py3grok 0.1.0

Parse strings and extract information from structured or unstructured data.

py3grok

A Python library to parse strings and extract information from structured or unstructured data. This library is based on pygrok.

Why?

• Parsing and matching patterns from a string.
• Relieving from complex regular expressions.
• Extracting information from structured/unstructured data.

Installation

pip install py3grok

Getting Started

from py3grok import Grok

grok = Grok()
text = 'gary is male, 25 years old and weighs 68.5 kilograms'
grok.set_pattern('%{WORD:name} is %{WORD:gender}, %{NUMBER:age} years old and weighs %{NUMBER:weight} kilograms')
print(grok.match(text))

# {'gender': 'male', 'age': '25', 'name': 'gary', 'weight': '68.5'}

Numbers can be converted from string to int or float if you use %{pattern:name:type} syntax, such as %{NUMBER:age:int}

from py3grok import Grok

grok = Grok()
text = 'gary is male, 25 years old and weighs 68.5 kilograms'
grok.set_pattern('%{WORD:name} is %{WORD:gender}, %{NUMBER:age:int} years old and weighs %{NUMBER:weight:float} kilograms')
print(grok.match(text))

# {'gender': 'male', 'age': 25, 'name': 'gary', 'weight': 68.5}

Now age is of type int and weight is of type float.

See all available patterns here!

Additional Notes

The python re module does not support regular expression syntax atomic grouping (?>), so pygrok requires regex to be installed.

Grok is a simple software that allows you to easily parse strings, logs and other files. With grok, you can turn unstructured log and event data into structured data.

I recommend you to have a look at logstash filter grok, it explains how Grok works.

Pattern files come from logstash filter grok's pattern files