Comparison between Python and C++
Project Proposal
Group Members
Abdul Rafay
21-NTU-CS-1197
Arooba Zaman
21-NTU-CS-1211
Department of Computer Science
National Textile University Faisalabad
04-12-2023
Introduction
In our paper, we embark on a comprehensive exploration of the Python and C++
programming languages, examine critical dimensions that significantly impact their
applicability in diverse software development scenarios. The comparative analysis
encompasses factors such as execution speed, syntax clarity, code length, memory
management, portability, and a detailed examination of algorithmic complexities in
searching, sorting, insertion, and deletion operations.
Problem Description
Selecting the right programming language is a pivotal decision in software
development. However, the complex landscape of choices, especially between Python
and C++, demands a nuanced understanding. The absence of a consolidated resource
hinders decision-makers from making well-informed choices.
Objective
This study aims to comprehensively compare Python and C++ in diverse software
development contexts. Our objectives include evaluating execution speed, syntax
clarity, code length, memory management, and algorithmic complexities. We seek to
provide a nuanced understanding of each language's historical evolution, type systems,
and computational models.
Through graphical representations, including graphs, charts, and tables, our goal
is to offer valuable insights for developers and decision-makers, facilitating informed
language choices based on specific project requirements and optimizing software
development processes.
Key Dimensions of Comparison
1. Execution Speed:



Approach: Implement common algorithms in both Python and C++.
Measure and compare their execution times.
Example: Sorting algorithm, searching algorithm, insertion algorithm.
Presentation: Use a table or graph to visualize the performance
differences.
2. Syntax and Code Length:



Approach: Develop identical functionalities in both languages and
analyze the resulting code lengths.
Example: Implement a simple data manipulation task.
Presentation: Utilize a comparison chart highlighting code length
disparities.
3. Memory Management:

Approach: Execute memory-intensive operations in Python and C++,
evaluating their respective memory management efficiencies.


Example: Manipulation of datasets.
Presentation: Present findings through memory usage graphs or tables.
4. Type System:
 Approach: Test type-related behaviors in Python and C++ by creating


scenarios where type differences are critical that deals data types, syntax
etc.
Example: Handle numeric data with varying types.
Presentation: Visualize outcomes in a type system comparison table.
5. Readability and Code Structure:



Approach: Compare the readability and structure of code written in both
Python and C++, emphasizing common programming constructs.
Example: Implement a standard code snippet in both languages.
Presentation: Utilize readability metrics and code structure comparisons
to highlight differences.
6. Scope and Variable Handling:



Approach: Explore how Python and C++ handle variable scope and assess
the implications for code organization.
Example: Examine variable visibility in different scopes.
Presentation: Showcase findings through scope-related charts or graphs.
7. Order of Operator and Operand Evaluation:



Approach: Investigate how Python and C++ handle the order of
evaluation for operators and operands.
Example: Assess the outcome of expressions with multiple operators and
operands.
Presentation: Present results through visual representations,
emphasizing language-specific nuances.
8. Computational Model:



Approach: Examine the computational models of Python and C++.
Example: Implement a task requiring computational model in both
languages.
Presentation: Illustrate findings through a comparative computational
model graph, highlighting performance in each language.
9. Operator Overloading and Type Casting:
 Approach: Explore and compare operator overloading and type casting


capabilities in Python and C++.
Example: Perform operations on user-defined objects.
Presentation: Present results in a table highlighting language-specific
features.
Tools and Technology
⮚
⮚
⮚
⮚
Python as a programming language
Jupyter Notebook (Version)
C++ as a programming language
Dev-C++ (Version 5.11)