diff --git a/environment.yaml b/environment.yaml
index a36e2f1..98f460a 100644
--- a/environment.yaml
+++ b/environment.yaml
@@ -2,8 +2,4 @@ name: mpyez
 channels:
     - conda-forge
     - defaults
-dependencies:
-    - python=3.9.*
-    - numpy==1.26.4
-    - matplotlib
-    - setuptools
+dependencies: [ python=3.9, numpy==2, matplotlib, setuptools ]
diff --git a/pyproject.toml b/pyproject.toml
index 72087d1..bee597f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,4 +1,4 @@
 [build-system]
-requires = ["setuptools", "numpy==1.26.4", "matplotlib"]
+requires = ["setuptools", "numpy<2.1.0", "matplotlib"]
 
 build-backend = "setuptools.build_meta:__legacy__"
diff --git a/requirements.txt b/requirements.txt
index 1061981..f42e317 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,2 +1,3 @@
-numpy==1.26.4
+numpy<2.1.0
 matplotlib
+setuptools
diff --git a/setup.py b/setup.py
index 5fc6ed4..ccce88b 100644
--- a/setup.py
+++ b/setup.py
@@ -30,8 +30,7 @@ def load_metadata():
       long_description=readme,
       long_description_content_type="text/markdown",
       python_requires=">=3.9",
-      install_requires=["numpy==1.26.4", "matplotlib", "setuptools"],
-      include_package_data=True,
+      install_requires=["numpy<2.1.0", "matplotlib", "setuptools"],
       classifiers=["License :: OSI Approved :: MIT License",
                    "Programming Language :: Python :: 3.9",
                    "Programming Language :: Python :: 3.10",
diff --git a/src/mpyez/backend/uPlotting.py b/src/mpyez/backend/uPlotting.py
index 9ad9aaf..e6f4f1d 100644
--- a/src/mpyez/backend/uPlotting.py
+++ b/src/mpyez/backend/uPlotting.py
@@ -152,7 +152,7 @@ def __init__(self, line_style=None, line_width=None, color=None, alpha=None,
                          alpha=alpha, marker=marker, marker_size=marker_size,
                          marker_edge_color=marker_edge_color, marker_face_color=marker_face_color,
                          marker_edge_width=marker_edge_width)
-        self.color = get_color()
+        self.color = color or get_color()
 
     def __repr__(self):
         param_str = ', '.join(f"{key}={value!r}" for key, value in self.to_dict().items())
@@ -221,7 +221,7 @@ def __init__(self, color=None, alpha=None, marker=None, size=None, cmap=None, fa
         super().__init__(color=color, alpha=alpha, marker=marker, size=size, cmap=cmap, face_color=face_color)
 
         if self.color is None:
-            self.color = get_color()
+            self.color = color or get_color()
 
     def __repr__(self):
         param_str = ', '.join(f"{key}={value!r}" for key, value in self.to_dict().items())
diff --git a/src/mpyez/ezArray.py b/src/mpyez/ezArray.py
index 984463f..d8a0dfd 100644
--- a/src/mpyez/ezArray.py
+++ b/src/mpyez/ezArray.py
@@ -62,3 +62,29 @@ def moving_average(array: np.ndarray, window_size: int) -> np.ndarray:
         An array containing the moving averages. The length of this array will be `len(array) - window_size + 1`.
     """
     return np.convolve(array, np.ones(window_size), 'valid') / window_size
+
+
+def evaluate_with_broadcast(func, constant_array, **param_arrays):
+    """
+    Evaluate a function with a constant array and multiple parameter arrays using broadcasting.
+
+    Parameters
+    ----------
+    func : callable
+        The function to evaluate. It must support broadcasting of inputs. The function signature should match `func(constant_array, **param_arrays)`.
+    constant_array : ndarray
+        The constant array to evaluate the function over.
+    **param_arrays : dict
+        Keyword arguments representing parameter arrays. Each array should be compatible with broadcasting.
+
+    Returns
+    -------
+    ndarray
+        The result of the function evaluation. The shape of the result is `(len(constant_array), ...)`,
+        where the additional dimensions correspond to the shapes of the parameter arrays.
+    """
+    # Expand constant_array to add a broadcast dimension
+    expanded_constant = constant_array[:, np.newaxis]
+    params_ = {key: value[np.newaxis, :] for key, value in param_arrays.items()}
+
+    return func(expanded_constant, **params_)
diff --git a/src/mpyez/ezMultiprocessing.py b/src/mpyez/ezMultiprocessing.py
index 70e15e9..b85b3c5 100644
--- a/src/mpyez/ezMultiprocessing.py
+++ b/src/mpyez/ezMultiprocessing.py
@@ -1 +1,46 @@
 """Created on Jun 12 13:48:59 2024"""
+
+from multiprocessing import Pool
+from typing import Callable, Dict, List
+
+import numpy as np
+
+
+class MultiProcessor:
+    """Generalized multiprocessing functionality for processing dictionary inputs."""
+
+    def __init__(self, func: Callable, args: Dict[str, List], n_processors: int = 3):
+        """
+        Initialize the `MultiProcessor` class.
+
+        Parameters
+        ----------
+        func: Callable
+            Function to be processed. The function should take arguments corresponding to the keys in the dictionary.
+        args: Dict[str, List]
+            A dictionary where keys are argument names, and values are lists of values for those arguments.
+        n_processors: int, optional
+            The number of processors to use for multiprocessing. Default is 3.
+        """
+        if n_processors < 1:
+            raise ValueError("`n_processors` must be at least 1.")
+
+        self.func = func
+        self.args = args
+        self.n_proc = n_processors
+
+        lengths = [len(v) for v in args.values()]
+        if len(set(lengths)) != 1:
+            raise ValueError("All argument lists must have the same length.")
+
+        self.arg_tuples = list(zip(*self.args.values()))
+
+    def run(self) -> np.ndarray:
+        """Run the multiprocessing task."""
+        with Pool(self.n_proc) as pool:
+            try:
+                results = pool.starmap(self.func, self.arg_tuples)
+            except Exception as e:
+                raise RuntimeError(f"Error occurred during parallel execution: {e}")
+
+        return np.array(results)
diff --git a/src/mpyez/ezPlotting.py b/src/mpyez/ezPlotting.py
index 65304da..9770cb6 100644
--- a/src/mpyez/ezPlotting.py
+++ b/src/mpyez/ezPlotting.py
@@ -1,4 +1,4 @@
-"""Created on Jul 23 23:41:18 2024"""
+"""Created on Jul 23 23:41:18 2024."""
 
 __all__ = ['plot_two_column_file', 'plot_xy', 'plot_xyy', 'plot_with_dual_axes', 'two_subplots', 'n_plotter']
 
@@ -27,7 +27,7 @@ def plot_two_column_file(file_name: str,
                          plot_dictionary: Optional[plot_dictionary_type] = None,
                          axis: Optional[Axes] = None) -> axis_return:
     """
-    Reads a two-column file (x, y) and plots the data.
+    Read a two-column file (x, y) and plots the data.
 
     This function reads a file containing two columns (e.g., x and y values) and plots them
     using either a line plot or scatter plot based on the user's preference.
@@ -47,7 +47,7 @@ def plot_two_column_file(file_name: str,
     is_scatter : bool, optional
         If True, creates a scatter plot. Otherwise, creates a line plot. Default is False.
     plot_dictionary: Union[LinePlot, ScatterPlot], optional
-        An object representing the plot data, either a `LinePlot` or `ScatterPlot`,  to be passed to the matplotlib plotting library.
+        An object representing the plot data, either a `LinePlot` or `ScatterPlot`, to be passed to the matplotlib plotting library.
          If None, a default plot type will be used.
     axis: Optional[Axes]
         The axis object to draw the plots on. If not passed, a new axis object will be created internally.
@@ -77,7 +77,7 @@ def plot_xy(x_data: np.ndarray, y_data: np.ndarray,
             plot_dictionary: Optional[plot_dictionary_type] = None,
             axis: Optional[Axes] = None) -> axis_return:
     """
-    Plots x_data against y_data with customizable options.
+    Plot the x_data against y_data with customizable options.
 
     This function accepts two arrays of data (x and y) and plots them using either
     a line plot or scatter plot, with options for labels and figure size.
@@ -189,7 +189,7 @@ def plot_with_dual_axes(x1_data: np.ndarray, y1_data: np.ndarray,
                         plot_dictionary: Optional[plot_dictionary_type] = None,
                         axis: Optional[Axes] = None) -> axis_return:
     """
-    Plots data with options for dual axes (x or y) or single axis.
+    Plot the data with options for dual axes (x or y) or single axis.
 
     Parameters
     ----------
@@ -295,7 +295,7 @@ def two_subplots(x_data: List[np.ndarray], y_data: List[np.ndarray],
                  subplot_dictionary: Optional[uPl.SubPlots] = None,
                  plot_dictionary: Optional[Union[uPl.LinePlot, uPl.ScatterPlot]] = None) -> None:
     """
-    Creates two subplots arranged horizontally or vertically, with optional customization.
+    Create two subplots arranged horizontally or vertically, with optional customization.
 
     This function internally calls `n_plotter` to handle the plotting of each subplot.
     `n_plotter` arranges the subplots and applies relevant plot and subplot dictionaries.
@@ -359,7 +359,7 @@ def n_plotter(x_data: List[np.ndarray], y_data: List[np.ndarray],
               subplot_dictionary: Optional[uPl.SubPlots] = None,
               plot_dictionary: Optional[Union[uPl.LinePlot, uPl.ScatterPlot]] = None) -> Union[plt.figure, Axes]:
     """
-    Plots multiple subplots in a grid with optional customization for each subplot.
+    Plot multiple subplots in a grid with optional customization for each subplot.
 
     Parameters
     ----------
diff --git a/src/mpyez/version.py b/src/mpyez/version.py
index 054cc11..90612e8 100644
--- a/src/mpyez/version.py
+++ b/src/mpyez/version.py
@@ -1,6 +1,7 @@
 """Created on Nov 02 21:24:07 2024"""
 
-__version__ = "0.0.9a0"
+__name__ = 'mpyez'
+__version__ = "0.1.0"
 __author__ = "Syed Ali Mohsin Bukhari"
 __email__ = "syedali.b@outlook.com"
 __license__ = "MIT"