Skill UI

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.

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.

This comprehensive guide demonstrates how to scrape live webpages using Bright Data's Web Unlocker proxy. It details how to bypass advanced anti-scraping mechanisms, such as CAPTCHAs and fingerprinting, automatically. Users are provided with full code examples in both Node.js and Python, showing methods for scraping via the proxy endpoint and through the dedicated REST API. Ideal for starting new scraping projects or integrating Bright Data into existing workflows.

This guide provides production-ready patterns for integrating with Bright Data proxy services. It covers critical aspects like setting up a proxy client, implementing robust retry logic for transient errors (e.g., 502, 503), managing sticky sessions for consistent IPs, and parsing complex HTML responses. Essential for building reliable, high-scale web scrapers using TypeScript and Python.

This skill manages the complexities of Clari API version changes, ensuring smooth transitions (e.g., v3 to v4). It guides developers through detecting schema drift, performing data field compatibility checks, and executing necessary database migrations (SQL/Python), ensuring reliable data pipelines after platform updates.

This skill guides users on automating fundraising workflow analysis using local data methods. Since Finta lacks a public API, it teaches how to export pipeline data (CSV) and use Python (Pandas) scripts to calculate key funnel metrics, conversion rates, and generate detailed weekly reports for investor tracking and reporting.

A structured guide for setting up a robust local development environment for Palantir Foundry data pipelines. This workflow enables users to run Python transforms and unit tests using PySpark against sample data, and mock the Foundry API client, ensuring fast, isolated iteration cycles before deploying code to the official Foundry environment. Ideal for data engineers and developers building complex ETL logic.

Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. It enables pKa prediction, molecular docking, conformer search, and protein-ligand cofolding without local HPC infrastructure. Ideal for batch screening and multi-step chemistry pipelines in drug discovery.

This guide provides a comprehensive workflow for searching and retrieving biomedical literature from PubMed and NCBI. It covers advanced query construction using MeSH terms and specific field tags, advanced filtering (date, publication type), and a repeatable programmatic workflow using NCBI E-utilities (esearch, efetch). Essential for researchers conducting systematic reviews and literature monitoring.

Execute arbitrary PySpark or pure Python code directly on Fabric Spark compute using the Livy API. This method creates ephemeral sessions without generating persistent notebook artifacts. It provides full read/write access to lakehouse Delta tables, making it ideal for agent-driven ETL pipelines, quick data transformations, or analyses where session cleanup is critical. Users must manage the session lifecycle (create, run, and delete).

This guide provides a comprehensive workflow for searching and retrieving biomedical literature from PubMed and NCBI. It covers advanced query construction using MeSH terms and specific field tags, advanced filtering (date, publication type), and a repeatable programmatic workflow using NCBI E-utilities (esearch, efetch). Essential for researchers conducting systematic reviews and literature monitoring.

gget is a versatile CLI and Python package designed for rapid, reproducible bioinformatics searches across major genomic reference databases (e.g., Ensembl, UniProt). It allows users to quickly query gene metadata, perform initial BLAST/BLAT style alignments, and explore associated pathways, cancer, or disease modules. It is ideal for initial data exploration and generating reproducible evidence logs before building complex, full-scale local pipelines.