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8 Commits
dietz/REP-
...
v1.5.0
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a8c7e6a972 | ||
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b30c375c5b | ||
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cec5acf58f | ||
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24d0f2d00a | ||
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94007b0b92 | ||
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1a5548f171 | ||
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53c49b9121 | ||
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bd50872043 |
@@ -6,6 +6,6 @@ joblib
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lxml>=2.3.3
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numpy
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regex>=1
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scikit-learn==0.24.1 # pickled versions of classifier, else rebuild
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scikit-learn>=1.0.0
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scipy
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six>=1.10.0
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16
setup.py
16
setup.py
@@ -29,7 +29,7 @@ class InstallCommand(install):
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setup(name='talon',
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version='1.4.8',
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version='1.5.0',
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description=("Mailgun library "
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"to extract message quotations and signatures."),
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long_description=open("README.rst").read(),
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@@ -44,21 +44,21 @@ setup(name='talon',
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include_package_data=True,
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zip_safe=True,
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install_requires=[
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"lxml>=2.3.3",
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"regex>=1",
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"lxml",
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"regex",
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"numpy",
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"scipy",
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"scikit-learn==0.24.1", # pickled versions of classifier, else rebuild
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"chardet>=1.0.1",
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"cchardet>=0.3.5",
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"scikit-learn>=1.0.0",
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"chardet",
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"cchardet",
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"cssselect",
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"six>=1.10.0",
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"six",
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"html5lib",
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"joblib",
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],
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tests_require=[
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"mock",
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"nose>=1.2.1",
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"nose",
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"coverage"
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]
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)
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@@ -193,9 +193,6 @@ RE_PARENTHESIS_LINK = re.compile("\(https?://")
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SPLITTER_MAX_LINES = 6
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MAX_LINES_COUNT = 1000
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# an extensive research shows that exceeding this limit
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# leads to excessive processing time
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MAX_HTML_LEN = 2794202
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QUOT_PATTERN = re.compile('^>+ ?')
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NO_QUOT_LINE = re.compile('^[^>].*[\S].*')
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@@ -421,25 +418,31 @@ def extract_from_html(msg_body):
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Returns a unicode string.
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"""
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msg_body_bytes = msg_body
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if isinstance(msg_body, six.text_type):
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msg_body = msg_body.encode('utf8')
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elif not isinstance(msg_body, bytes):
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msg_body = msg_body.encode('ascii')
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msg_body_bytes = msg_body.encode('utf8')
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result = _extract_from_html(msg_body)
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if isinstance(result, bytes):
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result = result.decode('utf8')
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if msg_body_bytes.strip() == b'':
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return msg_body
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msg_body_bytes = msg_body_bytes.replace(b'\r\n', b'\n')
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# Cut out xml and doctype tags to avoid conflict with unicode decoding.
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msg_body_bytes = re.sub(br"\<\?xml.+\?\>|\<\!DOCTYPE.+]\>", b"", msg_body_bytes)
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html_tree = html_document_fromstring(msg_body_bytes)
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if html_tree is None:
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return msg_body
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result = extract_from_html_tree(html_tree)
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if not result:
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return msg_body
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return result
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def _extract_from_html(msg_body):
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def extract_from_html_tree(html_tree):
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"""
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Extract not quoted message from provided html message body
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using tags and plain text algorithm.
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Cut out first some encoding html tags such as xml and doctype
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for avoiding conflict with unicode decoding
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Extract not quoted message from provided parsed html tree using tags and
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plain text algorithm.
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Cut out the 'blockquote', 'gmail_quote' tags.
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Cut Microsoft quotations.
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@@ -452,18 +455,6 @@ def _extract_from_html(msg_body):
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then checking deleted checkpoints,
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then deleting necessary tags.
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"""
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if msg_body.strip() == b'':
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return msg_body
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msg_body = msg_body.replace(b'\r\n', b'\n')
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msg_body = re.sub(br"\<\?xml.+\?\>|\<\!DOCTYPE.+]\>", "", msg_body)
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html_tree = html_document_fromstring(msg_body)
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if html_tree is None:
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return msg_body
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cut_quotations = (html_quotations.cut_gmail_quote(html_tree) or
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html_quotations.cut_zimbra_quote(html_tree) or
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html_quotations.cut_blockquote(html_tree) or
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@@ -481,7 +472,7 @@ def _extract_from_html(msg_body):
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# Don't process too long messages
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if len(lines) > MAX_LINES_COUNT:
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return msg_body
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return None
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# Collect checkpoints on each line
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line_checkpoints = [
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@@ -500,7 +491,7 @@ def _extract_from_html(msg_body):
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lines_were_deleted, first_deleted, last_deleted = return_flags
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if not lines_were_deleted and not cut_quotations:
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return msg_body
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return None
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if lines_were_deleted:
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#collect checkpoints from deleted lines
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@@ -514,7 +505,7 @@ def _extract_from_html(msg_body):
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)
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if _readable_text_empty(html_tree_copy):
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return msg_body
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return None
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# NOTE: We remove_namespaces() because we are using an HTML5 Parser, HTML
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# parsers do not recognize namespaces in HTML tags. As such the rendered
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@@ -540,7 +531,11 @@ def _extract_from_html(msg_body):
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# of replacing data outside the <tag> which might be essential to
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# the customer.
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remove_namespaces(html_tree_copy)
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return html.tostring(html_tree_copy)
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s = html.tostring(html_tree_copy)
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if not s:
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return None
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return s.decode('utf-8')
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def remove_namespaces(root):
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@@ -23,17 +23,14 @@ trained against, don't forget to regenerate:
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from __future__ import absolute_import
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import os
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from . import extraction
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from . extraction import extract #noqa
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from . learning import classifier
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DATA_DIR = os.path.join(os.path.dirname(__file__), 'data')
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EXTRACTOR_FILENAME = os.path.join(DATA_DIR, 'classifier')
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EXTRACTOR_DATA = os.path.join(DATA_DIR, 'train.data')
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from talon.signature import extraction
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from talon.signature.extraction import extract
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from talon.signature.learning import classifier
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def initialize():
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extraction.EXTRACTOR = classifier.load(EXTRACTOR_FILENAME,
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EXTRACTOR_DATA)
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data_dir = os.path.join(os.path.dirname(__file__), 'data')
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extractor_filename = os.path.join(data_dir, 'classifier')
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extractor_data_filename = os.path.join(data_dir, 'train.data')
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extraction.EXTRACTOR = classifier.load(extractor_filename,
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extractor_data_filename)
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Binary file not shown.
@@ -102,7 +102,7 @@ def flatten_list(list_to_flatten):
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def contains_sender_names(sender):
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'''Returns a functions to search sender\'s name or it\'s part.
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"""Returns a functions to search sender\'s name or it\'s part.
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>>> feature = contains_sender_names("Sergey N. Obukhov <xxx@example.com>")
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>>> feature("Sergey Obukhov")
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@@ -115,7 +115,7 @@ def contains_sender_names(sender):
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1
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>>> contains_sender_names("<serobnic@mail.ru>")("serobnic")
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1
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'''
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"""
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names = '( |$)|'.join(flatten_list([[e, e.capitalize()]
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for e in extract_names(sender)]))
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names = names or sender
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@@ -140,10 +140,16 @@ def extract_names(sender):
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sender = "".join([char if char.isalpha() else ' ' for char in sender])
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# Remove too short words and words from "black" list i.e.
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# words like `ru`, `gmail`, `com`, `org`, etc.
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sender = [word for word in sender.split() if len(word) > 1 and
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not word in BAD_SENDER_NAMES]
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# Remove duplicates
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names = list(set(sender))
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names = list()
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for word in sender.split():
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if len(word) < 2:
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continue
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if word in BAD_SENDER_NAMES:
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continue
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if word in names:
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continue
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names.append(word)
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return names
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@@ -208,20 +214,26 @@ def many_capitalized_words(s):
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def has_signature(body, sender):
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'''Checks if the body has signature. Returns True or False.'''
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"""Checks if the body has signature. Returns True or False."""
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non_empty = [line for line in body.splitlines() if line.strip()]
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candidate = non_empty[-SIGNATURE_MAX_LINES:]
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upvotes = 0
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sender_check = contains_sender_names(sender)
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for line in candidate:
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# we check lines for sender's name, phone, email and url,
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# those signature lines don't take more then 27 lines
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if len(line.strip()) > 27:
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continue
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elif contains_sender_names(sender)(line):
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if sender_check(line):
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return True
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elif (binary_regex_search(RE_RELAX_PHONE)(line) +
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binary_regex_search(RE_EMAIL)(line) +
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binary_regex_search(RE_URL)(line) == 1):
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if (binary_regex_search(RE_RELAX_PHONE)(line) +
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binary_regex_search(RE_EMAIL)(line) +
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binary_regex_search(RE_URL)(line) == 1):
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upvotes += 1
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if upvotes > 1:
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return True
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return False
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@@ -180,9 +180,6 @@ def html_fromstring(s):
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if isinstance(s, six.text_type):
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s = s.encode('utf8')
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try:
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if html_too_big(s):
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return None
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return html5parser.fromstring(s, parser=_html5lib_parser())
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except Exception:
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pass
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@@ -194,9 +191,6 @@ def html_document_fromstring(s):
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if isinstance(s, six.text_type):
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s = s.encode('utf8')
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try:
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if html_too_big(s):
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return None
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return html5parser.document_fromstring(s, parser=_html5lib_parser())
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except Exception:
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pass
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@@ -206,12 +200,6 @@ def cssselect(expr, tree):
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return CSSSelector(expr)(tree)
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def html_too_big(s):
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if isinstance(s, six.text_type):
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s = s.encode('utf8')
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return s.count(b'<') > _MAX_TAGS_COUNT
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def _contains_charset_spec(s):
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"""Return True if the first 4KB contain charset spec
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"""
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@@ -258,7 +246,3 @@ _BLOCKTAGS = ['div', 'p', 'ul', 'li', 'h1', 'h2', 'h3']
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_HARDBREAKS = ['br', 'hr', 'tr']
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_RE_EXCESSIVE_NEWLINES = re.compile("\n{2,10}")
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# an extensive research shows that exceeding this limit
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# might lead to excessive processing time
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_MAX_TAGS_COUNT = 419
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@@ -391,18 +391,6 @@ def test_gmail_forwarded_msg():
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eq_(RE_WHITESPACE.sub('', msg_body), RE_WHITESPACE.sub('', extracted))
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@patch.object(u, '_MAX_TAGS_COUNT', 4)
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def test_too_large_html():
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msg_body = 'Reply' \
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'<div class="gmail_quote">' \
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'<div class="gmail_quote">On 11-Apr-2011, at 6:54 PM, Bob <bob@example.com> wrote:' \
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'<div>Test</div>' \
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'</div>' \
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'</div>'
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eq_(RE_WHITESPACE.sub('', msg_body),
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RE_WHITESPACE.sub('', quotations.extract_from_html(msg_body)))
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def test_readable_html_empty():
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msg_body = """
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<blockquote>
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@@ -125,39 +125,13 @@ def test_html_fromstring_exception():
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eq_(None, u.html_fromstring("<html></html>"))
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@patch.object(u, 'html_too_big', Mock())
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@patch.object(u.html5parser, 'fromstring')
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def test_html_fromstring_too_big(fromstring):
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eq_(None, u.html_fromstring("<html></html>"))
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assert_false(fromstring.called)
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@patch.object(u.html5parser, 'document_fromstring')
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def test_html_document_fromstring_exception(document_fromstring):
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document_fromstring.side_effect = Exception()
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eq_(None, u.html_document_fromstring("<html></html>"))
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@patch.object(u, 'html_too_big', Mock())
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@patch.object(u.html5parser, 'document_fromstring')
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def test_html_document_fromstring_too_big(document_fromstring):
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eq_(None, u.html_document_fromstring("<html></html>"))
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assert_false(document_fromstring.called)
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@patch.object(u, 'html_fromstring', Mock(return_value=None))
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def test_bad_html_to_text():
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bad_html = "one<br>two<br>three"
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eq_(None, u.html_to_text(bad_html))
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@patch.object(u, '_MAX_TAGS_COUNT', 3)
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def test_html_too_big():
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eq_(False, u.html_too_big("<div></div>"))
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eq_(True, u.html_too_big("<div><span>Hi</span></div>"))
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@patch.object(u, '_MAX_TAGS_COUNT', 3)
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def test_html_to_text():
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eq_(b"Hello", u.html_to_text("<div>Hello</div>"))
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eq_(None, u.html_to_text("<div><span>Hi</span></div>"))
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Reference in New Issue
Block a user