Binggen Li -Tokyo Senior Software Engineer’s Post

Understanding Shallow vs. Deep Copies in Python: Immutable vs. Mutable Objects 💼 Senior Software Engineer Available in Tokyo Open to Work | Agile Team Leader | Cloud & API Integration | Python, Django & Flask Expert (Available in 1 Month) With 18 years of experience in Agile leadership, cloud integration, and backend development, I’m actively seeking a Senior Software Engineer role in Tokyo. Specializing in Python, Django, and Flask, I’m ready to bring my expertise to a dynamic team. Open to new opportunities starting in 1 month. Any leads or recommendations are greatly appreciated! libinggenjp@gmail.com In Python, understanding how copies of objects work is crucial for writing efficient and bug-free code: • Immutable Objects (Shallow Reference Only): Objects like int, str, and tuple are immutable, meaning their state cannot be modified. Any assignment or copy simply references the same object in memory because changes to the object’s state are impossible. • Mutable Objects (Shallow Reference / Deep Copy): • Shallow Copy: For mutable objects like list, dict, and set, a shallow copy creates a new container, but the elements within it reference the same objects as the original. Changes to these elements will affect both the original and the shallow copy. • Deep Copy: A deep copy, on the other hand, creates an independent copy of both the container and its contents, ensuring no cross-impact between the original and copied objects. Understanding these concepts helps avoid unintended side effects, especially when dealing with complex data structures. #Python #Programming #SoftwareEngineering #DeepCopy #ShallowCopy #Immutable #Mutable #CodingBestPractices #PythonTips #DataStructures

Optimizing Performance with Asynchronous Programming in Python 💼 Senior Software Engineer Available in Tokyo Python, Django & Flask Expert | Agile Team Leader I have 18 years of experience in backend development, cloud integration, and Agile leadership. I’m seeking new opportunities in Tokyo and can start in 1 month. Feel free to reach out with any leads! libinggenjp@gmail.com In modern applications, tasks often run independently and can proceed without waiting for each other. This is where asynchronous programming in Python shines, improving overall performance by allowing tasks to run concurrently. Example of Independent Tasks Running Concurrently: import asyncio async def task_one(): await asyncio.sleep(2) print("Task one complete") async def task_two(): await asyncio.sleep(1) print("Task two complete") async def task_three(): await asyncio.sleep(3) print("Task three complete") async def main(): await asyncio.gather(task_one(), task_two(), task_three()) asyncio.run(main()) Key Insights: I/O-Bound Tasks: Asynchronous programming is perfect for managing tasks like network requests or file I/O, which involve waiting for external resources. Real-Time Applications: It helps manage multiple real-time events and connections while keeping your application responsive. Independent Tasks: Tasks that don't depend on each other can run concurrently, significantly improving execution speed and system performance. By leveraging Python’s async and await keywords, and using utilities like asyncio.gather and asyncio.run, you can efficiently manage tasks, making your applications more scalable and responsive. #Python #AsynchronousProgramming #Concurrency #SoftwareDevelopment #AsyncAwait #Asyncio #Scalability #IOTasks #PerformanceOptimization #ProgrammingTips #DeveloperTools #TechInnovation

Understanding Python’s Types and Collections: Immutability vs. Mutability 💼 Senior Software Engineer Available in Tokyo Open to Work | Agile Team Leader | Cloud & API Integration | Python, Django & Flask Expert (Available in 1 Month) With 18 years of experience in Agile leadership, cloud integration, and backend development, I’m actively seeking a Senior Software Engineer role in Tokyo. Specializing in Python, Django, and Flask, I’m ready to bring my expertise to a dynamic team. Open to new opportunities starting in 1 month. Any leads or recommendations are greatly appreciated! In Python, understanding the distinction between immutable and mutable types is key to optimizing both performance and safety in your code. Here’s a concise breakdown: Immutable Types • Performance & Safety: Immutable objects, such as int, float, str, and tuple, are thread-safe and efficient because they can’t be modified after creation. Copying them is usually just copying references. • Examples: • Primitive types: int, float, bool, complex • Compound types: tuple, range, frozenset, bytes Mutable Types • Mutability: Mutable types like list, set, and dict allow changes after creation, offering flexibility but requiring careful management. • Copying: When dealing with mutable objects, be cautious with shallow vs. deep copies to avoid unexpected side effects. • Examples: • Basic collections: list, set, dict, bytearray • Specialized collections: collections.deque, heapq, collections.Counter Special Categories • Classes, Functions, Modules: Mutable by design, allowing for dynamic adjustments in attributes or methods. A solid grasp of these concepts helps ensure efficient code design, particularly when dealing with concurrency or large-scale applications. #Python #Programming #SoftwareEngineering #MutableAndImmutable #PythonTypes #SoftwareDevelopment #PythonCollections #TechTips #CodingBestPractices #LearningPython #DataStructures

Python and Object-Oriented Programming (OOP) 💼 Senior Software Engineer Available in Tokyo Open to Work | Agile Team Leader | Cloud & API Integration | Python, Django & Flask Expert (Available in 1 Month) With 18 years of experience in Agile leadership, cloud integration, and backend development, I’m actively seeking a Senior Software Engineer role in Tokyo. Specializing in Python, Django, and Flask, I’m ready to bring my expertise to a dynamic team. Open to new opportunities starting in 1 month. Any leads or recommendations are greatly appreciated! libinggenjp@gmail.com As I continue deepening my understanding of Python and OOP, I’ve been exploring essential concepts that form the foundation of effective software design and architecture. Python Function Concepts: Parameters are variables defined in a function signature, while arguments are the actual values passed when the function is called. Object-Oriented Programming (OOP): A class serves as a blueprint for creating objects. Each object is an instance of the class, containing attributes and methods. Concepts such as inheritance, encapsulation, and polymorphism allow us to write flexible and reusable code: class Child(Parent): pass # Inheritance class MyClass: def __init__(self): self.__private = "Private attribute" # Encapsulation Design Patterns: Design patterns like the Singleton Pattern ensure a class only has one instance, providing a global access point, while the Factory Pattern offers an interface for creating objects, allowing for customization in subclasses. These are just a few of the key principles and patterns that help in writing clean, scalable, and maintainable code! #Python #OOP #SoftwareDevelopment #DesignPatterns #CleanCode #Scalability #SingletonPattern #FactoryPattern #Inheritance #Encapsulation #Polymorphism #BackendDevelopment #CodingSkills #SoftwareEngineering

💡 Dive into the dynamic world of Python development! 🚀 Whether you're a seasoned pro or just starting your coding journey, understanding the ins and outs of the Python Developer role is key to unlocking endless possibilities in tech. 🌐💡 🔍 Ever wondered what makes Python developers so essential in today's tech landscape? 🤔 From crafting responsive web apps to unraveling complex data sets, Python developers are the driving force behind innovation across industries like web development, data analysis, and AI. 📈💻 💼 Ready to explore the core responsibilities of a Python Developer? 🛠️ From developing high-performance applications to safeguarding data integrity and troubleshooting errors, Python developers wear many hats to ensure smooth sailing in the digital realm. ⚙️🔒 🤝 Collaboration is key! Python developers work hand in hand with team members to understand user needs and craft technical solutions that hit the mark. 🎯 Effective communication and problem-solving skills are the secret sauce to success in this collaborative journey. 💬👩💻 🛠️ Building a solid skill set is crucial for thriving in the Python development world. 🧰 From Python proficiency to mastering frameworks like Django and Flask, along with dabbling in front-end technologies and database management, there's no shortage of tools to sharpen in your arsenal. 🛠️📊 📚 But it's not just about technical prowess! Soft skills like adaptability, communication, and continuous learning are equally vital for conquering the Python development landscape. 🧠💬 Embrace the journey of growth and discovery as you navigate the ever-evolving tech terrain. 🚀🔍 🎓 Ready to kickstart your Python Developer journey? 🚀 Lay a solid foundation in programming principles, consider certifications like the Certified Python Developer™ from the Global Tech Council, and stay hungry for knowledge as you embark on this exciting career path. 🎓💼 💡The role of a Python developer transcends mere coding; it's about shaping the future of technology one line of code at a time. 🌟 Whether you're delving into web development, data science, or AI, Python developers hold the key to unlocking endless possibilities in the digital realm. 🌐💡 Embrace the challenges, seize the opportunities, and let your Python journey unfold with boundless potential! 🚀 𝐋𝐞𝐚𝐫𝐧 𝐦𝐨𝐫𝐞: https://lnkd.in/gir34-tb #python #programming #coding #developer #Globaltechcouncil #pythondeveloper #pythoncourse #pythoncoding #usa #uk

🚀 Software Engineers: Top Programming Languages in Demand! 🚀 As we move through 2024, it's fascinating to see how the tech landscape is evolving. From my experience and recent industry reports, several programming languages are standing out as must-knows for software engineers. Python continues to dominate due to its versatility and ease of learning. It's widely used in web development, data science, and AI projects. The demand for Python skills is only growing, with many startups and established companies seeking Python developers to drive innovation. JavaScript remains a cornerstone for front-end development. With frameworks like React and Angular gaining traction, JavaScript proficiency is essential for creating dynamic and responsive web applications. Many businesses are looking for engineers who can bring their web projects to life with these tools. Lastly, Java is making a strong comeback, particularly in enterprise environments. Its robustness and scalability make it a preferred choice for large-scale applications. Companies are increasingly investing in Java for backend development, ensuring their systems are both reliable and efficient. What programming languages are you focusing on this year? #ProgrammingLanguages #TechTrends #SoftwareEngineering

🌿 Need extra capacity to build out a feature or meet a deadline? Meet Alex, our #FullStack developer with expertise in Python/Django, Ruby/Rails, Site Reliability, DevOps, PERL, and Data Engineering. Alex excels in finding lightweight, flexible solutions to complex problems, ensuring that our projects are both efficient and adaptable. With a strong emphasis on secure software development practices, Alex prioritizes the safety and integrity of our systems. Additionally, Alex has a keen ability to assess platforms and make gradual, impactful improvements, continuously enhancing performance and user experience. Our team of highly skilled engineers can quickly integrate with your existing team to provide the additional capacity you need. We understand the importance of moving fast to meet deadlines and scale quickly. 🚀💡 📅 To discuss augmenting your team, schedule some time with Kevin Bullock, VP of Engineering: https://lnkd.in/gnDzyfa9 #SoftwareEngineering #StaffAugmentation #TechExperts #InteractiveContent #SocialImpactStories #TechForGoodCommunity #ProfessionalNetwork #ThoughtLeadership #B2BEngagement #TechInnovation #FullStackDeveloper #HealthcareTech #TeamPlayer #Fintech #SustainableTech #SoftwareForGood #TechWithPurpose #ValuesInAction #HumanSideOfTech #TechForGoodStories #LinkedInFollowers

🚀 Unlock the Power of Python: Dive into the digital realm with offshore Python developers! In today's tech-driven world, Python stands tall, fueling innovations in AI, ML, and beyond. With its unmatched versatility and community support, Python remains a top choice for enterprises worldwide. By harnessing the expertise of offshore teams, you unlock cost efficiency, scalability, and round-the-clock productivity. Embrace the potential, propel your projects forward, and lead the way in the digital revolution. 💼💡 #Python #PythonDevelopment #OffshoreDevelopment #findapro

"Golang vs. Python: Choosing the Right Tool for the Job ⚡️" In the world of DevOps, SRE, and software development, Golang (Go) and Python are two widely loved programming languages, each with its own strengths. Here’s a breakdown of how they stack up and where each shines: 🔷 Performance: Go: Compiled, fast, and optimized for performance. Ideal for high-load systems, APIs, and real-time applications. Python: Interpreted and slower but perfect for quick development and prototyping. 🔷 Ease of Learning: Go: Simple and straightforward syntax but may feel low-level for beginners. Python: Extremely beginner-friendly with readable syntax and a massive community for learning resources. 🔷 Concurrency: Go: Built-in concurrency support with goroutines and channels makes it perfect for multi-threaded applications. Python: Offers concurrency via libraries, but the Global Interpreter Lock (GIL) can be a bottleneck. 🔷 Ecosystem: Go: Powers robust tools like Docker, Kubernetes, and Terraform. Great for system-level programming. Python: A massive library ecosystem for data science, machine learning, web development, and DevOps. 🔷 Use Cases: Go: Best for cloud-native apps, system tools, and microservices where performance matters. Python: Excellent for scripting, automation, data analysis, and machine learning tasks. 🔷 Scalability: Go: Designed with scalability in mind, making it ideal for distributed systems. Python: Scales well but may require more effort to handle high-performance demands. My Take: As a DevOps/SRE professional, I use Python for quick scripts and automation tasks, while Golang is my go-to for building scalable, high-performance tools and services. Both are incredible choosing the right one depends on your project needs. What’s your preference? Let me know in the comments! 🚀 #Golang #Python #DevOps #SRE #Programming #CloudNative #Automation #TechInnovation InfoDataWorx

🚀 Python: The Power Behind SaaS Innovation 🐍 At Wundertalent, we’ve seen firsthand how Python is shaping the future of SaaS. Its flexibility and rich libraries are the secret sauce behind many groundbreaking projects. Whether it's powering ML algorithms, streamlining data analysis, or building scalable, robust platforms, Python makes innovation feel effortless. For SaaS companies, Python isn’t just a programming language, it’s a game-changer. And for developers? It’s the toolkit that helps you turn big ideas into even bigger realities. We love connecting Python developers with SaaS companies that are pushing the boundaries of what’s possible. If you're a developer ready for your next big opportunity or a SaaS leader looking to scale with Python talent, let’s chat! #Wundertalent #Softwaredevelopment #Softwareengineering #ML #Machinelearning #AI ##Python #SaaS #Innovation #TechRecruitment #SaaSrecruitment 🐍💻🚀