emoji-lexicon 0.2.0

A build-time generated emoji lexicon for Python

emoji-lexicon

🚀 emoji-lexicon is a fast, build-time generated emoji lexicon for Python, powered by Unicode emoji-test and CLDR annotations.

Features

• Fast emoji lookup by short name, alias, or tag
• Designed for CLI, IME, and dictionary tools
• Unicode / CLDR based canonical data
• Build-time normalization, runtime zero-cost lookup
• Optional gemoji-compatible export

Requirements

• Python 3.12+

Status

• Stable build-time generation pipeline
• ~98% test coverage
• Deterministic emoji catalog generation
• Public API is stable

Development

Emoji data is generated at build time from:

• Unicode emoji-test.txt
• CLDR annotations (English)

The runtime catalog is fully read-only and cached.

Installation

pip install emoji-lexicon

Usage

Basic usage:

from emoji_lexicon import get_catalog

catalog = get_catalog()

.get(), get_by_char(), get_all()

# lookup by short name or alias
catalog.get("smile")
# -> Emoji | None

# Slack / gemoji style
catalog.get(":smile:")

# lookup by emoji character
catalog.get_by_char("😁")
# -> Emoji | None

# get all emojis
catalog.get_all()

.search() , .find()

# partial match (short_name / alias / tag)
catalog.search("happy")
# -> tuple[Emoji, ...]

# alias of .search()
catalog.find("happy")
# -> tuple[Emoji, ...]

.search() and .find() perform partial matching and return multiple emojis. .find() is a user-facing alias of .search().

.groups(), .subgroups()

from emoji_lexicon import get_catalog
catalog = get_catalog()

# available emoji groups
catalog.groups()

# available emoji subgroups
catalog.subgroups()

Misc

# total emoji count
len(catalog)

# iterator
for emoji in catalog:
	print(emoji.char, emoji.short_name)

Application examples:

• Categories UI
• IME candidate narrowing down
• emoji picker

Search behavior

The .search() and .find() methods perform token-based emoji search.

Search rules:

• Case-insensitive
• Supports Slack / gemoji style queries (e.g. :smile)
• Space-separated tokens are combined using AND logic
• Results are ranked by relevance

Matching priority (high -> low):

1. Exact short name match
2. Exact alias match
3. Exact tag match
4. Prefix match (only for tokens with 3+ characters)

Ranking is deterministic and stable (score-based, then emoji ID)

Example:

catalog.search("smile")
catalog.search("smile face")
catalog.search(":smile:")

Notes:

• Prefix matching is disabled for very short tokens to reduce noise.
• Result order is deterministic and stable.

Design philosophy

• zero-cost at runtime
• immutable catalog
• Pythonic & typed

License

MIT License © 2026 Kiminori Kato