Results for “portals”

Pulls pathway, book, course, article, and content item records from a Supabase database for the alan-hirsch tenant, organizes them by portal, and exports the results as markdown files into a local docs repository.

Write, review, debug, test, and optimize Python Polars code with version-grounded object types, schemas, and execution boundaries.

High-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.

Scans local repositories and a Supabase database to inventory all pathway, portal, and theme content, producing a categorized report organized by portal.

Process data with high-performance DataFrames using Polars' expression-based API, lazy evaluation, and parallel execution for ETL, analytics, and pandas migration.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Search the web, extract URL content, enrich datasets with web-sourced fields, and run deep research reports, prioritizing academic and scientific sources.

Automate browser tasks, scrape websites, fill forms, capture screenshots, and extract structured data from web pages using Playwright.

Authenticate, browse pipelines, samples, and projects, upload data, launch pipeline executions, and check run status on any Flow.bio instance via CLI.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Perform fast genomic interval operations (overlap, nearest, merge, coverage, cluster, complement, subtract, count-overlaps), multi-format bioinformatics I/O, DataFusion SQL, and pileup on Polars DataFrames via the polars-bio library, serving as a scalable alternative to bioframe and bedtools.

Biblioteca DataFrame rápida (Apache Arrow). Selecione, filtre, group_by, joins, avaliação preguiçosa, I/O CSV/Parquet, expression API, para fluxos de trabalho de análise de dados de alto desempenho.