Skip to content

radiens-drive-catalog

A Python package for programmatically managing large neural datasets stored on Google Drive. It handles Drive scanning, local cataloging, and selective dataset download — analysis itself is done locally.

Neural data is stored as xdat filesets (NeuroNexus format) on a shared Google Drive. Each dataset consists of three files sharing a common base_name:

{base_name}_data.xdat
{base_name}.xdat.json
{base_name}_timestamp.xdat

The package scans the Drive hierarchy, builds a local catalog indexed by base_name, and lets you query and download datasets selectively. Non-xdat content found alongside datasets — logs directories, PowerPoints, writeups — is also discovered and tracked as Drive items.

Quick Start

from radiens_drive_catalog import Catalog, Config

config = Config.from_file("config.json")
catalog = Catalog(config)

catalog.scan()                                                                          # scan Drive — finds recordings and items
df = catalog.list_recordings(drive_path="2026-02-15_batch", drive_path_mode="prefix")   # query recordings by date folder
path = catalog.get_recording_path("2026-02-15_batch/reaching", "rat01_session3")        # download if not already local

# Drive items (non-xdat files and folders)
catalog.list_items(drive_path="reaching", drive_path_mode="contains")                   # query items
path = catalog.get_item_path("2026-02-15_batch/reaching", "logs")                       # download if needed

What's in this site

  • Configuration — Config file format, path expansion, service account setup
  • Usage Guide — Scanning, querying, downloading, and working with the DataFrame
  • API Reference — Full auto-generated API docs (see nav above)
  • Changelog — Version history