fingerprints
A library to generate entity fingerprints.
Decision gist · record as of 2026-08-14
Yes, but with conditions. Install if you need entity fingerprinting now and can tolerate an unmaintained library; the code is stable and has no known vulnerabilities. However, for new projects, evaluate rigour first—it is the maintained successor and likely has improvements. The low install friction and permissive MIT license make this a low-risk addition, but plan a migration path if long-term support matters.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Low friction: pure Python wheel with a single runtime dependency (normality).
- However, the package is now unmaintained as of 2025-05; active development has moved to rigour.
License · maintenance · safety
permissive license (permissive) — MIT license (permissive): you may use, modify, and distribute the package freely with minimal restrictions, provided you retain the copyright notice and license text.
last release 2025-08-01 (378 days) · last repo commit 2025-11-24 · 150 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 227,342 downloads/mo, #9,182 on PyPI
Alternatives
Verify before relying
pip install fingerprints
import fingerprints
fp = fingerprints.generate('Mr. Sherlock Holmes')
print(fp) # 'holmes sherlock'- Whether fingerprints will be maintained or if users should migrate to rigour immediately.
- Performance characteristics on large entity datasets or real-world matching tasks.
- How well the company legal form database covers non-English or emerging markets.
What it is and what it does
Fingerprints is a library for generating normalized entity identifiers from names and addresses, designed to help match the same entity across different data sources. It takes messy input like 'Mr. Sherlock Holmes' or 'Siemens Aktiengesellschaft' and produces a canonical simplified form ('holmes sherlock', 'ag siemens') suitable for deduplication and cross-referencing. The library includes a database of company legal forms drawn from OCCRP, ISO 20275, and other sources, allowing it to recognize and standardize abbreviations like 'AG' for Aktiengesellschaft or 'ООО' for Russian limited liability companies.
The package depends on normality for text processing and installs as a pure Python wheel with low friction. However, as of May 2025, fingerprints is unmaintained—the codebase has been superseded by rigour, which incorporates the next generation of this functionality. The repository remains available and the latest release is from August 2025, but no further development is planned.
Use it for
- Deduplicating entity records in compliance or sanctions databases by generating fingerprints for matching.
- Normalizing company names across multiple data sources to identify the same legal entity.
- Extracting and standardizing company legal forms from unstructured text for entity classification.
- Building entity resolution pipelines where fingerprints serve as a first-pass matching key.
- Preprocessing name data for downstream clustering or similarity matching algorithms.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, but with conditions.
Install if you need entity fingerprinting now and can tolerate an unmaintained library; the code is stable and has no known vulnerabilities. However, for new projects, evaluate rigour first—it is the maintained successor and likely has improvements. The low install friction and permissive MIT license make this a low-risk addition, but plan a migration path if long-term support matters.
Install
fingerprints on PyPI
Before you install
Low friction: pure Python wheel with a single runtime dependency (normality). However, the package is now unmaintained as of 2025-05; active development has moved to rigour. The repository is not archived, but no new releases are planned.
Requires Python 3.10 or later.
License in practice
MIT license (permissive): you may use, modify, and distribute the package freely with minimal restrictions, provided you retain the copyright notice and license text.
Quickstart
pip install fingerprints
import fingerprints
fp = fingerprints.generate('Mr. Sherlock Holmes')
print(fp) # 'holmes sherlock'Verify before relying
- Whether fingerprints will be maintained or if users should migrate to rigour immediately.
- Performance characteristics on large entity datasets or real-world matching tasks.
- How well the company legal form database covers non-English or emerging markets.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagenormality |
| Maintenance | Aging 378 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 227,342 / month, #9,182 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3.11Programming Language :: Python :: 3.12 |
Evidence: fingerprints-1.3.1-py3-none-any.whl
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