From 7a27f2ff118cf2204000c4c3a6049722ef9baa7b Mon Sep 17 00:00:00 2001
From: Matt Chan <thewchan@gmail.com>
Date: Thu, 25 Jun 2020 14:30:47 -0700
Subject: [PATCH] Added bokeh plot builder.

---
 ticker.py | 111 ++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 111 insertions(+)
 create mode 100644 ticker.py

diff --git a/ticker.py b/ticker.py
new file mode 100644
index 000000000..4e6228676
--- /dev/null
+++ b/ticker.py
@@ -0,0 +1,111 @@
+"""Render the bokeh visualization of the stock time series."""
+import json
+import pandas as pd
+import requests
+import sys
+import bokeh.plotting as bkp
+from bokeh.embed import json_item
+from bokeh.models import HoverTool
+from bokeh.models.tickers import DatetimeTicker
+
+
+KEY = 'Q7JC95BEFD22FQDA'
+
+
+def get_data(symbol):
+    """Get stock data given symbol from api, return json."""
+    url = (f"https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&"
+           f"symbol={symbol}&apikey={KEY}")
+    response = requests.get(url)
+    data = response.json()
+
+    return data
+
+
+def get_df(data):
+    """Return formatted dataframe from json data."""
+    df = pd.DataFrame(data['Time Series (Daily)']).T
+    df.index = pd.to_datetime(df.index)
+    df = df.sort_index().copy()
+    df.columns = df.columns.str.replace(r'\d+\.\s', '')
+    df.columns = map(str.title, df.columns)
+    df = df.drop('Volume', axis=1).astype(float).copy()
+
+    return df
+
+
+def ticker(symbol):
+    """Render the boken html file."""
+    data = get_data(symbol)
+    df = get_df(data)
+
+    monthago = df.index[-20]
+    now = df.index[-1]
+    high = df.loc[monthago:now].max().max() + 5
+    low = df.loc[monthago:now].min().min() - 5
+
+    p = bkp.figure(title=f'{symbol} Stock Price',
+                   y_axis_label='Dollars',
+                   x_axis_type='datetime',
+                   plot_width=800,
+                   plot_height=400,
+                   x_range=(monthago, now),
+                   y_range=(low, high),
+                   toolbar_location="below",
+                   tools="pan,box_zoom,wheel_zoom,reset,save",
+                   active_drag="pan",
+                   )
+    p.circle(df.index,
+             df['Open'],
+             size=8,
+             color='olive',
+             alpha=0.6,
+             legend_label='Open',
+             )
+    p.circle(df.index,
+             df['Close'],
+             size=8,
+             color='orange',
+             alpha=0.6,
+             legend_label='Close',
+             )
+    p.line(df.index,
+           df['High'],
+           line_width=2,
+           color='steelblue',
+           legend_label='High',
+           )
+    p.line(df.index,
+           df['Low'],
+           line_width=2,
+           color='firebrick',
+           legend_label='Low',
+           )
+    p.xaxis.ticker = DatetimeTicker(desired_num_ticks=20)
+    hover = HoverTool(tooltips=[('Date', '@x{%F}'),
+                                ('Price', '$@y{0.00 a}'),
+                                ],
+                      formatters={'@x': 'datetime'})
+    p.add_tools(hover)
+    p.toolbar.active_inspect = hover
+
+    return p
+
+
+def main():
+    """Return raw json text from plot with given ticker symbol argument.
+
+    Default ticker symbol is 'IBM'.
+    """
+    if len(sys.argv) == 1:
+        symbol = 'IBM'
+
+    else:
+        symbol = sys.argv[1]
+
+    p = ticker(symbol)
+    print(json.dumps(json_item(p, f'{symbol}_stocks')))
+
+
+if __name__ == '__main__':
+    main()