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نویسندگان: kpk. success
سری:
ناشر: Independently Published
سال نشر: 2024
تعداد صفحات: 337
زبان: English
فرمت فایل : EPUB (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود)
حجم فایل: 330 Kb
در صورت تبدیل فایل کتاب Object-Oriented Programming with Python به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
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Advanced Topics in Object-Oriented Programming in Python Applying Design Patterns from the Gang of Four GoF and other sources to Python Object-Oriented Programming 1. Singleton Pattern 2. Factory Method Pattern 3. Observer Pattern Best Practices and Tips for Object-Oriented Programming in Python Building Command-Line Interfaces CLI with Object-Oriented Programming in Python Building Custom Frameworks and Libraries with Object-Oriented Programming in Python Step 1: Define r Requirements Step 2: Design r Classes Step 3: Implement r Classes Step 4: Provide Documentation Step 5: Include Unit Tests Step 6: Package r Code Step 7: Publish r Code Step 8: Maintain and Iterate Example: Building Data Warehousing and Business Intelligence Solutions with Object-Oriented Python Building Digital Twins and Simulation Models for Industry 40 with Object-Oriented Python Building Distributed Computing Systems with Object-Oriented Programming in Python Building Energy Management Systems and Smart Grid Solutions with Object-Oriented Python Building Enterprise Resource Planning ERP and Customer Relationship Management CRM Systems with Object-Oriented Python 1. Define Requirements: 2. Design the System: 3. Choose Frameworks and Libraries: 4. Implement Functionalities: 5. Integrate ERP and CRM: 6. Testing: 7. Deployment and Maintenance: Example Code Snippet: Conclusion: Building Knowledge Graphs and Semantic Web Applications using Object-Oriented Python Building Natural Disaster Prediction and Emergency Response Systems with Object-Oriented Python 1. Define the Problem 2. Design the System 3. Implementation 4. Data Collection and Processing 5. Prediction 6. Emergency Response Planning 7. Testing and Iteration 8. Deployment Additional Considerations Building Recommendation Systems with Object-Oriented Programming in Python 1. Define Classes: 2. Implement Recommendation Algorithms: 3. Construct Recommendation System: 4. Extend and Optimize: Building Recommender Systems and Personalization Engines using Object-Oriented Programming in Python Building Scalable Web Applications with Object-Oriented Programming and Frameworks like Django or Flask Case Studies and Real-World Applications of Object-Oriented Programming in Python Class Methods and Static Methods in Python Classes and Objects in Python Classes: Objects: Example: Composition and Aggregation in Python Concurrency and Multithreading in Python Continuous Integration and Deployment CICD for Object-Oriented Python Projects Creating Blockchain-based Smart Contracts and Decentralized Applications DApps with Object-Oriented Python Creating Custom Visualization Libraries and Tools with Object-Oriented Python Step 1: Define the Structure Step 2: Design the Class Hierarchy Step 3: Implement Customization Options Step 4: Implement Rendering Logic Step 5: Provide Examples and Documentation Step 6: Test and Iterate Example Usage: Creating Cybersecurity Tools and Threat Intelligence Platforms with Object-Oriented Programming in Python 1. Define Classes: 2. Implement Encapsulation: 3. Use Inheritance: 4. Implement Polymorphism: 5. Handle Exceptions: 6. Use Design Patterns: 7. Implement Data Structures: 8. Secure Input and Output: 9. Unit Testing: 10. Document r Code: Creating Digital Humanities Tools and Text Analysis Pipelines with Object-Oriented Programming in Python 1. Define Object Classes: 2. Implement Methods and Functionality: 3. Design Text Analysis Pipelines: 4. Extend and Customize: 5. Testing and Refinement: Creating Domain-Specific Languages DSLs using Object-Oriented Programming in Python Creating Interactive Data Visualization with Object-Oriented Programming in Python using libraries like Matplotlib or Plotly Using Matplotlib: Using Plotly: Creating Interactive Educational Tools and Simulations with Object-Oriented Programming in Python Creating Predictive Maintenance Systems and Condition Monitoring Solutions with Object-Oriented Python Creating RESTful APIs using Object-Oriented Programming in Python Data Structures and Algorithms in Python Debugging Techniques and Tools for Object-Oriented Python Programs Decorators and Metaclasses in Python Decorators: Metaclasses: Design Patterns in Python Designing and Implementing Microservices Architectures with Object-Oriented Python 1. Understand Microservices Architecture: 2. Choose a Framework: 3. Design Object-Oriented Microservices: 4. Implement Microservices: 5. Containerize Microservices: 6. Manage Configuration and Deployment: 7. Monitor and Maintain: Example: Conclusion: Designing GUI Applications with Object-Oriented Programming in Python Developing Augmented Reality AR and Virtual Reality VR Applications using Object-Oriented Programming in Python Developing Automated Trading Systems and Algorithmic Trading Strategies with Object-Oriented Python Developing Chatbots and Conversational AI using Object-Oriented Programming in Python Developing Concurrent and Parallel Algorithms with Object-Oriented Programming in Python Developing Data Governance and Compliance Solutions with Object-Oriented Programming in Python Developing Desktop Applications using Object-Oriented Programming in Python using libraries like PyQt or Tkinter Using Tkinter: Using PyQt: Developing Embedded Systems and Firmware using Object-Oriented Programming in Python Developing Games with Object-Oriented Programming in Python Developing Geographic Information Systems GIS and Spatial Analysis Tools with Object-Oriented Python Developing Geospatial Analysis and Remote Sensing Applications using Object-Oriented Python 1. Choose Python Libraries: 2. Object-Oriented Design: 3. Workflow: 4. Example Workflow: 5. Deployment and Integration: 6. Testing and Documentation: Developing Medical Imaging and Healthcare Analytics Solutions with Object-Oriented Programming in Python Developing Natural Language Understanding NLU Systems with Object-Oriented Python 1. Define a Token Class: 2. Define a Sentence Class: 3. Implement a Tokenizer Class: 4. Define a Parser Class: 5. Implement a SemanticAnalyzer Class: 6. Define a NLU Class: Usage Example: Notes: Developing Self-driving Car Simulations and Autonomous Vehicle Control Systems with Object-Oriented Python Developing Simulation and Modeling Applications with Object-Oriented Programming in Python Distributed Systems and Microservices with Object-Oriented Programming in Python Encapsulation and Abstraction in Python Exploring Advanced Python Features for Object-Oriented Programming, such as Metaprogramming, Context Managers, and Descriptors Metaprogramming: Context Managers: Descriptors: Exploring Bioinformatics and Computational Biology Applications with Object-Oriented Programming in Python Exploring Computational Fluid Dynamics CFD Simulations with Object-Oriented Python Exploring Computational Geometry and Algorithms with Object-Oriented Python 1. Understanding Computational Geometry Concepts: 2. Implementing Basic Geometric Objects: 3. Algorithms and Data Structures: 4. Visualization: 5. Optimization and Advanced Topics: Sample Code (Point Class): Exploring Computational Neuroscience and Brain-Machine Interfaces with Object-Oriented Python Exploring Computational Social Science and Social Network Analysis with Object-Oriented Python 1. Understanding Computational Social Science (CSS) and Social Network Analysis (SNA) 2. Python Libraries for CSS and SNA 3. Object-Oriented Python Approach 4. Analyze and Visualize Data Exploring Ethical AI and Bias Mitigation Strategies in Object-Oriented Python Applications Exploring Explainable AI XAI and Model Interpretability Techniques with Object-Oriented Python Exploring Future Trends and Innovations in Object-Oriented Programming with Python Exploring Quantum Chemistry Simulations and Molecular Modeling with Object-Oriented Python 1. Understanding Quantum Chemistry Basics: 2. Python Libraries for Quantum Chemistry: 3. Object-Oriented Programming (OOP) Concepts: 4. Building Molecular Models in Python: 5. Quantum Chemistry Simulations: 6. Visualization: Example Code Snippet: Tips: Exploring Quantum Computing Algorithms and Simulations with Object-Oriented Python Setting Up the Environment Building Quantum Circuits Simulating Quantum Circuits Object-Oriented Approach Conclusion Extending Python with CC++ using Object-Oriented Approach Extending Python's Capabilities with Custom Data Types and Structures 1. Classes 2. Namedtuples 3. Dataclasses (Python 3.7+) 4. Custom Collections 5. Third-party Libraries Financial Modeling and Quantitative Analysis with Object-Oriented Programming in Python 1. Understanding Financial Concepts: 2. Choose the Right Libraries: 3. Design Object-Oriented Architecture: 4. Implement Classes and Methods: 5. Utilize Design Patterns: 6. Test r Code: 7. Optimize Performance: 8. Document r Code: 9. Stay Updated: Example: GUI Testing and Automation with Object-Oriented Programming in Python Image Processing and Computer Vision with Object-Oriented Programming in Python Implementing Asynchronous Programming Patterns with Object-Oriented Programming in Python asyncio Implementing Audio Processing and Digital Signal Processing Algorithms with Object-Oriented Programming in Python Implementing Behavioral Analysis and Anomaly Detection Systems using Object-Oriented Programming in Python Implementing Blockchain and Cryptocurrency Solutions with Object-Oriented Python Implementing Evolutionary Algorithms and Genetic Programming with Object-Oriented Python Implementing Finite State Machines FSMs with Object-Oriented Programming in Python Implementing Game Development Frameworks and Engines with Object-Oriented Python Implementing Game Theory and Mechanism Design Algorithms with Object-Oriented Python Implementing Machine Learning Models with Object-Oriented Programming in Python Implementing Natural Language Generation NLG Systems with Object-Oriented Python Implementing Quantum Machine Learning Algorithms with Object-Oriented Python Implementing Reinforcement Learning Algorithms and Autonomous Agents with Object-Oriented Python Inheritance and Method Resolution Order in Python Inheritance: Method Resolution Order (MRO): Inheritance and Polymorphism in Python Inheritance: Polymorphism: Integrating External APIs and Services with Object-Oriented Python Applications 1. Choose an API 2. Install Required Libraries 3. Design Object-Oriented Structure 4. Create API Wrapper Class 5. Implement Authentication 6. Define Data Models 7. Make API Requests 8. Error Handling Example Code: Tips: Integrating Hardware Interfaces and Sensors with Object-Oriented Python for IoT Applications Introduction to Object-Oriented Programming in Python Classes and Objects: Attributes and Methods: Inheritance: Encapsulation: Polymorphism: Conclusion: Machine Learning and Data Science Applications with Object-Oriented Programming in Python Metaprogramming and Reflection in Python Reflection: Metaprogramming: Use Cases: Mobile App Development with Object-Oriented Programming in Python using frameworks like Kivy or BeeWare Natural Language Processing NLP and Text Analysis using Object-Oriented Programming in Python 1. Object-Oriented Design: TextData Class: NLPProcessor Class: TextAnalyzer Class: 2. Libraries for NLP: 3. Example Implementation: Networking and Socket Programming with Object-Oriented Approach in Python Object-Oriented Approach: Socket Programming in Python: Example: Explanation: Object-Oriented Database Programming in Python Object-Oriented Design Principles in Python Operator Overloading in Python Performance Optimization Strategies for Object-Oriented Python Applications Robotics and IoT Internet of Things Applications with Object-Oriented Programming in Python Security and Cryptography with Object-Oriented Programming in Python Unit Testing and Test-Driven Development in Python Unit Testing with unittest: Test-Driven Development (TDD) with unittest: Unit Testing with pytest: Test-Driven Development (TDD) with pytest: Web Development with Object-Oriented Programming in Python Web Scraping and Automation with Object-Oriented Programming in Python 1. Understand OOP Concepts: 2. Choose the Right Libraries: 3. Design r Classes: 4. Implement the Classes: 5. Utilize Inheritance and Composition: 6. Error Handling and Testing: 7. Modularize r Code: 8. Follow Best Practices: