This document summarizes best practices for designing a REST API, including making the API easy to use, read, and extend. It provides real-world examples and discusses tools for documentation, validation, and JSON generation. Key recommendations include using nouns for resources, explicit versioning, token-based or OAuth authentication, and representing resources as complete URLs.
SQLAlchemy is a Python SQL toolkit and object relational mapper that allows developers to work with relational databases in Python. It provides a way to generate SQL expressions programmatically and functions as an object relational mapper, allowing Python classes to be mapped to database tables. SQLAlchemy aims to provide a full suite of tools for working with relational databases directly or via an object-relational abstraction layer.
Building data flows with Celery and SQLAlchemyRoger Barnes
Reporting and analysis systems rely on coherent and reliable data, often from disparate sources. To that end, a series of well established data warehousing practices have emerged to extract data and produce a consistent data store.
This talk will look at some options for composing workflows using Python. In particular, we'll explore beyond Celery's asynchronous task processing functionality into its workflow (aka Canvas) system and how it can be used in conjunction with SQLAlchemy's architecture to provide the building blocks for data stream processing.
This document discusses various methods for communication between processes in Python, including client-server architectures, message queues, serialization, multiprocessing pipes, forking, and memory-mapped files. It provides code examples and performance results for different serialization formats like JSON, msgpack, and pickle. Memory usage is also compared for multiprocessing pipes, forking, and memory mapping for inter-process communication.
