Python Multithreading and Multiprocessing Explained | Real-Time Examples + AWS ETL Projects

Master Python multithreading and multiprocessing with in-depth explanations and real-time examples. Learn how to enhance performance in Python applications, including AWS ETL projects.
📌 Projects Covered:

AWS ETL Data Pipeline Project: Build an end-to-end ETL pipeline with data extraction from S3, transformation using AWS Glue, and loading to Redshift. (Python, AWS Glue, S3, Redshift, Lambda, CloudFormation)
AWS ETL APIs Integration Project: Develop APIs to trigger ETL workflows, manage data flows, and ensure seamless integration using API Gateway. (Python, AWS Lambda, API Gateway, S3, DynamoDB)
AWS ORM-Based ETL Project: Leverage ORM tools to handle database operations in ETL processes, ensuring data integrity and efficient transactions. (Python, SQLAlchemy, AWS RDS, Lambda, S3)

Python Multithreading, Python Multiprocessing, Python Concurrency, Python Parallel Processing, Python Performance Optimization, Python AWS Projects, AWS ETL Pipeline, Python AWS Lambda, AWS Glue, AWS API Gateway, AWS Data Engineering, Python ORM, Python React Integration, Python AWS S3

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