NewsBlur/apps/rss_feeds/icon_importer.py

268 lines
9.2 KiB
Python
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import urllib2
import lxml.html
import scipy
import scipy.misc
import scipy.cluster
import urlparse
import struct
import operator
import BmpImagePlugin, PngImagePlugin, Image
from StringIO import StringIO
from apps.rss_feeds.models import MFeedPage, MFeedIcon
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from utils.feed_functions import timelimit, TimeoutError
HEADERS = {
'User-Agent': 'NewsBlur Favicon Fetcher - http://www.newsblur.com',
'Connection': 'close',
}
class IconImporter(object):
def __init__(self, feed, force=False):
self.feed = feed
self.force = force
self.feed_icon, _ = MFeedIcon.objects.get_or_create(feed_id=self.feed.pk)
def save(self):
if not self.force and self.feed.favicon_not_found:
# print 'Not found, skipping...'
return
if not self.force and not self.feed.favicon_not_found and self.feed_icon.icon_url:
# print 'Found, but skipping...'
return
image, image_file, icon_url = self.fetch_image_from_page_data()
if not image:
image, image_file, icon_url = self.fetch_image_from_path(force=self.force)
if image:
try:
ico_image = self.load_icon(image_file)
if ico_image: image = ico_image
except ValueError:
# print "Bad .ICO"
pass
image = self.normalize_image(image)
color = self.determine_dominant_color_in_image(image)
image_str = self.string_from_image(image)
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if (self.feed_icon.color != color or
self.feed_icon.data != image_str or
self.feed_icon.icon_url != icon_url or
self.feed_icon.not_found):
self.feed_icon.data = image_str
self.feed_icon.icon_url = icon_url
self.feed_icon.color = color
self.feed_icon.not_found = False
self.feed_icon.save()
self.feed.favicon_color = color
self.feed.favicon_not_found = False
else:
self.feed_icon.not_found = True
self.feed.favicon_not_found = True
self.feed.save()
return not self.feed.favicon_not_found
def load_icon(self, image_file, index=None):
'''
Load Windows ICO image.
See http://en.wikipedia.org/w/index.php?oldid=264332061 for file format
description.
Cribbed and modified from http://djangosnippets.org/snippets/1287/
'''
try:
image_file.seek(0)
header = struct.unpack('<3H', image_file.read(6))
except Exception, e:
return
# Check magic
if header[:2] != (0, 1):
return
# Collect icon directories
directories = []
for i in xrange(header[2]):
directory = list(struct.unpack('<4B2H2I', image_file.read(16)))
for j in xrange(3):
if not directory[j]:
directory[j] = 256
directories.append(directory)
if index is None:
# Select best icon
directory = max(directories, key=operator.itemgetter(slice(0, 3)))
else:
directory = directories[index]
# Seek to the bitmap data
image_file.seek(directory[7])
prefix = image_file.read(16)
image_file.seek(-16, 1)
if PngImagePlugin._accept(prefix):
# Windows Vista icon with PNG inside
try:
image = PngImagePlugin.PngImageFile(image_file)
except IOError:
return
else:
# Load XOR bitmap
image = BmpImagePlugin.DibImageFile(image_file)
if image.mode == 'RGBA':
# Windows XP 32-bit color depth icon without AND bitmap
pass
else:
# Patch up the bitmap height
image.size = image.size[0], image.size[1] >> 1
d, e, o, a = image.tile[0]
image.tile[0] = d, (0, 0) + image.size, o, a
# Calculate AND bitmap dimensions. See
# http://en.wikipedia.org/w/index.php?oldid=264236948#Pixel_storage
# for description
offset = o + a[1] * image.size[1]
stride = ((image.size[0] + 31) >> 5) << 2
size = stride * image.size[1]
# Load AND bitmap
image_file.seek(offset)
string = image_file.read(size)
mask = Image.fromstring('1', image.size, string, 'raw',
('1;I', stride, -1))
image = image.convert('RGBA')
image.putalpha(mask)
return image
def fetch_image_from_page_data(self):
image = None
image_file = None
content = MFeedPage.get_data(feed_id=self.feed.pk)
url = self._url_from_html(content)
if url:
image, image_file = self.get_image_from_url(url)
return image, image_file, url
def fetch_image_from_path(self, path='favicon.ico', force=False):
image = None
url = None
if not force:
url = self.feed_icon.icon_url
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if not url and self.feed.feed_link and len(self.feed.feed_link) > 6:
url = urlparse.urljoin(self.feed.feed_link, 'favicon.ico')
if not url: return None, None, None
image, image_file = self.get_image_from_url(url)
if not image:
url = urlparse.urljoin(self.feed.feed_link, '/favicon.ico')
image, image_file = self.get_image_from_url(url)
# print 'Found: %s - %s' % (url, image)
return image, image_file, url
def get_image_from_url(self, url):
# print 'Requesting: %s' % url
@timelimit(30)
def _1(url):
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try:
request = urllib2.Request(url, headers=HEADERS)
icon = urllib2.urlopen(request).read()
except Exception:
return None
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return icon
try:
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icon = _1(url)
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except TimeoutError:
return None, None
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try:
icon_file = StringIO(icon)
image = Image.open(icon_file)
except (IOError, ValueError):
return None, None
return image, icon_file
def _url_from_html(self, content):
url = None
if not content: return url
try:
icon_path = lxml.html.fromstring(content).xpath(
'//link[@rel="icon" or @rel="shortcut icon"]/@href'
)
except (lxml.etree.ParserError, TypeError):
return url
if icon_path:
if str(icon_path[0]).startswith('http'):
url = icon_path[0]
else:
url = urlparse.urljoin(self.feed.feed_link, icon_path[0])
return url
def normalize_image(self, image):
# if image.size != (16, 16):
# image = image.resize((16, 16), Image.BICUBIC)
if image.mode != 'RGBA':
try:
image = image.convert('RGBA')
except IOError:
pass
return image
def determine_dominant_color_in_image(self, image):
NUM_CLUSTERS = 5
# Convert image into array of values for each point.
ar = scipy.misc.fromimage(image)
shape = ar.shape
# Reshape array of values to merge color bands. [[R], [G], [B], [A]] => [R, G, B, A]
if len(shape) > 2:
ar = ar.reshape(scipy.product(shape[:2]), shape[2])
# Get NUM_CLUSTERS worth of centroids.
codes, _ = scipy.cluster.vq.kmeans(ar, NUM_CLUSTERS)
# Pare centroids, removing blacks and whites and shades of really dark and really light.
original_codes = codes
for low, hi in [(60, 200), (35, 230), (10, 250)]:
codes = scipy.array([code for code in codes
if not ((code[0] < low and code[1] < low and code[2] < low) or
(code[0] > hi and code[1] > hi and code[2] > hi))])
if not len(codes): codes = original_codes
else: break
# Assign codes (vector quantization). Each vector is compared to the centroids
# and assigned the nearest one.
vecs, _ = scipy.cluster.vq.vq(ar, codes)
# Count occurences of each clustered vector.
counts, bins = scipy.histogram(vecs, len(codes))
# Show colors for each code in its hex value.
# colors = [''.join(chr(c) for c in code).encode('hex') for code in codes]
# total = scipy.sum(counts)
# print dict(zip(colors, [count/float(total) for count in counts]))
# Find the most frequent color, based on the counts.
index_max = scipy.argmax(counts)
peak = codes[index_max]
color = ''.join(chr(c) for c in peak).encode('hex')
return color[:6]
def string_from_image(self, image):
output = StringIO()
image.save(output, 'png', quality=95)
contents = output.getvalue()
output.close()
return contents.encode('base64')