Skip to main content

Markov model implementation

Project description

![](resources/markovx_banner.png)

### Intro ###
[Markov Chains](https://en.wikipedia.org/wiki/Markov_chain) implementation <br>

### Installation ###
in your terminal:

> pip install markovx

### Examples ###

Adding Chains
```python
from markovx.model import MarkovModel

mx = MarkovModel()
mx.add_one('123456')
mx.add_one('qwerty')
mx.add_many(['admin', 'root', 'user'])
```

Generating Chains
```python
mx.generate(10) # len of tokens in chain
```
```python
mx.generate(10, random_init=True)
# when True first token in chain would be assigned randomly
# when False first token would be assigned based on observed firs tokens
# default to False
```
```python
mx.generate(10, smart_ending=False)
# when False chain wouldn't be terminated before len(chain) == n even if model got to an end token
# when True if model got to an end token while len(chain) < n chain would terminate
# default to True
```

### Contact ###
[Tal Peretz](https://www.linkedin.com/in/tal-per/)





Project details


Release history Release notifications

This version
History Node

1.0.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
markovx-1.0.0.tar.gz (2.8 kB) Copy SHA256 hash SHA256 Source None Dec 4, 2017

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page