Skill UI

This skill provides comprehensive guidance on implementing high-performance, non-blocking applications in Python. It utilizes asyncio, async/await, and advanced concurrency patterns to handle I/O-bound workloads efficiently. Ideal for building async web APIs, real-time systems, and concurrent data processing.

This SDK provides a comprehensive client library for Azure AI Document Translation service. It enables large-scale, batch translation of various document formats, including Word, PDF, Excel, and PowerPoint, while accurately preserving the original document structure and formatting. It supports features like glossary integration and async operations, making it ideal for enterprise content localization pipelines.

This SDK provides a comprehensive client library for Azure AI Document Translation service. It enables large-scale, batch translation of various document formats, including Word, PDF, Excel, and PowerPoint, while accurately preserving the original document structure and formatting. It supports features like glossary integration and async operations, making it ideal for enterprise content localization pipelines.

A comprehensive guide and client library for interacting with Azure Cosmos DB, a globally distributed, multi-model NoSQL database, using Python. It provides full support for performing document CRUD operations, executing complex partitioned and cross-partition queries, managing containers, and handling advanced concepts like throughput and asynchronous operations.

A comprehensive Python SDK for interacting with Azure Table Storage and Cosmos DB Table API. This library enables developers to perform full NoSQL key-value operations, including creating, reading, updating, and deleting (CRUD) entities, executing complex queries using filtering, and managing batch transactions. It supports both synchronous and asynchronous operations, making it ideal for building resilient, high-throughput cloud applications.

This SDK provides a dedicated Python interface for securely sending custom logs to Azure Monitor Log Analytics workspace. It utilizes the Logs Ingestion API, supporting features like batch compression, advanced error handling, asynchronous uploads, and compatibility with various authentication models, including sovereign clouds.

This SDK provides a comprehensive Python interface for interacting with Azure Blob Storage, Microsoft's scalable object storage service. It enables users to perform core object storage operations, including uploading, downloading, listing, deleting blobs, managing containers, and setting custom metadata. The library supports both synchronous and asynchronous workflows, making it ideal for building robust data pipelines, data lakes, or cloud-native applications that require reliable, scalable file storage.

A comprehensive Python SDK for interacting with Azure Queue Storage. This tool enables reliable, asynchronous communication patterns by managing message queuing, task distribution, and data processing workflows. It supports core operations including sending, receiving, peeking, updating, and deleting messages, making it ideal for building resilient, decoupled backend systems on Azure.

A comprehensive expert resource for building high-performance, async-first APIs using FastAPI, SQLAlchemy 2.0, and Pydantic V2. Covers advanced topics like microservices architecture, WebSockets, advanced security (OAuth2, RBAC), robust testing strategies (pytest), performance optimization, and modern DevOps practices (Docker, Kubernetes). Ideal for mastering scalable, production-ready Python web services.

This template provides production-ready FastAPI project skeletons, incorporating advanced features such as async patterns, dependency injection, middleware, and robust error handling. It is essential for developers starting new high-performance REST APIs, microservices, or complex backend systems in Python, ensuring adherence to best architectural practices.

This skill provides a comprehensive guide and multiple code examples (cURL, Node.js, Python) for generating presentations using the Gamma API. It implements the standard asynchronous 'Generate-Poll-Retrieve' pattern: first POST to create the generation job, then GET to poll the status until complete, and finally retrieve the viewable and exportable URLs (PDF/PPTX).

This tool provides comprehensive Python solutions for processing batches of text-to-video requests using the Kling AI API. It handles controlled parallelism, rate-limiting, and detailed status tracking. Use this when building robust content pipelines that require generating multiple videos efficiently from a list of prompts, supporting synchronous, asynchronous, and webhook callback methods.