Metadata-Version: 2.1
Name: monkstools
Version: 0.6
Summary: Tools for the Monks advertising platform
Home-page: https://github.com/williampolicy/monkstools
Author: xiaowen kang
Author-email: kangxiaowen@gmail.com
License: UNKNOWN
Description: # monkstools
        monkstools for team
        
        begin to work. by Xiaowen kang. 2023.8.24.
        check . well done.  by xiaowen kang. 2023.8.24
        prepare for pypi package. by xiaowen kang. 2023.8.24.
        
        
        
        ---
        
        ### 1. Use Case
        
        Analyze and calculate ROI (Return On Investment) based on given datasets: one reflecting group demographics and another indicating secondary preferences.
        
        ### 2. Sample Code
        
        ```python
        from monkstools.top_module import TopModule
        
        def main():
            # Sample user data
            data = {
                "person_group": "TensorData Representation",  # Replace with actual data
                "secondary_preference": "Preferences Dataset"  # Replace with actual data
            }
        
            # Utilizing monkstools for ROI computation
            instance = TopModule(data)
            instance.calculate_roi()
            instance.display_results()
        
        if __name__ == "__main__":
            main()
        ```
        
        ### 3. Documentation
        
        **monkstools Library Guide**
        
        ---
        
        **Class: TopModule**
        - **Description**: Central module for ROI calculations integrating `PersonGroup` and `SecondaryPreference` sub-modules.
        - **Methods**:
            - `__init__(self, data: dict)`: Constructor expecting a dictionary containing data for `person_group` and `secondary_preference`.
            - `calculate_roi()`: Executes ROI calculation, invoking the analyze methods of sub-modules.
            - `display_results()`: Outputs the computed ROI results.
        
        **Class: PersonGroup**
        - **Description**: Analyzes specific group data.
        - **Methods**:
            - `__init__(self, tensor_data: str)`: Constructor expecting a string representation of the group data.
            - `analyze()`: Analyzes the group data.
        
        **Class: SecondaryPreference**
        - **Description**: Focuses on secondary preference analysis.
        - **Methods**:
            - `__init__(self, preferences_data: str)`: Constructor expecting a string representation of preference data.
            - `analyze()`: Analyzes the preference data.
        
        ---
        
        To leverage this library, ensure `monkstools` is installed and data provided matches expected formats.
        
        ---
        
        xiaowen kang. 2023.8.23
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
