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所在平台: Udemy |
课程主页: https://www.udemy.com/course/pyuvm-series-part-3-python-oops-fundamentals/
课程评论：没有评论
**课程名称：** PyUVM 系列第三部分：Python 面向对象编程基础 **课程概述：** 本课程专为软件工程师、开发人员和验证工程师设计，旨在教授高级 Python 编程技能，重点关注面向对象编程 (OOP) 在硬件验证中的应用。学员将深入学习 Python 的基本概念，并探索类、继承、复制机制、随机化、使用队列进行进程间通信以及使用事件进行任务同步等高级主题。课程还将提供实践经验，指导学员构建包括生成器、驱动器、监视器和记分板在内的验证环境，以实现对被测设计 (DUT) 的可靠验证。 **主要课程内容：** * **Python 面向对象编程 (OOP)：** * 理解类和对象 * 封装、继承和多态 * 方法重写和运算符重载 * **复制机制：** * Python 中的浅复制和深复制 * 高效复制的最佳实践 * 复制复杂数据结构 * **随机化技术：** * 使用 'random' 模块生成伪随机数 * 为不同测试场景随机化数据 * 种子管理用于可复现性 * **进程间通信 (IPC)：** * Python 多进程简介 * 通过队列进行通信 * 进程间的同步和数据交换 * **任务同步：** * 事件驱动同步的实现 * 使用事件协调任务 * 避免竞态条件和死锁 * **验证环境构建：** * 为被测设计 (DUT) 设计验证环境 * 开发生成器以创建激励 * 构建鲁棒的驱动器与 DUT 交互 * 使用监视器监控和分析 DUT 行为 * 记分板技术用于结果验证 **实践项目：** 学员将在课程中参与实践练习和项目，将所学概念应用于实际场景。这将包括创建一个完整的验证环境，用于测试样本 DUT，并整合 OOP 原理、复制机制、随机化和进程间通信。 **学习目标：** 完成本课程后，学员将掌握高级 Python 技能，能够设计和实现高效、可扩展的硬件设计验证环境，并遵循 OOP 和软件开发的最佳实践。本课程特别适合在硬件验证领域工作、希望提升 Python 熟练度以构建基于类别的 Python 验证环境的专业人士。
This comprehensive course is designed to empower software engineers, developers, and verification engineers with advanced Python programming skills for effective Object-Oriented Programming (OOP) and hardware verification tasks. Participants will delve into the fundamentals of Python and explore advanced concepts, including classes, inheritance, copy mechanisms, randomization, inter-process communication with queues, and task synchronization with events. The course will also provide hands-on experience in building a verification environment, encompassing generators, drivers, monitors, and scoreboards for robust Design Under Test (DUT) verification.Key Topics Covered:Object-Oriented Programming (OOP) in Python:Understanding classes and objectsEncapsulation, inheritance, and polymorphismMethod overriding and operator overloadingCopy Mechanisms:Shallow and deep copy in PythonBest practices for efficient copyingCopying complex data structuresRandomization Techniques:Utilizing the 'random' module for pseudo-random number generationRandomizing data for diverse test scenariosSeed management for reproducibilityInter-Process Communication:Introduction to Python multiprocessingCommunication using queuesSynchronization and data exchange between processesTask Synchronization:Implementation of event-driven synchronizationCoordinating tasks with eventsAvoiding race conditions and deadlocksVerification Environment:Designing a verification environment for a Design Under Test (DUT)Developing generators for stimulus creationBuilding robust drivers for interfacing with the DUTMonitoring and analyzing DUT behavior with monitorsScoreboarding techniques for result verificationHands-On Projects:Participants will engage in practical exercises and projects throughout the course, applying the learned concepts to real-world scenarios. This will include creating a complete verification environment for a sample DUT, incorporating OOP principles, copy mechanisms, randomization, and inter-process communication.By the end of this course, participants will possess advanced Python skills, enabling them to design and implement efficient and scalable verification environments for hardware designs, while incorporating best practices in OOP and software development. This course is ideal for professionals working in fields such as hardware verification who want to enhance their Python proficiency for building Class based Verification environment in Python.
