overloaded-iterables 0.6

Overloaded version of the built-in python classes: list and set to include some extra functionalities.

Overloaded Iterables

Overloaded version of the built-in python classes: <list> and <set> to include some extra functionalities as an experiment.

The current iteration contains the following classes

Specifications

1. Python Version: Python v3.8+
2. Code Coverage:
3. Tests Status:

Python Package Index

1. Project Homepage
2. Contents

Installation

python -m pip install overloaded-iterables

Classes

1. OverloadedList

• A non-datatype constrained, single-dimensional collection of values.
• Inherits solely from Python's built-in <list> class.

from overloaded_iterables.classes import OverloadedList

obj = OverloadedList(*args)

2. OverloadedSet

• A non-datatype constrained, single-dimensional collection of unique values.
• Inherits solely from Python's built-in <set> class.

    from overloaded_iterables.classes import OverloadedSet

    obj = OverloadedSet(*args)

Functions and Methods

1. <class>.mean()

   • Find the mean of the values in the given iterable class object.

   • Arguments: self

   • Returns: float (64-bit)

   • Example:

         _mean: float = obj.mean()
     

2. <class>.sum()

   • Claculate the sum of all the elements in the given iterable class object.

   • Arguments: self

   • Returns: float (64-bit)

   • Example:

         _sum: float = obj.sum()
     

3. <class>.prod()

   • Calculate the product of all the elements in the given iterable class object.

   • Arguments: self

   • Returns: float (64-bit)

   • Example:

         _product: float = obj.prod()
     

4. <class>.sort()

   • Sorts the contents of the given iterable class object via the Timsort sorting algorithm.

   • Arguments: self, key: None | default: None, reverse: bool | default: False

   • Returns object: <list>

   • Example:

         sorted_seq: list = obj.sort()
     

5. <class>.raise_to()

   • Raises each element in the iterable class object to the given power.

   • Arguments: self, power: float (64-bit) | default: 1.0

   • Returns object: <class>

   • Example:

         import numpy as np
         from secrets import choice
     
         ## Taking the power variable, 'z' to be a random integer between -10 and +10
         z:float = choice([i for i in np.arange(-10, 10, 0.5)])
         _raised_sequence: type(obj) = obj.raise_to(power=z)
     

6. <class>.rms()

   • Finds the Root-Mean-Square (RMS) of the values in the current iterable class object.

   • Arguments: self, power: float | default: 2, root: int | default: 2

   • Returns: float (64-bit)

   • Example:

         _rms: float = obj.rms()
     

7. <class>.median()

   • Finds the median of the contents of the given iterable class object.

   • Arguments: self

   • Returns: float (64-bit)

   • Example:

         _median:float = obj.median()
     

8. <class>.hist()    (OverloadedList only)

   • Plots the histogram of the frequency distribution of the elements in the OverloadedList.

   • Arguments: self, bins: int | default: 10, title: str | default: 'Histogram', x_label: str | default: 'Values --->', y_label: str | default: 'Frequencies --->', save_dir: str | default: None, file_name: str | default: None, histtype: str | default: 'step', align: str | default: 'mid', orientation: str | default: 'vertical', log_scale: bool | default: False, show: bool | default: False

   • Process:

     • Shows the generated figure if show is set to True
     • Saves the generated figure if save_dir is provided.

   • Returns: bool

   • Example:

         fig_check:float = obj.hist(show=True, save_dir='figures', file_name='some-figure')
     

9. <class>.plot()    (OverloadedList only)

   • Plots the lineplot of the frequency distribution of the elements in the OverloadedList.

   • Arguments: self, title: str | default: 'Line Plot', x_label: str | default: 'Values --->', y_label: str | default: 'Frequencies --->', save_dir: str | default: None, file_name: str | default: None, color: str | default: '#000000', linewidth: float | default: 1, marker: str | default: ',', markerfacecolor: str | default: '#252525', marker_size: float | default: 1.0, show: bool | default: False

   • Process:

     • Shows the generated figure if show is set to True
     • Saves the generated figure if save_dir is provided.

   • Returns: bool

   • Example:

         fig_check:float = obj.plot(show=True, save_dir='figures', file_name='some-figure')
     

10. <class>.scatter()    (OverloadedList only)

    • Plots the scatterplot of the frequency distribution of the elements in the OverloadedList.

    • Arguments: self, title: str | default: 'Scatter Plot', x_label: str | default: 'Values --->', y_label: str | default: 'Frequencies --->', save_dir: str | default: None, file_name: str | default: None, size: List[float] | default: [1.25], color: str | default: '#000000', marker: str | default: ',', line_width: float | default: 2, show: bool | default: False

    • Process:

      • Shows the generated figure if show is set to True
      • Saves the generated figure if save_dir is provided.

    • Returns: bool

    • Example:

          fig_check:float = obj.scatter(show=True, save_dir='figures', file_name='some-figure')
      

11. <class>.len (property)

    • Finds and returns the length of the current iterable class object as a property.

    • Arguments: self

    • Returns: int

    • Example:

          _l: int = obj.len
      

12. <class>.frequencies (property)    (OverloadedList only)

    • Finds the frequencies of all elements of the given OverloadedList class and returns a list of unique values with their discovered frequencies.

    • Arguments: self

    • Returns: OverloadedList, OverloadedList

    • Example:

          values: Overloadedlist, frequencies: OverloadedList = obj.frequencies