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9
MANIFEST.in
Normal file
9
MANIFEST.in
Normal file
@@ -0,0 +1,9 @@
|
||||
recursive-include tests *
|
||||
recursive-include talon *
|
||||
recursive-exclude tests *.pyc *~
|
||||
recursive-exclude talon *.pyc *~
|
||||
include train.data
|
||||
include classifier
|
||||
include LICENSE
|
||||
include MANIFEST.in
|
||||
include README.rst
|
||||
97
README.md
97
README.md
@@ -1,97 +0,0 @@
|
||||
talon
|
||||
=====
|
||||
|
||||
Mailgun library to extract message quotations and signatures.
|
||||
|
||||
If you ever tried to parse message quotations or signatures you know that absense of any formatting standards in this area
|
||||
could make this task a nightmare. Hopefully this library will make your life much eathier. The name of the project is
|
||||
inspired by TALON - multipurpose robot designed to perform missions ranging from reconnaissance to combat and operate in
|
||||
a number of hostile environments. That's what a good quotations and signature parser should be like :smile:
|
||||
|
||||
Usage
|
||||
-----
|
||||
|
||||
Here's how you initialize the library and extract a reply from a text message:
|
||||
|
||||
```python
|
||||
import talon
|
||||
from talon import quotations
|
||||
|
||||
talon.init()
|
||||
|
||||
text = """Reply
|
||||
|
||||
-----Original Message-----
|
||||
|
||||
Quote"""
|
||||
|
||||
reply = quotations.extract_from(text, 'text/plain')
|
||||
reply = quotations.extract_from_plain(text)
|
||||
# reply == "Reply"
|
||||
```
|
||||
|
||||
To extract a reply from html:
|
||||
|
||||
```python
|
||||
html = """Reply
|
||||
<blockquote>
|
||||
|
||||
<div>
|
||||
On 11-Apr-2011, at 6:54 PM, Bob <bob@example.com> wrote:
|
||||
</div>
|
||||
|
||||
<div>
|
||||
Quote
|
||||
</div>
|
||||
|
||||
</blockquote>"""
|
||||
|
||||
reply = quotations.extract_from(html, 'text/html')
|
||||
reply = quotations.extract_from_html(html)
|
||||
# reply == "<html><body><p>Reply</p></body></html>"
|
||||
```
|
||||
|
||||
Often the best way is the easiest one. Here's how you can extract signature from email message without any
|
||||
machine learning fancy stuff:
|
||||
|
||||
```python
|
||||
from talon.signature.bruteforce import extract_signature
|
||||
|
||||
|
||||
message = """Wow. Awesome!
|
||||
--
|
||||
Bob Smith"""
|
||||
|
||||
text, signature = extract_signature(message)
|
||||
# text == "Wow. Awesome!"
|
||||
# signature == "--\nBob Smith"
|
||||
```
|
||||
|
||||
Quick and works like a charm 90% of the time. For other 10% you can use the power of machine learning algorithms:
|
||||
|
||||
```python
|
||||
from talon import signature
|
||||
|
||||
|
||||
message = """Thanks Sasha, I can't go any higher and is why I limited it to the
|
||||
homepage.
|
||||
|
||||
John Doe
|
||||
via mobile"""
|
||||
|
||||
text, signature = signature.extract(message, sender='john.doe@example.com')
|
||||
# text == "Thanks Sasha, I can't go any higher and is why I limited it to the\nhomepage."
|
||||
# signature == "John Doe\nvia mobile"
|
||||
```
|
||||
|
||||
For machine learning talon currently uses [PyML](http://pyml.sourceforge.net/) library to build SVM classifiers. The core of machine learning algorithm lays in ``talon.signature.learning package``. It defines a set of features to apply to a message (``featurespace.py``), how data sets are built (``dataset.py``), classifier's interface (``classifier.py``).
|
||||
|
||||
The data used for training is taken from our personal email conversations and from [ENRON](https://www.cs.cmu.edu/~enron/) dataset. As a result of applying our set of features to the dataset we provide files ``classifier`` and ``train.data`` that don't have any personal information but could be used to load trained classifier. Those files should be regenerated every time the feature/data set is changed.
|
||||
|
||||
Research
|
||||
--------
|
||||
|
||||
The library is inspired by the following research papers and projects:
|
||||
|
||||
* http://www.cs.cmu.edu/~vitor/papers/sigFilePaper_finalversion.pdf
|
||||
* http://www.cs.cornell.edu/people/tj/publications/joachims_01a.pdf
|
||||
114
README.rst
Normal file
114
README.rst
Normal file
@@ -0,0 +1,114 @@
|
||||
talon
|
||||
=====
|
||||
|
||||
Mailgun library to extract message quotations and signatures.
|
||||
|
||||
If you ever tried to parse message quotations or signatures you know that absence of any formatting standards in this area could make this task a nightmare. Hopefully this library will make your life much easier. The name of the project is inspired by TALON - multipurpose robot designed to perform missions ranging from reconnaissance to combat and operate in a number of hostile environments. That’s what a good quotations and signature parser should be like :smile:
|
||||
|
||||
Usage
|
||||
-----
|
||||
|
||||
Here’s how you initialize the library and extract a reply from a text
|
||||
message:
|
||||
|
||||
.. code:: python
|
||||
|
||||
import talon
|
||||
from talon import quotations
|
||||
|
||||
talon.init()
|
||||
|
||||
text = """Reply
|
||||
|
||||
-----Original Message-----
|
||||
|
||||
Quote"""
|
||||
|
||||
reply = quotations.extract_from(text, 'text/plain')
|
||||
reply = quotations.extract_from_plain(text)
|
||||
# reply == "Reply"
|
||||
|
||||
To extract a reply from html:
|
||||
|
||||
.. code:: python
|
||||
|
||||
html = """Reply
|
||||
<blockquote>
|
||||
|
||||
<div>
|
||||
On 11-Apr-2011, at 6:54 PM, Bob <bob@example.com> wrote:
|
||||
</div>
|
||||
|
||||
<div>
|
||||
Quote
|
||||
</div>
|
||||
|
||||
</blockquote>"""
|
||||
|
||||
reply = quotations.extract_from(html, 'text/html')
|
||||
reply = quotations.extract_from_html(html)
|
||||
# reply == "<html><body><p>Reply</p></body></html>"
|
||||
|
||||
Often the best way is the easiest one. Here’s how you can extract
|
||||
signature from email message without any
|
||||
machine learning fancy stuff:
|
||||
|
||||
.. code:: python
|
||||
|
||||
from talon.signature.bruteforce import extract_signature
|
||||
|
||||
|
||||
message = """Wow. Awesome!
|
||||
--
|
||||
Bob Smith"""
|
||||
|
||||
text, signature = extract_signature(message)
|
||||
# text == "Wow. Awesome!"
|
||||
# signature == "--\nBob Smith"
|
||||
|
||||
Quick and works like a charm 90% of the time. For other 10% you can use
|
||||
the power of machine learning algorithms:
|
||||
|
||||
.. code:: python
|
||||
|
||||
import talon
|
||||
# don't forget to init the library first
|
||||
# it loads machine learning classifiers
|
||||
talon.init()
|
||||
|
||||
from talon import signature
|
||||
|
||||
|
||||
message = """Thanks Sasha, I can't go any higher and is why I limited it to the
|
||||
homepage.
|
||||
|
||||
John Doe
|
||||
via mobile"""
|
||||
|
||||
text, signature = signature.extract(message, sender='john.doe@example.com')
|
||||
# text == "Thanks Sasha, I can't go any higher and is why I limited it to the\nhomepage."
|
||||
# signature == "John Doe\nvia mobile"
|
||||
|
||||
For machine learning talon currently uses `PyML`_ library to build SVM
|
||||
classifiers. The core of machine learning algorithm lays in
|
||||
``talon.signature.learning package``. It defines a set of features to
|
||||
apply to a message (``featurespace.py``), how data sets are built
|
||||
(``dataset.py``), classifier’s interface (``classifier.py``).
|
||||
|
||||
The data used for training is taken from our personal email
|
||||
conversations and from `ENRON`_ dataset. As a result of applying our set
|
||||
of features to the dataset we provide files ``classifier`` and
|
||||
``train.data`` that don’t have any personal information but could be
|
||||
used to load trained classifier. Those files should be regenerated every
|
||||
time the feature/data set is changed.
|
||||
|
||||
.. _PyML: http://pyml.sourceforge.net/
|
||||
.. _ENRON: https://www.cs.cmu.edu/~enron/
|
||||
|
||||
Research
|
||||
--------
|
||||
|
||||
The library is inspired by the following research papers and projects:
|
||||
|
||||
- http://www.cs.cmu.edu/~vitor/papers/sigFilePaper_finalversion.pdf
|
||||
- http://www.cs.cornell.edu/people/tj/publications/joachims_01a.pdf
|
||||
7
setup.py
7
setup.py
@@ -7,10 +7,10 @@ from setuptools import setup, find_packages
|
||||
|
||||
|
||||
setup(name='talon',
|
||||
version='1.0',
|
||||
version='1.0.2',
|
||||
description=("Mailgun library "
|
||||
"to extract message quotations and signatures."),
|
||||
long_description=open("README.md").read(),
|
||||
long_description=open("README.rst").read(),
|
||||
author='Mailgun Inc.',
|
||||
author_email='admin@mailgunhq.com',
|
||||
url='https://github.com/mailgun/talon',
|
||||
@@ -26,7 +26,8 @@ setup(name='talon',
|
||||
"html2text",
|
||||
"nose==1.2.1",
|
||||
"mock",
|
||||
"coverage"
|
||||
"coverage",
|
||||
"flanker"
|
||||
]
|
||||
)
|
||||
|
||||
|
||||
@@ -23,14 +23,49 @@ log = logging.getLogger(__name__)
|
||||
RE_FWD = re.compile("^[-]+[ ]*Forwarded message[ ]*[-]+$", re.I | re.M)
|
||||
|
||||
RE_ON_DATE_SMB_WROTE = re.compile(
|
||||
r'''
|
||||
(
|
||||
-* # could include dashes
|
||||
[ ]?On[ ].*, # date part ends with comma
|
||||
(.*\n){0,2} # splitter takes 4 lines at most
|
||||
.*(wrote|sent):
|
||||
u'(-*[ ]?({0})[ ].*({1})(.*\n){{0,2}}.*({2}):?-*)'.format(
|
||||
# Beginning of the line
|
||||
u'|'.join((
|
||||
# English
|
||||
'On',
|
||||
# French
|
||||
'Le',
|
||||
# Polish
|
||||
'W dniu',
|
||||
# Dutch
|
||||
'Op'
|
||||
)),
|
||||
# Date and sender separator
|
||||
u'|'.join((
|
||||
# most languages separate date and sender address by comma
|
||||
',',
|
||||
# polish date and sender address separator
|
||||
u'użytkownik'
|
||||
)),
|
||||
# Ending of the line
|
||||
u'|'.join((
|
||||
# English
|
||||
'wrote', 'sent',
|
||||
# French
|
||||
u'a écrit',
|
||||
# Polish
|
||||
u'napisał',
|
||||
# Dutch
|
||||
'schreef','verzond','geschreven'
|
||||
))
|
||||
))
|
||||
# Special case for languages where text is translated like this: 'on {date} wrote {somebody}:'
|
||||
RE_ON_DATE_WROTE_SMB = re.compile(
|
||||
u'(-*[ ]?({0})[ ].*(.*\n){{0,2}}.*({1})[ ].*:)'.format(
|
||||
# Beginning of the line
|
||||
'Op',
|
||||
# Ending of the line
|
||||
u'|'.join((
|
||||
# Dutch
|
||||
'schreef','verzond','geschreven'
|
||||
))
|
||||
)
|
||||
)
|
||||
''', re.VERBOSE)
|
||||
|
||||
RE_QUOTATION = re.compile(
|
||||
r'''
|
||||
@@ -66,13 +101,33 @@ RE_EMPTY_QUOTATION = re.compile(
|
||||
e*
|
||||
''', re.VERBOSE)
|
||||
|
||||
# ------Original Message------ or ---- Reply Message ----
|
||||
# With variations in other languages.
|
||||
RE_ORIGINAL_MESSAGE = re.compile(u'[\s]*[-]+[ ]*({})[ ]*[-]+'.format(
|
||||
u'|'.join((
|
||||
# English
|
||||
'Original Message', 'Reply Message',
|
||||
# German
|
||||
u'Ursprüngliche Nachricht', 'Antwort Nachricht',
|
||||
# Danish
|
||||
'Oprindelig meddelelse',
|
||||
))), re.I)
|
||||
|
||||
RE_FROM_COLON_OR_DATE_COLON = re.compile(u'(_+\r?\n)?[\s]*(:?[*]?{})[\s]?:[*]? .*'.format(
|
||||
u'|'.join((
|
||||
# "From" in different languages.
|
||||
'From', 'Van', 'De', 'Von', 'Fra',
|
||||
# "Date" in different languages.
|
||||
'Date', 'Datum', u'Envoyé'
|
||||
))), re.I)
|
||||
|
||||
SPLITTER_PATTERNS = [
|
||||
# ------Original Message------ or ---- Reply Message ----
|
||||
re.compile("[\s]*[-]+[ ]*(Original|Reply) Message[ ]*[-]+", re.I),
|
||||
RE_ORIGINAL_MESSAGE,
|
||||
# <date> <person>
|
||||
re.compile("(\d+/\d+/\d+|\d+\.\d+\.\d+).*@", re.VERBOSE),
|
||||
RE_ON_DATE_SMB_WROTE,
|
||||
re.compile('(_+\r?\n)?[\s]*(:?[*]?From|Date):[*]? .*'),
|
||||
RE_ON_DATE_WROTE_SMB,
|
||||
RE_FROM_COLON_OR_DATE_COLON,
|
||||
re.compile('\S{3,10}, \d\d? \S{3,10} 20\d\d,? \d\d?:\d\d(:\d\d)?'
|
||||
'( \S+){3,6}@\S+:')
|
||||
]
|
||||
@@ -81,7 +136,7 @@ SPLITTER_PATTERNS = [
|
||||
RE_LINK = re.compile('<(http://[^>]*)>')
|
||||
RE_NORMALIZED_LINK = re.compile('@@(http://[^>@]*)@@')
|
||||
|
||||
RE_PARANTHESIS_LINK = re.compile("\(https?://")
|
||||
RE_PARENTHESIS_LINK = re.compile("\(https?://")
|
||||
|
||||
SPLITTER_MAX_LINES = 4
|
||||
MAX_LINES_COUNT = 1000
|
||||
@@ -169,8 +224,8 @@ def process_marked_lines(lines, markers, return_flags=[False, -1, -1]):
|
||||
# long links could break sequence of quotation lines but they shouldn't
|
||||
# be considered an inline reply
|
||||
links = (
|
||||
RE_PARANTHESIS_LINK.search(lines[inline_reply.start() - 1]) or
|
||||
RE_PARANTHESIS_LINK.match(lines[inline_reply.start()].strip()))
|
||||
RE_PARENTHESIS_LINK.search(lines[inline_reply.start() - 1]) or
|
||||
RE_PARENTHESIS_LINK.match(lines[inline_reply.start()].strip()))
|
||||
if not links:
|
||||
return_flags[:] = [False, -1, -1]
|
||||
return lines
|
||||
@@ -197,7 +252,7 @@ def preprocess(msg_body, delimiter, content_type='text/plain'):
|
||||
"""Prepares msg_body for being stripped.
|
||||
|
||||
Replaces link brackets so that they couldn't be taken for quotation marker.
|
||||
Splits line in two if splitter pattern preceeded by some text on the same
|
||||
Splits line in two if splitter pattern preceded by some text on the same
|
||||
line (done only for 'On <date> <person> wrote:' pattern).
|
||||
"""
|
||||
# normalize links i.e. replace '<', '>' wrapping the link with some symbols
|
||||
@@ -213,7 +268,7 @@ def preprocess(msg_body, delimiter, content_type='text/plain'):
|
||||
msg_body = re.sub(RE_LINK, link_wrapper, msg_body)
|
||||
|
||||
def splitter_wrapper(splitter):
|
||||
"""Wrapps splitter with new line"""
|
||||
"""Wraps splitter with new line"""
|
||||
if splitter.start() and msg_body[splitter.start() - 1] != '\n':
|
||||
return '%s%s' % (delimiter, splitter.group())
|
||||
else:
|
||||
@@ -268,7 +323,7 @@ def extract_from_html(msg_body):
|
||||
then converting html to text,
|
||||
then extracting quotations from text,
|
||||
then checking deleted checkpoints,
|
||||
then deleting neccessary tags.
|
||||
then deleting necessary tags.
|
||||
"""
|
||||
|
||||
if msg_body.strip() == '':
|
||||
|
||||
@@ -49,7 +49,7 @@ RE_PHONE_SIGNATURE = re.compile(r'''
|
||||
# c - could be signature line
|
||||
# d - line starts with dashes (could be signature or list item)
|
||||
# l - long line
|
||||
RE_SIGNATURE_CANDIDAATE = re.compile(r'''
|
||||
RE_SIGNATURE_CANDIDATE = re.compile(r'''
|
||||
(?P<candidate>c+d)[^d]
|
||||
|
|
||||
(?P<candidate>c+d)$
|
||||
@@ -184,5 +184,5 @@ def _process_marked_candidate_indexes(candidate, markers):
|
||||
>>> _process_marked_candidate_indexes([9, 12, 14, 15, 17], 'clddc')
|
||||
[15, 17]
|
||||
"""
|
||||
match = RE_SIGNATURE_CANDIDAATE.match(markers[::-1])
|
||||
match = RE_SIGNATURE_CANDIDATE.match(markers[::-1])
|
||||
return candidate[-match.end('candidate'):] if match else []
|
||||
|
||||
@@ -1,13 +1,14 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
""" The module provides functions for convertion of a message body/body lines
|
||||
""" The module provides functions for conversion of a message body/body lines
|
||||
into classifiers features space.
|
||||
|
||||
The body and the message sender string are converted into unicode before
|
||||
applying features to them.
|
||||
"""
|
||||
|
||||
from talon.signature.constants import SIGNATURE_MAX_LINES
|
||||
from talon.signature.constants import (SIGNATURE_MAX_LINES,
|
||||
TOO_LONG_SIGNATURE_LINE)
|
||||
from talon.signature.learning.helpers import *
|
||||
|
||||
|
||||
@@ -20,7 +21,7 @@ def features(sender=''):
|
||||
# This one is not from paper.
|
||||
# Line is too long.
|
||||
# This one is less aggressive than `Line is too short`
|
||||
lambda line: 1 if len(line) > 60 else 0,
|
||||
lambda line: 1 if len(line) > TOO_LONG_SIGNATURE_LINE else 0,
|
||||
# Line contains email pattern.
|
||||
binary_regex_search(RE_EMAIL),
|
||||
# Line contains url.
|
||||
@@ -47,9 +48,9 @@ def apply_features(body, features):
|
||||
'''Applies features to message body lines.
|
||||
|
||||
Returns list of lists. Each of the lists corresponds to the body line
|
||||
and is constituted by the numbers of features occurances (0 or 1).
|
||||
and is constituted by the numbers of features occurrences (0 or 1).
|
||||
E.g. if element j of list i equals 1 this means that
|
||||
feature j occured in line i (counting from the last line of the body).
|
||||
feature j occurred in line i (counting from the last line of the body).
|
||||
'''
|
||||
# collect all non empty lines
|
||||
lines = [line for line in body.splitlines() if line.strip()]
|
||||
@@ -66,7 +67,7 @@ def build_pattern(body, features):
|
||||
'''Converts body into a pattern i.e. a point in the features space.
|
||||
|
||||
Applies features to the body lines and sums up the results.
|
||||
Elements of the pattern indicate how many times a certain feature occured
|
||||
Elements of the pattern indicate how many times a certain feature occurred
|
||||
in the last lines of the body.
|
||||
'''
|
||||
line_patterns = apply_features(body, features)
|
||||
|
||||
@@ -94,7 +94,7 @@ def binary_regex_match(prog):
|
||||
|
||||
|
||||
def flatten_list(list_to_flatten):
|
||||
"""Simple list comprehesion to flatten list.
|
||||
"""Simple list comprehension to flatten list.
|
||||
|
||||
>>> flatten_list([[1, 2], [3, 4, 5]])
|
||||
[1, 2, 3, 4, 5]
|
||||
@@ -155,7 +155,7 @@ def extract_names(sender):
|
||||
|
||||
|
||||
def categories_percent(s, categories):
|
||||
'''Returns category characters persent.
|
||||
'''Returns category characters percent.
|
||||
|
||||
>>> categories_percent("qqq ggg hhh", ["Po"])
|
||||
0.0
|
||||
@@ -177,7 +177,7 @@ def categories_percent(s, categories):
|
||||
|
||||
|
||||
def punctuation_percent(s):
|
||||
'''Returns punctuation persent.
|
||||
'''Returns punctuation percent.
|
||||
|
||||
>>> punctuation_percent("qqq ggg hhh")
|
||||
0.0
|
||||
|
||||
@@ -33,6 +33,16 @@ On 11-Apr-2011, at 6:54 PM, Roman Tkachenko <romant@example.com> wrote:
|
||||
eq_("Test reply", quotations.extract_from_plain(msg_body))
|
||||
|
||||
|
||||
def test_pattern_on_date_wrote_somebody():
|
||||
eq_('Lorem', quotations.extract_from_plain(
|
||||
"""Lorem
|
||||
|
||||
Op 13-02-2014 3:18 schreef Julius Caesar <pantheon@rome.com>:
|
||||
|
||||
Veniam laborum mlkshk kale chips authentic. Normcore mumblecore laboris, fanny pack readymade eu blog chia pop-up freegan enim master cleanse.
|
||||
"""))
|
||||
|
||||
|
||||
def test_pattern_on_date_somebody_wrote_date_with_slashes():
|
||||
msg_body = """Test reply
|
||||
|
||||
@@ -98,22 +108,24 @@ bla-bla - bla"""
|
||||
eq_(reply, quotations.extract_from_plain(msg_body))
|
||||
|
||||
|
||||
def test_pattern_original_message():
|
||||
msg_body = """Test reply
|
||||
def _check_pattern_original_message(original_message_indicator):
|
||||
msg_body = u"""Test reply
|
||||
|
||||
-----Original Message-----
|
||||
-----{}-----
|
||||
|
||||
Test"""
|
||||
eq_('Test reply', quotations.extract_from_plain(msg_body.format(unicode(original_message_indicator))))
|
||||
|
||||
eq_("Test reply", quotations.extract_from_plain(msg_body))
|
||||
def test_english_original_message():
|
||||
_check_pattern_original_message('Original Message')
|
||||
_check_pattern_original_message('Reply Message')
|
||||
|
||||
msg_body = """Test reply
|
||||
def test_german_original_message():
|
||||
_check_pattern_original_message(u'Ursprüngliche Nachricht')
|
||||
_check_pattern_original_message('Antwort Nachricht')
|
||||
|
||||
-----Original Message-----
|
||||
|
||||
Test"""
|
||||
|
||||
eq_("Test reply", quotations.extract_from_plain(msg_body))
|
||||
def test_danish_original_message():
|
||||
_check_pattern_original_message('Oprindelig meddelelse')
|
||||
|
||||
|
||||
def test_reply_after_quotations():
|
||||
@@ -199,6 +211,33 @@ On 04/19/2011 07:10 AM, Roman Tkachenko wrote:
|
||||
> Hello"""
|
||||
eq_("Hi", quotations.extract_from_plain(msg_body))
|
||||
|
||||
def test_with_indent():
|
||||
msg_body = """YOLO salvia cillum kogi typewriter mumblecore cardigan skateboard Austin.
|
||||
|
||||
------On 12/29/1987 17:32 PM, Julius Caesar wrote-----
|
||||
|
||||
Brunch mumblecore pug Marfa tofu, irure taxidermy hoodie readymade pariatur.
|
||||
"""
|
||||
eq_("YOLO salvia cillum kogi typewriter mumblecore cardigan skateboard Austin.", quotations.extract_from_plain(msg_body))
|
||||
|
||||
|
||||
def test_short_quotation_with_newline():
|
||||
msg_body = """Btw blah blah...
|
||||
|
||||
On Tue, Jan 27, 2015 at 12:42 PM -0800, "Company" <christine.XXX@XXX.com> wrote:
|
||||
|
||||
Hi Mark,
|
||||
Blah blah?
|
||||
Thanks,Christine
|
||||
|
||||
On Jan 27, 2015, at 11:55 AM, Mark XXX <mark@XXX.com> wrote:
|
||||
|
||||
Lorem ipsum?
|
||||
Mark
|
||||
|
||||
Sent from Acompli"""
|
||||
eq_("Btw blah blah...", quotations.extract_from_plain(msg_body))
|
||||
|
||||
|
||||
def test_pattern_date_email_with_unicode():
|
||||
msg_body = """Replying ok
|
||||
@@ -208,8 +247,8 @@ def test_pattern_date_email_with_unicode():
|
||||
eq_("Replying ok", quotations.extract_from_plain(msg_body))
|
||||
|
||||
|
||||
def test_pattern_from_block():
|
||||
msg_body = """Allo! Follow up MIME!
|
||||
def test_english_from_block():
|
||||
eq_('Allo! Follow up MIME!', quotations.extract_from_plain("""Allo! Follow up MIME!
|
||||
|
||||
From: somebody@example.com
|
||||
Sent: March-19-11 5:42 PM
|
||||
@@ -217,8 +256,70 @@ To: Somebody
|
||||
Subject: The manager has commented on your Loop
|
||||
|
||||
Blah-blah-blah
|
||||
"""
|
||||
eq_("Allo! Follow up MIME!", quotations.extract_from_plain(msg_body))
|
||||
"""))
|
||||
|
||||
def test_german_from_block():
|
||||
eq_('Allo! Follow up MIME!', quotations.extract_from_plain(
|
||||
"""Allo! Follow up MIME!
|
||||
|
||||
Von: somebody@example.com
|
||||
Gesendet: Dienstag, 25. November 2014 14:59
|
||||
An: Somebody
|
||||
Betreff: The manager has commented on your Loop
|
||||
|
||||
Blah-blah-blah
|
||||
"""))
|
||||
|
||||
def test_french_multiline_from_block():
|
||||
eq_('Lorem ipsum', quotations.extract_from_plain(
|
||||
u"""Lorem ipsum
|
||||
|
||||
De : Brendan xxx [mailto:brendan.xxx@xxx.com]
|
||||
Envoyé : vendredi 23 janvier 2015 16:39
|
||||
À : Camille XXX
|
||||
Objet : Follow Up
|
||||
|
||||
Blah-blah-blah
|
||||
"""))
|
||||
|
||||
def test_french_from_block():
|
||||
eq_('Lorem ipsum', quotations.extract_from_plain(
|
||||
u"""Lorem ipsum
|
||||
|
||||
Le 23 janv. 2015 à 22:03, Brendan xxx <brendan.xxx@xxx.com<mailto:brendan.xxx@xxx.com>> a écrit:
|
||||
|
||||
Bonjour!"""))
|
||||
|
||||
def test_polish_from_block():
|
||||
eq_('Lorem ipsum', quotations.extract_from_plain(
|
||||
u"""Lorem ipsum
|
||||
|
||||
W dniu 28 stycznia 2015 01:53 użytkownik Zoe xxx <zoe.xxx@xxx.com>
|
||||
napisał:
|
||||
|
||||
Blah!
|
||||
"""))
|
||||
|
||||
def test_danish_from_block():
|
||||
eq_('Allo! Follow up MIME!', quotations.extract_from_plain(
|
||||
"""Allo! Follow up MIME!
|
||||
|
||||
Fra: somebody@example.com
|
||||
Sendt: 19. march 2011 12:10
|
||||
Til: Somebody
|
||||
Emne: The manager has commented on your Loop
|
||||
|
||||
Blah-blah-blah
|
||||
"""))
|
||||
|
||||
def test_dutch_from_block():
|
||||
eq_('Gluten-free culpa lo-fi et nesciunt nostrud.', quotations.extract_from_plain(
|
||||
"""Gluten-free culpa lo-fi et nesciunt nostrud.
|
||||
|
||||
Op 17-feb.-2015, om 13:18 heeft Julius Caesar <pantheon@rome.com> het volgende geschreven:
|
||||
|
||||
Small batch beard laboris tempor, non listicle hella Tumblr heirloom.
|
||||
"""))
|
||||
|
||||
|
||||
def test_quotation_marker_false_positive():
|
||||
|
||||
Reference in New Issue
Block a user