Merge pull request #3526 from samuelgarcia/parralel_with_thread

Implement engine="thread" in ChunkRecordingExecutor

Author: samuelgarcia

doc/get_started/quickstart.rst

@@ -287,7 +287,7 @@ available parameters are dictionaries and can be accessed with:
      'detect_threshold': 5,
      'freq_max': 5000.0,
      'freq_min': 400.0,
-     'max_threads_per_process': 1,
+     'max_threads_per_worker': 1,
      'mp_context': None,
      'n_jobs': 20,
      'nested_params': None,

src/spikeinterface/core/__init__.py

@@ -91,7 +91,14 @@
     write_python,
     normal_pdf,
 )
-from .job_tools import ensure_n_jobs, ensure_chunk_size, ChunkRecordingExecutor, split_job_kwargs, fix_job_kwargs
+from .job_tools import (
+    get_best_job_kwargs,
+    ensure_n_jobs,
+    ensure_chunk_size,
+    ChunkRecordingExecutor,
+    split_job_kwargs,
+    fix_job_kwargs,
+)
 from .recording_tools import (
     write_binary_recording,
     write_to_h5_dataset_format,

src/spikeinterface/core/globals.py

@@ -97,7 +97,9 @@ def is_set_global_dataset_folder() -> bool:
 
 
 ########################################
-_default_job_kwargs = dict(n_jobs=1, chunk_duration="1s", progress_bar=True, mp_context=None, max_threads_per_process=1)
+_default_job_kwargs = dict(
+    pool_engine="thread", n_jobs=1, chunk_duration="1s", progress_bar=True, mp_context=None, max_threads_per_worker=1
+)
 
 global global_job_kwargs
 global_job_kwargs = _default_job_kwargs.copy()