skillfed

cleanco

Python library to process company names

cleanco v2.3 3.9M downloads/30d#2,471 on PyPI360
Permissive license MIT Active released

What it is and what it does

Cleanco is a Python library for standardizing and analyzing company names. It removes legal suffixes and organizational type indicators (such as "Ltd.", "Corp", "LLC") from company names to produce a clean base name, and uses a built-in database of organization type terms to classify the business entity type (e.g., "limited liability company") and infer possible jurisdictions of establishment.

The package is designed for data cleaning and enrichment workflows where you need to normalize company names across datasets or deduce organizational structure from name alone. It has no external runtime dependencies, making it lightweight to integrate. The library supports custom term databases if you need to extend or override the default classifications.

Use it for:

  • Normalize company names in CRM or database records by removing legal suffixes for consistent matching and deduplication.
  • Classify business entity types from company names in bulk data imports or company research workflows.
  • Infer possible countries of incorporation from company name suffixes to enrich company metadata.
  • Clean company names in financial or procurement datasets before aggregation or reporting.
  • Deduplicate company records by comparing cleaned base names across multiple data sources.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Cleanco strips legal suffixes (Ltd, Corp, LLC, etc.) from company names and classifies organization types and possible jurisdictions based on those terms.

Yes. Cleanco is actively maintained, has no dependencies, installs easily, carries a permissive MIT license, and solves a real data-cleaning problem for anyone working with company names. The library is well-established (first released in 2015) and popular (top 5000 on PyPI). No known security vulnerabilities. Install it if you need to normalize or classify company names in bulk.

Install

cleanco on PyPI

pip

pip install cleanco

uv

uv add cleanco

poetry

poetry add cleanco

Installing cleanco

Before you install

Low friction installation with no runtime dependencies. Actively maintained with recent commits; last release was 2024-05-15 and the repository shows ongoing activity.

License in practice

MIT license is permissive, allowing commercial and private use with minimal restrictions—suitable for most projects.

Quickstart

pip install cleanco

from cleanco import basename, typesources, matches

business_name = "Some Big Pharma, LLC"
clean_name = basename(business_name)  # 'Some Big Pharma'

classification_sources = typesources()
org_types = matches(business_name, classification_sources)  # ['Limited Liability Company']

Verify before relying

  • Whether the organization type and country classification databases are regularly updated to reflect new or changed legal entity terms.
  • Performance characteristics when processing large batches of company names.
  • Coverage of non-English or non-Western business entity types beyond US/UK classifications.

Package facts

License MIT (permissive)
Python support not specified
Install friction low — pure-Python wheel
Runtime dependencies none
Maintenance actively maintained — 821 days since the last release
Last repo commit
First released
Downloads 3,869,129/month — #2,471 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: cleanco-2.3-py3-none-any.whl

Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3Topic :: Office/Business

Tags

company name cleaningstrip legal suffixesorganization type classificationbusiness entity detectioncompany name normalizationjurisdiction inference from company namelegal entity type extraction
data-cleaningcompany-metadatatext-normalization

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