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alphavantage.py
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alphavantage.py
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from alpha_vantage.timeseries import TimeSeries
from plotly.subplots import make_subplots
import plotly.graph_objects as go
import plotly.express as px
from datetime import datetime
import pandas as pd
import numpy as np
class Stonks:
def __init__(self, ticker, timeframe, mode):
self.ts = TimeSeries(key='INSERT API KEY HERE', output_format='pandas', indexing_type='integer')
self.ticker = ticker
self.timeframe = timeframe
self.mode = mode
self.data, self.meta_data = self.slice_ticker_data()
self.data['index'] = pd.to_datetime(self.data['index'])
def fix_date(self):
self.data['index'] = pd.to_datetime(self.data['index'])
def slice_ticker_data(self):
# response = request.get("https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=" + ticker +"&outputsize=full&apikey=RI148SC1TRRU91UD")
data, meta_data = self.ts.get_daily(symbol=self.ticker ,outputsize='full')
if self.mode == 0:
self.timeframe *= 31
else:
self.timeframe*=7
data = data[::-1]
data = data[len(data)-1:len(data)-1-self.timeframe:-1]
# data = data.drop('index', axis=1)
return data, meta_data
def plot_candlesticks(self):
fig = go.Figure(data=[go.Candlestick(x=self.data['index'],
open=self.data['1. open'],
high=self.data['2. high'],
low=self.data['3. low'],
close=self.data['4. close'])])
fig.update_layout(
xaxis=go.layout.XAxis(
rangeselector=dict(
buttons=list([
dict(count=1,
label="1m",
step="month",
stepmode="backward"),
dict(count=6,
label="6m",
step="month",
stepmode="backward"),
dict(count=1,
label="1y",
step="year",
stepmode="backward"),
dict(step="all")
])
),
rangeslider=dict(
visible=True
),
type="date"
)
)
fig.show()
def plot_high_low(self):
fig = make_subplots(specs=[[{"secondary_y": True}]])
fig.add_trace(go.Scatter(x = self.data['index'], y = self.data['3. low'], name = 'low'),
secondary_y = False
)
fig.add_trace(go.Scatter(x = self.data['index'], y = self.data['2. high'], name = 'high'),
secondary_y = False
)
fig.update_layout(
xaxis=go.layout.XAxis(
rangeselector=dict(
buttons=list([
dict(count=1,
label="1m",
step="month",
stepmode="backward"),
dict(count=6,
label="6m",
step="month",
stepmode="backward"),
dict(count=1,
label="1y",
step="year",
stepmode="backward"),
dict(step="all")
])
),
rangeslider=dict(
visible=True
),
type="date"
)
)
fig.show()
def plot_predict(self, actual, prediction):
x_vals = np.arange(60)
fig = make_subplots(specs=[[{"secondary_y": True}]])
fig.add_trace(go.Scatter(x = x_vals, y = actual, name = 'actual price'),
secondary_y = False
)
fig.add_trace(go.Scatter(x = x_vals, y = prediction, name = 'predicted price'),
secondary_y = False
)
fig.update_layout(
xaxis=go.layout.XAxis(
rangeselector=dict(
buttons=list([
dict(count=1,
label="1m",
step="month",
stepmode="backward"),
dict(count=6,
label="6m",
step="month",
stepmode="backward"),
dict(count=1,
label="1y",
step="year",
stepmode="backward"),
dict(step="all")
])
),
rangeslider=dict(
visible=True
),
type="date"
)
)
fig.show()