Finall the method with nltk is really slow...

4 files changed, 3 insertions, 54 deletions

diff --git a/README.rst b/README.rst
index 52a22cfd..eeb75a6d 100644
--- a/README.rst
+++ b/README.rst
@@ -69,7 +69,6 @@ The geek way
     $ cd pyaggr3g470r
     $ heroku create
     $ heroku addons:add heroku-postgresql:dev
-    $ heroku config:set BUILDPACK_URL=https://github.com/cedricbonhomme/heroku-buildpack-scipy
     $ heroku config:set HEROKU=1
     $ git push heroku master
     $ heroku run init
@@ -110,9 +109,7 @@ Deploying the application on a traditional server
 .. code:: bash
 
     $ sudo apt-get install python libpq-dev python-dev python-pip build-essential git
-    $ sudo apt-get install libatlas-base-dev gfortran # for scipy
     $ sudo apt-get install libxml2-dev libxslt1-dev # for lxml
-    $ sudo apt-get install python-nose # for scikit-learn
     $ git clone https://bitbucket.org/cedricbonhomme/pyaggr3g470r.git
     $ cd pyaggr3g470r
     $ sudo pip install --upgrade -r requirements.txt
diff --git a/pyaggr3g470r/duplicate.py b/pyaggr3g470r/duplicate.py
index 6220a3cb..23f4adc0 100644
--- a/pyaggr3g470r/duplicate.py
+++ b/pyaggr3g470r/duplicate.py
@@ -2,55 +2,15 @@
 #-*- coding: utf-8 -*-
 
 import itertools
-import nltk, string
-from sklearn.feature_extraction.text import TfidfVectorizer
-
 import utils
 
-# tokenizers/punkt/english.pickle
-
-
-stemmer = nltk.stem.porter.PorterStemmer()
-remove_punctuation_map = dict((ord(char), None) for char in string.punctuation)
-
-def stem_tokens(tokens):
-    return [stemmer.stem(item) for item in tokens]
-
-def normalize(text):
-    """
-    Remove punctuation, lowercase, stem
-    """
-    return stem_tokens(nltk.word_tokenize(text.lower().translate(remove_punctuation_map)))
-
-vectorizer = TfidfVectorizer(tokenizer=normalize, stop_words='english')
-
-def cosine_sim(article1, article2):
-    try:
-        tfidf = vectorizer.fit_transform([utils.clear_string(article1.content),
-                                        utils.clear_string(article2.content)])
-    except ValueError as e:
-        raise e
-    return ((tfidf * tfidf.T).A)[0,1]
-
 
 def compare_documents(feed):
     """
     Compare a list of documents by pair.
     """
-    downloaded = nltk.download("punkt")
-    if not downloaded:
-        #  Ubuntu packaged version still uses old URL
-        dl = nltk.downloader.Downloader("https://nltk.github.com/nltk_data/")
-        dl.download("punkt")
     duplicates = []
     for pair in itertools.combinations(feed.articles, 2):
-        try:
-            result = cosine_sim(*pair)
-            if abs(result.item() - 1.0) < 1e-10:
-                duplicates.append(pair)
-                #print pair[0].id, pair[0].title, pair[0].link
-                #print pair[1].id, pair[1].title, pair[1].link
-                #print
-        except ValueError:
-            continue
+        if pair[0].content != "" and pair[0].content == pair[1].content:
+            duplicates.append(pair)
     return duplicates
\ No newline at end of file
diff --git a/requirements.txt b/requirements.txt
index b2cae674..a9b3756f 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -17,8 +17,4 @@ WTForms
 python-postmark
 gevent
 whoosh
-python-dateutil
-nltk
-numpy==1.8.1
-scipy==0.14.0
-scikit-learn==0.13.1
\ No newline at end of file
+python-dateutil
\ No newline at end of file
diff --git a/vagrant/bootstrap.sh b/vagrant/bootstrap.sh
index 750fe4f5..f756c468 100644
--- a/vagrant/bootstrap.sh
+++ b/vagrant/bootstrap.sh
@@ -15,10 +15,6 @@ fi
 cd pyaggr3g470r

 # For lxml:

 apt-get install -y libxml2-dev libxslt1-dev

-# For scipy:

-apt-get install -y libatlas-base-dev gfortran

-# For scikit-learn:

-apt-get install -y python-nose

 # installation with pip

 sudo pip install --upgrade -r requirements.txt

 # copy of the default configuration files for vagrant