PGen 0.2.1

Features:

• Input format is JSON-text or object

• Unlimited depth of data

• Pure python without dependencies

• Basic types generation (int, double, string)

• Generation of complex types (graph, tree, container)

Installation:

pip install PGen

Documentation:

Basic types:

• int

• double

• string

Complex types:

• pair

• container

• array

• tree

• graph

Will be extended soon…

Examples:

Typical usage often looks like this:

#!/usr/bin/env python

from pgen.generator import Generator

data_description = {
    'seed': 42,
    'count': 3,
    'format': {
        'name': 'N',
        'type': 'int',
        'from': 10,
        'to': 100
    },
    'output': {
        'type': 'file',
        'format': 'tests/{0:03d}.dat',
        'start_index': 3
    }
}

generator = Generator(data_description)
generator.write()

Using variable name:

#!/usr/bin/env python

from pgen.generator import Generator

data_description = {
    'seed': 42,
    'count': 3,
    'format': {
        'type': 'container',
        'elements': [
            {'name': 'n', 'type': 'int', 'from': 3, 'to': 15},
            {
                'type': 'array', 'length': 'n', 'subelement': {
                    'type': 'int',
                    'from': 0,
                    'to': 1
                }
            }
        ]
    },
    'output': {
        'type': 'file',
        'format': 'tests/y_{0:03d}.dat',
        'start_index': 3
    }
}

generator = Generator(data_description)
generator.write()

String patterns:

#!/usr/bin/env python

from pgen.generator import Generator

data_description = {
    'seed': 42,
    'count': 3,
    'format': {
        'type': 'string',
        'length': 32,
        'patterns': ['A-B', 'a-b']
    },
    'output': {
        'type': 'file',
        'format': 'test/{0:03d}_out.dat',
        'start_index': 3
    }
}

generator = Generator(data_description)
generator.write()