Technical Blog
Deep dives into data engineering, cloud architecture, AI/ML, and the technologies that power modern data platforms.
Production-ready async Python pattern for extracting millions of API records with automatic pagination, retry logic with exponential backoff, and seamless BigQuery integration using aiohttp and uvloop for maximum throughput.
Scala, Python, and Java are all popular programming languages, each with its own strengths and weaknesses. The choice between them depends on factors such as project requirements, ecosystem, performance needs, and personal preference.
Mkdocs for quick static website generator
PoC for sending alerts and notifications to slack channel using python
Proof of Concept to demo the encryption and decryption of AWS S3 files using AWS KMS
The email template gives us an idea about the error before moving to the cloud watch logs and reduces our time in searching error log stream.
Learn Python context managers for bulletproof resource handling in data pipelines. Master the with statement, __enter__/__exit__ protocols, contextlib decorators, and patterns for database connections, file I/O, and subprocess management.
Deep dive into Python coroutines for building efficient data processing pipelines. Learn generator-based coroutines, the send method, coroutine decorators, and patterns for streaming data transformations.
Master Python decorators for building reusable, maintainable data pipelines. Learn closures, higher-order functions, functools.wraps, and practical patterns for input validation and logging in production code.
Deep dive into Python descriptors for creating managed attributes and data models. Learn __get__, __set__, __delete__ protocols, property decorators, and patterns for validation, type checking, and read-only attributes in production code.
Master Python Abstract Base Classes (ABC) for building robust data engineering frameworks. Learn class methods, static methods, abstract method decorators, and inheritance patterns for scalable pipeline architectures.
