diff --git a/executorlib/__init__.py b/executorlib/__init__.py
index 2bf66ec7..bd8153c9 100644
--- a/executorlib/__init__.py
+++ b/executorlib/__init__.py
@@ -12,6 +12,9 @@
 pandas.DataFrame.
 """
 
+from typing import Optional
+
+import executorlib._version
 from executorlib.executor.base import BaseExecutor
 from executorlib.executor.flux import (
     FluxClusterExecutor,
@@ -22,12 +25,48 @@
     SlurmClusterExecutor,
     SlurmJobExecutor,
 )
-from executorlib.standalone.cache import get_cache_data
 
-from . import _version
+
+def get_cache_data(cache_directory: str) -> list[dict]:
+    """
+    Collect all HDF5 files in the cache directory
+
+    Args:
+        cache_directory (str): The directory to store cache files.
+
+    Returns:
+        list[dict]: List of dictionaries each representing on of the HDF5 files in the cache directory.
+    """
+    from executorlib.standalone.hdf import get_cache_data
+
+    return get_cache_data(cache_directory=cache_directory)
+
+
+def terminate_tasks_in_cache(
+    cache_directory: str,
+    config_directory: Optional[str] = None,
+    backend: Optional[str] = None,
+):
+    """
+    Delete all jobs stored in the cache directory from the queuing system
+
+    Args:
+        cache_directory (str): The directory to store cache files.
+        config_directory (str, optional): path to the config directory.
+        backend (str, optional): name of the backend used to spawn tasks ["slurm", "flux"].
+    """
+    from executorlib.task_scheduler.file.queue_spawner import terminate_tasks_in_cache
+
+    return terminate_tasks_in_cache(
+        cache_directory=cache_directory,
+        config_directory=config_directory,
+        backend=backend,
+    )
+
 
 __all__: list[str] = [
     "get_cache_data",
+    "terminate_tasks_in_cache",
     "BaseExecutor",
     "FluxJobExecutor",
     "FluxClusterExecutor",
@@ -36,11 +75,4 @@
     "SlurmClusterExecutor",
 ]
 
-try:
-    from executorlib.task_scheduler.file.queue_spawner import terminate_tasks_in_cache
-
-    __all__ += ["terminate_tasks_in_cache"]
-except ImportError:
-    pass
-
-__version__ = _version.__version__
+__version__ = executorlib._version.__version__
diff --git a/executorlib/standalone/cache.py b/executorlib/standalone/cache.py
deleted file mode 100644
index 92e1ae68..00000000
--- a/executorlib/standalone/cache.py
+++ /dev/null
@@ -1,57 +0,0 @@
-import os
-
-import cloudpickle
-
-group_dict = {
-    "fn": "function",
-    "args": "input_args",
-    "kwargs": "input_kwargs",
-    "output": "output",
-    "error": "error",
-    "runtime": "runtime",
-    "queue_id": "queue_id",
-    "error_log_file": "error_log_file",
-}
-
-
-def get_cache_files(cache_directory: str) -> list[str]:
-    """
-    Recursively find all HDF5 files in the cache_directory which contain outputs.
-
-    Args:
-        cache_directory (str): The directory to store cache files.
-
-    Returns:
-        list[str]: List of HDF5 file in the cache directory which contain outputs.
-    """
-    file_lst = []
-    cache_directory_abs = os.path.abspath(cache_directory)
-    for dirpath, _, filenames in os.walk(cache_directory_abs):
-        file_lst += [os.path.join(dirpath, f) for f in filenames if f.endswith("_o.h5")]
-    return file_lst
-
-
-def get_cache_data(cache_directory: str) -> list[dict]:
-    """
-    Collect all HDF5 files in the cache directory
-
-    Args:
-        cache_directory (str): The directory to store cache files.
-
-    Returns:
-        list[dict]: List of dictionaries each representing on of the HDF5 files in the cache directory.
-    """
-    import h5py
-    import numpy as np
-
-    file_lst = []
-    for file_name in get_cache_files(cache_directory=cache_directory):
-        with h5py.File(file_name, "r") as hdf:
-            file_content_dict = {
-                key: cloudpickle.loads(np.void(hdf["/" + key]))
-                for key in group_dict.values()
-                if key in hdf
-            }
-        file_content_dict["filename"] = file_name
-        file_lst.append(file_content_dict)
-    return file_lst
diff --git a/executorlib/task_scheduler/file/hdf.py b/executorlib/standalone/hdf.py
similarity index 67%
rename from executorlib/task_scheduler/file/hdf.py
rename to executorlib/standalone/hdf.py
index 812198c9..5e8970f4 100644
--- a/executorlib/task_scheduler/file/hdf.py
+++ b/executorlib/standalone/hdf.py
@@ -5,7 +5,16 @@
 import h5py
 import numpy as np
 
-from executorlib.standalone.cache import group_dict
+group_dict = {
+    "fn": "function",
+    "args": "input_args",
+    "kwargs": "input_kwargs",
+    "output": "output",
+    "error": "error",
+    "runtime": "runtime",
+    "queue_id": "queue_id",
+    "error_log_file": "error_log_file",
+}
 
 
 def dump(file_name: Optional[str], data_dict: dict) -> None:
@@ -110,3 +119,54 @@ def get_queue_id(file_name: Optional[str]) -> Optional[int]:
             if "queue_id" in hdf:
                 return cloudpickle.loads(np.void(hdf["/queue_id"]))
     return None
+
+
+def get_cache_data(cache_directory: str) -> list[dict]:
+    """
+    Collect all HDF5 files in the cache directory
+
+    Args:
+        cache_directory (str): The directory to store cache files.
+
+    Returns:
+        list[dict]: List of dictionaries each representing on of the HDF5 files in the cache directory.
+    """
+    return [
+        _get_content_of_file(file_name=file_name) | {"filename": file_name}
+        for file_name in get_cache_files(cache_directory=cache_directory)
+    ]
+
+
+def get_cache_files(cache_directory: str) -> list[str]:
+    """
+    Recursively find all HDF5 files in the cache_directory which contain outputs.
+
+    Args:
+        cache_directory (str): The directory to store cache files.
+
+    Returns:
+        list[str]: List of HDF5 file in the cache directory which contain outputs.
+    """
+    file_lst = []
+    cache_directory_abs = os.path.abspath(cache_directory)
+    for dirpath, _, filenames in os.walk(cache_directory_abs):
+        file_lst += [os.path.join(dirpath, f) for f in filenames if f.endswith("_o.h5")]
+    return file_lst
+
+
+def _get_content_of_file(file_name: str) -> dict:
+    """
+    Get content of an HDF5 file
+
+    Args:
+        file_name (str): file name
+
+    Returns:
+        dict: Content of HDF5 file
+    """
+    with h5py.File(file_name, "r") as hdf:
+        return {
+            key: cloudpickle.loads(np.void(hdf["/" + key]))
+            for key in group_dict.values()
+            if key in hdf
+        }
diff --git a/executorlib/task_scheduler/file/backend.py b/executorlib/task_scheduler/file/backend.py
index cbe869cc..a945d30c 100644
--- a/executorlib/task_scheduler/file/backend.py
+++ b/executorlib/task_scheduler/file/backend.py
@@ -3,7 +3,7 @@
 from typing import Any
 
 from executorlib.standalone.error import backend_write_error_file
-from executorlib.task_scheduler.file.hdf import dump, load
+from executorlib.standalone.hdf import dump, load
 from executorlib.task_scheduler.file.shared import FutureItem
 
 
diff --git a/executorlib/task_scheduler/file/queue_spawner.py b/executorlib/task_scheduler/file/queue_spawner.py
index 0cc2364f..66c5e4f4 100644
--- a/executorlib/task_scheduler/file/queue_spawner.py
+++ b/executorlib/task_scheduler/file/queue_spawner.py
@@ -3,9 +3,9 @@
 
 from pysqa import QueueAdapter
 
+from executorlib.standalone.hdf import dump, get_queue_id
 from executorlib.standalone.inputcheck import check_file_exists
 from executorlib.standalone.scheduler import pysqa_execute_command, terminate_with_pysqa
-from executorlib.task_scheduler.file.hdf import dump, get_queue_id
 
 
 def execute_with_pysqa(
diff --git a/executorlib/task_scheduler/file/shared.py b/executorlib/task_scheduler/file/shared.py
index 5902d8e1..c712c863 100644
--- a/executorlib/task_scheduler/file/shared.py
+++ b/executorlib/task_scheduler/file/shared.py
@@ -4,10 +4,9 @@
 from concurrent.futures import Future
 from typing import Any, Callable, Optional
 
-from executorlib.standalone.cache import get_cache_files
 from executorlib.standalone.command import get_cache_execute_command
+from executorlib.standalone.hdf import get_cache_files, get_output
 from executorlib.standalone.serialize import serialize_funct
-from executorlib.task_scheduler.file.hdf import get_output
 from executorlib.task_scheduler.file.subprocess_spawner import terminate_subprocess
 
 
diff --git a/executorlib/task_scheduler/file/subprocess_spawner.py b/executorlib/task_scheduler/file/subprocess_spawner.py
index d418a3d4..c1b2157f 100644
--- a/executorlib/task_scheduler/file/subprocess_spawner.py
+++ b/executorlib/task_scheduler/file/subprocess_spawner.py
@@ -3,8 +3,8 @@
 import time
 from typing import Optional
 
+from executorlib.standalone.hdf import dump
 from executorlib.standalone.inputcheck import check_file_exists
-from executorlib.task_scheduler.file.hdf import dump
 
 
 def execute_in_subprocess(
diff --git a/executorlib/task_scheduler/interactive/shared.py b/executorlib/task_scheduler/interactive/shared.py
index d4b57982..e64db61b 100644
--- a/executorlib/task_scheduler/interactive/shared.py
+++ b/executorlib/task_scheduler/interactive/shared.py
@@ -4,7 +4,6 @@
 import time
 from typing import Callable, Optional
 
-from executorlib.standalone.cache import get_cache_files
 from executorlib.standalone.command import get_interactive_execute_command
 from executorlib.standalone.interactive.communication import (
     SocketInterface,
@@ -130,7 +129,7 @@ def _execute_task_with_cache(
         cache_key (str, optional): By default the cache_key is generated based on the function hash, this can be
                                   overwritten by setting the cache_key.
     """
-    from executorlib.task_scheduler.file.hdf import dump, get_output
+    from executorlib.standalone.hdf import dump, get_cache_files, get_output
 
     task_key, data_dict = serialize_funct(
         fn=task_dict["fn"],
diff --git a/tests/test_cache_backend_execute.py b/tests/test_cache_backend_execute.py
index 30dd7238..4e7d681d 100644
--- a/tests/test_cache_backend_execute.py
+++ b/tests/test_cache_backend_execute.py
@@ -7,7 +7,7 @@
 try:
     from executorlib.task_scheduler.file.backend import backend_execute_task_in_file
     from executorlib.task_scheduler.file.shared import _check_task_output, FutureItem
-    from executorlib.task_scheduler.file.hdf import dump, get_runtime
+    from executorlib.standalone.hdf import dump, get_runtime
     from executorlib.standalone.serialize import serialize_funct
 
     skip_h5io_test = False
diff --git a/tests/test_fluxclusterexecutor.py b/tests/test_fluxclusterexecutor.py
index 107d5add..0968fabb 100644
--- a/tests/test_fluxclusterexecutor.py
+++ b/tests/test_fluxclusterexecutor.py
@@ -10,8 +10,9 @@
 
 try:
     import flux.job
-    from executorlib.task_scheduler.file.hdf import dump
-    from executorlib.task_scheduler.file.queue_spawner import terminate_tasks_in_cache, execute_with_pysqa
+    from executorlib import terminate_tasks_in_cache
+    from executorlib.standalone.hdf import dump
+    from executorlib.task_scheduler.file.queue_spawner import execute_with_pysqa
     from executorlib.standalone.scheduler import terminate_with_pysqa
 
     skip_flux_test = "FLUX_URI" not in os.environ
diff --git a/tests/test_slurmclusterexecutor.py b/tests/test_slurmclusterexecutor.py
index 4973037d..a26524e7 100644
--- a/tests/test_slurmclusterexecutor.py
+++ b/tests/test_slurmclusterexecutor.py
@@ -14,7 +14,7 @@
 skip_mpi4py_test = importlib.util.find_spec("mpi4py") is None
 
 try:
-    from executorlib.task_scheduler.file.hdf import dump
+    from executorlib.standalone.hdf import dump
 
     skip_h5py_test = False
 except ImportError:
diff --git a/tests/test_standalone_hdf.py b/tests/test_standalone_hdf.py
index fd77d8df..3327e583 100644
--- a/tests/test_standalone_hdf.py
+++ b/tests/test_standalone_hdf.py
@@ -4,7 +4,7 @@
 
 
 try:
-    from executorlib.task_scheduler.file.hdf import (
+    from executorlib.standalone.hdf import (
         dump,
         load,
         get_output,