init

2025-01-06 18:48:10 +02:00 · 2025-01-06 18:48:10 +02:00 · 247eeef281
commit 247eeef281
5 changed files with 323 additions and 0 deletions
--- a/15
+++ b/15
@ -0,0 +1,15 @@
+[[source]]
+url = "https://pypi.org/simple"
+verify_ssl = true
+name = "pypi"
+
+[packages]
+randonautentropy = "*"
+lyagushka = {path = "./lyagushka-0.1.0-py2.py3-none-any.whl"}
+questionary = "*"
+rich = "*"
+
+[dev-packages]
+
+[requires]
+python_version = "3.12"
--- a/Pipfile.lock
+++ b/Pipfile.lock
@ -0,0 +1,222 @@
+{
+    "_meta": {
+        "hash": {
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+        },
+        "pipfile-spec": 6,
+        "requires": {
+            "python_version": "3.12"
+        },
+        "sources": [
+            {
+                "name": "pypi",
+                "url": "https://pypi.org/simple",
+                "verify_ssl": true
+            }
+        ]
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+            ],
+            "markers": "python_version >= '3.7'",
+            "version": "==3.4.1"
+        },
+        "idna": {
+            "hashes": [
+                "sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9",
+                "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3"
+            ],
+            "markers": "python_version >= '3.6'",
+            "version": "==3.10"
+        },
+        "lyagushka": {
+            "hashes": [
+                "sha256:cd9530f3b12d048e3549573c5afd383bc3498a1ee780b7daeb3640114d3e8fbd"
+            ],
+            "path": "./lyagushka-0.1.0-py2.py3-none-any.whl"
+        },
+        "markdown-it-py": {
+            "hashes": [
+                "sha256:355216845c60bd96232cd8d8c40e8f9765cc86f46880e43a8fd22dc1a1a8cab1",
+                "sha256:e3f60a94fa066dc52ec76661e37c851cb232d92f9886b15cb560aaada2df8feb"
+            ],
+            "markers": "python_version >= '3.8'",
+            "version": "==3.0.0"
+        },
+        "mdurl": {
+            "hashes": [
+                "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8",
+                "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba"
+            ],
+            "markers": "python_version >= '3.7'",
+            "version": "==0.1.2"
+        },
+        "prompt-toolkit": {
+            "hashes": [
+                "sha256:d6623ab0477a80df74e646bdbc93621143f5caf104206aa29294d53de1a03d90",
+                "sha256:f49a827f90062e411f1ce1f854f2aedb3c23353244f8108b89283587397ac10e"
+            ],
+            "markers": "python_full_version >= '3.7.0'",
+            "version": "==3.0.48"
+        },
+        "pygments": {
+            "hashes": [
+                "sha256:4755e6e64d22161d5b61432c0600c923c5927214e7c956e31c23923c89251a9b",
+                "sha256:afc4146269910d4bdfabcd27c24923137a74d562a23a320a41a55ad303e19783"
+            ],
+            "markers": "python_version >= '3.8'",
+            "version": "==2.19.0"
+        },
+        "questionary": {
+            "hashes": [
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+            ],
+            "index": "pypi",
+            "markers": "python_version >= '3.8'",
+            "version": "==2.1.0"
+        },
+        "randonautentropy": {
+            "hashes": [
+                "sha256:2ea19e5122769d47b7502ce554bcf8743491a39457255d93712ab8a9ea487c81"
+            ],
+            "index": "pypi",
+            "markers": "python_version >= '3.6'",
+            "version": "==1.0.2"
+        },
+        "requests": {
+            "hashes": [
+                "sha256:55365417734eb18255590a9ff9eb97e9e1da868d4ccd6402399eaf68af20a760",
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+            ],
+            "markers": "python_version >= '3.8'",
+            "version": "==2.32.3"
+        },
+        "rich": {
+            "hashes": [
+                "sha256:439594978a49a09530cff7ebc4b5c7103ef57baf48d5ea3184f21d9a2befa098",
+                "sha256:6049d5e6ec054bf2779ab3358186963bac2ea89175919d699e378b99738c2a90"
+            ],
+            "index": "pypi",
+            "markers": "python_full_version >= '3.8.0'",
+            "version": "==13.9.4"
+        },
+        "urllib3": {
+            "hashes": [
+                "sha256:1cee9ad369867bfdbbb48b7dd50374c0967a0bb7710050facf0dd6911440e3df",
+                "sha256:f8c5449b3cf0861679ce7e0503c7b44b5ec981bec0d1d3795a07f1ba96f0204d"
+            ],
+            "markers": "python_version >= '3.9'",
+            "version": "==2.3.0"
+        },
+        "wcwidth": {
+            "hashes": [
+                "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859",
+                "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"
+            ],
+            "version": "==0.2.13"
+        }
+    },
+    "develop": {}
+}
--- a/pycache/main.cpython-312.pyc
+++ b/pycache/main.cpython-312.pyc
--- a/lyagushka-0.1.0-py2.py3-none-any.whl
+++ b/lyagushka-0.1.0-py2.py3-none-any.whl
--- a/main.py
+++ b/main.py
@ -0,0 +1,86 @@
+from lyagushka import Lyagushka
+from randonautentropy import rndo
+import json
+import questionary
+from rich.console import Console
+from rich.text import Text
+from rich.progress import Progress, TextColumn, BarColumn
+
+def generate_random_data(size=1024, max_value=100):
+
+    random_data = []
+    max_value_bytes = (max_value.bit_length() + 7) // 8
+    max_int_for_bytes = 2**(max_value_bytes * 8) - 1
+    min_bytes_needed =  max_value_bytes * size
+    mod_cutoff = max_int_for_bytes - (max_int_for_bytes % max_value) - 1
+
+    # Populate the 'random_data' array
+    while len(random_data) < size:
+        hex_data = rndo.get(length=min_bytes_needed)
+        hex_chunks = list((hex_data[0+i:2 * max_value_bytes+i] for i in range(0, len(hex_data), 2 * max_value_bytes)))
+        for i in hex_chunks:
+            num = int(i, 16)
+            if num <= mod_cutoff and len(random_data) < size:
+                random_data.append( num % (max_value + 1) )
+
+    return random_data
+
+def pull_number(numbers: set, top: int, amount: int):
+    dataset = generate_random_data(444, top-1)
+    dataset.sort()
+    # calculate the anomalies in the data
+    zhaba = Lyagushka(dataset)
+    analysis_results = json.loads(zhaba.search(4.0, 10))
+    pick = [obj for obj in analysis_results if obj['num_elements'] == max(obj['num_elements'] for obj in analysis_results)]
+    for p in pick:
+        if len(numbers) < amount:
+            numbers.add(int(p['centroid'] + 1))
+    return numbers
+
+def main():
+
+    console = Console()
+
+    description = "\nEach lottery ball is selected by generating hundreds of random values within the provided range. The data is analyzed to identify the most frequently occurring number, which is then chosen as the lottery ball. 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")
+    
+    num_lotto_balls = questionary.text(
+        "Amount of balls to draw? (default: 5)",
+        validate=lambda val: val.isdigit() or "Please enter a valid integer.",
+        default="5"
+    ).ask()
+    num_lotto_balls = int(num_lotto_balls)
+
+    highest_number = questionary.text(
+        "Amount of balls in the lottery? (default: 70)",
+        validate=lambda val: val.isdigit() or "Please enter a valid integer.",
+        default="70"
+    ).ask()
+    highest_number = int(highest_number)
+
+    highest_extra_ball = 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()
+    highest_extra_ball = int(highest_extra_ball)
+
+    numbers = set()
+
+    # Animation before displaying the results
+    with Progress(TextColumn("[progress.description]{task.description}"), BarColumn(), transient=True) as progress:
+        task = progress.add_task("Drawing numbers...", total=num_lotto_balls+1)
+        while len(numbers) < num_lotto_balls:
+            numbers = pull_number(numbers, highest_number, num_lotto_balls)
+            progress.update(task, completed=(len(numbers)/(num_lotto_balls+1)*num_lotto_balls+1))
+        megaball = pull_number(set(), highest_extra_ball, 1)
+        progress.stop()
+
+    # Print the results as styled lottery balls
+    console.print("\nLottery numbers:\n", style="bold green")
+    lottery_balls = [Text(f" {n} ", style="bold black on white") for n in sorted(numbers)]
+    bonus_ball = Text(f" {list(megaball)[0]} ", style="bold black on yellow")
+    console.print(*lottery_balls, bonus_ball, sep=" ")
+
+if __name__ == "__main__":
+    main()