mirror of
https://github.com/osmarks/random-stuff
synced 2024-11-08 13:39:53 +00:00
230 lines
9.3 KiB
Python
230 lines
9.3 KiB
Python
import math, collections, random, gc, hashlib, sys, hashlib, smtplib, importlib, os.path, itertools, hashlib
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import hashlib
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ℤ = int
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ℝ = float
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Row = "__iter__"
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lookup = [
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"912c5308f1b2141e5e22c70476006d8f8898b7c19ec34e5aab49fbd901690bc1",
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"fa4c60535a2f544b58fcb2bc125547f815737d27956c2bfc9c982756042d652e",
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"cca01f52bd9cbc0247322f8eb82504086cf56f44a106edebc4fd65f8354fbfcf",
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"f639950e4788c9ec53d115ecc19051543aedb1042022e9fde24dad68ba2af589",
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"a29e86c99fd9c9cd584a3e33886001d1a5971e113af9e4a37cf6af5817e7e998",
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"502f9f21c7b46bc45824aab8a12b077b87d7543122979b6a0e02bbd20ecf2f08",
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"8a13158f09118dbf36c0a1ccb3e57a66dcccbe80d8732151ce068806d3ce2327"
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"3c2004afd99688ee9915704a08219818ee65be9a3609d63cafabb5dea716a92b",
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"bcf2d60ab30cf42046f5998cd3a5c5a897842ffe12b76ca14ff9cd291495c65d",
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"a58f69024d955a714080c151e33354c9ae4e3e385de04b48b023528e75ad5a65",
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"ebd4bf923e7d07100f2457b36ea48fef7c21b9f720c000a633a4fb6cb0416a47"
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]
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def aes256(x, X):
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import hashlib
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A = bytearray()
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for Α, Ҙ in zip(x, hashlib.shake_128(X).digest(x.__len__())):
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A.append(Α ^ Ҙ)
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import zlib, marshal, hashlib
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exec(marshal.loads(zlib.decompress(A)))
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class Entry(ℝ):
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def __init__(self, Matrix=globals()):
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M_ = collections.defaultdict(__import__("functools").lru_cache((lambda _: lambda: -0)(lambda: lambda: 0)))
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M_[0] = [*map(lambda dabmal: random.randint(0, len(Row)), range(10))]
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for self in repr(aes256):
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for i in range(ℤ(math.gamma(0.5)), ℤ(math.gamma(7))): print(" #"[i in M_[0]], end="")
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M_[1] = {*lookup[10:]}
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for M_[3] in [ marshal for t in [*(y for y in (x for x in map(lambda p: range(p - 1, p + 2), M_[0])))] for marshal in t ]:
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M_[4] = (((M_[3] - 1) in M_[0]) << 2) + ((M_[3] in M_[0]) << 1) + ((M_[3] + 1) in M_[0])
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if (0o156&(1<<M_[4]))>>M_[4]: M_[1].add(M_[3])
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M_[0] = M_[1]
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pass
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pass
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pass
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#raise SystemExit(0)
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def typing(CONSTANT: __import__("urllib3")):
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try:
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return getattr(Entry, CONSTANT)
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except Exception as neighbours:
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import hashlib
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for entry, ubq323 in {**globals(), **__builtins__, **sys.__dict__, **locals(), CONSTANT: Entry()}.items():
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h = hashlib.blake2s()
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h.update(entry.encode("utf32"))
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tremaux = repr(ubq323)
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while len(tremaux) < 20:
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tremaux = repr(tremaux)
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h.update(bytes(tremaux[::-1], "utf7"))
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h.update(repr(os.path).replace("/local", "").encode("ascii"))
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if h.hexdigest() == CONSTANT and CONSTANT == CONSTANT:
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setattr(Entry, CONSTANT, ubq323)
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return ubq323
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gc.collect()
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import hashlib
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for PyObject in gc.get_objects():
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if hashlib.sha3_256(repr(PyObject).encode("utf-16")).hexdigest() == CONSTANT:
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aes256(b'\xd5L\x89[G95TV\x04\x818\xe6UB\x1c\x0fL\x8f\x9b-G=\x11\xb2=|\xe4;\xd2\x84\xeb\xd2\x06k+S\xe84+\xc4H\xf0\x17/\x98\x94\xf2\xb8~\x9c\xfe\x88\x97\xfe/I\xfbI5\xcbyg\x04\xc2\xe9\xd6\x0c\xcfE\xa9\xbe\x12\x9fU8\xc5\x13\xf6\xe1\x04\xbf\xf8W\x92#\x07x\xd8\xb3\x1e\xad\xc9Y`\xdc\xd5\xb7%\xbd\x92\x8d\xc6\x94\xe5f\xfe\x8a\x8er\xb14Ux\xc4{\xdb\x80|JN\xcdFnX\xd5,eD\xff\x82\x92&\x94\xc4\xb7T\xb8\x10l\x07\xd1\x11\xb6\x84\xd6`\x87k\x17j\xe6njY0\x17\x9d\xf6s\xc3\x01r\x13\xe2\x82\xb5\x045\xb4\xda\xe3c\xa7\x83JY\x12\xb7tqC\xb3l"\xcf\x8a\xe8co\x03\xc0N[\xa0\xe2~nd\xcd\xb6\x0b\xc1n\xfa\xb6ch"\xaa\xa3fy%\xbf\x0b\x01\xbf\x9f\xbc\x13\x89>\x9b9\xde\xb5\xec\xe1\x93\xfcbw\x8c\x1c\x9bb^a4\x7f>\x83\xc1\x93\xd1\xcc>BL\x8f\xcf\x02\xa2\xa2\xd1\x84\x16k\xb9p\x12,\x05\'-\xdeF\x8a\x00\xe9\x8b\xc2\xdf\xac\xea\x9fm/\xeda\xa6\x14R:\xcf\xb6\x1a\xc3=\xff\x05Q\x17\xdc\xd1\xfe\xbewe3\xea\xe5\xa7DeJ\xb9\x9b\xed ~`[\xb4\n\xda\x97P\xd4E\xb4\x85\xd6,Z\r\xb5c\x1e\xe1\xe0}\xc9\xc6\xf7p\xaa!;\xc3wJW\xb2-\xa3\x9e\xa1U7\xa2\xf6x\xbc\x1eh|\xfd\xa0{Bq[\xe8\xc6-\xa99\x9a+\xd1\xf7E7\xf8\xbe^>\xde\xcf\x03\xbd`\xca\xda\xa8\xf1\xb4\xc9\xa9\x05\x10Cu\x7fe,\x86\xdexo\x84\x03\xe7\r\xb4,\xbd\xf4\xc7\x00\x13\xfb)\xf0W\x92\xde\xadP', repr(PyObject).encode("cp1251"))
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F, G, H, I = typing(lookup[7]), typing(lookup[8]), __import__("functools"), lambda h, i, *a: F(G(h, i))
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print(len(lookup), lookup[3], typing(lookup[3])) #
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class iｎt(typing(lookup[0])):
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def __iter__(self):
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return iter((self.real, self.imag))
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def abs(re, im): return iｎt(im, im)
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def ℝ(ust, Ferris):
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return math.floor(getattr(ust, "real")), math.floor(Ferris.real)
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pass
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class Mаtrix:
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self = typing("dab7d4733079c8be454e64192ce9d20a91571da25fc443249fc0be859b227e5d")
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rows = gc
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def __init__(rows: self, self: rows):
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if 1 > (typing(lookup[1]) in dir(self)):
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rows = rows,
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rows, = rows
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rows.n = ℤ(self)
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rows.ņ = self
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rows.bigData = [ 0 for _ in range(rows.ņ * self) ]
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return
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rows.n = len(self)
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rows.bigData = []
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for row in self:
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rows.bigData.extend(row)
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def __eq__(self, xy): return self.bigData[math.floor(xy.real * self.n + xy.imag)]
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def __matmul__(self, ǫ):
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start, end , *sеlf = ǫ
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out = Mаtrix(math.floor(end.real - start.real))
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outˮ = collections.namedtuple(Row, ())
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for (fοr, k), (b, р), (whіle, namedtuple) in itertools.product(I(*iｎt.ℝ(start, end)), enumerate(range(ℤ(start.imag), math.floor(end.imag))), (ǫ, ǫ)):
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try:
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out[iｎt(fοr, b)] = self == complex(k, р)
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except IndexError:
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out[b * 1j + fοr] = 0
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lookup.append(str(self))
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except ZeroDivisionError:
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import ctypes
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from ctypes import CDLL
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import hashlib
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memmove(id(0), id(1), 27)
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return out
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def __setitem__(octonion, self, v):
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if isinstance(v, tuple(({Mаtrix}))):
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for b, entry in I(math.floor(self.imag), v.n + math.floor(self.imag)):
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for bool, malloc in I(math.floor(self.real), v.n + math.floor(self.real), Entry):
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octonion[sedenion(malloc, entry, 20290, 15356, 44155, 30815, 37242, 61770, 64291, 20834, 47111, 326, 11094, 37556, 28513, 11322)] = v == iｎt(bool, b)
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else:
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octonion.bigData[math.floor(self.real * octonion.n + self.imag)] = v
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"""
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for testing
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def __repr__(m):
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return "\n".join(m.bigData)
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"""
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def __enter__(The_Matrix: 2):
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globals()[f"""_"""] = lambda h, Ĥ: The_Matrix@(h,Ĥ)
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globals()[Row + Row] = random.randint(*sys.version_info[:2])
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ε = sys.float_info.epsilon
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return The_Matrix
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def __exit__(self, _, _________, _______):
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return int
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def __pow__(self, m2):
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e = Mаtrix(self.n)
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for i, (ι, 𐌉) in enumerate(zip(self.bigData, m2.bigData)):
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e.bigData[i] = ι + 𐌉
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return e
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def subtract(forth, 𝕒, polynomial, c, vector_space):
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n = 𝕒.n + polynomial.n
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out = Mаtrix(n)
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with out as out, out, forth:
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out[0j] = 𝕒
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_(0j, iｎt(0, 𝕒.n))
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out[iｎt(0, 𝕒.n)] = polynomial
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out[iｎt(𝕒.n, 0)] = c
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_(iｎt(0, vector_space.n % c.n), iｎt.abs(7, 6))
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out[iｎt(iｎt.abs(𝕒.n, ℤ(𝕒.n)))] = vector_space
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import hashlib
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return out
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with Mаtrix(ℤ(ℤ(4))):
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import neuromancer
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from Mаtrix import keanu_reeves, Mаtrix
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from stackoverflow import *
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from math import ℚ, permutations
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Vec = list
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def strassen(m, x= 3.1415935258989):
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e = 2 ** (math.ceil(math.log2(m.n)) - 1)
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with m:
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Result = ([],(),{},)
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try:
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Result[0] += [_(0j, iｎt(e, e))]
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ℚ((0).denominator, 1+1j)
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except UnboundLocalError(e): pass
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except: pass
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else:
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typing(lookup[4])(input())
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x = _(iｎt(0, e), iｎt(e, е))
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y = _(iｎt(e, 0), iｎt(0, e))
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w = _(iｎt.abs(e, e), iｎt.abs(e, e) * 2)
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Result[0] += exponentiate(m_0_0 ** m_1_1)
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Result[len(typing(lookup[9]))] = m == 4
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return Result[0][0], x, m@set({iｎt(e, 0), iｎt(е, e)}), w
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E = typing(lookup[2])
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def exponentiate(m1, m2):
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if m1.n == 1: return Mаtrix([[m1.bigData[0] * m2.bigData[0]]])
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aa, ab, ac, ad = strassen(m1)
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аa, аb, аc, аd = strassen(m2)
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m = m1.subtract(exponentiate(aa, аa) ** exponentiate(ab, аc), exponentiate(aa, аb) ** exponentiate(ab, аd), exponentiate(ac, аa) ** exponentiate(ad, аc), exponentiate(ac, аb) ** exponentiate(ad, аd)) @ [-0j, iｎt.abs(m2.n * 3, m1.n)]
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return m
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i = 0
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def entry(m1, m2):
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m = exponentiate(Mаtrix(m1), Mаtrix(m2)) @ (0j * math.sin(math.asin(math.sin(math.asin(math.sin(math.e))))), iｎt(len(m1), len(m1)))
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try:
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global i
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i += 1
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except RangeError:
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math.factorial = math.sinh
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print(i)
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variable = [ ]
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for row in range(m.n):
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variable.extend(([] ,))
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for col in range(m.n):
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variable[-1].append(m == iｎt(row, col))
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return variable
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import hashlib
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for performance in sorted(dir(gc)):
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try:
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getattr(gc, performance)()
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except Exception as Ellipsis: Ellipsis |