refactor: Move to use concurrent

Ref: #58

Author: caffeine-addictt

README.md

@@ -79,7 +79,7 @@ _Below is an example of how you can install and use thread._
 2. Import thread into your library!
    ```py
    import thread
-   from thread import Thread, ParallelProcessing
+   from thread import Thread, ConcurrentProcessing
    ```
 
 <p align="right">(<a href="#readme-top">back to top</a>)</p>

src/thread/__init__.py

@@ -22,7 +22,7 @@
 
 
 # Export Core
-from .thread import Thread, ParallelProcessing
+from .thread import Thread, ConcurrentProcessing
 
 
 from . import _types as types, exceptions
@@ -39,7 +39,7 @@
 # Wildcard Export
 __all__ = [
     'Thread',
-    'ParallelProcessing',
+    'ConcurrentProcessing',
     'threaded',
     'processor',
     'types',

src/thread/decorators/_processor.py

@@ -5,7 +5,7 @@
 """
 
 from functools import wraps
-from ..thread import ParallelProcessing
+from ..thread import ConcurrentProcessing
 
 from .._types import (
     Overflow_In,
@@ -29,15 +29,15 @@
 
 NoParamReturn = Callable[
     Concatenate[Dataset[_DataT], _TargetP],
-    ParallelProcessing[_TargetP, _TargetT, _DataT],
+    ConcurrentProcessing[_TargetP, _TargetT, _DataT],
 ]
 WithParamReturn = Callable[
     [TargetFunction[_DataT, _TargetP, _TargetT]],
     NoParamReturn[_DataT, _TargetP, _TargetT],
 ]
 FullParamReturn = Callable[
     Concatenate[Dataset[_DataT], _TargetP],
-    ParallelProcessing[_TargetP, _TargetT, _DataT],
+    ConcurrentProcessing[_TargetP, _TargetT, _DataT],
 ]
 
 
@@ -150,15 +150,15 @@ def wrapped(
         data: Dataset[_DataT],
         *parsed_args: _TargetP.args,
         **parsed_kwargs: _TargetP.kwargs,
-    ) -> ParallelProcessing[_TargetP, _TargetT, _DataT]:
+    ) -> ConcurrentProcessing[_TargetP, _TargetT, _DataT]:
         kwargs.update(parsed_kwargs)
 
         processed_args = (*args, *parsed_args)
         processed_kwargs = {
             i: v for i, v in kwargs.items() if i not in ['args', 'kwargs']
         }
 
-        job = ParallelProcessing(
+        job = ConcurrentProcessing(
             function=__function,
             dataset=data,
             args=processed_args,

src/thread/thread.py

@@ -5,7 +5,7 @@
 class Thread: ...
 
 
-class ParallelProcessing: ...
+class ConcurrentProcessing: ...
 ```
 
 Documentation: https://thread.ngjx.org/docs/v1.1.1
@@ -341,9 +341,9 @@ def __init__(self, thread: Thread, progress: float = 0) -> None:
         self.progress = progress
 
 
-class ParallelProcessing(Generic[_Target_P, _Target_T, _Dataset_T]):
+class ConcurrentProcessing(Generic[_Target_P, _Target_T, _Dataset_T]):
     """
-    Multi-Threaded Parallel Processing
+    Concurrent Processing
     ---------------------------------------
 
     Type-Safe and provides more functionality on top
@@ -442,10 +442,10 @@ def __init__(
         **overflow_kwargs: Overflow_In,
     ) -> None:
         """
-        Initializes a new Multi-Threaded Pool\n
+        Initializes a new Concurrent Process\n
         Best for data processing
 
-        Splits a dataset as evenly as it can among the threads and run them in parallel
+        Splits a dataset as evenly as it can among the threads and run them concurrently
 
         Parameters
         ----------

tests/test_parallelprocessing.py tests/test_concurrentprocessing.pytests/test_parallelprocessing.py renamed to tests/test_concurrentprocessing.py

@@ -1,6 +1,6 @@
 import time
 import pytest
-from src.thread import ParallelProcessing, exceptions
+from src.thread import ConcurrentProcessing, exceptions
 
 
 # >>>>>>>>>> Dummy Functions <<<<<<<<<< #
@@ -18,7 +18,7 @@ def _dummy_raiseException(x: Exception, delay: float = 0):
 def test_threadsScaleDown():
     """This test is for testing if threads scale down `max_threads` when the dataset is lesser than the thread count"""
     dataset = list(range(0, 2))
-    new = ParallelProcessing(
+    new = ConcurrentProcessing(
         function=_dummy_dataProcessor,
         dataset=dataset,
         max_threads=4,
@@ -32,7 +32,7 @@ def test_threadsScaleDown():
 def test_threadsProcessing():
     """This test is for testing if threads correctly order data in the `dataset` arrangement"""
     dataset = list(range(0, 500))
-    new = ParallelProcessing(
+    new = ConcurrentProcessing(
         function=_dummy_dataProcessor, dataset=dataset, args=[0.001], daemon=True
     )
     new.start()
@@ -43,7 +43,7 @@ def test_threadsProcessing():
 def test_raises_StillRunningError():
     """This test should raise ThreadStillRunningError"""
     dataset = list(range(0, 8))
-    new = ParallelProcessing(
+    new = ConcurrentProcessing(
         function=_dummy_dataProcessor, dataset=dataset, args=[1], daemon=True
     )
     new.start()
@@ -54,7 +54,7 @@ def test_raises_StillRunningError():
 def test_raises_RunTimeError():
     """This test should raise a RunTimeError"""
     dataset = [RuntimeError()] * 8
-    new = ParallelProcessing(
+    new = ConcurrentProcessing(
         function=_dummy_raiseException, dataset=dataset, args=[0.01], daemon=True
     )
     with pytest.raises(RuntimeError):