Software Programming with Python II.pptx

software programming python

1. Software Programming with Python II Harnessing the Power of Python for Software Development By Gevita Chinnaiah

2. Agenda Introduction to Python Python Data Structures Python Libraries and Frameworks Object-Oriented Programming (OOP) in Python Error Handling and Testing in Python Python for Web Development Python for Data Science and Machine Learning Best Practices in Python Development Conclusion

3. Introduction to Python Python is a high-level, interpreted programming language known for its simplicity, readability, and versatility . Created by Guido van Rossum and first released in 1991, Python has since become one of the most popular programming languages worldwide

4. Why Python is Popular for Software Development Simplicity Python's syntax is designed to be straightforward and easy to understand Readability Python code is highly readable, thanks to its use of meaningful whitespace and English-like syntax Versatility Python's versatility allows it to be used in various domains, including web development, data science, machine learning, artificial intelligence, scientific computing, automation, and more

5. Examples of Python's Versatility Web Development Django , flask Data Science and Machine Learning Numpy , pandas, , matplotlib , Scripting and Automation Scientific Computing

6. Python Data Structures Python provides a rich set of built-in data structures 1. Lists 2. Tuples 3. Dictionaries

7. Lists A list in Python is an ordered collection of items which can be of mixed types. Lists are mutable. S toring a series of items, iterating over data for processing, or keeping elements for later processing

8. Example : List

9. Tuples A tuple in Python is similar to a list in that it is an ordered collection of items Tuples are immutable Tuples can contain mixed data types

10. Example : Tuple

11. Dictionaries A dictionary in Python is an unordered collection of items Each item in a dictionary is stored as a key-value pair Dictionaries are mutable Dictionaries are incredibly useful for mappings

12. Example : Dictionaries

13. Data Manipulation Examples List Comprehension Dictionary Access and Iteration

14. Python Libraries and Frameworks Python, with its vast ecosystem, hosts an array of libraries and frameworks designed to streamline software development across various domains such as web development, data analysis, machine learning, and more Popular Python libraries and frameworks e.g., NumPy , Pandas, Django

15. NumPy NumPy is the cornerstone library for numerical computing in Python. It provides support for large, multi-dimensional arrays and matrices Collection of mathematical functions to operate on these arrays

16. Pandas Pandas is a powerful, flexible data manipulation and analysis library. It offers data structures like DataFrame and Series, making it easy to clean, analyze, and visualize data

17. Django Django is a high-level Python web framework that encourages rapid development and clean, pragmatic design. It follows the DRY (Don't Repeat Yourself) principle and comes with many features to handle common web development tasks.

18. Streamlining Software Development Tasks Libraries and frameworks greatly reduce the time and effort required for developing software by providing pre-written code that developers can use to solve common programming tasks. Helps in maintaining a high level of code quality and reliability Efficiency Security Scalability

19. Real-World Applications Finance Pandas and NumPy are used for quantitative analysis, algorithmic trading, and risk management Science and Engineering Scientific research and engineering projects leverage NumPy for its mathematical capabilities Web Development Django and Flask (another popular Python web framework) power many web applications

20. Object-Oriented Programming (OOP ) in Python Object-Oriented Programming (OOP) is a programming paradigm that organizes software design around objects and data, rather than actions and logic. OOP concepts ( classes, objects, inheritance, polymorphism )

21. Classes and Objects A class is a blueprint for creating objects. It defines attributes (data) and methods (functions) that operate on those attributes. An object is an instance of a class. It represents a specific instance of the class, with its own unique data.

22. Inheritance Inheritance allows a class (child class) to inherit attributes and methods from another class (parent class). It promotes code reusability and establishes an "is-a" relationship between classes.

23. Polymorphism Polymorphism allows objects of different classes to be treated as objects of a common superclass. It enables flexibility and code extensibility by using a unified interface.

24. How Python Supports OOP Principles Built-in features such as classes, inheritance, polymorphism, encapsulation (data hiding), and abstraction It has a clear and readable syntax Python's dynamic typing and flexibility allow for dynamic object creation and modification during runtime.

25. Benefits of Using OOP in Software Development Modularity Code Reusability Encapsulation Flexibility and Scalability Abstraction

26. Error Handling Techniques in Python Try-Except Blocks Raising Exceptions Handling Specific Exceptions

27. Importance of Testing in Software Development Quality Assurance Reliability and Robustness Regression Testing Customer Satisfaction

28. Python Testing Frameworks unittest : This is Python's built-in testing framework, inspired by Java's JUnit . pytest : pytest is a popular third-party testing framework that simplifies writing and executing tests. nose2: nose2 is a successor to the nose testing framework. It provides an extended feature set and improved test discovery mechanisms.

29. Best Practices in Python Development Coding conventions and style guides (e.g., PEP 8) W riting clean, maintainable code Importance of documentation and code comments

30. Coding Conventions and Style Guides Follow PEP 8 Use descriptive names Maintain consistent indentation Limit line length Use blank lines sparingly

31. Writing Clean, Maintainable Code Keep functions small and focused Avoid unnecessary complexity Use meaningful comments Write modular and reusable code

32. Importance of Documentation and Code Comments Write docstrings Comment where necessary Update documentation and comments

33. Conclusion In conclusion, we have covered several key points in today's presentation about Python in software development. We discussed Python's versatility as a programming language, its readability and simplicity which make it ideal for both beginners and experienced developers, as well as its extensive library support and community-driven ecosystem. I want to encourage you all to further explore Python in your software development journey. Whether you are interested in web development, data science, machine learning, or automation, Python has a wide range of applications that can benefit your projects and career growth.

34. THANK YOU