implemented keyword api

README.md

@@ -74,4 +74,6 @@ This is the wireframe that the team has been given to replicate in python using
     * define update method
     * docstrings
     * add keyword/genre to load method
+* **1 hr** implemented data.filter() method
+* **30 min** api parser/docs/keywords
     

requirements.txt

@@ -1,4 +1,5 @@
 flask
+flask-restplus
 gunicorn
 pandas
 -e git+https://github.com/WaylonWalker/iplotter.git@master#egg=iplotter

src/etl.py

@@ -14,6 +14,10 @@ class Data(object):
         """
         if data == None:
             self.load()
+        else:
+            self.movie = data.movie
+            self.genre = data.genre
+            self.keyword = data.keyword
 
     def __str__(self):
 
@@ -58,6 +62,65 @@ class Data(object):
         keyword = generate_keyword(movie)
         keyword.to_pickle(os.path.join(settings.processed_data_dir, 'keyword.pkl'))
 
+    def filter(self, start_year=None, end_year=None, 
+                     genre=None, country=None, language=None, 
+                     top=None, title=None, color=None):
+
+            """
+            Efficiently filters 
+
+            """
+            data = Data(self)
+
+            if start_year:
+                start_year_mask = data.movie.title_year > f'{str(int(start_year)-1)}-01-01'
+            else:
+                start_year_mask = True
+            if end_year:
+                end_year_mask = data.movie.title_year <= f'{str(end_year)}-01-01'
+            else:
+                end_year_mask = True
+                
+            if genre:
+                genre_indexes = data.genre[data.genre.genres == genre]['index'].values
+                genre_mask = data.movie.index.isin(genre_indexes)
+            else:
+                genre_mask = True
+
+            if country:
+                country_mask = data.movie.country == country
+            else:
+                country_mask = True
+
+            if language:
+                language_mask = data.movie.language == language
+            else:
+                language_mask = True
+
+            if title:
+                title_mask = data.movie.movie_title == title
+            else: 
+                title_mask = True
+
+            if color:
+                color_mask = data.movie.color == color
+            else:
+                color_mask = True
+            masks = genre_mask & start_year_mask & end_year_mask & country_mask & language_mask & title_mask & color_mask
+
+            try:
+                len(masks)
+            except TypeError: # object type 'bool' has no len() i.e. not a list
+                masks = [True]*len(data.movie)
+
+            data.movie = data.movie[masks].sort_values('imdb_score', ascending=False)
+            if top:
+                data.movie = data.movie.head(int(top))
+            data.genre = data.genre[data.genre['index'].isin(data.movie.index.values.tolist())]
+            data.keyword = data.keyword[data.keyword['index'].isin(data.movie.index.values.tolist())]
+
+            return data
+
 
 def generate_genre(movie):
     """

src/pyDataVizDay.py

@@ -9,9 +9,11 @@ IMDB 5000 Movie Dataset.
 import os
 import io
 import base64 as b64
+from collections import Counter
 
 from flask import Flask
-from flask import request, render_template, make_response, jsonify
+from flask import request, render_template, make_response, jsonify, Blueprint, url_for
+from flask_restplus import Resource, Api, fields, reqparse
 import settings
 import etl
 import palettes as pal
@@ -19,26 +21,25 @@ import palettes as pal
 from iplotter import C3Plotter
 c3 = C3Plotter()
 
-def fig_to_html(fig):
+app = Flask(__name__)
-    """
+api_blueprint = Blueprint('api', __name__, url_prefix='/api')
-    converts a matplotlib figure into an html image
+api = Api(api_blueprint, title='pyDataVizday api', 
+          description='This api is used for the pyDataVizDay visualization',
+          doc='/doc/')
+app.register_blueprint(api_blueprint)
+
+parser = reqparse.RequestParser()
+parser.add_argument('start_year', help='start date for data', required=False)
+parser.add_argument('end_year', help='end date for data', required=False)
+parser.add_argument('genre', help='movie genre', required=False)
+parser.add_argument('country', help='geographical country location', required=False)
+parser.add_argument('language', help='language of the movie (ex. english)', required=False)
+parser.add_argument('top', help='top n titles by imdb rating', required=False)
+parser.add_argument('title', help='title of the movie', required=False)
+parser.add_argument('color', help='"Color" or "Black and White"', required=False)
 
-    :param fig: matplotlibe figure object
-    :returns: STR html string
-    """
-    buf = io.BytesIO()
-    fig.savefig(buf, format='png')
-    img = ('<img src="data:image/png;base64,{}">'
-           .format(b64.b64encode(buf.getvalue()))
-           .replace("b'",'')
-           .replace("'",''))
-    return img
 
 data = etl.Data()
-data.load()
-
-
-app = Flask(__name__)
 
 @app.route('/')
 def index():
@@ -71,6 +72,25 @@ def slides():
     slide_body = render_template('slide_body.html')
     return render_template('slides.html', body=slide_body)
 
+@api.route('/keywords')
+@api.expect(parser)
+class keywords(Resource):
+  def get(self):
+    args = parser.parse_args()
+    keyword_data = data.filter(start_year=args['start_year'],
+                               end_year=args['end_year'],
+                               genre=args['genre'],
+                               country=args['country'],
+                               language=args['language'],
+                               top=args['top'],
+                               title=args['title'],
+                               color=args['color']
+                               )
+    c = Counter(keyword_data.keyword.plot_keywords.values.tolist())
+    words = [{'text': word[0], 'weight': word[1]} for word in c.most_common(50)]
+
+    return jsonify(words)
+
 if __name__ == '__main__':
     port = int(os.environ.get("PORT", 5000))
     app.run(host='0.0.0.0', port=port, debug=True)