PyRando

PyRando is a Python 3 module for interacting with the random.org JSON API. PyRando can generate random values using basic methods as well as digitally signed random values using the signed methods.

PyRando is compatible with Python 3.6+.

Installation

To install pyrando, use pip3:

$ pip3 install pyrando

Getting Started

To interact with random.org, you will first need to get an api key. Go to api.random.org and click on Get a Beta Key. Once you have an API key, using PyRando is quite straightforward.

For example:

>>> from pyrando import PyRando
>>> pr = PyRando('YOUR_API_KEY')
>>> pr.integers(5, 0, 10)
[0, 7, 10, 3, 5]

Basic Methods

Integers

The integers method generates true random integers within a user-defined range. Integer requests take up to four positional arguments:

• n - How many random integers you need. Must be within the [1,1e4] range
• min - The lower boundary for the range. Must be within the [-1e9,1e9] range
• max - The upper boundary for the range. Must be within the [-1e9,1e9] range
• base (optional) - If not provided, the default base is set to 10. Allowed values for base are 2, 8, 10, and 16

Examples:

pr.integers(10, 1, 6)
pr.integers(10, 1, 100, 2)

Decimals

The decimals method generates true random decimal fractions from a uniform distribution across the [0,1] interval with a user-defined number of decimal places. Decimal requests take three positional arguments:

• n - How many random decimal fractions you need. Must be within the [1,1e4] range
• decimalPlaces - The number of decimal places to use. Must be within the [1,20] range

Example:

pr.decimals(10, 8)

Gaussians

The gaussians method generates true random numbers from a Gaussian distribution. Integer requests take four positional arguments:

• n - How many random numbers you need
• mean - The distributions mean. Must be within the [1,1e4] range
• standardDeviation - The distributions standard deviation. Must be with the [-1e6,1e6] range
• significantDigits - The number of significant digits to use. Must be within the [2,20] range

Example:

pr.gaussians(4, 0.0, 1.0, 8)

Strings

The strings method generates true random strings. String requests take three positional arguments:

• n - How many random strings you need. Must be within the [1,1e4] range
• length - The length of each string. Must bbe within the [1,20] range. All strings will be of the same length
• characters - A string that contains the set of characters that are allowed to occur in the random stings. The maximum number of characters is 80

Example:

pr.strings(10, 20, 'abcdefghijklmnopqrstuvwxyz')

UUIDs

The uuids method generates version 4 true random UUIDs. UUID requests take a single positional argument:

• n - How many random UUIDs you need. Must be within the [1,1e3] range

Example:

pr.uuids(1)

Blobs

The blobs method generates BLOBs containing true random data. Blob requests take up to three positional argument:

• n - How many random blobs you need. Must be within the [1,100] range
• size - The size of each blob, measured in bits. Must be within the [1,1048576] range and divisible by 8. The total size of all requested blobs much not exceed 1,048,576 bits (128KiB)
• format - Specifies the format in which the blobs will be returned. Values allowed are base64 and hex. If not value is provided, the default value of base64 is used.

Examples:

pr.blobs(1, 2048)
pr.blobs(1, 1024, 'hex')

Usage

The usage method returns information related to the usage of a given API.

Example:

pr.usage()

Signed Methods

Usage of signed methods is quite similar to that of basic methods. For example, to use signed methods you could input the commands as follows:

>>> pr.signed_integers(10, 1, 6)
>>> pr.signed_decimals(10, 8)
>>> pr.signed_gaussians(4, 0.0, 1.0, 8)
>>> pr.signed_strings(10, 20, 'abcdefghijklmnopqrstuvwxyz')
>>> pr.signed_uuids(1)
>>> pr.signed_blobs(1, 2048)

The difference between basic methods and signed methods is the response. Instead of just a list with the random values, signed methods return a dictionary with values for the following keys data, random, and signature. The random and signature values can be used to authenticate signed values.

To verify a response, use the verify_signature method. The method take the random and signature values as arguments and responds with a boolean value of either True or False. For example:

>>> signed_ints = pr.signed_integers(10, 1, 6)
>>> pr.verify_signature(signed_ints['random'], signed_ints['signature'])
True