# hwrandom
**hwrandom** is a Python package that provides a high-performance random number generator using Intel's RDRAND instruction. By leveraging hardware-based randomness, **hwrandom** delivers cryptographically secure random numbers with superior entropy compared to traditional software-based methods.
Its aim is to have all the same functionalities as the standard ```random``` package.
## Index
- [Features](#features)
- [Usage](#usage)
- [Instalation](#instalation)
- [Examples](#examples)
- [Functions](#functions)
- [Tested](#tested)
- [To Add](#to-add)
## Features
- **Hardware-Based Randomness**: Utilizes Intel's RDRAND instruction for generating true hardware-based random numbers.
- **Cryptographic Security**: Provides cryptographically secure random numbers suitable for secure applications.
- **Versatile Functionality**: Includes functions for generating random integers, floating-point numbers, and selections from sequences.
## Usage
### Instalation
To install **hwrandom**, you can use pip. Simply run:
```
pip install hwrandom
```
### Examples
Here are some examples of how to use the **hwrandom** package:
#### Generating a Random Number
```py
from hwrandom import random
# Generate a random number between 0 and 1
print(random())
```
#### Generating a Random Integer
```py
from hwrandom import randint
# Generate a random integer between 1 and 10
print(randint(1, 10))
```
#### Choosing from a list
```py
from hwrandom import choice
# Choose a random element from a list
print(choice(['apple', 'banana', 'cherry', 'date']))
```
#### Shuffling a list
```py
from hwrandom import shuffle
lst = [1, 2, 3, 4, 5]
shuffle(lst)
print(lst)
```
#### Generating Random Bits
```py
from rdrandom import getrandbits
# Generate a random number with 8 bits
print(getrandbits(8))
```
## Functions
- **`random()`**: Generates a random floating-point number between 0 and 1.
- **`randint(a, b)`**: Returns a random integer N such that `a <= N <= b`.
- **`randrange(start, stop, step)`**: Returns a randomly selected element from the range `start` to `stop` with the specified `step`.
- **`choice(seq)`**: Returns a random element from a non-empty sequence.
- **`shuffle(seq)`**: Shuffles the sequence in place.
- **`getrandbits(k)`**: Returns a Python integer with `k` random bits.
- **`choices(population, weights=None, cum_weights=None, k=1, repetitions=True)`**: Returns a list of `k` elements chosen from the population with optional weights.
- **`sample(population, k=1)`**: Returns a list of `k` unique elements chosen from the population.
- **`uniform(a, b)`**: Returns a random floating-point number between `a` and `b`.
- **`triangular(low, high, mode)`**: Returns a random number between `low` and `high` with the specified `mode`.
## Tested
**hwrandom** was tested in the following:
- [x] Windows 64 bits (Intel)
- [ ] Windows 32 bits (Intel)
- [ ] Windows 64 bits (AMD)
- [ ] Windows 32 bits (AMD)
- [ ] Linux 64 bits (Intel)
- [ ] Linux 32 bits (Intel)
- [ ] Linux 64 bits (AMD)
- [ ] Linux 32 bits (AMD)
## To Add
- [ ] **betavariate(alpha, beta)**: Beta distribution.
- [ ] **expovariate(lambd)**: Exponential distribution.
- [ ] **gammavariate(alpha, beta)**: Gamma distribution.
- [ ] **gauss(mu, sigma)**: Gaussian distribution.
- [ ] **lognormvariate(mu, sigma)**: Log-normal distribution.
- [ ] **normalvariate(mu, sigma)**: Normal distribution.
- [ ] **vonmisesvariate(mu, kappa)**: Von Mises distribution.
- [ ] **paretovariate(alpha)**: Pareto distribution.
- [ ] **weibullvariate(alpha, beta)**: Weibull distribution.
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"description": "# hwrandom\r\n\r\n**hwrandom** is a Python package that provides a high-performance random number generator using Intel's RDRAND instruction. By leveraging hardware-based randomness, **hwrandom** delivers cryptographically secure random numbers with superior entropy compared to traditional software-based methods.\r\n\r\nIts aim is to have all the same functionalities as the standard ```random``` package.\r\n\r\n## Index\r\n- [Features](#features)\r\n- [Usage](#usage)\r\n - [Instalation](#instalation)\r\n - [Examples](#examples)\r\n- [Functions](#functions)\r\n- [Tested](#tested)\r\n- [To Add](#to-add)\r\n\r\n## Features\r\n\r\n- **Hardware-Based Randomness**: Utilizes Intel's RDRAND instruction for generating true hardware-based random numbers.\r\n- **Cryptographic Security**: Provides cryptographically secure random numbers suitable for secure applications.\r\n- **Versatile Functionality**: Includes functions for generating random integers, floating-point numbers, and selections from sequences.\r\n\r\n## Usage\r\n\r\n### Instalation\r\n\r\nTo install **hwrandom**, you can use pip. Simply run:\r\n\r\n```\r\npip install hwrandom\r\n```\r\n\r\n### Examples\r\n\r\nHere are some examples of how to use the **hwrandom** package:\r\n\r\n#### Generating a Random Number\r\n```py\r\nfrom hwrandom import random\r\n\r\n# Generate a random number between 0 and 1\r\nprint(random())\r\n```\r\n\r\n#### Generating a Random Integer\r\n```py\r\nfrom hwrandom import randint \r\n\r\n# Generate a random integer between 1 and 10 \r\nprint(randint(1, 10))\r\n```\r\n#### Choosing from a list\r\n```py\r\nfrom hwrandom import choice\r\n\r\n# Choose a random element from a list\r\nprint(choice(['apple', 'banana', 'cherry', 'date']))\r\n```\r\n#### Shuffling a list\r\n```py\r\nfrom hwrandom import shuffle\r\n\r\nlst = [1, 2, 3, 4, 5]\r\nshuffle(lst)\r\nprint(lst)\r\n```\r\n#### Generating Random Bits\r\n```py\r\nfrom rdrandom import getrandbits\r\n\r\n# Generate a random number with 8 bits\r\nprint(getrandbits(8))\r\n```\r\n\r\n\r\n## Functions\r\n- **`random()`**: Generates a random floating-point number between 0 and 1.\r\n- **`randint(a, b)`**: Returns a random integer N such that `a <= N <= b`.\r\n- **`randrange(start, stop, step)`**: Returns a randomly selected element from the range `start` to `stop` with the specified `step`.\r\n- **`choice(seq)`**: Returns a random element from a non-empty sequence.\r\n- **`shuffle(seq)`**: Shuffles the sequence in place.\r\n- **`getrandbits(k)`**: Returns a Python integer with `k` random bits.\r\n- **`choices(population, weights=None, cum_weights=None, k=1, repetitions=True)`**: Returns a list of `k` elements chosen from the population with optional weights.\r\n- **`sample(population, k=1)`**: Returns a list of `k` unique elements chosen from the population.\r\n- **`uniform(a, b)`**: Returns a random floating-point number between `a` and `b`.\r\n- **`triangular(low, high, mode)`**: Returns a random number between `low` and `high` with the specified `mode`.\r\n\r\n\r\n## Tested\r\n\r\n**hwrandom** was tested in the following:\r\n\r\n- [x] Windows 64 bits (Intel)\r\n- [ ] Windows 32 bits (Intel)\r\n- [ ] Windows 64 bits (AMD)\r\n- [ ] Windows 32 bits (AMD)\r\n- [ ] Linux 64 bits (Intel)\r\n- [ ] Linux 32 bits (Intel)\r\n- [ ] Linux 64 bits (AMD)\r\n- [ ] Linux 32 bits (AMD)\r\n\r\n## To Add\r\n\r\n- [ ] **betavariate(alpha, beta)**: Beta distribution.\r\n- [ ] **expovariate(lambd)**: Exponential distribution.\r\n- [ ] **gammavariate(alpha, beta)**: Gamma distribution.\r\n- [ ] **gauss(mu, sigma)**: Gaussian distribution.\r\n- [ ] **lognormvariate(mu, sigma)**: Log-normal distribution.\r\n- [ ] **normalvariate(mu, sigma)**: Normal distribution.\r\n- [ ] **vonmisesvariate(mu, kappa)**: Von Mises distribution.\r\n- [ ] **paretovariate(alpha)**: Pareto distribution.\r\n- [ ] **weibullvariate(alpha, beta)**: Weibull distribution.\r\n",
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