#emoji

National flag design as an API — built on the classic UCI "Flags" dataset (194 countries) and enriched with each country's ISO 3166-1 alpha-2 code, its Unicode flag emoji and ready-to-use SVG / PNG image URLs. For each flag the API exposes its real design attributes: the number of vertical bars and horizontal stripes, the colours present, the predominant ("main") hue, the colours of the top-left and bottom-right corners, and which symbols appear — circles, crosses, saltires, quartered fields, stars or suns, a crescent, a triangle, an inanimate icon (e.g. an anchor), an animate image (e.g. an eagle) or written text. Look a flag up by country or code, search, or FILTER flags by colour, main hue or symbol — "every flag with a crescent", "flags that are mainly green". Served from memory — always fast.

api.oanor.com/flags-api

Strip, extract and count emoji in any text. The strip endpoint removes every emoji from a string — or replaces each one with a marker you choose — and gets multi-code-point emoji right: ZWJ sequences like the family 👩‍👩‍👧‍👦, skin-tone modifiers (👍🏽), country flags (🇩🇪), keycaps (1️⃣) and variation selectors all count as a single emoji, so nothing is left half-deleted. The extract endpoint lists every emoji it finds with its position in the text and returns per-emoji and unique counts, ideal for analytics and moderation. A bare ©, ® or ™ is deliberately left alone unless it carries an emoji variation selector, and plain digits are never touched. Perfect for cleaning user input before search indexing or storage, sanitising usernames and display names, moderation and analytics, and preparing text for systems that choke on emoji. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This cleans and extracts emoji from text; to look an emoji up by name or shortcode use an emoji database API, and to count graphemes use a text-segmentation API.

api.oanor.com/emojistrip-api

Count and split text the way people actually read it, using Unicode-correct segmentation. The count endpoint returns the number of grapheme clusters — the real, user-perceived characters, so a family emoji counts as 1 (not 7) and an accented letter as 1 — alongside words, sentences, code points, UTF-16 code units (the naive string length that over-counts) and UTF-8 byte length. This is exactly what character-limit fields, tweet/SMS counters and validation need so the count agrees with what the user sees. The segment endpoint splits text into grapheme, word or sentence segments (word segments are flagged word-like versus punctuation and spaces) and is locale-aware, so Japanese, Chinese and Thai word boundaries come out right. Everything is computed locally with no network calls. A Unicode text segmenter — distinct from the Unicode codepoint database (unicode), the case/text-utilities toolkit (text) and string similarity (similarity). No upstream key, no cache.

api.oanor.com/segmenter-api

A complete emoji database in one fast API. Search roughly 1,870 emojis by name, keyword, alias or tag, look up a single emoji by its alias (like rocket or :fire:) or by the emoji character itself, browse any of the nine Unicode categories, or get random emojis (optionally from a category). Every emoji comes with its name, category, aliases, search tags, Unicode code points and the version it was introduced in. Built on the open GitHub gemoji dataset and served entirely in-memory, so responses are instant and the service is always available. Ideal for chat and messaging apps, emoji pickers and search, social and content tools, games and fun widgets.

api.oanor.com/emoji-api