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Search Python API , found 316 results

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Benchling Lab Data Integration

benchling-integration

K-Dense-AI/scientific-agent-skills

Integrate Benchling registry entities, inventory, ELN entries, workflows, and Data Warehouse using the Python benchling-sdk (1.25.0) and v2 REST API. Automates lab data import, FASTA sequence creation, inventory audits, and event-driven Benchling Apps with API key or OAuth authentication.

Bioinformatics Service Python API

K-Dense-AI/scientific-agent-skills

Python client for bioinformatics services such as UniProt, KEGG, ChEMBL, Reactome, QuickGO and UniChem, enabling cross-database protein annotation, pathway retrieval, compound cross-referencing and integrated biological data workflows.

LabArchives API Integration

labarchive-integration

K-Dense-AI/scientific-agent-skills

Safely integrate with the official LabArchives ELN API and Inventory API v1: pick regional endpoints, build HMAC-SHA-512 signed requests, handle user authorization and UID flows, and validate local lab containers with bundled Python tools.

Modal Serverless Python Platform

K-Dense-AI/scientific-agent-skills

Modal is a serverless cloud platform for running Python code on demand, including GPU-accelerated AI/ML workloads. Use for deploying models, serving web APIs, batch processing, and scaling Python applications to cloud containers with automatic scaling from zero to thousands of instances. Supports custom container images, persistent storage, and sub-second cold starts for low-latency inference.

Opentrons Protocol Integration

opentrons-integration

K-Dense-AI/scientific-agent-skills

Author, review, simulate, and troubleshoot Opentrons Python Protocol API v2 protocols for Flex and OT-2 robots, covering deck and labware setup, pipettes, modules, runtime parameters, liquid handling, and safe deployment.

Python GPU Optimization

optimize-for-gpu

K-Dense-AI/scientific-agent-skills

Accelerate scientific Python code on NVIDIA hardware using CUDA and RAPIDS libraries. Optimizes NumPy, pandas, scikit-learn, and ML workloads for GPU execution. Includes profiling, memory management, and kernel optimization to ensure correctness and performance gains.

Polars DataFrame Analytics

K-Dense-AI/scientific-agent-skills

High-performance Python DataFrame library built on Apache Arrow. Covers expression-based API, lazy query optimization, streaming out-of-core processing, aggregations, window functions, joins, and pandas migration for ETL and analytics pipelines.

Protocols.io API Integration

protocolsio-integration

K-Dense-AI/scientific-agent-skills

Read, validate, and safely export protocols.io protocol data using official REST endpoints, or create non-executing mutation plans. The bundled Python client makes bounded authenticated GET requests only when --execute is supplied.

Pyzotero Reference Library Automation

K-Dense-AI/scientific-agent-skills

Manage Zotero reference libraries programmatically with the pyzotero Python client and Zotero Web API v3. Retrieve, create, update and delete items, collections, tags and attachments; search libraries and export BibTeX or CSL-JSON citations for research automation workflows.

Hugging Face Transformers Guide

K-Dense-AI/scientific-agent-skills

Load Hugging Face Hub models, run pipeline inference, generate text, and fine-tune with the Trainer API across NLP, vision, audio, and multimodal tasks using Python and PyTorch.

Advanced Anthropic API Debugging Guide

anth-advanced-troubleshooting

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive guide for developers encountering complex issues with the Claude API, including context window overflow management, debugging tool use failures, handling streaming corruption, and diagnosing unexpected stop reasons. Provides Python code snippets and diagnostic commands to ensure robust AI integration.

Anthropic Streaming and Message Batches

anth-core-workflow-b

jeremylongshore/claude-code-plugins-plus-skills

Master building robust AI workflows with Anthropic's core APIs. This guide details two powerful patterns: real-time streaming via SSE events for interactive chat UIs, and the cost-efficient Message Batches API for asynchronously processing up to 100,000 requests. Includes comprehensive code examples for Python and TypeScript.

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