> ## Documentation Index
> Fetch the complete documentation index at: https://resq-dependabot-github-actions-github-actions-478e18be3d.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Bloom

<a id="resq_dsa.bloom" />

# resq\_dsa.bloom

Bloom Filter probabilistic data structure.

This module provides a Bloom Filter implementation for set membership
testing with configurable false positive rate and space efficiency.

<a id="resq_dsa.bloom.hashlib" />

## hashlib

<a id="resq_dsa.bloom.math" />

## math

<a id="resq_dsa.bloom.BloomFilter" />

## BloomFilter Objects

```python theme={null}
class BloomFilter()
```

Space-efficient probabilistic set membership data structure.

A Bloom Filter can test whether an element is possibly in a set
or definitely not in the set. It may return false positives but
never false negatives.

**Attributes**:

* `_m` - Number of bits        \_k: in the filter.
  Number of hash functions.
* `_bits` - Bit array storage.

**Example**:

> > > bf = BloomFilter(capacity=1000)
> > > bf.add("hello")
> > > bf.add("world")
> > > bf.has("hello")
> > > True
> > > bf.has("missing")
> > > False

<a id="resq_dsa.bloom.BloomFilter.__init__" />

#### BloomFilter.\_\_init\_\_

```python theme={null}
def __init__(capacity: int, error_rate: float = 0.01) -> None
```

Initialize the Bloom Filter.

**Arguments**:

* `capacity` - Expected number of elements to be added.
* `error_rate` - Desired false positive rate (default: 0.01 = 1%).

**Raises**:

* `ValueError` - If error\_rate is not in (0, 1) or capacity \< 1.

**Example**:

> > > bf = BloomFilter(capacity=1000, error\_rate=0.05)

<a id="resq_dsa.bloom.BloomFilter.add" />

#### BloomFilter.add

```python theme={null}
def add(item: str) -> None
```

Add an item to the Bloom Filter.

**Arguments**:

* `item` - The string item to add.

**Example**:

> > > bf = BloomFilter(capacity=100)
> > > bf.add("new\_item")

<a id="resq_dsa.bloom.BloomFilter.has" />

#### BloomFilter.has

```python theme={null}
def has(item: str) -> bool
```

Check if an item might be in the set.

Returns True if the item may have been added (possibly a false
positive), False if definitely not in the set.

**Arguments**:

* `item` - The item to check.

**Returns**:

True if possibly in set, False if definitely not.

**Example**:

> > > bf = BloomFilter(capacity=100)
> > > bf.add("present")
> > > bf.has("present")
> > > True
> > > bf.has("absent")
> > > False