"""Primary techniques for the core functionality of namebot."""
from __future__ import absolute_import
from __future__ import division
import re
from collections import defaultdict
from random import choice
from string import ascii_uppercase
# import nltk
from . import nlp
from . import normalization
from . import settings as namebot_settings
_prefixes = namebot_settings.PREFIXES
_suffixes = namebot_settings.SUFFIXES
_alphabet = namebot_settings.ALPHABET
_consonants = namebot_settings.CONSONANTS
_vowels = namebot_settings.VOWELS
_regexes = namebot_settings.regexes
[docs]def domainify(words, tld='com'):
"""Convert words into a domain format for testing domains.
Args:
words (list): List of words
tld (str, optional): The TLD (top-level domain) to use.
Returns:
list: The modified list of words.
"""
_words = []
if tld.startswith('.'):
tld = tld.replace('.', '')
for word in words:
if word.endswith(tld) and tld != '':
word = word.replace(tld, '.{}'.format(tld))
_words.append(word)
return _words
[docs]def spoonerism(words):
"""Convert a list of words formatted with the spoonerism technique.
Args:
words (list) - The list of words to operate on
Returns:
words (list) - The updated list of words
>>> spoonerism(['foo', 'bar'])
>>> ['boo', 'far']
"""
"First: [f]oo [b]ar => boo far"
new_words = []
if len(words) < 2:
raise ValueError('Need more than one word to combine')
for k, word in enumerate(words):
try:
new_words.append('{}{} {}{}'.format(
words[k + 1][0], # 2nd word, 1st letter
word[1:], # 1st word, 2nd letter to end
word[0], # 1st word, 1st letter
words[k + 1][1:])) # 2nd word, 2nd letter to end
except IndexError:
continue
return new_words
[docs]def kniferism(words):
"""Convert a list of words formatted with the kniferism technique.
Args:
words (list) - The list of words to operate on
Returns:
words (list) - The updated list of words
>>> kniferism(['foo', 'bar'])
>>> ['fao', 'bor']
"""
"Mid: f[o]o b[a]r => fao bor"
if len(words) < 2:
raise ValueError('Need more than one word to combine')
new_words = []
for k, word in enumerate(words):
try:
middle_second = int(len(words[k + 1]) / 2)
middle_first = int(len(word) / 2)
new_words.append('{}{}{} {}{}{}'.format(
word[:middle_first],
words[k + 1][middle_second],
word[middle_first + 1:],
words[k + 1][:middle_second],
word[middle_first],
words[k + 1][middle_second + 1:]))
except IndexError:
continue
return new_words
[docs]def forkerism(words):
"""Convert a list of words formatted with the forkerism technique.
Args:
words (list) - The list of words to operate on
Returns:
words (list) - The updated list of words
>>> forkerism(['foo', 'bar'])
>>> ['for', 'bao']
"""
"Last: fo[o] ba[r] => for bao"
if len(words) < 2:
raise ValueError('Need more than one word to combine')
new_words = []
for k, word in enumerate(words):
try:
s_word = words[k + 1]
s_word_len = len(s_word)
f_word_len = len(word)
f_w_last_letter = word[f_word_len - 1]
s_w_last_letter = words[k + 1][s_word_len - 1]
new_words.append('{}{} {}{}'.format(
word[:f_word_len - 1], # 1st word, 1st letter to last - 1
s_w_last_letter, # 2nd word, last letter
s_word[:s_word_len - 1], # 2nd word, 1st letter to last - 1
f_w_last_letter)) # 1st word, last letter
except IndexError:
continue
return new_words
[docs]def reduplication_ablaut(words, count=1, random=True, vowel='e'):
"""A technique to combine words and altering the vowels.
e.g ch[i]t-ch[a]t, d[i]lly, d[a]lly.
See http://phrases.org.uk/meanings/reduplication.html.
"""
if len(words) < 2:
raise ValueError('Need more than one word to combine')
new_words = []
substitution = choice(_vowels) if random else vowel
for word in words:
second = re.sub(r'a|e|i|o|u', substitution, word, count=count)
# Only append if the first and second are different.
if word != second:
new_words.append('{} {}'.format(word, second))
return new_words
[docs]def prefixify(words):
"""Apply a prefix technique to a set of words.
Args:
words (list) - The list of words to operate on.
Returns:
new_arr (list): the updated *fixed words
"""
new_arr = []
for word in words:
if not word:
continue
for prefix in _prefixes:
first_prefix_no_vowel = re.search(
_regexes['no_vowels'], word[0])
second_prefix_no_vowel = re.search(
_regexes['no_vowels'], prefix[0])
if first_prefix_no_vowel or second_prefix_no_vowel:
# if there's a vowel at the end of
# prefix but not at the beginning
# of the word (or vice versa)
vowel_beginning = re.search(r'a|e|i|o|u', prefix[-1:])
vowel_end = re.search(r'^a|e|i|o|u', word[:1])
if vowel_beginning or vowel_end:
new_arr.append('{}{}'.format(prefix, word))
return new_arr
[docs]def suffixify(words):
"""Apply a suffix technique to a set of words.
Args:
words (list) - The list of words to operate on.
(e.g -> chard + ard = chardard -> chard)
Returns:
new_arr (list): the updated *fixed words
"""
new_arr = []
for word in words:
if not word:
continue
for suffix in _suffixes:
prefix_start_vowel = re.search(_regexes['all_vowels'], word[0])
suffix_start_vowel = re.search(_regexes['all_vowels'], suffix[0])
if prefix_start_vowel or suffix_start_vowel:
if suffix is 'ify':
if word[-1] is 'e':
if word[-2] is not 'i':
new_arr.append('{}{}'.format(word[:-2], suffix))
else:
new_arr.append('{}{}'.format(word[:-1], suffix))
new_arr.append(word + suffix)
else:
new_arr.append(word + suffix)
return new_arr
[docs]def duplifixify(words):
"""Apply a duplifix technique to a set of words (e.g: teeny weeny, etc...).
Args:
words (list) - The list of words to operate on.
Returns:
new_arr (list): the updated *fixed words
"""
new_arr = []
for word in words:
if not word:
continue
for letter in _alphabet:
# check if the first letter is NOT the same as the second letter,
# or the combined word is not a duplicate of the first.
duplicate_word = '{}{}'.format(letter, word[1:]) == word
if word[0] is not letter and not duplicate_word:
new_arr.append('{} {}{}'.format(word, letter, word[1:]))
return new_arr
[docs]def disfixify(words, replaces=1):
"""Apply a disfix technique to a set of words.
Disfixing is done by removing the first set of vowel-consonant pairs.
Args:
words (list) - The list of words to operate on.
replaces (int, optional): Number of replacements
to make on this string.
Returns:
new_arr (list): the updated *fixed words
"""
new_arr = []
vc_combo = r'[a-zA-Z][aeiou]{1}[qwrtypsdfghjklzxcvbnm]{1}'
for word in words:
if len(re.findall(vc_combo, word)) > 1:
new_arr.append(re.sub(vc_combo, '', word, replaces))
else:
new_arr.append(word)
return new_arr
[docs]def infixify(words):
"""Apply a infix technique to a set of words.
Adds all consonant+vowel pairs to all inner matching vowel+consonant pairs
of a word, giving all combinations for each word.
Args:
words (list) - The list of words to operate on.
Returns:
new_arr (list): the updated *fixed words
"""
new_arr = []
vc_combo_pair = re.compile(
r'[a-zA-Z][aeiou]{1}[qwrtypsdfghjklzxcvbnm]{1}[aeiou]'
'{1}[qwrtypsdfghjklzxcvbnm]{1}')
for word in words:
matches = re.findall(vc_combo_pair, word)
if matches:
for match in matches:
for infix_pair in namebot_settings.CV_TL_PAIRS:
# Get midpoint of this string.
mid = len(match) // 2
# Get the left and right substrings to join with.
first, second = match[0:mid], match[mid:]
# Check if the infix_pair is the same as start, or end.
bad_matches = [
# Duplicates joined is bad.
infix_pair == first, infix_pair == second,
# Matching letters on start/end joining substrings
# is bad.
first[-1] == infix_pair[0],
# Matching letters on end/start joining substrings
# is also bad.
first[0] == infix_pair[-1],
]
# Skip bad 'fusings'
if any(bad_matches):
continue
replacer = '{}{}{}'.format(first, infix_pair, second)
new_arr.append(word.replace(match, replacer))
else:
new_arr.append(word)
return new_arr
[docs]def simulfixify(words, pairs=None, max=5):
"""Generate simulfixed words.
Args:
words (list) - List of words to operate on.
pairs (list, optional) - Simulfix pairs to use for each word.
If not specified, these will be generated
randomly as vowel + consonant strings.
max (int, optional): The number of simulfix pairs to generate
(if pairs is not specified.)
Returns:
results (list) - The simulfix version of each word,
for each simulfix pair.
"""
results = []
if pairs is None:
pairs = ['{}{}'.format(choice(_vowels), choice(_consonants))
for _ in range(max)]
for word in words:
for combo in pairs:
mid = len(word) // 2
_word = '{}{}{}'.format(word[0:mid], combo, word[mid:])
results.append(_word)
return results
[docs]def palindrome(word):
"""Create a palindrome from a word.
Args:
word (str): The word.
Returns:
str: The updated palindrome.
"""
return '{}{}'.format(word, word[::-1])
[docs]def palindromes(words):
"""Convert a list of words into their palindromic form.
Args:
words (list): The words.
Returns:
list: The list of palindromes.
"""
return [palindrome(word) for word in words]
[docs]def make_founder_product_name(founder1, founder2, product):
"""Get the name of two people forming a company and combine it."""
return '{} & {} {}'.format(
founder1[0].upper(),
founder2[0].upper(),
product)
[docs]def make_name_alliteration(word_array, divider=' '):
"""Make an alliteration with a set of words, if applicable.
Examples:
java jacket
singing sally
earth engines
...etc
1. Loop through a given array of words
2. group by words with the same first letter
3. combine them and return to new array
"""
new_arr = []
word_array = sorted(word_array)
for word1 in word_array:
for word2 in word_array:
if word1[:1] is word2[:1] and word1 is not word2:
new_arr.append(word1 + divider + word2)
return new_arr
[docs]def make_name_abbreviation(words):
"""Will make some kind of company acronym.
eg: BASF, AT&T, A&W
Returns a single string of the new word combined.
"""
return ''.join([word[:1].upper() for word in words])
[docs]def make_vowel(words, vowel_type, vowel_index):
"""Primary for all Portmanteau generators.
This creates the portmanteau based on :vowel_index, and :vowel_type.
The algorithm works as following:
It looks for the first occurrence of a specified vowel in the first word,
then gets the matching occurrence (if any) of the second word,
then determines which should be first or second position, based on
the ratio of letters (for each word) divided by the position of the vowel
in question (e.g. c[a]t (2/3) vs. cr[a]te (3/5)).
The higher number is ordered first, and the two words are then fused
together by the single matching vowel.
"""
new_arr = []
for i in words:
for j in words:
is_match_i = re.search(vowel_type, i)
is_match_j = re.search(vowel_type, j)
if i is not j and is_match_i and is_match_j:
# get the indices and lengths to use in finding the ratio
pos_i = i.index(vowel_index)
len_i = len(i)
pos_j = j.index(vowel_index)
len_j = len(j)
# If starting index is 0,
# add 1 to it so we're not dividing by zero
if pos_i is 0:
pos_i = 1
if pos_j is 0:
pos_j = 1
# Decide which word should be the
# prefix and which should be suffix
if round(pos_i / len_i) > round(pos_j / len_j):
p = i[0: pos_i + 1]
p2 = j[pos_j: len(j)]
if len(p) + len(p2) > 2:
if re.search(
_regexes['all_vowels'], p) or re.search(
_regexes['all_vowels'], p2):
if p[-1] is p2[0]:
new_arr.append(p[:-1] + p2)
else:
new_arr.append(p + p2)
return new_arr
[docs]def make_portmanteau_default_vowel(words):
"""Make a portmanteau based on vowel matches.
E.g. (ala Brad+Angelina = Brangelina)
Only matches for second to last letter
in first word and matching vowel in second word.
This defers to the make_vowel function for all the internal
magic, but is a helper in that it provides all types of vowel
combinations in one function.
"""
new_arr = []
vowel_a_re = re.compile(r'a{1}')
vowel_e_re = re.compile(r'e{1}')
vowel_i_re = re.compile(r'i{1}')
vowel_o_re = re.compile(r'o{1}')
vowel_u_re = re.compile(r'u{1}')
new_arr += make_vowel(words, vowel_a_re, 'a')
new_arr += make_vowel(words, vowel_e_re, 'e')
new_arr += make_vowel(words, vowel_i_re, 'i')
new_arr += make_vowel(words, vowel_o_re, 'o')
new_arr += make_vowel(words, vowel_u_re, 'u')
return new_arr
[docs]def make_portmanteau_split(words):
"""Make a portmeanteau, split by vowel/consonant combos.
Based on the word formation of nikon: [ni]pp[on] go[k]aku,
which is comprised of Nippon + Gokaku.
We get the first C+V in the first word,
then last V+C in the first word,
then all C in the second word.
"""
new_arr = []
for i in words:
for j in words:
if i is not j:
l1 = re.search(r'[^a|e|i|o|u{1}]+[a|e|i|o|u{1}]', i)
l2 = re.search(r'[a|e|i|o|u{1}]+[^a|e|i|o|u{1}]$', j)
if i and l1 and l2:
# Third letter used for
# consonant middle splits only
l3 = re.split(r'[a|e|i|o|u{1}]', i)
l1 = l1.group(0)
l2 = l2.group(0)
if l3 and len(l3) > 0:
for v in l3:
new_arr.append(l1 + v + l2)
else:
new_arr.append('{}{}{}'.format(l1, 't', l2))
new_arr.append('{}{}{}'.format(l1, 's', l2))
new_arr.append('{}{}{}'.format(l1, 'z', l2))
new_arr.append('{}{}{}'.format(l1, 'x', l2))
return new_arr
[docs]def make_punctuator(words, replace):
"""Put some hyphens or dots, or a given punctutation.
Works via :replace in the word, but only around vowels ala "del.ic.ious"
"""
def _replace(words, replace, replace_type='.'):
return [word.replace(
replace, replace + replace_type) for word in words]
hyphens = _replace(words, replace, replace_type='-')
periods = _replace(words, replace)
return hyphens + periods
[docs]def make_punctuator_vowels(words):
"""Helper function that combines all possible combinations for vowels."""
new_words = []
new_words += make_punctuator(words, 'a')
new_words += make_punctuator(words, 'e')
new_words += make_punctuator(words, 'i')
new_words += make_punctuator(words, 'o')
new_words += make_punctuator(words, 'u')
return new_words
[docs]def make_vowelify(words):
"""Chop off consonant ala nautica if second to last letter is a vowel."""
new_arr = []
for word in words:
if re.search(_regexes['all_vowels'], word[:-2]):
new_arr.append(word[:-1])
return new_arr
[docs]def make_misspelling(words):
"""Misspell a word in numerous ways, to create interesting results."""
token_groups = (
('ics', 'ix'),
('ph', 'f'),
('kew', 'cue'),
('f', 'ph'),
('o', 'ough'),
# these seem to have
# sucked in practice
('o', 'off'),
('ow', 'o'),
('x', 'ecks'),
('za', 'xa'),
('xa', 'za'),
('ze', 'xe'),
('xe', 'ze'),
('zi', 'xi'),
('xi', 'zi'),
('zo', 'xo'),
('xo', 'zo'),
('zu', 'xu'),
('xu', 'zu'),
# number based
('one', '1'),
('1', 'one'),
('two', '2'),
('2', 'two'),
('three', '3'),
('3', 'three'),
('four', '4'),
('4', 'four'),
('five', '5'),
('5', 'five'),
('six', '6'),
('6', 'six'),
('seven', '7'),
('7', 'seven'),
('eight', '8'),
('8', 'eight'),
('nine', '9'),
('9', 'nine'),
('ten', '10'),
('10', 'ten'),
('ecks', 'x'),
('spir', 'speer'),
('speer', 'spir'),
('x', 'ex'),
('on', 'awn'),
('ow', 'owoo'),
('awn', 'on'),
('awf', 'off'),
('s', 'z'),
('ce', 'ze'),
('ss', 'zz'),
('ku', 'koo'),
('trate', 'trait'),
('trait', 'trate'),
('ance', 'anz'),
('il', 'yll'),
('ice', 'ize'),
('chr', 'kr'),
# These should only be at end of word!
('er', 'r'),
('lee', 'ly'),
)
new_arr = []
for word in words:
for tokens in token_groups:
new_arr.append(word.replace(*tokens))
return normalization.uniquify(new_arr)
def _pig_latinize(word, postfix='ay'):
"""Generate standard pig latin style, with optional postfix argument."""
# Common postfixes: ['ay', 'yay', 'way']
if not type(postfix) is str:
raise TypeError('Must use a string for postfix.')
piggified = None
vowel_re = re.compile(r'(a|e|i|o|u)')
first_letter = word[0:1]
# clean up non letters
word = word.replace(r'[^a-zA-Z]', '')
if vowel_re.match(first_letter):
piggified = word + 'way'
else:
piggified = ''.join([word[1: len(word)], first_letter, postfix])
return piggified
[docs]def pig_latinize(words, postfix='ay'):
"""Pig latinize a set of words.
Args:
words (list): A list of words.
postfix (str, optional): A postfix to use. Default is `ay`.
Returns:
words (list): The updated list.
"""
return [_pig_latinize(word, postfix=postfix) for word in words]
[docs]def acronym_lastname(description, lastname):
"""Create an acronym plus the last name.
Inspiration: ALFA Romeo.
"""
desc = ''.join([word[0].upper() for word
in normalization.remove_stop_words(description.split(' '))])
return '{} {}'.format(desc, lastname)
[docs]def get_descriptors(words):
"""Group words by their NLTK part-of-speech descriptors.
Use NLTK to first grab tokens by looping through words,
then tag part-of-speech (in isolation)
and provide a dictionary with a list of each type
for later retrieval and usage.
"""
descriptors = defaultdict(list)
tokens = nltk.word_tokenize(' '.join(words))
parts = nltk.pos_tag(tokens)
# Then, push the word into the matching type
for part in parts:
descriptors[part[1]].append(part[0])
return descriptors
def _add_pos_subtypes(nouns, verbs):
"""Combine alternating verbs and nouns into a new list.
Args:
nouns (list) - List of nouns, noun phrases, etc...
verbs (list) - List of verbs, verb phrases, etc...
Returns:
words (list) - The newly combined list
"""
words = []
try:
for noun in nouns:
for verb in verbs:
words.append('{} {}'.format(noun, verb))
words.append('{} {}'.format(verb, noun))
except KeyError:
pass
return words
def _create_pos_subtypes(words):
"""Check part-of-speech tags for a noun-phrase, adding combinations if so.
If it exists, add combinations with noun-phrase + verb-phrase,
noun-phrase + verb, and noun-phrase + adverb,
for each pos type that exists.
Args:
words (list) - List of verbs, verb phrases, etc...
Returns:
new_words (list) - The newly combined list
"""
new_words = []
types = words.keys()
if 'NNP' in types:
if 'VBP' in types:
new_words += _add_pos_subtypes(words['NNP'], words['VBP'])
if 'VB' in types:
new_words += _add_pos_subtypes(words['NNP'], words['VB'])
if 'RB' in types:
new_words += _add_pos_subtypes(words['NNP'], words['RB'])
return new_words
[docs]def make_descriptors(words):
"""Make descriptor names.
Based from a verb + noun, adjective + noun combination.
Examples:
-Pop Cap,
-Big Fish,
-Red Fin,
-Cold Water (grill), etc...
Combines VBP/VB/RB, with NN/NNS
"""
return list(set(_create_pos_subtypes(words)))
[docs]def all_prefix_first_vowel(word, letters=list(ascii_uppercase)):
"""Find the first vowel in a word and prefixes with consonants.
Args:
word (str) - the word to update
letters (list) - the letters to use for prefixing.
Returns:
words (list) - All prefixed words
"""
re_vowels = re.compile(r'[aeiouy]')
matches = re.search(re_vowels, word)
if matches is None:
return [word]
words = []
vowels = ['A', 'E', 'I', 'O', 'U']
first_match = matches.start(0)
for letter in letters:
if letter not in vowels:
# If beginning letter is a vowel, don't offset the index
if first_match == 0:
words.append('{}{}'.format(letter, word))
else:
words.append('{}{}'.format(letter, word[first_match:]))
return words
[docs]def recycle(words, func, times=2):
"""Run a set of words applied to a function repeatedly.
It will re-run with the last output as the new input.
`words` must be a list, and `func` must return a list.
"""
if times > 0:
return recycle(func(words), func, times - 1)
return words
[docs]def backronym(acronym, theme, max_attempts=10):
"""Attempt to generate a backronym based on a given acronym and theme.
Args:
acronym (str): The starting acronym.
theme (str): The seed word to base other words off of.
max_attempts (int, optional): The number of attempts before failing.
Returns:
dict: The result dictionary. If a backronym was successfully generated,
the `success` key will be True, otherwise False.
"""
ret = {
'acronym': '.'.join(list(acronym)).upper(),
'backronym': '',
'words': [],
'success_ratio': 0.0,
'success': False
}
if not acronym or not theme:
return ret
all_words = set()
words = nlp._get_synset_words(theme)
_backronym = []
acronym = acronym.lower()
# Add words if they contain the same first letter
# as any in the given acronym.
cur_step = 0
while len(_backronym) < len(acronym) or cur_step < max_attempts:
all_words.update(words)
for word in words:
if word[0].lower() in acronym:
if '_' in word:
# Don't add multi-word strings, but don't leave it blank.
_backronym.append(word[0])
else:
_backronym.append(word)
sdict = {}
# Sort the word in order of the acronyms
# letters by re-arranging indices.
for word in _backronym:
try:
index = acronym.index(word[0].lower())
sdict[index] = word
except IndexError:
continue
cur_step += 1
# Refresh words for next attempt.
words = nlp._get_synset_words(theme)
# Try again if no words existed.
if not words:
continue
# Get new theme, similar to originating theme.
theme = words[0]
vals = sdict.values()
ret.update({
'backronym': ' '.join(vals).upper(),
'words': vals,
'success_ratio': float(len(vals)) / float(len(acronym)),
'success': len(vals) == len(acronym)
})
return ret
[docs]def super_scrub(data):
"""Run words through a comprehensive list of filtering functions.
Expects a dictionary with key "words"
"""
for technique in data['words']:
data['words'][technique] = normalization.uniquify(
normalization.remove_odd_sounding_words(
normalization.clean_sort(
data['words'][technique])))
return data
[docs]def generate_all_techniques(words):
"""Generate all techniques across the library in one place."""
data = {
'words': {
'alliterations': make_name_alliteration(words),
'alliterations': make_name_alliteration(words),
'portmanteau': make_portmanteau_default_vowel(words),
'vowels': make_vowelify(words),
'suffix': suffixify(words),
'prefix': prefixify(words),
'duplifix': duplifixify(words),
'disfix': disfixify(words),
'infix': infixify(words),
'simulfix': simulfixify(words),
'founder_product_name': make_founder_product_name(
'Lindsey', 'Chris', 'Widgets'),
'punctuator': make_punctuator_vowels(words),
'name_abbreviation': make_name_abbreviation(words),
'make_portmanteau_split': make_portmanteau_split(words),
'forkerism': forkerism(words),
'kniferism': kniferism(words),
'spoonerism': spoonerism(words),
'palindrome': palindromes(words),
'reduplication_ablaut': reduplication_ablaut(words),
'misspelling': make_misspelling(words),
'descriptors': make_descriptors(
get_descriptors(words))
}
}
return super_scrub(data)