{"id":51139826,"url":"https://github.com/dots-suite/thunderdots","last_synced_at":"2026-06-25T22:00:25.575Z","repository":{"id":364337598,"uuid":"1161905700","full_name":"dots-suite/ThunderDots","owner":"dots-suite","description":"ThunderDoTS: a DTS Crawler via DoTS","archived":false,"fork":false,"pushed_at":"2026-06-12T16:09:52.000Z","size":4226,"stargazers_count":0,"open_issues_count":1,"forks_count":0,"subscribers_count":0,"default_branch":"master","last_synced_at":"2026-06-18T16:31:44.106Z","etag":null,"topics":["api","corpora","crawler","digital-humanities","distributed-text-services","dots","dts","humanities"],"latest_commit_sha":null,"homepage":"https://dots-suite.github.io/ThunderDots/","language":"Jupyter 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ch1 align=\"center\"\u003e\n  \u003cimg src=\"assets/dots-light.png\" width=\"450\"\u003e\u003cbr\u003e\n  ThunderDots — DTS client for documentary corpora\n\u003c/h1\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cstrong\u003eDTS scrapping, TEI fragmentation, metadata filtering, validation, and export pipelines.\u003c/strong\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://github.com/astral-sh/uv\"\u003e\n    \u003cimg src=\"https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json\" alt=\"uv\"\u003e\n  \u003c/a\u003e\n  \u003ca href=\"https://github.com/astral-sh/ruff\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/lint-ruff-0A0A0A?logo=ruff\u0026logoColor=white\" alt=\"ruff\"\u003e\n  \u003c/a\u003e\n  \u003ca href=\"https://github.com/chartes/thunderdots/actions/workflows/ci.yml\"\u003e\n    \u003cimg src=\"https://github.com/chartes/thunderdots/actions/workflows/ci.yml/badge.svg\" alt=\"CI\"\u003e\n  \u003c/a\u003e\n  \u003ca href=\"https://github.com/chartes/thunderdots/blob/master/LICENSE.md\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/License-MIT-blue.svg\" alt=\"License: MIT\"\u003e\n  \u003c/a\u003e\n\u003ca href=\"https://pypi.org/project/thunderdots/\"\u003e\n  \u003cimg src=\"https://img.shields.io/pypi/v/thunderdots.svg\" alt=\"PyPI version\"\u003e\n\u003c/a\u003e\n\u003c/p\u003e\n\n---\n\n## Overview\n\n**ThunderDots** is a Python client for [DTS](https://dtsapi.org/specifications/) (*Distributed Text Services*) endpoints, initially built for [DoTS](https://dots-suite.github.io/dots_documentation/).\n\nIt 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.\n\nThunderDots 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.\n\n---\n\n## What ThunderDots does\n\nThunderDots can:\n\n- walk DTS collections and subcollections;\n- fetch resources and TEI/XML documents;\n- extract text fragments from full documents, DTS navigation, or custom TEI XPath rules;\n- preserve or filter Dublin Core and extension metadata;\n- enrich temporal metadata such as dates and coverage ranges;\n- validate generated outputs with JSON Schema;\n- transform DTS resources into Pandas/Polars DataFrames;\n- export records to indexing pipelines such as Elasticsearch or Qdrant-compatible formats;\n- cache fetched corpora as JSON and CSV;\n- run synchronous or asynchronous workflows.\n\n---\n\n## Installation\n\n### With `uv`\n\n```bash\nuv add thunderdots\n```\n\n### With pip\n\n```bash\npip install thunderdots\n```\n\n### For development\n\n```bash\ngit clone https://github.com/chartes/thunderdots.git\ncd thunderdots\n\nuv venv\nsource .venv/bin/activate\nuv sync --all-extras --dev\n```\n\nor with pip\n\n```bash\npython -m venv .venv\nsource .venv/bin/activate\npip install -e \".[dev]\"\n```\n\n## Minimal example\n\n```python\nfrom thunderdots import ThunderDots\n\ntd = ThunderDots(\n    endpoint_dts=\"https://dots.chartes.psl.eu/api/dts\",\n    collection_params={\"collection_id\": \"ENCPOS_1900\"},\n    resource_params={\"fragment_mode\": \"document\"},\n)\n\ntd.fetch()\nresults = td.results()\n\nprint(td.stats())\n```\n\n## Development\n\n### Run tests\n\n```bash\npytest\n```\n\nOnline DTS tests are opt-in:\n\n```bash\nRUN_NETWORK_TESTS=1 pytest\n```\n\n### Run Ruff (linter, format)\n\n```bash\nruff format --check\nruff check\n```\n\n### Build the documentation\n\n```bash\nmkdocs build --strict -f mkdocs/mkdocs.yml\n```\n\n### Create a new PyPI release\n\nCheck the [release checklist](./RELEASE.md) for details.\n\n### License\n\nThunderDots is distributed under the [MIT License](./LICENSE.md).\n\n### Citation\n\nIf you use ThunderDots in academic work, please cite it as:\n\n```\n@software{terriel_thunderdots_2026,\n  author       = {Terriel, Lucas},\n  title        = {ThunderDots},\n  year         = {2026},\n  publisher    = {GitHub},\n  institution  = {{École nationale des chartes}},\n  url          = {https://github.com/chartes/thunderdots},\n  note         = {Python client for Distributed Text Services (DTS) via DoTS}\n}\n```\n\nYou can also use the repository metadata from [CITATION.cff](./CITATION.cff).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdots-suite%2Fthunderdots","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdots-suite%2Fthunderdots","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdots-suite%2Fthunderdots/lists"}