Search and explore the Holy Qur'an with Arabic text, transliteration, and advanced search support.
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Alfanous is a Quranic search engine API that provides simple and advanced search capabilities for the Holy Qur'an. It enables developers to build applications that search through Quranic text in Arabic, with support for Buckwalter transliteration, advanced query syntax, and rich metadata.
Install from PyPI using pip:
You can also use the public web service:
Or run your own web service locally (see alfanous_webapi).
Search for phrases:
Boolean search (AND, OR, NOT):
Fielded search:
Wildcard search:
Faceted search (aggregate by fields):
api.search(query, **options) - Search Quran versesapi.do(params) - Unified interface for all actions (search, suggest, show, list_values, correct_query)api.correct_query(query, unit, flags) - Get a spelling-corrected version of a queryapi.get_info(category) - Get metadata informationThe underlying Raw output engine is exposed as Engine in alfanous.api (and re-exported from alfanous directly). Use it as a context manager to ensure index resources are properly released:
Common parameters for api.do() with action="search":
query (str): Search query (required)unit (str): Search unit - "aya", "word", or "translation" (default: "aya")page (int): Page number (default: 1)perpage (int): Results per page, 1-100 (default: 10)sortedby (str): Sort order - "score", "relevance", "mushaf", "tanzil", "ayalength" (default: "score")reverse (bool): Reverse the sort order (default: False)view (str): Output view - "minimal", "normal", "full", "statistic", "linguistic" (default: "normal")highlight (str): Highlight style - "css", "html", "bold", "bbcode" (default: "css")script (str): Text script - "standard" or "uthmani" (default: "standard")vocalized (bool): Include Arabic vocalization (default: True)translation (str): Translation ID to includerecitation (str): Recitation ID to include (1-30, default: "1")fuzzy (bool): Enable fuzzy search โ searches both aya_ (exact) and aya (normalised/stemmed) fields, plus Levenshtein distance matching (default: False). See Exact Search vs Fuzzy Search.fuzzy_maxdist (int): Maximum Levenshtein edit distance for fuzzy term matching โ 1, 2, or 3 (default: 1, only used when fuzzy=True).facets (str): Comma-separated list of fields for faceted searchfilter (dict): Filter results by field valuesFor a complete list of parameters and options, see the detailed documentation.
Alfanous provides two complementary search modes that control which index fields are queried.
fuzzy=False)When fuzzy search is off (the default), queries run against the aya_ field, which stores the fully-vocalized Quranic text with diacritical marks (tashkeel) preserved. This mode is designed for precise, statistical matching:
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ููููู and ู
ูุงูููู are treated as different words.fuzzy=True)When fuzzy search is on, queries run against both the aya_ field (exact matches) and the aya field (a separate index built for broad, forgiving search). At index time the aya field is processed through a richer pipeline:
pystemmer), so different morphological forms of the same root match each other.No heavy operations are performed on the query string at search time; all the linguistic enrichment lives in the index.
Additionally, for each Arabic term in the query, a Levenshtein distance search is performed against the aya_ac field (unvocalized, non-stemmed). This catches spelling variants and typos within a configurable edit-distance budget controlled by fuzzy_maxdist.
fuzzy_maxdist | Behaviour |
|---|---|
1 (default) | Catches single-character insertions, deletions, or substitutions |
2 | Broader tolerance โ useful for longer words or noisy input |
3 | Maximum supported โ use with care as recall increases significantly |
Fuzzy mode is particularly useful when:
Note:
pystemmermust be installed for stemming to take effect (pip install pystemmer). If the package is absent the stem filter degrades silently to a no-op, leaving normalisation and stop-word removal still active.
list_values returns every unique indexed value for a given field. Use it to discover the full vocabulary of searchable fields โ for example, all available translation identifiers, part-of-speech tags, or root words โ before composing a query.
Parameters:
field (str): The name of the indexed field whose unique values you want (required).Return value:
A dictionary with a list_values key containing:
field โ the requested field name.values โ sorted list of unique non-empty indexed values.count โ length of the values list.correct_query() uses Whoosh's built-in spell-checker to compare each term in the query against the index vocabulary and replace unknown terms with the closest known alternative. When the query is already valid (all terms appear in the index) the corrected value in the response is identical to the original input.
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