59 lines
1.3 KiB
Python
59 lines
1.3 KiB
Python
import pymongo
|
|
import markovify
|
|
import sys
|
|
import random
|
|
|
|
def log(msg, err=False, tabs=0):
|
|
if (not err):
|
|
print("[*] " + "\t" * tabs + msg)
|
|
else:
|
|
print("[X] " + "\t" * tabs + msg)
|
|
|
|
def dbg(msg, tabs=0):
|
|
print("[D] " + "\t" * tabs + msg)
|
|
|
|
if (len(sys.argv) < 3):
|
|
log("Not enough arguments!", err=True)
|
|
sys.exit(1)
|
|
|
|
# Load the model for the markov chains
|
|
file = open("bee-movie.txt", "r")
|
|
text = file.read()
|
|
file.close()
|
|
|
|
# Create the model using Markov Chains
|
|
model = markovify.Text(text)
|
|
|
|
# Generate 10 levels
|
|
levels = []
|
|
vocab = list(range(1, 100))
|
|
level = 1
|
|
for i in range(10):
|
|
name = model.make_short_sentence(50, tries=100)
|
|
description = ". ".join([model.make_sentence(tries=100) for x in range(4)])
|
|
level_vocab = []
|
|
|
|
# Get random vocabulary
|
|
for v in range(4):
|
|
index = random.randint(0, len(vocab))
|
|
level_vocab.append(index)
|
|
del vocab[index]
|
|
|
|
print("{0}: {1} -> {2}".format(level, name, description))
|
|
levels.append({
|
|
"level": level,
|
|
"name": name,
|
|
"description": description,
|
|
"vocab": level_vocab
|
|
})
|
|
level += 1
|
|
|
|
log("Connecting to database...")
|
|
client = pymongo.MongoClient(sys.argv[1])
|
|
log("Getting DB...")
|
|
db = client[sys.argv[2]]
|
|
log("Inserting...")
|
|
res = db["levels"].insert_many(levels)
|
|
|
|
log("Success", tabs=1)
|