoa_maxcut.ipynb b/doc/source/tutorials/machine_learning/qaoa_maxcut.ipynb
index 78b1ba86b..f0712fd3e 100644
--- a/doc/source/tutorials/machine_learning/qaoa_maxcut.ipynb
+++ b/doc/source/tutorials/machine_learning/qaoa_maxcut.ipynb
@@ -409,7 +409,7 @@
     }
    ],
    "source": [
-    "result = ct.get_result(id, wait=ct.wait.LONG)\n",
+    "result = ct.get_result(id, wait=True)\n",
     "result = result.result\n",
     "for i in range(len(result)):\n",
     "    plt.plot(np.array(result[i]).T, label=\"GradientDescentOptimizer\")\n",
@@ -473,7 +473,7 @@
     }
    ],
    "source": [
-    "result = ct.get_result(id, wait=ct.wait.LONG)\n",
+    "result = ct.get_result(id, wait=True)\n",
     "result = result.result\n",
     "simulators = [\n",
     "    \"GradientDescentOptimizer\",\n",
@@ -584,7 +584,7 @@
     }
    ],
    "source": [
-    "result = ct.get_result(id, wait=ct.wait.LONG)\n",
+    "result = ct.get_result(id, wait=True)\n",
     "result = result.result\n",
     "for i in range(len(result)):\n",
     "    plt.plot(np.array(result[i]).T, label=simulators[i])\n",
@@ -654,7 +654,7 @@
     }
    ],
    "source": [
-    "result = ct.get_result(id, wait=ct.wait.LONG)\n",
+    "result = ct.get_result(id, wait=True)\n",
     "alpha = result.result[1]\n",
     "beta = result.result[2]\n",
     "for i in range(len(alpha)):\n",
diff --git a/doc/source/tutorials/machine_learning/quantum_embedding_kernel.ipynb b/doc/source/tutorials/machine_learning/quantum_embedding_kernel.ipynb
index b5a78ec60..0d423ef6d 100644
--- a/doc/source/tutorials/machine_learning/quantum_embedding_kernel.ipynb
+++ b/doc/source/tutorials/machine_learning/quantum_embedding_kernel.ipynb
@@ -267,7 +267,7 @@
    "outputs": [],
    "source": [
     "dispatch_id = ct.dispatch(init_qsvm)(18, 5, 3)\n",
-    "result = ct.get_result(dispatch_id=dispatch_id, wait=ct.wait.LONG)\n",
+    "result = ct.get_result(dispatch_id=dispatch_id, wait=True)\n",
     "qsvm, X_train, y_train, X_test, y_test, train_acc, test_acc = result.result"
    ]
   },
@@ -454,7 +454,7 @@
    "outputs": [],
    "source": [
     "dispatch_id = ct.dispatch(trained_qsvm)(18, 5, 3, 300)\n",
-    "result = ct.get_result(dispatch_id=dispatch_id, wait=ct.wait.LONG)\n",
+    "result = ct.get_result(dispatch_id=dispatch_id, wait=True)\n",
     "opt_qsvm, KTAs, X_train, y_train, X_test, y_test, train_acc, test_acc = result.result"
    ]
   },
diff --git a/doc/source/tutorials/quantum_chemistry/nitrogen_copper_interaction.ipynb b/doc/source/tutorials/quantum_chemistry/nitrogen_copper_interaction.ipynb
index 305ae5ae9..9a4fcd601 100644
--- a/doc/source/tutorials/quantum_chemistry/nitrogen_copper_interaction.ipynb
+++ b/doc/source/tutorials/quantum_chemistry/nitrogen_copper_interaction.ipynb
@@ -254,7 +254,7 @@
     }
    ],
    "source": [
-    "result = ct.get_result(dispatch_id=dispatch_id, wait=ct.wait.LONG)\n",
+    "result = ct.get_result(dispatch_id=dispatch_id, wait=True)\n",
     "\n",
     "print(\n",
     "    f\"Computation status = {result.status}\\nEnergy of slab + nitrogen system = {result.result:.4f}\"\n",
@@ -468,7 +468,7 @@
     }
    ],
    "source": [
-    "result = ct.get_result(dispatch_id, wait=ct.wait.LONG)\n",
+    "result = ct.get_result(dispatch_id, wait=True)\n",
     "print(result.status)\n"
    ]
   },
diff --git a/doc/source/tutorials/quantum_gravity/spacetime_classification.ipynb b/doc/source/tutorials/quantum_gravity/spacetime_classification.ipynb
index 5bfc3d7c6..3545e4e00 100644
--- a/doc/source/tutorials/quantum_gravity/spacetime_classification.ipynb
+++ b/doc/source/tutorials/quantum_gravity/spacetime_classification.ipynb
@@ -131,7 +131,7 @@
    ],
    "source": [
     "dispatch_id = ct.dispatch(ct.lattice(generate_flat_spacetime))(num_elements=1000, dim=2)\n",
-    "coordinates = ct.get_result(dispatch_id, wait=ct.wait.LONG).result\n",
+    "coordinates = ct.get_result(dispatch_id, wait=True).result\n",
     "visualize_spacetime(coordinates)"
    ]
   },


Test patch:
diff --git a/tests/covalent_tests/results_manager_tests/results_manager_test.py b/tests/covalent_tests/results_manager_tests/results_manager_test.py
index 00838afbe..0cc53cf7a 100644
--- a/tests/covalent_tests/results_manager_tests/results_manager_test.py
+++ b/tests/covalent_tests/results_manager_tests/results_manager_test.py
@@ -127,17 +127,15 @@ def test_sync(lattice_record, mocker, tmp_path):
     dispatch_id = "9d1b308b-4763-4990-ae7f-6a6e36d35893"
     sync(db, dispatch_id)
     mock_get_result_from_dispatcher.assert_called_once_with(
-        dispatch_id, wait=wait.EXTREME, status_only=True
+        dispatch_id, wait=True, status_only=True
     )
     mock_get_result_from_dispatcher.reset_mock()
     dispatch_ids = ["f34671d1-48f2-41ce-89d9-9a8cb5c60e5d", "02dfd929-d96b-4ad1-8411-a818ce465169"]
     sync(db, dispatch_ids)
     for dispatch_id in dispatch_ids:
-        mock_get_result_from_dispatcher.assert_any_call(
-            dispatch_id, wait=wait.EXTREME, status_only=True
-        )
+        mock_get_result_from_dispatcher.assert_any_call(dispatch_id, wait=True, status_only=True)
     mock_get_result_from_dispatcher.reset_mock()
     sync(db)
     mock_get_result_from_dispatcher.assert_called_once_with(
-        DISPATCH_ID, wait=wait.EXTREME, status_only=True
+        DISPATCH_ID, wait=True, status_only=True
     )
diff --git a/tests/functional_tests/dask_executor_test.py b/tests/functional_tests/dask_executor_test.py
index 4fcbda704..01a159e53 100644
--- a/tests/functional_tests/dask_executor_test.py
+++ b/tests/functional_tests/dask_executor_test.py
@@ -71,7 +71,7 @@ def workflow(n):
     dispatch_id = dispatcher(n=n)
     print(f"Dispatching with dispatch_id: {dispatch_id}")
 
-    result = ct.get_result(dispatch_id=dispatch_id, wait=ct.WAIT.LONG)
+    result = ct.get_result(dispatch_id=dispatch_id, wait=True)
 
     time_taken = (result.end_time - result.start_time).total_seconds()
     print(f"Time taken: {time_taken}")