fixing company_news_rh() function to comply with API update

EVEprosper · Aug 16, 2017 · 96d72f6 · 96d72f6
1 parent a9e6d3f
commit 96d72f6
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Showing 2 changed files with 12 additions and 12 deletions.
diff --git a/tests/schemas/stocks/rh_news.schema b/tests/schemas/stocks/rh_news.schema
@@ -9,10 +9,13 @@
         "summary": {"type":"string"},
         "api_source": {"type":"string", "enum":["yahoo_finance", "seeking_alpha"]},
         "updated_at": {"type":"string"},
-        "instrument": {"type":"string", "format":"uri"}
+        "instrument": {"type":"string", "format":"uri"},
+        "num_clicks": {"type":"integer"},
+        "uuid": {"type":"null"}
     },
     "requires": [
         "url", "title", "source", "published_at", "author", 
-        "summary", "api_source", "updated_at", "instrument"],
+        "summary", "api_source", "updated_at", "instrument", 
+        "num_clicks", "uuid"],
     "additionalProperties": false
 }
diff --git a/tests/test_stocks_news.py b/tests/test_stocks_news.py
@@ -177,6 +177,10 @@ class TestCompanyNewsRobinhood:
     """validate behavior for news.fetch_company_news_rh()"""
     good_ticker = helpers.CONFIG.get('STOCKS', 'good_ticker')
     bad_ticker = helpers.CONFIG.get('STOCKS', 'bad_ticker')
+    expected_news_cols = [
+        'api_source', 'author', 'instrument', 'num_clicks', 'published_at',
+        'source', 'summary', 'title', 'updated_at', 'url', 'uuid'
+    ]
 
     @pytest.mark.long
     def test_default_happypath(self):
@@ -225,11 +229,7 @@ def test_company_news_rh_happypath(self):
 
         assert isinstance(all_news_df, pandas.DataFrame)
 
-        expected_cols = [
-            'api_source', 'author', 'instrument', 'published_at',
-            'source', 'summary', 'title', 'updated_at', 'url'
-        ]
-        assert list(all_news_df.columns.values) == expected_cols
+        assert list(all_news_df.columns.values) == self.expected_news_cols
 
     @pytest.mark.long
     def test_vader_application(self):
@@ -239,10 +239,7 @@ def test_vader_application(self):
 
         graded_news = utils.vader_sentiment(all_news_df, 'title')
 
-        expected_cols = [
-            'api_source', 'author', 'instrument', 'published_at',
-            'source', 'summary', 'title', 'updated_at', 'url',
-            'neu', 'pos', 'compound', 'neg'
-        ]
+        expected_cols = self.expected_news_cols
+        expected_cols.extend(['neu', 'pos', 'compound', 'neg'])
 
         assert list(graded_news.columns.values) == expected_cols