Really PEP8ify

Broke the API, but it's now fully compliant (AFAIK)

README.md

@@ -3,10 +3,11 @@ historical data from Yahoo! Finance. It's perfect for developers who can't
 afford the (often high) prices charged by many stock data APIs.
 
 # Requirements
-* Python 3.6+
+* Python 3.5+
 * Beautiful Soup 4
 
 # Installation
+
     pip3 install stockquotes
 
 # Usage
@@ -20,15 +21,15 @@ parameter is the ticker symbol to look up.
     kroger = stockquotes.Stock('KR')
 
 ## Basic data
-To get the current price of a share, get the `Stock`'s `currentPrice`.
+To get the current price of a share, get the `Stock`'s `current_price`.
 
-    krogerPrice = kroger.currentPrice
+    krogerPrice = kroger.current_price
 
-To get the day gain in dollars, get the `Stock`'s `increaseDollars`.
+To get the day gain in dollars, get the `Stock`'s `increase_dollars`.
 
-    krogerGainDollars = kroger.increaseDollars
+    krogerGainDollars = kroger.increase_dollars
 
-The same value as a percent is available in the `increasePercent` property. To
+The same value as a percent is available in the `increase_percent` property. To
 indicate losses, these values are negative.
 
 ## Historical data
@@ -37,10 +38,10 @@ The historical data for a stock can be accessed through the `Stock`'s
 representing the most recent quote. The `dict`'s `date` property is a
 `datetime` object representing the date the quote is from. `open` is the
 opening price for that day. `high` and `low` are the high and low prices,
-respectively, for that day. `close` and `adjClose` are the closing price. The
+respectively, for that day. `close` and `adjusted_close` are the closing
-difference is that `adjClose` is adjusted for splits and dividends, whereas
+price. The difference is that `adjClose` is adjusted for splits and
-`close` is adjusted only for splits. `volume` is the stock's volume for that
+dividends, whereas `close` is adjusted only for splits. `volume` is the
-day.
+stock's volume for that day.
 
 Typically, this should give at least a month of data. Obviously, it gives less
 for recent IPOs. Also, a known but unexplained bug causes it to only give two
@@ -78,4 +79,3 @@ ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
 OTHER DEALINGS IN THE SOFTWARE.
 
 For more information, please refer to <https://unlicense.org/>
-

stockquotes/__init__.py

@@ -67,26 +67,28 @@ class Stock:
                         "high": float(row[2].span.string.replace(',', '')),
                         "low": float(row[3].span.string.replace(',', '')),
                         "close": float(row[4].span.string.replace(',', '')),
-                        "adjClose": float(row[5].span.string.replace(',', '')),
+                        "adjusted_close": float(
+                                row[5].span.string.replace(',', '')),
                         "volume": int(row[6].span.string.replace(',', ''))
                     }
                 except:
                     continue
-                self.historical.append(parsed)
-            topData = soup.find(id='quote-header-info')
-            try:
-                self.currentPrice = float(
-                        topData.findAll('span')[11].string.replace(',', ''))
-                rawChange = topData.findAll('span')[12].string
-            except IndexError:
-                self.currentPrice = float(
-                        topData.findAll('span')[3].string.replace(',', ''))
-                rawChange = topData.findAll('span')[4].string
 
-            self.increaseDollars = float(
+                self.historical.append(parsed)
-                    rawChange.split(' ')[0].replace(',', ''))
+            top_data = soup.find(id='quote-header-info')
-            self.increasePercent = float(
+            try:
-                    rawChange.split(' ')[1]\
+                self.current_price = float(
+                        top_data.findAll('span')[11].string.replace(',', ''))
+                raw_change = top_data.findAll('span')[12].string
+            except IndexError:
+                self.current_price = float(
+                        top_data.findAll('span')[3].string.replace(',', ''))
+                raw_change = top_data.findAll('span')[4].string
+                
+            self.increase_dollars = float(
+                    raw_change.split(' ')[0].replace(',', ''))
+            self.increase_percent = float(
+                    raw_change.split(' ')[1]\
                             .replace(',', '')\
                             .replace('(', '')\
                             .replace(')', '')\