flask_jsondash/data_utils/wordcloud.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
flask_jsondash.data_utils.wordcloud
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Utilities for working with wordcloud formatted data.
:copyright: (c) 2016 by Chris Tabor.
:license: MIT, see LICENSE for more details.
"""
from collections import Counter
from string import punctuation
import re
import requests
from pyquery import PyQuery as Pq
# Py2/3 compat.
try:
_unicode = unicode
except NameError:
_unicode = str
# NLTK stopwords
stopwords = [
'i', 'me', 'my', 'myself', 'we', 'our', 'ours', 'ourselves', 'you', 'your',
'yours', 'yourself', 'yourselves', 'he', 'him', 'his', 'himself', 'she',
'her', 'hers', 'herself', 'it', 'its', 'itself', 'they', 'them', 'their',
'theirs', 'themselves', 'what', 'which', 'who', 'whom', 'this', 'that',
'these', 'those', 'am', 'is', 'are', 'was', 'were', 'be', 'been', 'being',
'have', 'has', 'had', 'having', 'do', 'does', 'did', 'doing', 'a', 'an',
'the', 'and', 'but', 'if', 'or', 'because', 'as', 'until', 'while', 'of',
'at', 'by', 'for', 'with', 'about', 'against', 'between', 'into',
'through', 'during', 'before', 'after', 'above', 'below', 'to', 'from',
'up', 'down', 'in', 'out', 'on', 'off', 'over', 'under', 'again',
'further', 'then', 'once', 'here', 'there', 'when', 'where', 'why',
'how', 'all', 'any', 'both', 'each', 'few', 'more', 'most', 'other',
'some', 'such', 'no', 'nor', 'not', 'only', 'own', 'same', 'so', 'than',
'too', 'very', 's', 't', 'can', 'will', 'just', 'don', 'should', 'now',
]
def get_word_freq_distribution(words):
"""Get the counted word frequency distribution of all words.
Arg:
words (list): A list of strings indicating words.
Returns:
collections.Counter: The Counter object with word frequencies.
"""
return Counter([w for w in words if w not in stopwords])
def format_4_wordcloud(words, size_multiplier=2):
"""Format words in a way suitable for wordcloud plugin.
Args:
words (list): A list 2-tuples of format: (word-string, occurences).
size_multiplier (int, optional): The size multiplier to scale
word sizing. Can improve visual display of word cloud.
Returns:
list: A list of dicts w/ appropriate keys.
"""
return [
{'text': word, 'size': size * size_multiplier}
for (word, size) in words if word
]
def url2wordcloud(url, requests_kwargs={},
exclude_punct=True,
normalized=True,
limit=None,
size=1,
min_len=None):
"""Convert the text content of a urls' html to a wordcloud config.
Args:
url (str): The url to load.
requests_kwargs (dict, optional): The kwargs to pass to the
requests library. (e.g. auth, headers, mimetypes)
exclude_punc (bool, optional): exclude punctuation
min_length (int, optional): the minimum required length, if any
limit (int, optional): the number of items to limit
(by most common), if any
normalized (bool, optional): normalize data by
lowercasing and strippping whitespace
Returns:
same value as :func:`~format_4_wordcloud`
"""
resp = requests.get(url, **requests_kwargs)
if not resp.status_code == 200:
return []
resp = Pq(resp.content).find('body').text().split(' ')
if exclude_punct:
resp = [
re.sub(r'[^a-zA-Z0-9]+', '', w) for w
in resp if w not in punctuation
]
if min_len is not None:
resp = [w for w in resp if len(w) >= min_len]
if normalized:
resp = [w.lower() for w in resp]
words = get_word_freq_distribution(resp)
if limit is not None:
words = words.most_common(limit)
else:
words = [(k, v) for k, v in words.items()]
return format_4_wordcloud(words, size_multiplier=size)