NIND — "nouvelle indexation"

nind is a flat-file inverted-index module: a simple, dependency-light indexing and search engine built around plain binary files instead of a database or a heavyweight library like Lucene. It ships as:

a production C++ library (src/cpp/), and
a Python package, nind (src/py/nind/) — an ergonomic frontend to the same binary formats (backed by a compiled nind._native extension, pybind11 bindings over the C++ stack), plus a modern BM25-style search API layered on top.

📖 Full documentation: https://aymara.github.io/nind/

Why nind?

In 2014, Atejcon designed and built nind to meet the indexing needs of an application such as ANT'inno's ANT'box, aiming for something simpler and faster than the alternatives available at the time.

CEA LIST/DIASI/LVIC later adapted nind for its Amose search engine, replacing the deprecated S2 and Lucene indexers. nind was extended to match Amose's richer functional needs — in particular its more elaborate term-type model and the various corpus-level measures its relevance calculations require.

nind indexes and searches using nothing but flat files: no database, no server process. Because those files are also usable directly, the indexed corpus can be inspected and analyzed offline, with tools as simple as the command line — see Command-line tools below.

To keep the binary file formats unambiguous and toolable, nind specifies them in an EBNF (Extended Backus-Naur Form) grammar; class comments throughout the source quote the relevant grammar rules directly above each class. That the format is written down formally is also what makes an ergonomic, non-C++ way of reading and writing the same files possible in the first place — which is exactly what the Python package above is.

Installation

pip install nind

This installs the nind Python package together with its compiled nind._native extension (prebuilt wheels are published for Linux, macOS and Windows). Building from source (e.g. an sdist install, or an unsupported platform) requires a C++14 compiler; pip/uv pull in the rest of the build toolchain (scikit-build-core, pybind11, cmake, ninja) automatically — no manual setup needed.

Requires Python ≥ 3.8.

Quickstart

Index a handful of files and run a BM25-ranked search over them:

from nind.nind_engine import NindIndexer, NindEngine

indexer = NindIndexer(index_dir="indices", prefix="corpus")
indexer.index_files([
    "src/py/nind/NindFile.py",
    "src/py/nind/NindPadFile.py",
    "src/py/nind/nind_engine.py",
])

engine = NindEngine("indices")
for doc_id, score in engine.search("ejcrit nombre", top_k=5):
    print(f"{doc_id}: {score:.3f}")

index_dir must already exist; each input file becomes one document, identified externally by its position in the list (0, 1, 2, ...). NindEngine also exposes the building blocks it uses internally (get_term_id, get_df, get_tf, get_doc_len) for inspecting relevance or a specific document directly.

See the Quickstart guide for more, including how to open index files produced by the C++ implementation directly.

Command-line tools

Every low-level reader module doubles as a runnable diagnostic script (analyse/dump/debug its own file format), and three higher-level scripts operate on a whole indexed corpus:

cd src/py/nind
uv run python3 Nind_search.py <fichier lexiconindex> <terme cherché>
uv run python3 Nind_dumpDocument.py <fichier nind> <n° doc>
uv run python3 Nind_trouveMotsSansOccurrence.py <fichier>

See the command-line tools guide for the full list and usage of each.

How it works

nind's binary files are a small fixed header, one or more fixed-size indirection blocks mapping an integer identifier to an (offset, length) pair, the variable-length data those indirections point to, and a trailer holding format-specific data plus an identification stamp. Every concrete format (the lexicon, the inverted term index, the per-document local index, the reverse lexicon) builds on that same envelope, adding only the meaning of its own records — see the architecture guide for the full module layering, on both the C++ and Python sides.

Development

C++: NIND_DIST=/path/to/dist ./gbuild.sh (wraps CMake + ctest; see ./gbuild.sh -h for build-mode/sanitizer/generator options).
Python: uv sync (builds nind._native and installs the package editable, plus dev dependencies), then uv run pytest tst/py -v.

See CLAUDE.md for the full architecture reference, build details, and release process.

License

nind is distributed under the GNU Lesser General Public License v3 (LGPL-3.0) — see LICENCE.md.

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nind 2.1.2

NIND — "nouvelle indexation"

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