isabl-query-data

Construct Python SDK queries to retrieve Isabl data with filters.

3|3|Updated Feb 3, 2026

Search Tags:#python #sdk #data #query #analyses #isabl

Ready to run

npx skills add https://github.com/juanesarango/isabl-mcp --skill isabl-query-data

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: isabl-query-data
Source: https://github.com/juanesarango/isabl-mcp/tree/main/skills/isabl-query-data
Command: npx skills add https://github.com/juanesarango/isabl-mcp --skill isabl-query-data

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps you construct queries to retrieve data from the Isabl platform using the Python SDK, enabling efficient access to experiments, analyses, samples, and related data.

Core Features & Use Cases

Guided query construction: Interactively determine entity types (experiments, analyses, samples, individuals) and applicable filters.
Filter-based retrieval: Build queries using project, status, dates, and relationship traversals to fetch precise results.
Output formatting: Return results in convenient formats (lists, dictionaries, or DataFrame) with identifiers suitable for downstream analysis.

Quick Start

Generate a Python SDK query to retrieve all experiments for a given project and return their system_id and sample identifier.

Frequently Asked Questions about isabl-query-data

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I query Isabl data using the Python SDK?▼

The Python SDK allows you to query Isabl data by specifying entity types like experiments or samples and applying filters such as status, dates, and project. You can traverse related objects and return results as lists, dictionaries, or DataFrames for downstream analysis.

Can I filter Isabl experiments by status and date ranges?▼

Yes, you can filter Isabl experiments by status and date ranges. The Skill guides you in applying these filters to experiments, analyses, and samples, enabling precise data retrieval and traversal of related objects across projects.

What is the best way to retrieve Isabl analysis results in a Python DataFrame?▼

The best way to retrieve Isabl analysis results in a DataFrame is to build a Python SDK query targeting the analysis entity type. The query supports output formatting into lists, dictionaries, or DataFrames containing identifiers for downstream analysis.

How do I traverse related objects when building Isabl data queries?▼

You traverse related objects in Isabl queries by using the Python SDK to build queries that connect entities like samples and experiments. This allows precise data retrieval across projects, applying filters and returning results in convenient formats.

Does the Isabl Python SDK support querying samples across multiple projects?▼

Yes, the Isabl Python SDK supports querying samples across multiple projects. You can build queries targeting the sample entity type and apply project-based filters to retrieve precise results and traverse related objects.

What formats are available for Isabl Python SDK query results?▼

Isabl Python SDK query results can be returned as lists, dictionaries, or DataFrames. These formats include identifiers suitable for downstream analysis, ensuring the retrieved experiments, analyses, and samples are ready for further use.