REPLICA is a toolkit for replication and reproduction in computational psycholinguistics. It combines dataset loading, feature extraction and cross-validated model comparison through configurable interfaces.
Website · Datasets · Tutorials · Architecture · Contributing
Install
Use Python 3.11 or newer:
python -m pip install replicaverse
The Python import and command are named replica. The base package supports
tabular analysis and precomputed predictors. The getting-started example uses
replicaverse[models,r] and requires R with lme4 for the default mixed-effects
backend. See the environment guide for setup,
optional dependencies and source installation.
Tutorials
Start with Getting started to load a dataset, evaluate a language-model predictor and interpret the results.
| Notebook | Topics |
|---|---|
| Benchmarking | Compare datasets and models |
| Loading datasets | Catalog, variants and loader options |
| Segmentation | Character, word and sentence units |
| Surprisal methods | Compare predictor calculations |
| Adding a study | Integrate and validate a study recipe |
Dataset walkthroughs: eye-tracking, self-paced reading, EEG and fMRI.
Datasets and storage
Explore available datasets with replica datasets or the
catalog. Download a supported source with
replica fetch DATASET; some sources require manual acquisition or licensed
materials, as described in their catalog entries.
Data and caches use automatic defaults; no path settings are required. The environment guide explains how to change their locations. The predictor-store guide covers precomputed predictors.
Contributing
The architecture guide describes the package and its extension points. Follow the contributor guide and test guide to develop and validate changes, then open a PR.
Related projects: ModelBlocks, pymovements and EyeBench.
Metadata
Release files for replicaverse 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| replicaverse-0.0.1.tar.gz | 1.1 MB | With provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| replicaverse-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.4 MB
Release files / replicaverse-0.0.1.tar.gz
| Download URL | replicaverse-0.0.1.tar.gz |
|---|---|
| Size | 1.1 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / replicaverse-0.0.1-py3-none-any.whl
| Download URL | replicaverse-0.0.1-py3-none-any.whl |
|---|---|
| Size | 1.3 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 24, 2026.
Transparency logSecurity for replicaverse 0.0.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
Full provenance
All 2 files in this release have been uploaded with provenance metadata.
Attestation for replicaverse-0.0.1.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 24, 2026.
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