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nemar-py

Python + CLI client for downloading public NEMAR datasets (BIDS / EEG / MEG / iEEG) from data.nemar.org.

Install

pip install nemar-py            # S3 + HTTPS backends
pip install nemar-py[datalad]   # + the optional DataLad layer

The default install uses the direct-S3 and HTTPS backends. The optional [datalad] extra adds the DataLad layer; it bundles the git-annex binary via the psychoinformatics-de PyPI wheel (Linux, macOS, Windows), so no system package step is needed. Without the extra, --downloader datalad and the auto chain's DataLad layer fall through to S3 / HTTPS automatically.

Quick start

nemar-py download nm000132 -o data/nm000132
import nemar
nemar.download(dataset="nm000132", target_dir="data/nm000132")

CLI

Command Purpose
nemar-py download <DATASET> Download a dataset
nemar-py versions <DATASET> List versions advertised by NEMAR

Common flags

Flag Effect
-o, --output DIR Target directory (default ./<DATASET>)
-j, --jobs N Parallel downloads (default 16)
--tag TAG Pin a version; default latest
--downloader BACKEND auto (default) | s3 | python | datalad
--no-data Sidecars only — skip annexed binaries
--stimuli Add stimuli/ scope
--derivatives Add derivatives/ scope
--sourcedata Add sourcedata/ scope — the original pre-BIDS distribution
--metadata-timeout S Override 30 s metadata timeout
--verbose Echo resolved parameters before transfer

BIDS filters (repeatable)

Flag Accepts
--subject, --session, --task, --run, --acq 001 or sub-001
--datatype, --suffix, --extension eeg, T1w, .set, …
--scope raw, derivatives, stimuli, …
--pipeline Subfolder under derivatives/
--entity key=value Generic BIDS entity
--include PATTERN, --exclude PATTERN Path globs

Labels accept either bare (001) or BIDS-prefixed (sub-001) form.

Examples

# One subject, one task, EEG .set + sidecars
nemar-py download nm000132 \
  --subject 001 --task MMN --datatype eeg --suffix eeg --extension .set

# Derivatives from one pipeline
nemar-py download nm000132 --derivatives --pipeline eeglab --subject 001

# Metadata sweep — sidecars only, no big binaries
nemar-py download nm000132 --no-data -o nm000132-metadata

# The original pre-BIDS distribution, exactly as the authors published it
nemar-py download nm000341 --scope sourcedata -o nm000341-original

sourcedata/ — the original upstream distribution

Many NEMAR deposits carry a sourcedata/ tree holding the original, pre-BIDS files as distributed by the dataset authors, alongside a sourcedata_provenance.json recording each file's upstream name, size and SHA-256. That makes NEMAR usable as a mirror of the original source when the upstream host is slow, gated, or gone.

sourcedata is not fetched by default — --scope sourcedata gets only that tree, while --sourcedata adds it alongside the default raw scope.

import nemar
nemar.download(
    dataset="nm000132",
    subject=["001", "002"],
    task="MMN", datatype="eeg", suffix="eeg", extension=".set",
)

Behaviour

  • Catalog (index, version, manifest) is fetched from https://data.nemar.org/{dataset}/. No auth.
  • File bytes use a layered chain: S3 → (DataLad) → HTTPS.
    • S3 is tried first — anonymous public-read against nemar.s3.us-east-2.amazonaws.com, content-addressed at <dataset>/objects/<git-annex-key> (eegdash-style direct fetch).
    • DataLad is an optional middle layer, active only when the [datalad] extra is installed and the dataset index advertises a datalad_url. Absent the extra, this layer is skipped (a missing import is caught and falls through).
    • HTTPS through data.nemar.org is the always-available fallback, with Range/206 resume.
  • BIDS root files (dataset_description.json, participants.tsv/json, README*, CHANGES, LICENSE) are always kept — even with --include / --exclude.

Release files for nemar-py 0.3.0

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