Black formatting

table.py

@@ -2,30 +2,37 @@ from tabulate import tabulate
 from decimal import Decimal
 import yfi as y
 
+
 def generate_table(stonks):
     table_data = []
     total = 0
     for ticker in stonks.keys():
         price = y.get_current_price(ticker)
         shares_count = stonks[ticker]
-        table_data.append([ticker, shares_count, round(Decimal(price) * Decimal(stonks[ticker]), 2)])
-        total += (Decimal(price) * Decimal(stonks[ticker]))
+        table_data.append(
+            [ticker, shares_count, round(Decimal(price) * Decimal(stonks[ticker]), 2)]
+        )
+        total += Decimal(price) * Decimal(stonks[ticker])
 
-    table_data.append(['Total', '', round(total, 2)])
+    table_data.append(["Total", "", round(total, 2)])
 
-    return str( tabulate(table_data, ['Ticker', 'Shares', 'Value ($)'], tablefmt="pretty") )
+    return str(
+        tabulate(table_data, ["Ticker", "Shares", "Value ($)"], tablefmt="pretty")
+    )
 
 
 def watchlist_table(watchlist):
 
     table_data = []
-    header = ['Ticker', 'Current Price ($)', 'Estimated Price ($)']
+    header = ["Ticker", "Current Price ($)", "Estimated Price ($)"]
 
     for stonk in watchlist.keys():
-        table_data.append([
-            stonk,
-            y.get_current_price(stonk),
-            watchlist[stonk],
-        ])
+        table_data.append(
+            [
+                stonk,
+                y.get_current_price(stonk),
+                watchlist[stonk],
+            ]
+        )
 
-    return str( tabulate( table_data, header, tablefmt="pretty" ) )
+    return str(tabulate(table_data, header, tablefmt="pretty"))

table2.py

@@ -3,14 +3,12 @@ import matplotlib, io
 from datetime import datetime
 
 
-def generate_table(headers, data, title="", bg='skyblue', border='steelblue'):
+def generate_table(headers, data, title="", bg="skyblue", border="steelblue"):
     timestamp = datetime.now().strftime("%d/%m/%Y %H:%M:%S")
 
-    font = {'family' : 'monospace',
-        'weight' : 'normal',
-        'size'   : 12}
+    font = {"family": "monospace", "weight": "normal", "size": 12}
 
-    matplotlib.rc('font', **font)
+    matplotlib.rc("font", **font)
 
     title_text = title
     footer_text = timestamp
@@ -19,36 +17,35 @@ def generate_table(headers, data, title="", bg='skyblue', border='steelblue'):
 
     column_headers = headers
 
-
     if data:
         cell_text = []
         for row in data:
             cell_text.append([x for x in row])
     else:
-        cell_text = [["No Data"] + ["" for x in range(len(headers)-1)]]
-
+        cell_text = [["No Data"] + ["" for x in range(len(headers) - 1)]]
 
     # Create the figure. Setting a small pad on tight_layout
     # seems to better regulate white space. Sometimes experimenting
     # with an explicit figsize here can produce better outcome.
 
     dpi = 160
-    #image_height = (( 0.5 + ( 0.4125 * ( len(data) + 1) ) ) * dpi)
-    image_height = 100 + (67 * ( len(data) +1 ))
+    # image_height = (( 0.5 + ( 0.4125 * ( len(data) + 1) ) ) * dpi)
+    image_height = 100 + (67 * (len(data) + 1))
     image_width = 6 * dpi
 
-    plt.figure(linewidth=2,
-               edgecolor=fig_border,
-               facecolor=fig_background_color,
-               tight_layout={'pad':1},
-               dpi=dpi,
-               figsize=(image_width/dpi, image_height/dpi)
-              )
+    plt.figure(
+        linewidth=2,
+        edgecolor=fig_border,
+        facecolor=fig_background_color,
+        tight_layout={"pad": 1},
+        dpi=dpi,
+        figsize=(image_width / dpi, image_height / dpi),
+    )
 
     # Add a table at the bottom of the axes
-    the_table = plt.table(cellText=cell_text,
-                          colLabels=column_headers,
-                          loc='upper center')
+    the_table = plt.table(
+        cellText=cell_text, colLabels=column_headers, loc="upper center"
+    )
 
     # Scaling is the only influence we have over top and bottom cell padding.
     # Make the rows taller (i.e., make cell y scale larger).
@@ -63,10 +60,17 @@ def generate_table(headers, data, title="", bg='skyblue', border='steelblue'):
     plt.box(on=None)
 
     # Add title
-    plt.suptitle(title_text, x=0.5, y=((image_height - 15)/image_height))
+    plt.suptitle(title_text, x=0.5, y=((image_height - 15) / image_height))
 
     # Add footer
-    plt.figtext(((image_width - 15)/image_width), 1-((image_height - 15)/image_height), footer_text, horizontalalignment='right', size=12, weight='light')
+    plt.figtext(
+        ((image_width - 15) / image_width),
+        1 - ((image_height - 15) / image_height),
+        footer_text,
+        horizontalalignment="right",
+        size=12,
+        weight="light",
+    )
 
     # Force the figure to update, so backends center objects correctly within the figure.
     # Without plt.draw() here, the title will center on the axes and not the figure.
@@ -74,6 +78,6 @@ def generate_table(headers, data, title="", bg='skyblue', border='steelblue'):
 
     # Create image. plt.savefig ignores figure edge and face colors, so map them.
     image_buffer = io.BytesIO()
-    plt.savefig(image_buffer, format='png')
+    plt.savefig(image_buffer, format="png")
     image_buffer.seek(0)
     return image_buffer

yfi.py

@@ -8,21 +8,24 @@ def stock_exists(ticker):
     except KeyError:
         return False
 
+
 def get_current_price(ticker):
     yf_obj = yf.Ticker(ticker)
-    todays_data = yf_obj.history(period='1d')
-    return round(todays_data['Close'][0], 2)
+    todays_data = yf_obj.history(period="1d")
+    return round(todays_data["Close"][0], 2)
+
 
 def get_delta(ticker, return_old_price=False):
     yf_obj = yf.Ticker(ticker)
-    old_price = yf_obj.history(interval='1d')['Close'][-2]
+    old_price = yf_obj.history(interval="1d")["Close"][-2]
     current_price = get_current_price(ticker)
-    delta = 100 * ( (current_price / old_price) - 1 )
+    delta = 100 * ((current_price / old_price) - 1)
     if return_old_price:
         return delta, old_price
     else:
         return delta
 
+
 def get_delta_old_price(ticker):
     yf_obj = yf.Ticker(ticker)
-    return yf_obj.history(interval='1d')['Close'][-2]
+    return yf_obj.history(interval="1d")["Close"][-2]