m_names = json.load(open("bogus/names_m.json", "r"))
f_names = json.load(open("bogus/names_f.json", "r"))
mlen = len(m_names)
flen = len(f_names)
lipsum = "Lorem ipsum dolor sit amet, consectetur adipiscing elit. Phasellus efficitur urna nec interdum scelerisque. Quisque tempor augue at ipsum dignissim, eget pharetra ipsum ullamcorper. Proin eu eleifend enim. Nam iaculis placerat molestie. Praesent feugiat rutrum arcu eget semper. Praesent efficitur massa eu urna bibendum, sit amet efficitur sapien molestie. Ut euismod urna quis placerat aliquam. Sed elementum nunc eu posuere laoreet. Vestibulum congue eleifend convallis."
liptag = lipsum.split(" ")
imgs = []
for e in range(0, 84):
n = surnames[random.randint(0, len(surnames) - 1)]
if e % 2:
fn = m_names[random.randint(0, mlen-1)]
else:
fn = f_names[random.randint(0, flen-1)]
print("making user: %s %s" % (fn, n))
usr = User(uname=fn[:1]+n[:4], email="*****@*****.**" % (fn, n), password="******")
User.activate_account(usr)
profile = Account(usr, fname=fn, lname=n, dob=str(random.randint(1980, 2000))+"-07-06")
profile.images.append("data:image/jpeg;base64,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")
profile.tags = [liptag[random.randint(0, len(liptag) - 1)] for i in range(0, 6)]
profile.gender = ["Female", "Male"][e % 2]
profile.interest= ["Men", "Women", "Both"][random.randint(0, 2)]
profile.biography = lipsum
print("Registered user ", usr.uname)
profile.save()
