better than GPT-3?

sweet_chariot.py

import sys, itertools, functools, more_itertools
import numpy as np, os, networkx as nx
import community as community_louvain
from glob import glob
from time import time


def louvain(G, resolution):
    partition = community_louvain.best_partition(
        G, resolution=resolution, random_state=0
    )

    distribution = [
        [q for q in partition.keys() if partition[q] == p] for p in partition.values()
    ]

    return (nx.subgraph(G, mod) for mod in distribution)


def make_graph(source):
    base = nx.Graph()
    with open(source) as f:
        lines = f.readlines()
        eta = 2 * (len(lines) / 50) ** 2
        print(len(lines), eta / 60, eta / 3600)
        for line in lines:
            base = nx.compose(base, nx.complete_graph(line.split(" ")))
    return base


def center(graph):
    centralities = nx.pagerank(graph)
    return sorted(centralities.items(), key=lambda x: x[1], reverse=True)[
        len(centralities) // 2
    ][0]


def traversals(graph):
    return (
        nx.topological_sort(nx.dfs_tree(mod,center(mod))) for mod in louvain(graph, resolution=1.0)
    )


def punctuation(length, period_prob=1 / 8, paragraph_prob=1 / 30):

    periods = np.random.poisson(period_prob, length)
    paragraphs = np.random.poisson(paragraph_prob, length)
    return (
        period_count * "." + paragraph_count * "\n"
        for (period_count, paragraph_count) in zip(periods, paragraphs)
    )


if __name__ == "__main__":
    sources = sys.argv[1]
    graph = make_graph(sources)
    text = " ".join(
        set(more_itertools.collapse(zip(traversals(graph), punctuation(len(graph)))))
    )
    with open(f"output {time()}.txt", "w") as fp:
        fp.write(text)
    with open(f"output.txt", "w") as fp:
        fp.write(text)