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Dev
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🧠 Building “Memory Maze” with Amazon Q CLI and Python — A Brain-Training Game with AI Power ⚡🎮
- A Brain-Training Game called Memory Maze was built using Amazon Q CLI and Python in the #BuildOnAWS challenge.
- A generative AI assistant by AWS, Amazon Q CLI, was used to create the game quickly and efficiently.
- Memory Maze challenges players to remember and follow a disappearing path within a countdown timer.
- The game features difficulty scaling, lives system, score tracking, sound effects, and level progression.
- Python and Pygame were utilized for game logic and UI rendering, aided by Amazon Q CLI for code generation.
- Amazon Q CLI streamlined the development process, allowing for more focus on creativity and faster learning.
- The project highlighted how generative AI can quickly turn ideas into working prototypes.
- The Memory Maze game was refined through natural language prompts with Amazon Q CLI, showcasing its versatility.
- Special thanks were given to the challenge leader, Shafraz Rahim, for inspiring the project.
- The game premise involves the player following a disappearing path to reach the goal without mistakes, testing memory and focus.
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Dev
4w
423
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What is Selenium? Why Choose Selenium for Automation? The Power Couple: Selenium and Python for Automation Testing
- Selenium is a versatile open-source framework for automating web browsers, offering tools like WebDriver, IDE, and Grid for efficient testing with real user interaction.
- Choosing Selenium for automation testing provides advantages such as being open-source, efficient, supporting parallel execution, integrating with CI/CD tools, and enhancing test management.
- The combination of Selenium and Python for automation testing is powerful due to Python's simplicity, readability, and extensive library support, along with Selenium's robust web automation capabilities.
- Python's ease of use and cross-platform support complement Selenium, enabling the development of efficient and scalable test automation frameworks for high-quality web applications.
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Javarevisited
4w
57
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Top 8 Courses to learn Pandas and Python Data Analysis for Beginners in 2025 - Best of Lot
- Pandas is a powerful Python library for Data Analysis, widely used by Data scientists for tasks like cleaning, transformation, and manipulation of data.
- Learning Pandas is crucial for effectively working with real-world messy data before analysis and is essential in the field of Data Science.
- Here are the top online courses recommended for learning Pandas and Data Analysis with Python in 2025.
- Java, Unix, Tibco RV and FIX Protocol Tutorial
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Dev
4w
374
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🚀 Building a Space Asteroid Dodge Game Using Amazon Q CLI and Python 🎮☄️
- Pavan Mali explored using Amazon Q CLI and Python to build a Space Asteroid Dodge Game as part of the Build on AWS Challenge.
- Amazon Q is an AI-powered assistant by AWS that helps developers in coding, debugging, and building applications with simple prompts.
- The Space Asteroid Dodge Game project involved creating a game where a spaceship avoids falling asteroids, incorporating score tracking and a progress bar.
- Tools used in the project included Python, Pygame for game development, Amazon Q CLI for code generation, and VS Code for editing and testing.
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Dev
4w
370
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How to Use Docker Compose and Python to Automate Your Jenkins Environment
- The article discusses using Docker Compose and Python to automate the creation of a Jenkins environment.
- Docker is highlighted as a tool for consistent environment creation, and Docker Compose is mentioned for orchestrating multi-container applications locally.
- Automation is emphasized for reducing errors and saving time, with specific steps automated using Python in the project.
- The process involves writing a docker-compose.yml file, creating a Dockerfile for a custom Jenkins image, and using Python script (automate.py) for automation.
- Common roadblocks include issues like 'mypy Not Recognized' and 'ModuleNotFoundError: No module named 'docker', with solutions provided.
- The article concludes by recommending similar projects for skill enhancement and sharing the GitHub repository link for reference.
- The author invites readers to engage by dropping comments or sharing the article with those interested in DevOps.
- Hands-on cloud builds, automation tricks, and AWS-focused deep dives are shared by the author on platforms like LinkedIn, Medium, GitHub, and Dev.to.
- The article encourages readers to continue learning about DevOps, Docker, and automation for skill improvement.
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Dev
4w
218
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Kivy vs BeeWare: Best Python Frameworks for iOS App Development
- Python has become popular for iOS app development with frameworks like Kivy and BeeWare bridging the gap with Swift and Objective-C.
- Kivy is known for cross-platform support and rich graphical interfaces like media players and games.
- BeeWare enables native iOS experiences with access to native UI components directly.
- Kivy excels in GPU-accelerated performance, while BeeWare focuses on smooth performance and compatibility with Apple's ecosystem.
- Kivy's UI customization contrasts with BeeWare's direct access to native UI elements for consistency with iOS guidelines.
- Kivy has extensive documentation, making it beginner-friendly, while BeeWare benefits from a growing community focused on native apps.
- Choosing between Kivy and BeeWare depends on factors like cross-platform needs, native UI guidelines, and app scalability.
- Kivy is suitable for quick cross-platform development, MVPs, and custom animations, while BeeWare shines with native look and feel, App Store compliance, and long-term scalability.
- Final verdict: Kivy for flexibility and speed, BeeWare for native feel and iOS ecosystem integration.
- Kivy and BeeWare cater to different iOS app development needs, with BeeWare often preferred for client-facing or enterprise-level apps.
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Dev
4w
165
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🚀 Building My Own Mars Rover Simulator with Python & Tkinter
- A developer created a Mars Rover Simulator using Python and Tkinter to enhance their software engineering skills and simulate real rover decision-making logic.
- The simulator includes features like obstacle detection, 2D terrain mapping, undo/reset functionality, and command logging with timestamps, providing a real-world inspired project for learning.
- Through this project, the developer practiced Object-Oriented Programming, 2D grid movement with obstacle avoidance, GUI building with Tkinter, and clean Python project structure.
- The Mars Rover Simulator project is a significant step towards the developer's dream of working in space, aerospace, or robotics, showcasing their passion for space exploration and software development.
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Hackernoon
4w
116
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Here's The Code You Need to Build a Secure Password Manager in Python
- Password management is crucial for online security, and creating a password manager is a beneficial cybersecurity project.
- When developing a password manager, prioritize security and usability by storing data securely, using encryption, and blocking unauthorized access.
- For this project, Python, SQLite, and the cryptography library are recommended as the tech stack.
- Encryption, specifically Fernet symmetric encryption using PBKDF2HMAC, is crucial for securing passwords.
- The process involves creating a key from a master password and storing it securely with a randomly generated salt.
- Data, including website names, usernames, and encrypted passwords, should be stored in a SQLite database.
- Functions to encrypt, decrypt, save, and retrieve passwords are implemented in the program for secure password management.
- Best practices include not hardcoding passwords, always encrypting sensitive information, and adding security measures like locking after inactivity.
- Building a password manager offers a practical way to learn about encryption, secure storage, and security practices for both personal use and educational purposes.
- By following the outlined steps and best practices, you can create a secure and functional password manager in Python.
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Geeky-Gadgets
4w
183
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LangChain Sandbox Run Untrusted Python Safely for AI Agents
- LangChain Sandbox is an innovative solution designed to securely run untrusted Python code for AI agents, addressing the risks associated with executing unverified code.
- It creates a secure and isolated environment using technologies like Pyodide and Deno, ensuring safe execution of Python code while empowering developers to explore boundaries without compromising security.
- LangChain Sandbox provides detailed outputs, minimizes risks related to vulnerabilities or malicious code, and supports both stateless and stateful workflows, making it a reliable solution for secure code execution.
- The tool offers features such as dynamic dependency management, detailed monitoring capabilities, and support for React-style and CodeAct-style agents, making it versatile for a wide range of AI-driven tasks.
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Arxiv
4w
8
Image Credit: Arxiv
AllMetrics: A Unified Python Library for Standardized Metric Evaluation and Robust Data Validation in Machine Learning
- A new unified Python library called AllMetrics has been introduced to address the issue of fragmentation and inconsistent implementations in existing libraries for evaluating machine learning models.
- AllMetrics aims to standardize metric evaluation across various machine learning tasks like regression, classification, clustering, segmentation, and image-to-image translation.
- The library implements class-specific reporting for multi-class tasks and task-specific parameters to resolve metric computation discrepancies found in different implementations.
- AllMetrics combines a modular API with robust input validation mechanisms to ensure reproducibility and reliability in model evaluation, enhancing the trustworthiness of machine learning workflows.
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Dev
4w
402
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Behind the Underscores EP01: Understanding Python’s Special Methods Conceptually
- Special methods, also known as dunder methods, are key to how Python objects behave and interact.
- They start and end with double underscores, like __str__, __call__, __getitem__. They act as hooks into Python's syntax.
- Special methods allow your custom classes to print objects, compare instances, add objects, and more.
- They make code more Pythonic, intuitive, and seamless with Python's native syntax.
- Understanding special methods helps in writing elegant, readable code and building powerful abstractions.
- They define how objects behave in different situations such as len(obj), obj + other, str(obj), and more.
- Python automatically calls special methods when needed, enabling customization of object behavior.
- Overriding special methods allows precise definition of object behavior and fallback mechanisms.
- Misusing special methods can lead to confusing bugs, performance issues, and unreadable code.
- Understanding and using special methods responsibly enhances code clarity and maintainability.
- The next posts in the series will delve into specific categories of special methods for deeper understanding and application.
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Dev
4w
17
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Destructor in python
- A destructor (del) in Python is used to clean up resources when an object is about to be destroyed.
- Python's garbage collector automatically triggers the destructor when there are no more references to that object.
- The del() method can be useful for closing files, disconnecting from databases, or freeing up custom resources.
- Python's memory management system handles memory allocation, and you cannot force the garbage collector to run at an exact time.
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PlanetPython
1M
178
Image Credit: PlanetPython
EuroPython: AI Keynote Reveal, Python Documentary Premiere & Last Chance for Combined Tickets
- Tickets for EuroPython are still available, but combined and tutorial tickets are almost sold out.
- Keynote speaker, Nerea Luis, will discuss the impact of generative AI on developers, managers, and tech professionals.
- A documentary on the history of Python, featuring over 20 core developers, will premiere at EuroPython.
- Last chance to apply as an on-site volunteer for EuroPython from July 14–20 by June 1st.
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Dev
1M
416
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🐍 Part 2: 5 More Python Scripts That Will Save You Hours Every Week!!
- Automate daily journal entries by emailing yourself using Python with the script provided.
- Convert CSV files to JSON easily and quickly with a Python script for efficient data handling.
- Perform find and replace operations in multiple files simultaneously using a Python script for bulk updates.
- Download YouTube videos as MP3 audio files using a Python script for offline listening.
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