---
id: vacuum-map-parser-base
version: "0.1.5"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# vacuum-map-parser-base — Common code for vacuum map parsers

License: permissive · Maintenance: active · Downloads: 83.0K/mo

## What it is and what it does

Vacuum Map Parser Base is a foundational library that defines the common interface and base classes for parsing map data from robot vacuum cleaners. It is not meant to be used directly but rather extended by vacuum-brand-specific implementations (such as those for Roborock, Viomi, Roidmi, or Dreame models). The package provides the structural framework that these implementations build upon, handling shared concerns around map parsing and image processing through its single runtime dependency, Pillow.

The package targets developers building integrations with robot vacuum APIs or home automation systems that need to work with vacuum-generated maps. It is actively maintained, supports current Python versions (3.11+), and carries no known security vulnerabilities. Its small dependency footprint and permissive Apache-2.0 license make it suitable for both open-source and commercial projects.

Use it for:

- Building a home automation integration that needs to parse and display robot vacuum floor maps.
- Creating a vacuum-specific map parser by extending the base classes for a particular robot model.
- Developing a unified dashboard that aggregates maps from multiple vacuum brands using their respective parsers.
- Processing and analyzing vacuum-generated map data for research or debugging purposes.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides base classes and utilities for parsing vacuum cleaner map data, designed to be extended by robot-specific implementations.

Yes, if you are building a vacuum-specific map parser or integrating with a robot vacuum API. Install only as a dependency of a brand-specific implementation (roborock, viomi, roidmi, or dreame), not directly for end-user functionality. The active maintenance, low friction, and permissive license make it a sound foundation for this use case.

## Install

pip install vacuum-map-parser-base
uv add vacuum-map-parser-base
poetry add vacuum-map-parser-base

## Installing vacuum-map-parser-base

Before you install: Low install friction with a single dependency on Pillow. Actively maintained with recent commits and regular releases since initial 2023 release.

License in practice: Apache-2.0 permissive license allows commercial and private use with minimal restrictions.

Quickstart:

pip install vacuum-map-parser-base

from vacuum_map_parser_base import MapParser
# Extend MapParser in your vacuum-specific implementation

Requires Python 3.11 or later; designed as a base class requiring extension by vacuum-specific implementations.

Verify before relying:

- What specific map formats or vacuum models the base parser is designed to support.
- Whether the base classes provide image processing utilities or only data structure definitions.
- How the extension pattern works and what methods subclasses must implement.

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 83.0K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

vacuum map parser base classes, robot vacuum map parsing, vacuum cleaner map data, base parser for robot vacuums, map parsing framework vacuum, vacuum map image processing, home-automation, robot-vacuum, map-parsing

[View on SkillFed](https://skillfed.io/packages/vacuum-map-parser-base) · [View on PyPI](https://pypi.org/project/vacuum-map-parser-base/)