Skip to main content


ThunderDots — DTS client for documentary corpora

DTS scrapping, TEI fragmentation, metadata filtering, validation, and export pipelines.

uv ruff CI License: MIT PyPI version


Overview

ThunderDots is a Python client for DTS (Distributed Text Services) endpoints, initially built for DoTS.

It helps you move from a remote DTS API to structured Python objects and JSON records that can feed indexing pipelines, including full-text search, RAG/vector databases, and corpus-analysis workflows.

ThunderDots focuses on practical documentary workflows: crawling DTS collections, fetching TEI/XML resources, extracting reusable text fragments, selecting metadata, validating outputs, and exporting data to downstream search or indexing systems.


What ThunderDots does

ThunderDots can:

  • walk DTS collections and subcollections;
  • fetch resources and TEI/XML documents;
  • extract text fragments from full documents, DTS navigation, or custom TEI XPath rules;
  • preserve or filter Dublin Core and extension metadata;
  • enrich temporal metadata such as dates and coverage ranges;
  • validate generated outputs with JSON Schema;
  • transform DTS resources into Pandas/Polars DataFrames;
  • export records to indexing pipelines such as Elasticsearch or Qdrant-compatible formats;
  • cache fetched corpora as JSON and CSV;
  • run synchronous or asynchronous workflows.

Installation

With uv

uv add thunderdots

With pip

pip install thunderdots

Notebook (Jupyter) support

notebook is not installed by default. Since Jupyter is only needed to run the documentation notebooks, it is shipped as an optional extra. Install it with:

# uv
uv add thunderdots[docs]

# pip
pip install thunderdots[docs]

For development

git clone https://github.com/chartes/thunderdots.git
cd thunderdots

uv venv
source .venv/bin/activate
uv sync --all-extras --dev

or with pip

python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"

Minimal example

from thunderdots import ThunderDots

td = ThunderDots(
    endpoint_dts="https://dots.chartes.psl.eu/api/dts",
    collection_params={"collection_id": "ENCPOS_1900"},
    resource_params={"fragment_mode": "document"},
)

td.fetch()
results = td.results()

print(td.stats())

Development

Run tests

pytest

Online DTS tests are opt-in:

RUN_NETWORK_TESTS=1 pytest

Run Ruff (linter, format)

ruff format --check
ruff check

Build the documentation

mkdocs build --strict -f mkdocs/mkdocs.yml

Create a new PyPI release

Check the release checklist for details.

License

ThunderDots is distributed under the MIT License.

Citation

If you use ThunderDots in academic work, please cite it as:

@software{terriel_thunderdots_2026,
  author       = {Terriel, Lucas},
  title        = {ThunderDots},
  year         = {2026},
  publisher    = {GitHub},
  institution  = {{École nationale des chartes}},
  url          = {https://github.com/dots-suite/thunderdots},
  note         = {Python client for Distributed Text Services (DTS) via DoTS}
}

You can also use the repository metadata from CITATION.cff.

Metadata

Release files for thunderdots 0.1.8

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for thunderdots 0.1.8
File Size Uploaded
thunderdots-0.1.8.tar.gz 1.3 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for thunderdots 0.1.8
File Interpreter ABI Platform
thunderdots-0.1.8-py3-none-any.whl Python 3 none any Details

Total release size: 1.4 MB

Release files / thunderdots-0.1.8.tar.gz

Download URL thunderdots-0.1.8.tar.gz
Size 1.3 MB
Tags Source
SHA-256 checksum
How to use checksums
c98c0b4007568c71ab81c7ad7787be853e76232edb62732640b3734ab5b24156
BLAKE2b-256 checksum
How to use checksums
6e00970355963d46d49848eb6d371127e3a094845b8a84542934150129576f9f
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 Sep 24, 2026.

Transparency log

Release files / thunderdots-0.1.8-py3-none-any.whl

Download URL thunderdots-0.1.8-py3-none-any.whl
Size 55.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
3faaec10b51eb7d1448a0b7bcdacd988170e7856976b3c25338f62ad4ae7bd9d
BLAKE2b-256 checksum
How to use checksums
f78d17df025663a4bdbd00f614594b3ba5cd4862b8a8c1bd16c38d9f77749054
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 Sep 24, 2026.

Transparency log

Release history Release notifications | RSS feed

This release

0.1.8 This release

2 release files

0.1.7

2 release files

0.1.6

2 release files

0.1.5

2 release files

0.1.4

2 release files

0.1.3

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page