> ## 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.

# Count min

<a id="resq_dsa.count_min" />

# resq\_dsa.count\_min

Count-Min Sketch probabilistic data structure.

This module provides a Count-Min Sketch implementation for frequency
estimation of elements in a data stream. Useful for top-k queries and
heavy hitter detection with sub-linear space.

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

## math

<a id="resq_dsa.count_min.CountMinSketch" />

## CountMinSketch Objects

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

Probabilistic data structure for frequency estimation.

The Count-Min Sketch uses multiple hash tables to estimate the count
of elements in a stream with guaranteed error bounds. It provides
an upper bound on frequencies (never underestimates, but may overestimate).

**Attributes**:

* `_w` - Number of columns in the sketch (width).
* `_d` - Number of rows in the sketch (depth).
* `_table` - The hash table storage.

**Example**:

> > > sketch = CountMinSketch(epsilon=0.1, delta=0.01)
> > > sketch.increment("item1")
> > > sketch.increment("item1")
> > > sketch.increment("item2")
> > > sketch.estimate("item1")  # Returns at least 2
> > > 2
> > > sketch.estimate("item2")  # Returns at least 1
> > > 1

<a id="resq_dsa.count_min.CountMinSketch.__init__" />

#### CountMinSketch.\_\_init\_\_

```python theme={null}
def __init__(epsilon: float, delta: float) -> None
```

Initialize the Count-Min Sketch.

**Arguments**:

* `epsilon` - Error parameter. The error in estimation is at most epsilon
  with probability delta. Must be in (0, 1).
* `delta` - Confidence parameter. Must be in (0, 1).

**Raises**:

* `ValueError` - If epsilon or delta are not in (0, 1).

**Example**:

> > > sketch = CountMinSketch(epsilon=0.1, delta=0.01)

<a id="resq_dsa.count_min.CountMinSketch.increment" />

#### CountMinSketch.increment

```python theme={null}
def increment(key: str, count: int = 1) -> None
```

Increment the count for a key.

**Arguments**:

* `key` - The key to increment.
* `count` - Amount to increment by (default: 1).

**Example**:

> > > sketch = CountMinSketch(epsilon=0.1, delta=0.01)
> > > sketch.increment("error")
> > > sketch.increment("error", 5)

<a id="resq_dsa.count_min.CountMinSketch.estimate" />

#### CountMinSketch.estimate

```python theme={null}
def estimate(key: str) -> int
```

Estimate the count for a key.

Returns the minimum across all hash table rows, providing an
upper bound on the true count.

**Arguments**:

* `key` - The key to estimate.

**Returns**:

Estimated count (upper bound).

**Example**:

> > > sketch = CountMinSketch(epsilon=0.1, delta=0.01)
> > > sketch.increment("event")
> > > sketch.estimate("event")
> > > 1