diff --git a/docs/examples/calling_scripts.rst b/docs/examples/calling_scripts.rst
index 183128b6e..708a9d128 100644
--- a/docs/examples/calling_scripts.rst
+++ b/docs/examples/calling_scripts.rst
@@ -45,19 +45,6 @@ One worker runs a persistent generator and the other four run the forces simulat
     :caption: tests/scaling_tests/forces/forces_simple/run_libe_forces.py
     :linenos:
 
-Object + yaml Version
-~~~~~~~~~~~~~~~~~~~~~
-
-..  literalinclude:: ../../libensemble/tests/scaling_tests/forces/forces_adv/run_libe_forces_from_yaml.py
-    :language: python
-    :caption: tests/scaling_tests/forces/forces_adv/run_libe_forces_from_yaml.py
-    :linenos:
-
-..  literalinclude:: ../../libensemble/tests/scaling_tests/forces/forces_adv/forces.yaml
-    :language: yaml
-    :caption: tests/scaling_tests/forces/forces_adv/forces.yaml
-    :linenos:
-
 Persistent APOSMM with Gradients
 --------------------------------
 
diff --git a/libensemble/ensemble.py b/libensemble/ensemble.py
index 0ceba2ab3..b6a220818 100644
--- a/libensemble/ensemble.py
+++ b/libensemble/ensemble.py
@@ -1,10 +1,6 @@
-import importlib
-import json
 import logging
 
 import numpy.typing as npt
-import tomli
-import yaml
 
 from libensemble.executors import Executor
 from libensemble.libE import libE
@@ -117,110 +113,6 @@ class Ensemble:
             experiment = Ensemble()
             experiment.sim_specs = sim_specs
 
-    .. dropdown:: Option 3: Loading parameters from files
-
-        .. code-block:: python
-            :linenos:
-
-            from libensemble import Ensemble
-
-            experiment = Ensemble()
-
-            my_experiment.from_yaml("my_parameters.yaml")
-            # or...
-            my_experiment.from_toml("my_parameters.toml")
-            # or...
-            my_experiment.from_json("my_parameters.json")
-
-        .. tab-set::
-
-            .. tab-item:: my_parameters.yaml
-
-                .. code-block:: yaml
-                    :linenos:
-
-                    libE_specs:
-                        save_every_k_gens: 20
-
-                    exit_criteria:
-                        sim_max: 80
-
-                    gen_specs:
-                        gen_f: generator.gen_random_sample
-                        outputs:
-                            x:
-                                type: float
-                                size: 1
-                        user:
-                            gen_batch_size: 5
-
-                    sim_specs:
-                        sim_f: simulator.sim_find_sine
-                        inputs:
-                            - x
-                        outputs:
-                            y:
-                                type: float
-
-            .. tab-item:: my_parameters.toml
-
-                .. code-block:: toml
-                    :linenos:
-
-                    [libE_specs]
-                        save_every_k_gens = 300
-
-                    [exit_criteria]
-                        sim_max = 80
-
-                    [gen_specs]
-                        gen_f = "generator.gen_random_sample"
-                        [gen_specs.outputs]
-                            [gen_specs.outputs.x]
-                                type = "float"
-                                size = 1
-                        [gen_specs.user]
-                            gen_batch_size = 5
-
-                    [sim_specs]
-                        sim_f = "simulator.sim_find_sine"
-                        inputs = ["x"]
-                        [sim_specs.outputs]
-                            [sim_specs.outputs.y]
-                                type = "float"
-
-            .. tab-item:: my_parameters.json
-
-                .. code-block:: json
-                    :linenos:
-
-                    {
-                        "libE_specs": {
-                            "save_every_k_gens": 300,
-                        },
-                        "exit_criteria": {
-                            "sim_max": 80
-                        },
-                        "gen_specs": {
-                            "gen_f": "generator.gen_random_sample",
-                            "outputs": {
-                                "x": {
-                                    "type": "float",
-                                    "size": 1
-                                }
-                            },
-                            "user": {
-                                "gen_batch_size": 5
-                            }
-                        },
-                        "sim_specs": {
-                            "sim_f": "simulator.sim_find_sine",
-                            "inputs": ["x"],
-                            "outputs": {
-                                "f": {"type": "float"}
-                            }
-                        }
-                    }
 
     Parameters
     ----------
@@ -431,111 +323,6 @@ def nworkers(self, value):
         if self._libE_specs:
             self._libE_specs.nworkers = value
 
-    def _get_func(self, loaded):
-        """Extracts user function specified in loaded dict"""
-        func_path_split = loaded.rsplit(".", 1)
-        func_name = func_path_split[-1]
-        try:
-            return getattr(importlib.import_module(func_path_split[0]), func_name)
-        except AttributeError:
-            self._util_logger.manager_warning(ATTR_ERR_MSG.format(func_name))
-            raise
-        except ModuleNotFoundError:
-            self._util_logger.manager_warning(NOTFOUND_ERR_MSG.format(func_name))
-            raise
-
-    @staticmethod
-    def _get_outputs(loaded):
-        """Extracts output parameters from loaded dict"""
-        if not loaded:
-            return []
-        fields = [i for i in loaded]
-        field_params = [i for i in loaded.values()]
-        results = []
-        for i in range(len(fields)):
-            field_type = field_params[i]["type"]
-            built_in_type = __builtins__.get(field_type, field_type)
-            try:
-                if field_params[i]["size"] == 1:
-                    size = (1,)  # formatting how size=1 is typically preferred
-                else:
-                    size = field_params[i]["size"]
-                results.append((fields[i], built_in_type, size))
-            except KeyError:
-                results.append((fields[i], built_in_type))
-        return results
-
-    @staticmethod
-    def _get_normal(loaded):
-        return loaded
-
-    def _get_option(self, specs, name):
-        """Gets a specs value, underlying spec is either a dict or a class"""
-        attr = getattr(self, specs)
-        if isinstance(attr, dict):
-            return attr.get(name)
-        else:
-            return getattr(attr, name)
-
-    def _parse_spec(self, loaded_spec):
-        """Parses and creates traditional libEnsemble dictionary from loaded dict info"""
-
-        field_f = {
-            "sim_f": self._get_func,
-            "gen_f": self._get_func,
-            "alloc_f": self._get_func,
-            "inputs": self._get_normal,
-            "persis_in": self._get_normal,
-            "outputs": self._get_outputs,
-            "globus_compute_endpoint": self._get_normal,
-            "user": self._get_normal,
-        }
-
-        userf_fields = [f for f in loaded_spec if f in field_f.keys()]
-
-        if len(userf_fields):
-            for f in userf_fields:
-                loaded_spec[f] = field_f[f](loaded_spec[f])
-
-        return loaded_spec
-
-    def _parameterize(self, loaded):
-        """Updates and sets attributes from specs loaded from file"""
-        for f in loaded:
-            loaded_spec = self._parse_spec(loaded[f])
-            old_spec = getattr(self, f)
-            ClassType = CORRESPONDING_CLASSES[f]
-            if isinstance(old_spec, dict):
-                old_spec.update(loaded_spec)
-                if old_spec.get("in") and old_spec.get("inputs"):
-                    old_spec.pop("inputs")  # avoid clashes
-                elif old_spec.get("out") and old_spec.get("outputs"):
-                    old_spec.pop("outputs")  # avoid clashes
-                setattr(self, f, ClassType(**old_spec))
-            else:  # None. attribute not set yet
-                setattr(self, f, ClassType(**loaded_spec))
-
-    def from_yaml(self, file_path: str):
-        """Parameterizes libEnsemble from ``yaml`` file"""
-        with open(file_path, "r") as f:
-            loaded = yaml.full_load(f)
-
-        self._parameterize(loaded)
-
-    def from_toml(self, file_path: str):
-        """Parameterizes libEnsemble from ``toml`` file"""
-        with open(file_path, "rb") as f:
-            loaded = tomli.load(f)
-
-        self._parameterize(loaded)
-
-    def from_json(self, file_path: str):
-        """Parameterizes libEnsemble from ``json`` file"""
-        with open(file_path, "rb") as f:
-            loaded = json.load(f)
-
-        self._parameterize(loaded)
-
     def add_random_streams(self, num_streams: int = 0, seed: str = ""):
         """
 
diff --git a/libensemble/tests/functionality_tests/1d_sampling.json b/libensemble/tests/functionality_tests/1d_sampling.json
deleted file mode 100644
index 6066cdd69..000000000
--- a/libensemble/tests/functionality_tests/1d_sampling.json
+++ /dev/null
@@ -1,32 +0,0 @@
-{
-  "libE_specs": {
-    "save_every_k_gens": 300,
-    "safe_mode": false
-  },
-  "exit_criteria": {
-    "gen_max": 501
-  },
-  "sim_specs": {
-    "sim_f": "libensemble.sim_funcs.simple_sim.norm_eval",
-    "inputs": [
-      "x"
-    ],
-    "outputs": {
-      "f": {
-        "type": "float"
-      }
-    }
-  },
-  "gen_specs": {
-    "gen_f": "libensemble.gen_funcs.sampling.latin_hypercube_sample",
-    "outputs": {
-      "x": {
-        "type": "float",
-        "size": 1
-      }
-    },
-    "user": {
-      "gen_batch_size": 500
-    }
-  }
-}
diff --git a/libensemble/tests/functionality_tests/1d_sampling.toml b/libensemble/tests/functionality_tests/1d_sampling.toml
deleted file mode 100644
index 6618019a6..000000000
--- a/libensemble/tests/functionality_tests/1d_sampling.toml
+++ /dev/null
@@ -1,22 +0,0 @@
-[libE_specs]
-  save_every_k_gens = 300
-  safe_mode = false
-
-[exit_criteria]
-  gen_max = 501
-
-[sim_specs]
-  sim_f = "libensemble.sim_funcs.simple_sim.norm_eval"
-  inputs = ["x"]
-  [sim_specs.outputs]
-    [sim_specs.outputs.f]
-      type = "float"
-
-[gen_specs]
-  gen_f = "libensemble.gen_funcs.sampling.latin_hypercube_sample"
-  [gen_specs.outputs]
-    [gen_specs.outputs.x]
-      type = "float"
-      size = 1
-  [gen_specs.user]
-    gen_batch_size = 500
diff --git a/libensemble/tests/functionality_tests/1d_sampling.yaml b/libensemble/tests/functionality_tests/1d_sampling.yaml
deleted file mode 100644
index 3e82548ae..000000000
--- a/libensemble/tests/functionality_tests/1d_sampling.yaml
+++ /dev/null
@@ -1,24 +0,0 @@
-libE_specs:
-    save_every_k_gens: 300
-    safe_mode: False
-    use_workflow_dir: True
-
-exit_criteria:
-    gen_max: 501
-
-sim_specs:
-    sim_f: libensemble.sim_funcs.simple_sim.norm_eval
-    inputs:
-        - x
-    outputs:
-        f:
-            type: float
-
-gen_specs:
-    gen_f: libensemble.gen_funcs.sampling.latin_hypercube_sample
-    outputs:
-        x:
-            type: float
-            size: 1
-    user:
-        gen_batch_size: 500
diff --git a/libensemble/tests/functionality_tests/test_1d_sampling_from_files.py b/libensemble/tests/functionality_tests/test_1d_sampling_from_files.py
deleted file mode 100644
index d80025d23..000000000
--- a/libensemble/tests/functionality_tests/test_1d_sampling_from_files.py
+++ /dev/null
@@ -1,44 +0,0 @@
-"""
-Runs libEnsemble with Latin hypercube sampling on a simple 1D problem using
-the libEnsemble yaml interface
-
-Execute via one of the following commands (e.g. 3 workers):
-   mpiexec -np 4 python test_1d_sampling_from_yaml.py
-   python test_1d_sampling_from_yaml.py --nworkers 3
-   python test_1d_sampling_from_yaml.py --nworkers 3 --comms tcp
-
-The number of concurrent evaluations of the objective function will be 4-1=3.
-"""
-
-# Do not change these lines - they are parsed by run-tests.sh
-# TESTSUITE_COMMS: mpi local tcp
-# TESTSUITE_NPROCS: 2 4
-# TESTSUITE_EXTRA: true
-
-import numpy as np
-
-from libensemble import Ensemble
-
-# Main block is necessary only when using local comms with spawn start method (default on macOS and Windows).
-if __name__ == "__main__":
-    sampling = Ensemble(parse_args=True)
-    sampling.from_json("1d_sampling.json")
-    sampling.from_toml("1d_sampling.toml")
-    sampling.from_yaml("1d_sampling.yaml")
-
-    sampling.gen_specs.user.update(
-        {
-            "lb": np.array([-3]),
-            "ub": np.array([3]),
-        }
-    )
-
-    sampling.add_random_streams()
-
-    # Perform the run
-    sampling.run()
-
-    if sampling.is_manager:
-        assert len(sampling.H) >= 501
-        print("\nlibEnsemble with random sampling has generated enough points")
-    sampling.save_output(__file__)
diff --git a/libensemble/tests/scaling_tests/forces/forces_adv/forces.yaml b/libensemble/tests/scaling_tests/forces/forces_adv/forces.yaml
deleted file mode 100644
index e3f38da8a..000000000
--- a/libensemble/tests/scaling_tests/forces/forces_adv/forces.yaml
+++ /dev/null
@@ -1,45 +0,0 @@
-libE_specs:
-    save_every_k_gens: 1000
-    sim_dirs_make: True
-    profile: False
-
-exit_criteria:
-    sim_max: 8
-
-sim_specs:
-    sim_f: forces_simf.run_forces
-    inputs:
-        - x
-    outputs:
-        energy:
-            type: float
-
-    user:
-        keys:
-            - seed
-        cores: 1
-        sim_particles: 1.e+3
-        sim_timesteps: 5
-        sim_kill_minutes: 10.0
-        particle_variance: 0.2
-        kill_rate: 0.5
-        fail_on_sim: False
-        fail_on_submit: False
-
-gen_specs:
-    gen_f: libensemble.gen_funcs.sampling.uniform_random_sample
-    outputs:
-        x:
-            type: float
-            size: 1
-    user:
-        gen_batch_size: 1000
-
-alloc_specs:
-    alloc_f: libensemble.alloc_funcs.give_sim_work_first.give_sim_work_first
-    outputs:
-        allocated:
-            type: bool
-    user:
-        batch_mode: True
-        num_active_gens: 1
diff --git a/libensemble/tests/scaling_tests/forces/forces_adv/readme.md b/libensemble/tests/scaling_tests/forces/forces_adv/readme.md
index 2d0daf9f7..e34cdfe8c 100644
--- a/libensemble/tests/scaling_tests/forces/forces_adv/readme.md
+++ b/libensemble/tests/scaling_tests/forces/forces_adv/readme.md
@@ -45,12 +45,6 @@ To remove output before the next run:
 
     ./cleanup.sh
 
-### Using YAML in calling script (optional)
-
-An alternative calling script `run_libe_forces_from_yaml.py` can be run in the same
-way as `run_libe_forces.py` above. This uses an alternative libEnsemble interface, where
-an ensemble object is created and parameters can be read from the `forces.yaml` file.
-
 ### Using batch scripts
 
 See `examples/libE_submission_scripts`
diff --git a/libensemble/tests/scaling_tests/forces/forces_adv/run_libe_forces_from_yaml.py b/libensemble/tests/scaling_tests/forces/forces_adv/run_libe_forces_from_yaml.py
deleted file mode 100644
index 0bca5e93d..000000000
--- a/libensemble/tests/scaling_tests/forces/forces_adv/run_libe_forces_from_yaml.py
+++ /dev/null
@@ -1,43 +0,0 @@
-#!/usr/bin/env python
-import os
-import sys
-
-import numpy as np
-
-from libensemble.ensemble import Ensemble
-from libensemble.executors.mpi_executor import MPIExecutor
-from libensemble.tools import add_unique_random_streams
-
-####################
-
-sim_app = os.path.join(os.getcwd(), "../forces_app/forces.x")
-
-if not os.path.isfile(sim_app):
-    sys.exit("forces.x not found - please build first in ../forces_app dir")
-
-
-####################
-
-forces = Ensemble(parse_args=True)
-forces.from_yaml("forces.yaml")
-
-forces.logger.set_level("INFO")
-
-if forces.is_manager:
-    print(f"\nRunning with {forces.nworkers} workers\n")
-
-exctr = MPIExecutor()
-exctr.register_app(full_path=sim_app, app_name="forces")
-
-forces.libE_specs["ensemble_dir_path"] = "./ensemble"
-forces.gen_specs.user.update(
-    {
-        "lb": np.array([0]),
-        "ub": np.array([32767]),
-    }
-)
-
-forces.persis_info = add_unique_random_streams({}, forces.nworkers + 1)
-
-forces.run()
-forces.save_output(__file__)
diff --git a/libensemble/tests/scaling_tests/forces/globus_compute_forces/cleanup.sh b/libensemble/tests/scaling_tests/forces/globus_compute_forces/cleanup.sh
deleted file mode 100755
index 54c41aa6e..000000000
--- a/libensemble/tests/scaling_tests/forces/globus_compute_forces/cleanup.sh
+++ /dev/null
@@ -1 +0,0 @@
-rm -r ensemble_* *.npy *.pickle ensemble.log lib*.txt
diff --git a/libensemble/tests/scaling_tests/forces/globus_compute_forces/forces_simf.py b/libensemble/tests/scaling_tests/forces/globus_compute_forces/forces_simf.py
deleted file mode 100644
index c3a31ff5d..000000000
--- a/libensemble/tests/scaling_tests/forces/globus_compute_forces/forces_simf.py
+++ /dev/null
@@ -1,137 +0,0 @@
-def run_forces_globus_compute(H, persis_info, sim_specs, libE_info):
-    import os
-    import secrets
-    import time
-
-    import numpy as np
-
-    from libensemble.executors.mpi_executor import MPIExecutor
-    from libensemble.message_numbers import TASK_FAILED, WORKER_DONE, WORKER_KILL
-
-    class ForcesException(Exception):
-        """Raised on some issue with Forces"""
-
-    def perturb(particles, seed, max_fraction):
-        MAX_SEED = 32767
-        """Modify particle count"""
-        seed_fraction = seed / MAX_SEED
-        max_delta = particles * max_fraction
-        delta = seed_fraction * max_delta
-        delta = delta - max_delta / 2  # translate so -/+
-        new_particles = particles + delta
-        return int(new_particles)
-
-    def read_last_line(filepath):
-        """Read last line of statfile"""
-        try:
-            with open(filepath, "rb") as fh:
-                line = fh.readlines()[-1].decode().rstrip()
-        except Exception:
-            line = ""  # In case file is empty or not yet created
-        return line
-
-    if sim_specs["user"]["fail_on_sim"]:
-        raise ForcesException(Exception)
-
-    calc_status = 0  # Returns to worker
-
-    x = H["x"]
-    sim_particles = sim_specs["user"]["sim_particles"]
-    sim_timesteps = sim_specs["user"]["sim_timesteps"]
-    time_limit = sim_specs["user"]["sim_kill_minutes"] * 60.0
-    sim_app = sim_specs["user"]["sim_app"]
-
-    exctr = MPIExecutor()
-    exctr.register_app(full_path=sim_app, app_name="forces")
-
-    calc_dir = os.path.join(sim_specs["user"]["remote_ensemble_dir"], secrets.token_hex(nbytes=4))
-    os.makedirs(calc_dir, exist_ok=True)
-    os.chdir(calc_dir)
-
-    # Get from dictionary if key exists, else return default (e.g. 0)
-    cores = sim_specs["user"].get("cores", None)
-    kill_rate = sim_specs["user"].get("kill_rate", 0)
-    particle_variance = sim_specs["user"].get("particle_variance", 0)
-
-    # Composing variable names and x values to set up simulation
-    seed = int(np.rint(x[0][0]))
-
-    # This is to give a random variance of work-load
-    sim_particles = perturb(sim_particles, seed, particle_variance)
-    print(f"seed: {seed}   particles: {sim_particles}")
-
-    args = str(int(sim_particles)) + " " + str(sim_timesteps) + " " + str(seed) + " " + str(kill_rate)
-
-    machinefile = None
-    if sim_specs["user"]["fail_on_submit"]:
-        machinefile = "fail"
-
-    # Machinefile only used here for exception testing
-    if cores:
-        task = exctr.submit(
-            app_name="forces",
-            num_procs=cores,
-            app_args=args,
-            stdout="out.txt",
-            stderr="err.txt",
-            wait_on_start=True,
-            machinefile=machinefile,
-        )
-    else:
-        task = exctr.submit(
-            app_name="forces",
-            app_args=args,
-            stdout="out.txt",
-            stderr="err.txt",
-            wait_on_start=True,
-            hyperthreads=True,
-            machinefile=machinefile,
-        )  # Auto-partition
-
-    # Stat file to check for bad runs
-    statfile = "forces.stat"
-    filepath = os.path.join(task.workdir, statfile)
-    line = None
-
-    poll_interval = 1  # secs
-    while not task.finished:
-        # Read last line of statfile
-        line = read_last_line(filepath)
-        if line == "kill":
-            task.kill()  # Bad run
-        elif task.runtime > time_limit:
-            task.kill()  # Timeout
-        else:
-            time.sleep(poll_interval)
-            task.poll()
-
-    if task.finished:
-        if task.state == "FINISHED":
-            print(f"Task {task.name} completed")
-            calc_status = WORKER_DONE
-            if read_last_line(filepath) == "kill":
-                # Generally mark as complete if want results (completed after poll - before readline)
-                print("Warning: Task completed although marked as a bad run (kill flag set in forces.stat)")
-        elif task.state == "FAILED":
-            print(f"Warning: Task {task.name} failed: Error code {task.errcode}")
-            calc_status = TASK_FAILED
-        elif task.state == "USER_KILLED":
-            print(f"Warning: Task {task.name} has been killed")
-            calc_status = WORKER_KILL
-        else:
-            print(f"Warning: Task {task.name} in unknown state {task.state}. Error code {task.errcode}")
-
-    time.sleep(0.2)
-    try:
-        data = np.loadtxt(filepath)
-        # task.read_file_in_workdir(statfile)
-        final_energy = data[-1]
-    except Exception:
-        final_energy = np.nan
-        # print('Warning - Energy Nan')
-
-    outspecs = sim_specs["out"]
-    output = np.zeros(1, dtype=outspecs)
-    output["energy"][0] = final_energy
-
-    return output, persis_info, calc_status
diff --git a/libensemble/tests/scaling_tests/forces/globus_compute_forces/globus_compute_forces.yaml b/libensemble/tests/scaling_tests/forces/globus_compute_forces/globus_compute_forces.yaml
deleted file mode 100644
index c7c0463bc..000000000
--- a/libensemble/tests/scaling_tests/forces/globus_compute_forces/globus_compute_forces.yaml
+++ /dev/null
@@ -1,37 +0,0 @@
-libE_specs:
-    save_every_k_gens: 1000
-    profile: False
-
-exit_criteria:
-    sim_max: 8
-
-sim_specs:
-    sim_f: libensemble.tests.scaling_tests.forces.globus_compute_forces.forces_simf.run_forces_globus_compute
-    inputs:
-        - x
-    outputs:
-        energy:
-            type: float
-    globus_compute_endpoint: ca766d22-49df-466a-8b51-cd0190c58bb0
-    user:
-        keys:
-            - seed
-        sim_app: /home/jnavarro/libensemble/libensemble/tests/scaling_tests/forces/forces_app/forces.x
-        remote_ensemble_dir: /home/jnavarro/bebop_output/ensemble_
-        cores: 1
-        sim_particles: 1.e+3
-        sim_timesteps: 5
-        sim_kill_minutes: 10.0
-        particle_variance: 0.2
-        kill_rate: 0.5
-        fail_on_sim: False
-        fail_on_submit: False
-
-gen_specs:
-    gen_f: libensemble.gen_funcs.sampling.uniform_random_sample
-    outputs:
-        x:
-            type: float
-            size: 1
-    user:
-        gen_batch_size: 1000
diff --git a/libensemble/tests/scaling_tests/forces/globus_compute_forces/readme.md b/libensemble/tests/scaling_tests/forces/globus_compute_forces/readme.md
deleted file mode 100644
index 793d869f4..000000000
--- a/libensemble/tests/scaling_tests/forces/globus_compute_forces/readme.md
+++ /dev/null
@@ -1,39 +0,0 @@
-## Running test run_libe_forces_funcx.py
-
-Naive Electrostatics Code Test
-
-This is designed only as an artificial, highly configurable test
-code for a libEnsemble sim func. This variant is primarily to test libEnsemble's
-capability to submit simulation functions to a separate machine from where libEnsemble's
-manager and workers are running.
-
-### Forces Mini-App
-
-A system of charged particles is initialized and simulated over a number of time-steps.
-
-See `forces_app` directory for details.
-
-This application will need to be compiled on the remote machine where the sim_f will run.
-See below.
-
-### Running with libEnsemble.
-
-On the remote machine, Configure the endpoint's `config.py` to include your project information and
-match the machine's specifications.
-
-Then to run with local comms (multiprocessing) with one manager and `N` workers:
-
-    python run_libe_forces_globus_compute.py --comms local --nworkers N
-
-To run with MPI comms using one manager and `N-1` workers:
-
-    mpirun -np N python run_libe_forces_globus_compute.py
-
-Application parameters can be adjusted in `globus_compute_forces.yaml`.
-
-Note that each function and path must be accessible and/or importable on the
-remote machine. Absolute paths are recommended.
-
-To remove output before the next run:
-
-    ./cleanup.sh
diff --git a/libensemble/tests/scaling_tests/forces/globus_compute_forces/run_libe_forces_globus_compute.py b/libensemble/tests/scaling_tests/forces/globus_compute_forces/run_libe_forces_globus_compute.py
deleted file mode 100644
index d9ac4e04b..000000000
--- a/libensemble/tests/scaling_tests/forces/globus_compute_forces/run_libe_forces_globus_compute.py
+++ /dev/null
@@ -1,23 +0,0 @@
-#!/usr/bin/env python
-import secrets
-
-import numpy as np
-
-from libensemble.ensemble import Ensemble
-
-if __name__ == "__main__":
-    forces = Ensemble(parse_args=True)
-    forces.from_yaml("globus_compute_forces.yaml")
-
-    forces.sim_specs.user["remote_ensemble_dir"] += secrets.token_hex(nbytes=3)
-
-    forces.gen_specs.user.update(
-        {
-            "lb": np.array([0]),
-            "ub": np.array([32767]),
-        }
-    )
-
-    forces.add_random_streams()
-
-    forces.run()
diff --git a/libensemble/tests/unit_tests/simdir/test_example.json b/libensemble/tests/unit_tests/simdir/test_example.json
deleted file mode 100644
index a6f5e2cb8..000000000
--- a/libensemble/tests/unit_tests/simdir/test_example.json
+++ /dev/null
@@ -1,46 +0,0 @@
-{
-  "libE_specs": {
-    "use_persis_return_sim": true
-  },
-  "exit_criteria": {
-    "sim_max": 10
-  },
-  "sim_specs": {
-    "sim_f": "numpy.linalg.norm",
-    "inputs": [
-      "x_on_cube"
-    ],
-    "outputs": {
-      "f": {
-        "type": "float"
-      },
-      "fvec": {
-        "type": "float",
-        "size": 3
-      }
-    }
-  },
-  "gen_specs": {
-    "gen_f": "numpy.random.uniform",
-    "outputs": {
-      "priority": {
-        "type": "float"
-      },
-      "local_pt": {
-        "type": "bool"
-      },
-      "local_min": {
-        "type": "bool"
-      },
-      "num_active_runs": {
-        "type": "int"
-      },
-      "x_on_cube": {
-        "type": "float"
-      }
-    },
-    "user": {
-      "nu": 0
-    }
-  }
-}
diff --git a/libensemble/tests/unit_tests/simdir/test_example.toml b/libensemble/tests/unit_tests/simdir/test_example.toml
deleted file mode 100644
index 1ac156cbb..000000000
--- a/libensemble/tests/unit_tests/simdir/test_example.toml
+++ /dev/null
@@ -1,31 +0,0 @@
-[libE_specs]
-  use_persis_return_sim = true
-
-[exit_criteria]
-  sim_max = 10
-
-[sim_specs]
-  sim_f = "numpy.linalg.norm"
-  inputs = ["x_on_cube"]
-  [sim_specs.outputs]
-    [sim_specs.outputs.f]
-      type = "float"
-    [sim_specs.outputs.fvec]
-      type = "float"
-      size = 3
-
-[gen_specs]
-  gen_f = "numpy.random.uniform"
-  [gen_specs.outputs]
-    [gen_specs.outputs.priority]
-      type = "float"
-    [gen_specs.outputs.local_pt]
-      type = "bool"
-    [gen_specs.outputs.local_min]
-      type = "bool"
-    [gen_specs.outputs.num_active_runs]
-      type = "int"
-    [gen_specs.outputs.x_on_cube]
-      type = "float"
-  [gen_specs.user]
-    nu = 0
diff --git a/libensemble/tests/unit_tests/simdir/test_example.yaml b/libensemble/tests/unit_tests/simdir/test_example.yaml
deleted file mode 100644
index af2cb34b3..000000000
--- a/libensemble/tests/unit_tests/simdir/test_example.yaml
+++ /dev/null
@@ -1,32 +0,0 @@
-libE_specs:
-    use_persis_return_sim: True
-
-exit_criteria:
-    sim_max: 10
-
-sim_specs:
-    sim_f: numpy.linalg.norm
-    inputs:
-        - x_on_cube
-    outputs:
-        f:
-            type: float
-        fvec:
-            type: float
-            size: 3
-
-gen_specs:
-    gen_f: numpy.random.uniform
-    outputs:
-        priority:
-            type: float
-        local_pt:
-            type: bool
-        local_min:
-            type: bool
-        num_active_runs:
-            type: int
-        x_on_cube:
-            type: float
-    user:
-        nu: 0
diff --git a/libensemble/tests/unit_tests/simdir/test_example_badfuncs_attribute.yaml b/libensemble/tests/unit_tests/simdir/test_example_badfuncs_attribute.yaml
deleted file mode 100644
index 85b3c90f4..000000000
--- a/libensemble/tests/unit_tests/simdir/test_example_badfuncs_attribute.yaml
+++ /dev/null
@@ -1,32 +0,0 @@
-libE_specs:
-    use_persis_return_gen: True
-
-exit_criteria:
-    sim_max: 10
-
-sim_specs:
-    sim_f: numpy.linalg.asdf
-    inputs:
-        - x_on_cube
-    outputs:
-        f:
-            type: float
-        fvec:
-            type: float
-            size: 3
-
-gen_specs:
-    gen_f: numpy.random.uniform
-    outputs:
-        priority:
-            type: float
-        local_pt:
-            type: bool
-        local_min:
-            type: bool
-        num_active_runs:
-            type: int
-        x_on_cube:
-            type: float
-    user:
-        nu: 0
diff --git a/libensemble/tests/unit_tests/simdir/test_example_badfuncs_notfound.yaml b/libensemble/tests/unit_tests/simdir/test_example_badfuncs_notfound.yaml
deleted file mode 100644
index da95afd1d..000000000
--- a/libensemble/tests/unit_tests/simdir/test_example_badfuncs_notfound.yaml
+++ /dev/null
@@ -1,32 +0,0 @@
-libE_specs:
-    use_persis_return_sim: True
-
-exit_criteria:
-    sim_max: 10
-
-sim_specs:
-    sim_f: numpy.linalg.norm
-    inputs:
-        - x_on_cube
-    outputs:
-        f:
-            type: float
-        fvec:
-            type: float
-            size: 3
-
-gen_specs:
-    gen_f: asdf
-    outputs:
-        priority:
-            type: float
-        local_pt:
-            type: bool
-        local_min:
-            type: bool
-        num_active_runs:
-            type: int
-        x_on_cube:
-            type: float
-    user:
-        nu: 0
diff --git a/libensemble/tests/unit_tests/test_ensemble.py b/libensemble/tests/unit_tests/test_ensemble.py
index 271932573..94c4865ad 100644
--- a/libensemble/tests/unit_tests/test_ensemble.py
+++ b/libensemble/tests/unit_tests/test_ensemble.py
@@ -2,7 +2,6 @@
 
 import numpy as np
 
-import libensemble.tests.unit_tests.setup as setup
 from libensemble.utils.misc import specs_dump
 
 
@@ -37,55 +36,6 @@ def test_ensemble_parse_args_false():
     assert e.libE_specs.nworkers == 8, "libE_specs nworkers not adjusted"
 
 
-def test_from_files():
-    """Test that Ensemble() specs dicts resemble setup dicts"""
-    from libensemble.ensemble import Ensemble
-
-    for ft in ["yaml", "json", "toml"]:
-        e = Ensemble(libE_specs={"comms": "local", "nworkers": 4})
-        file_path = f"./simdir/test_example.{ft}"
-        if ft == "yaml":
-            e.from_yaml(file_path)
-        elif ft == "json":
-            e.from_json(file_path)
-        else:
-            e.from_toml(file_path)
-
-        sim_specs, gen_specs, exit_criteria = setup.make_criteria_and_specs_0()
-
-        e.gen_specs.user["ub"] = np.ones(1)
-        e.gen_specs.user["lb"] = np.zeros(1)
-
-        sim_specs["inputs"] = sim_specs["in"]
-        sim_specs["outputs"] = sim_specs["out"]
-        gen_specs["outputs"] = gen_specs["out"]
-        sim_specs.pop("in")
-        sim_specs.pop("out")
-        gen_specs.pop("out")
-        assert all([i in specs_dump(e.sim_specs).items() for i in sim_specs.items()])
-        assert all([i in specs_dump(e.gen_specs).items() for i in gen_specs.items()])
-        assert all([i in specs_dump(e.exit_criteria).items() for i in exit_criteria.items()])
-
-
-def test_bad_func_loads():
-    """Test that Ensemble() raises expected errors (with warnings) on incorrect imports"""
-    from libensemble.ensemble import Ensemble
-
-    yaml_errors = {
-        "./simdir/test_example_badfuncs_attribute.yaml": AttributeError,
-        "./simdir/test_example_badfuncs_notfound.yaml": ModuleNotFoundError,
-    }
-
-    for f in yaml_errors:
-        e = Ensemble(libE_specs={"comms": "local", "nworkers": 4})
-        flag = 1
-        try:
-            e.from_yaml(f)
-        except yaml_errors[f]:
-            flag = 0
-        assert flag == 0
-
-
 def test_full_workflow():
     """Test initializing a workflow via Specs and Ensemble.run()"""
     from libensemble.ensemble import Ensemble
@@ -233,8 +183,6 @@ def test_local_comms_without_nworkers():
 if __name__ == "__main__":
     test_ensemble_init()
     test_ensemble_parse_args_false()
-    test_from_files()
-    test_bad_func_loads()
     test_full_workflow()
     test_flakey_workflow()
     test_ensemble_specs_update_libE_specs()
diff --git a/pyproject.toml b/pyproject.toml
index 80535d8cb..e025e7f02 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,7 @@ authors = [{name = "Jeffrey Larson"}, {name = "Stephen Hudson"},
             {name = "Stefan M. Wild"}, {name = "David Bindel"},
             {name = "John-Luke Navarro"}]
 
-dependencies = [ "numpy", "psutil", "pydantic", "pyyaml", "tomli"]
+dependencies = [ "numpy", "psutil", "pydantic"]
 
 description = "A Python toolkit for coordinating asynchronous and dynamic ensembles of calculations."
 name = "libensemble"
@@ -88,7 +88,6 @@ autodoc-pydantic = ">=2.1.0,<3"
 ipdb = ">=0.13.13,<0.14"
 mypy = ">=1.15.0,<2"
 types-psutil = ">=6.1.0.20241221,<7"
-types-pyyaml = ">=6.0.12.20250402,<7"
 
 [tool.pixi.dependencies]
 python = ">=3.10,<3.14"
@@ -96,8 +95,6 @@ pip = ">=24.3.1,<25"
 setuptools = ">=75.6.0,<76"
 numpy = ">=1.21,<3"
 pydantic = ">=1.10,<3"
-pyyaml = ">=6.0,<7"
-tomli = ">=1.2.1,<3"
 psutil = ">=5.9.4,<7"
 
 [tool.pixi.target.osx-arm64.dependencies]