---
title: Fuzzy
description: Allow for typos in the query string
canonical: https://docs.paradedb.com/documentation/full-text/fuzzy
---

Fuzziness allows for tokens to be considered a match even if they are not identical, allowing for typos
in the query string.

<Warning>
While fuzzy matching will work for non-latin characters (Chinese, Japanese, Korean, etc..), it may not
give expected results (with large result sets returned) as Levenshtein distance relies on individual character difference.

If you need this functionality then please thumbs-up this [issue](https://github.com/paradedb/paradedb/issues/3782), and leave
a comment with your use case.

</Warning>

## Overview

To add fuzziness to a query, cast it to the `fuzzy(n)` type, where `n` is the [edit distance](#how-it-works).
Fuzziness is supported for [match](/documentation/full-text/match) and [term](/documentation/full-text/term) queries.

<CodeGroup>
```sql SQL
-- Fuzzy match disjunction
SELECT id, description
FROM mock_items
WHERE description ||| 'runing shose'::pdb.fuzzy(2)
LIMIT 5;

-- Fuzzy match conjunction
SELECT id, description
FROM mock_items
WHERE description &&& 'runing shose'::pdb.fuzzy(2)
LIMIT 5;

-- Fuzzy Term
SELECT id, description
FROM mock_items
WHERE description === 'shose'::pdb.fuzzy(2)
LIMIT 5;
```

```python Django
from paradedb import Match, ParadeDB, Term

# Fuzzy match disjunction
MockItem.objects.filter(
    description=ParadeDB(Match('runing shose', operator='OR', distance=2))
).values('id', 'description')[:5]

# Fuzzy match conjunction
MockItem.objects.filter(
    description=ParadeDB(Match('runing shose', operator='AND', distance=2))
).values('id', 'description')[:5]

# Fuzzy term
MockItem.objects.filter(
    description=ParadeDB(Term('shose', distance=2))
).values('id', 'description')[:5]
```

```python SQLAlchemy
from sqlalchemy import select
from sqlalchemy.orm import Session
from paradedb.sqlalchemy import search

fuzzy_or_stmt = (
    select(MockItem.id, MockItem.description)
    .where(search.match_any(MockItem.description, "runing shose", distance=2))
    .limit(5)
)

fuzzy_and_stmt = (
    select(MockItem.id, MockItem.description)
    .where(search.match_all(MockItem.description, "runing shose", distance=2))
    .limit(5)
)

fuzzy_term_stmt = (
    select(MockItem.id, MockItem.description)
    .where(search.term(MockItem.description, "shose", distance=2))
    .limit(5)
)

with Session(engine) as session:
    {
        "or_rows": session.execute(fuzzy_or_stmt).all(),
        "and_rows": session.execute(fuzzy_and_stmt).all(),
        "term_rows": session.execute(fuzzy_term_stmt).all(),
    }
```

```ruby Rails
# Fuzzy match disjunction
MockItem.search(:description)
        .matching_any('runing shose', distance: 2)
        .select(:id, :description)
        .limit(5)

# Fuzzy match conjunction
MockItem.search(:description)
        .matching_all('runing shose', distance: 2)
        .select(:id, :description)
        .limit(5)

# Fuzzy term
MockItem.search(:description)
        .term("shose", distance: 2)
        .select(:id, :description)
        .limit(5)
```

</CodeGroup>

## How It Works

By default, the [match](/documentation/full-text/match) and [term](/documentation/full-text/term) queries require exact token matches between the query and indexed text. When a query is cast to `fuzzy(n)`, this requirement is relaxed -- tokens are matched if their Levenshtein distance, or edit distance, is less than or equal to `n`.

Edit distance is a measure of how many single-character operations are needed to turn one string into another. The allowed operations are:

- **Insertion** adds a character e.g., "shoe" → "shoes" (insert "s") has an edit distance of `1`
- **Deletion** removes a character e.g. "runnning" → "running" (delete one "n") has an edit distance of `1`
- **Transposition** replaces on character with another e.g., "shose" → "shoes" (transpose "s" → "e") has an edit distance of `2`

<Note>For performance reasons, the maximum allowed edit distance is `2`.</Note>

<Note>Casting a query to `fuzzy(0)` is the same as an exact token match.</Note>

## Fuzzy Prefix

`fuzzy` also supports prefix matching.
For instance, "runn" is a prefix of "running" because it matches the beginning of the token exactly. "rann" is a **fuzzy prefix** of "running" because it matches the
beginning within an edit distance of `1`.

To treat the query string as a prefix, set the second argument of `fuzzy` to either `t` or `"true"`:

<CodeGroup>
```sql SQL
SELECT id, description
FROM mock_items
WHERE description === 'rann'::pdb.fuzzy(1, t)
LIMIT 5;
```

```python Django
from paradedb import ParadeDB, Term

MockItem.objects.filter(
    description=ParadeDB(Term('rann', distance=1, prefix=True))
).values('id', 'description')[:5]
```

```python SQLAlchemy
from sqlalchemy import select
from sqlalchemy.orm import Session
from paradedb.sqlalchemy import search

stmt = (
    select(MockItem.id, MockItem.description)
    .where(search.term(MockItem.description, "rann", distance=1, prefix=True))
    .limit(5)
)

with Session(engine) as session:
    session.execute(stmt).all()
```

```ruby Rails
MockItem.search(:description)
        .term("rann", distance: 1, prefix: true)
        .select(:id, :description)
        .limit(5)
```

</CodeGroup>

<Note>
  Postgres requires that `true` be double-quoted, i.e. `fuzzy(1, "true")`.
</Note>

When used with [match](/documentation/full-text/match) queries, fuzzy prefix treats all tokens in the query string as prefixes.
For instance, the following query means "find all documents containing the fuzzy prefix `rann` AND the fuzzy prefix `slee`":

<CodeGroup>
```sql SQL
SELECT id, description
FROM mock_items
WHERE description &&& 'slee rann'::pdb.fuzzy(1, t)
LIMIT 5;
```

```python Django
from paradedb import Match, ParadeDB

MockItem.objects.filter(
    description=ParadeDB(Match('slee rann', operator='AND', distance=1, prefix=True))
).values('id', 'description')[:5]
```

```python SQLAlchemy
from sqlalchemy import select
from sqlalchemy.orm import Session
from paradedb.sqlalchemy import search

stmt = (
    select(MockItem.id, MockItem.description)
    .where(search.match_all(MockItem.description, "slee rann", distance=1, prefix=True))
    .limit(5)
)

with Session(engine) as session:
    session.execute(stmt).all()
```

```ruby Rails
MockItem.search(:description)
        .matching_all("slee rann", distance: 1, prefix: true)
        .select(:id, :description)
        .limit(5)
```

</CodeGroup>

## Transposition Cost

By default, the cost of a transposition (i.e. "shose" → "shoes") is `2`. Setting the third argument of `fuzzy` to `t` lowers the
cost of a transposition to `1`:

<CodeGroup>
```sql SQL
SELECT id, description
FROM mock_items
WHERE description === 'shose'::pdb.fuzzy(1, f, t)
LIMIT 5;
```

```python Django
from paradedb import ParadeDB, Term

MockItem.objects.filter(
    description=ParadeDB(Term('shose', distance=1, transposition_cost_one=True))
).values('id', 'description')[:5]
```

```python SQLAlchemy
from sqlalchemy import select
from sqlalchemy.orm import Session
from paradedb.sqlalchemy import search

stmt = (
    select(MockItem.id, MockItem.description)
    .where(search.term(MockItem.description, "shose", distance=1, transpose_cost_one=True))
    .limit(5)
)

with Session(engine) as session:
    session.execute(stmt).all()
```

```ruby Rails
MockItem.search(:description)
        .term("shose", distance: 1, transposition_cost_one: true)
        .select(:id, :description)
        .limit(5)
```

</CodeGroup>

<Note>
  The default value for the second and third arguments of `fuzzy` is `f`, which
  means `fuzzy(1)` is equivalent to `fuzzy(1, f, f)`.
</Note>
