---
id: cleanco
version: "2.3"
license: MIT
license_treatment: permissive
maintenance: active
---

# cleanco — Python library to process company names

License: permissive · Maintenance: active · Downloads: 3.9M/mo

## 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 above — 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

pip install cleanco
uv add cleanco
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: unspecified
- Install friction: low
- Maintenance: active
- Downloads: 3.9M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

company name cleaning, strip legal suffixes, organization type classification, business entity detection, company name normalization, jurisdiction inference from company name, legal entity type extraction, data-cleaning, company-metadata, text-normalization

[View on SkillFed](https://skillfed.io/packages/cleanco) · [View on PyPI](https://pypi.org/project/cleanco/)