got rid of problematic function

pytrends/request.py

@@ -541,80 +541,11 @@ def categories(self):
         )
         return req_json
 
-    def get_historical_interest(self, keywords, year_start=2018, month_start=1,
-                                day_start=1, hour_start=0, year_end=2018,
-                                month_end=2, day_end=1, hour_end=0, cat=0,
-                                geo='', gprop='', sleep=0, frequency='hourly'):
-        """Gets historical hourly data for interest by chunking requests to 1 week at a time (which is what Google allows)"""
-
-        # construct datetime objects - raises ValueError if invalid parameters
-        initial_start_date = start_date = datetime(year_start, month_start,
-                                                   day_start, hour_start)
-        end_date = datetime(year_end, month_end, day_end, hour_end)
-
-        # Timedeltas:
-        # 7 days for hourly
-        # ~250 days for daily (270 seems to be max but sometimes breaks?)
-        # For weekly can pull any date range so no method required here
-
-        if frequency == 'hourly':
-            delta = timedelta(days=7)
-        elif frequency == 'daily':
-            delta = timedelta(days=250)
-        else:
-            raise(ValueError('Frequency must be hourly or daily'))
-
-        df = pd.DataFrame()
-
-        date_iterator = start_date
-        date_iterator += delta
-
-        while True:
-            # format date to comply with API call (different for hourly/daily)
-
-            if frequency == 'hourly':
-                start_date_str = start_date.strftime('%Y-%m-%dT%H')
-                date_iterator_str = date_iterator.strftime('%Y-%m-%dT%H')
-            elif frequency == 'daily':
-                start_date_str = start_date.strftime('%Y-%m-%d')
-                date_iterator_str = date_iterator.strftime('%Y-%m-%d')
-
-            tf = start_date_str + ' ' + date_iterator_str
-
-            try:
-                self.build_payload(keywords, cat, tf, geo, gprop)
-                week_df = self.interest_over_time()
-                df = pd.concat([df,week_df], ignore_index = True)
-            except Exception as e:
-                print(e)
-                pass
-
-            start_date += delta
-            date_iterator += delta
-
-            if (date_iterator > end_date):
-                # Run more days to get remaining data that would have been truncated if we stopped now
-                if frequency == 'hourly':
-                    start_date_str = start_date.strftime('%Y-%m-%dT%H')
-                    date_iterator_str = date_iterator.strftime('%Y-%m-%dT%H')
-                elif frequency == 'daily':
-                    start_date_str = start_date.strftime('%Y-%m-%d')
-                    date_iterator_str = date_iterator.strftime('%Y-%m-%d')
-
-                tf = start_date_str + ' ' + date_iterator_str
-
-                try:
-                    self.build_payload(keywords, cat, tf, geo, gprop)
-                    week_df = self.interest_over_time()
-                    df = pd.concat([df,week_df] ,ignore_index = True)
-                except Exception as e:
-                    print(e)
-                    pass
-                break
-
-            # just in case you are rate-limited by Google. Recommended is 60 if you are.
-            if sleep > 0:
-                time.sleep(sleep)
-
-        # Return the dataframe with results from our timeframe
-        return df.loc[initial_start_date:end_date]
+    def get_historical_interest(self, *args, **kwargs):
+        raise NotImplementedError(
+            """This method has been removed for incorrectness. It will be removed completely in v5.
+If you'd like similar functionality, please try implementing it yourself and consider submitting a pull request to add it to pytrends.
+
+There is discussion at:
+https://github.com/GeneralMills/pytrends/pull/542"""
+        )