Pyuvm Series Part 3 Python Oops Fundamentals

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Pyuvm Series Part 3 : Python Oops Fundamentals
Published 1/2025
Created by Kumar Khandagle
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 74 Lectures ( 3h 13m ) | Size: 1.1 GB​

Step by Step Guide from Scratch
What you'll learn
Fundamentals of Classes
Class Methods
Inter-process communication
Randomization
Building verification environment in Python
Requirements
Fundamentals of Digital Electronics and Verilog
Completion of Python for VLSI Engineer P1, and P2 Course or Basics of Python & COCOTB
Description
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 Environmentesigning 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 Projectsarticipants 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.
Who this course is for
If you're excited about Python and DUT verification with Python, this is the place for you.
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