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35
Dockerfile
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# Use Python 3.12-slim as the base image
FROM python:3.12-slim
# Set the working directory in the container
WORKDIR /app
# Install system dependencies
RUN apt-get update && apt-get install -y \
git \
build-essential \
&& rm -rf /var/lib/apt/lists/*
# Copy requirements file
COPY requirements.txt requirements.txt
# Upgrade pip and install dependencies
RUN pip install --no-cache-dir -U pip && pip install --no-cache-dir -r requirements.txt
# Create a fake sudo command to bypass sudo errors
RUN echo '#!/bin/sh\nexec "$@"' > /usr/bin/sudo && chmod +x /usr/bin/sudo
# Clone and install TemporalLib
RUN git clone --depth 1 https://github.com/TheRandonauts/temporal.git /app/temporal \
&& cd /app/temporal \
&& ./make.sh \
&& rm -rf /app/temporal
# Copy application files
COPY . .
# Expose Streamlit's default port
EXPOSE 8501
# Run the application
CMD ["streamlit", "run", "main.py", "--server.port=8501", "--server.address=0.0.0.0"]

15
Pipfile Normal file
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[[source]]
url = "https://pypi.org/simple"
verify_ssl = true
name = "pypi"
[packages]
randonautentropy = "*"
questionary = "*"
rich = "*"
lyagushka = {file = "https://github.com/randogoth/lyagushka/releases/download/1.1.1/lyagushka-1.1.1-cp312-cp312-manylinux_2_34_x86_64.whl"}
[dev-packages]
[requires]
python_version = "3.12"

163
main.py
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import streamlit as st
import streamlit.components.v1 as components
from lyagushka import Lyagushka from lyagushka import Lyagushka
from randonautentropy import temporal from randonautentropy import rndo
import json import json
import time import questionary
from rich.console import Console
from rich.text import Text
from rich.progress import Progress, TextColumn, BarColumn
# Validate Z-Score # Validate Z-Score
def z_thresh(s): def z_thresh(s):
@ -18,131 +19,105 @@ def z_thresh(s):
# Generate random data with a specified size and maximum value # Generate random data with a specified size and maximum value
def generate_random_data(size=1024, max_value=100): def generate_random_data(size=1024, max_value=100):
random_data = [] random_data = []
# Calculate the number of bytes required to represent the max value
max_value_bytes = (max_value.bit_length() + 7) // 8 max_value_bytes = (max_value.bit_length() + 7) // 8
max_int_for_bytes = 2**(max_value_bytes * 8) - 1 max_int_for_bytes = 2**(max_value_bytes * 8) - 1
# Define the cutoff to ensure uniform distribution
mod_cutoff = max_int_for_bytes - (max_int_for_bytes % max_value) - 1 mod_cutoff = max_int_for_bytes - (max_int_for_bytes % max_value) - 1
while len(random_data) < size: while len(random_data) < size:
hex_data = temporal.get(length=max_value_bytes * size) # Generate random hexadecimal data
hex_data = rndo.get(length=max_value_bytes * size)
# Process the hex data in chunks
for i in (hex_data[j:j + 2 * max_value_bytes] for j in range(0, len(hex_data), 2 * max_value_bytes)): for i in (hex_data[j:j + 2 * max_value_bytes] for j in range(0, len(hex_data), 2 * max_value_bytes)):
num = int(i, 16) num = int(i, 16) # Convert hex chunk to integer
if num <= mod_cutoff: if num <= mod_cutoff:
# Add the value to random_data if within the cutoff
random_data.append(num % (max_value + 1)) random_data.append(num % (max_value + 1))
# Break early if enough data is collected
if len(random_data) >= size: if len(random_data) >= size:
break break
return random_data return random_data
# Analyze and select numbers based on Z-score # Analyze and select numbers based on Z-score
def pull_number(numbers: set, top: int, amount: int, z_score: float, progress_bar, task_name): def pull_number(numbers: set, top: int, amount: int, z_score: float):
# Generate and sort a dataset of random numbers
dataset = generate_random_data(3000, 999) dataset = generate_random_data(3000, 999)
dataset.sort() dataset.sort()
# Analyze the dataset using Lyagushka
zhaba = Lyagushka(dataset) zhaba = Lyagushka(dataset)
analysis_results = json.loads(zhaba.search(4.0, 30)) analysis_results = json.loads(zhaba.search(4.0, 30))
# Filter results for valid Z-scores
results = [obj for obj in analysis_results if obj['z_score'] is not None] results = [obj for obj in analysis_results if obj['z_score'] is not None]
max_z_score = max(obj['z_score'] for obj in results) max_z_score = max(obj['z_score'] for obj in results)
total_tasks = amount - len(numbers) for obj in results:
for idx, obj in enumerate(results): # Check if the object has the maximum Z-score and meets the threshold
if obj['z_score'] == max_z_score and obj['z_score'] >= z_score: if obj['z_score'] == max_z_score and obj['z_score'] >= z_score:
# Ensure the centroid is not an x.5 and add the scaled value
if len(numbers) < amount and (obj['centroid'] % 1 != 0.5): if len(numbers) < amount and (obj['centroid'] % 1 != 0.5):
numbers.add(int((obj['centroid'] / 999) * top) + 1) numbers.add(int((obj['centroid'] / 999) * top) + 1)
# Update progress
progress_bar.progress((len(numbers) / amount))
time.sleep(0.05) # Simulate some delay
if len(numbers) >= amount:
break
return numbers return numbers
def generate_ball_html(numbers, bonus): # Main function to drive the lottery draw process
balls_html = "" def main():
for num in numbers:
balls_html += f"""
<div class="ball white">{num}</div>
"""
balls_html += f"""
<div class="ball yellow">{bonus}</div>
"""
return balls_html
console = Console()
# Display an introduction to the lottery process
description = "\nEach lottery ball is selected by generating hundreds of random values within the provided range. The data is analyzed to identify number clusters. The centroid values of the attractor clusters with a z-score above the set threshold are selected as lotto numbers. This process repeats until all balls are drawn. The entire method is a one-dimensional analogy to how attractor points are calculated in Randonautica.\n" description = "\nEach lottery ball is selected by generating hundreds of random values within the provided range. The data is analyzed to identify number clusters. The centroid values of the attractor clusters with a z-score above the set threshold are selected as lotto numbers. This process repeats until all balls are drawn. The entire method is a one-dimensional analogy to how attractor points are calculated in Randonautica.\n"
console.print(description, style="italic green")
# Streamlit App # Get the number of lottery balls to draw
st.title("Lottonautica") num_lotto_balls = int(questionary.text(
st.write(description) "Amount of balls to draw? (default: 5)",
validate=lambda val: val.isdigit() or "Please enter a valid integer.",
default="5"
).ask())
# User Inputs # Get the highest possible number in the lottery
num_lotto_balls = st.number_input("Amount of balls to draw:", min_value=1, max_value=20, value=5) highest_number = int(questionary.text(
highest_number = st.number_input("Amount of balls in the lottery:", min_value=1, max_value=100, value=70) "Amount of balls in the lottery? (default: 70)",
highest_extra_ball = st.number_input("Amount of balls in the extra draw:", min_value=1, max_value=50, value=25) validate=lambda val: val.isdigit() or "Please enter a valid integer.",
z_score_threshold = st.number_input("Minimum Z-Score Threshold:", min_value=1.0, max_value=5.0, value=2.22) default="70"
).ask())
# Get the highest number for the extra draw
highest_extra_ball = int(questionary.text(
"Amount of balls in the extra draw? (default: 25)",
validate=lambda val: val.isdigit() or "Please enter a valid integer.",
default="25"
).ask())
# Get the Z-score threshold for anomaly detection
z_score_threshold = float(questionary.text(
"Minimum Z-Score Threshold? (default: 3.0)",
validate=lambda val: z_thresh(val) or "Please enter a valid value (1.0 - 5.0).",
default="3.0"
).ask())
if st.button("Generate Lottery Numbers"):
st.subheader("Generating Lottery Numbers...")
numbers = set() numbers = set()
megaball = set() megaball = set()
# Progress bar for main numbers # Show a progress bar during the number drawing process
progress_main = st.progress(0) with Progress(TextColumn("[progress.description]{task.description}"), BarColumn(), transient=True) as progress:
status_text = st.empty() task = progress.add_task("Drawing numbers...", total=num_lotto_balls + 1)
# Draw main lottery numbers
st.text("Drawing main numbers...")
while len(numbers) < num_lotto_balls: while len(numbers) < num_lotto_balls:
# Update numbers and progress numbers = pull_number(numbers, highest_number, num_lotto_balls, z_score_threshold)
numbers = pull_number(numbers, highest_number, num_lotto_balls, z_score_threshold, progress_main, "Main Numbers") progress.update(task, completed=len(numbers))
progress_main.progress(len(numbers) / num_lotto_balls) # Draw the extra ball
# Progress bar for extra ball
progress_extra = st.progress(0)
st.text("Drawing the extra ball...")
while len(megaball) < 1: while len(megaball) < 1:
# Update megaball and progress megaball = pull_number(megaball, highest_extra_ball, 1, z_score_threshold)
megaball = pull_number(megaball, highest_extra_ball, 1, z_score_threshold, progress_extra, "Bonus Ball")
# Display Results # Display the results
st.subheader("Lottery Numbers") console.print("\nLottery numbers:\n", style="bold green")
main_numbers = sorted(numbers) lottery_balls = [Text(f" {n} ", style="bold black on white") for n in sorted(numbers)]
bonus_number = list(megaball)[0] bonus_ball = Text(f" {list(megaball)[0]} ", style="bold black on yellow")
console.print(*lottery_balls, bonus_ball, sep=" ")
# Full HTML with inline CSS if __name__ == "__main__":
custom_html = f""" main()
<html>
<head>
<style>
.container {{
display: flex;
justify-content: center;
align-items: center;
margin-top: 20px;
}}
.ball {{
width: 50px;
height: 50px;
margin: 5px;
border-radius: 50%;
text-align: center;
line-height: 50px;
font-weight: bold;
font-size: 18px;
font-family: sans-serif;
border: 2px solid black;
}}
.white {{
background-color: white;
color: black;
}}
.yellow {{
background-color: yellow;
color: black;
}}
</style>
</head>
<body>
<div class="container">
{generate_ball_html(main_numbers, bonus_number)}
</div>
</body>
</html>
"""
components.html(custom_html, height=150)

3
requirements.txt
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randonautentropy
lyagushka @ https://github.com/randogoth/lyagushka/releases/download/1.1.1/lyagushka-1.1.1-cp312-cp312-manylinux_2_34_x86_64.whl
streamlit