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add/update examples (#383)
* add/update examples * added comment to on how to use
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‎examples/rest/stocks-aggregates_bars_highcharts.py‎

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from polygon import RESTClient
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from polygon.rest.models import (
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Agg,
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)
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import datetime
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import http.server
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import socketserver
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import traceback
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import json
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# This program retrieves stock price data for the AAPL stock from the Polygon
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# API using a REST client, and formats the data in a format expected by the
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# Highcharts JavaScript library. The program creates a web server that serves
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# an HTML page that includes a candlestick chart of the AAPL stock prices using
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# Highcharts. The chart displays data for the time range from January 1, 2019,
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# to February 16, 2023. The chart data is updated by retrieving the latest data
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# from the Polygon API every time the HTML page is loaded or refreshed. The
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# server listens on port 8888 and exits gracefully when a KeyboardInterrupt is
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# received.
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#
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# Connect to http://localhost:8888 in your browser to view candlestick chart.
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PORT = 8888
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# https://www.highcharts.com/blog/products/stock/
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# JavaScript StockChart with Date-Time Axis
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html = """
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<!DOCTYPE HTML>
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<html>
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<head>
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<style>
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#container {
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height: 750px;
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min-width: 310px;
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}
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</style>
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<script src="https://code.highcharts.com/stock/highstock.js"></script>
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<script src="https://code.highcharts.com/stock/modules/data.js"></script>
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<script src="https://code.highcharts.com/stock/modules/exporting.js"></script>
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<script src="https://code.highcharts.com/stock/modules/accessibility.js"></script>
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<div id="container"></div>
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<script type="text/javascript">
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Highcharts.getJSON('/data', function (data) {
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// create the chart
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Highcharts.stockChart('container', {
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rangeSelector: {
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selected: 1
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},
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title: {
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text: 'Stock Price'
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},
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series: [{
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type: 'candlestick',
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name: 'Stock Price',
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data: data
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}]
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});
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});
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</script>
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</head>
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<body>
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"""
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client = RESTClient() # POLYGON_API_KEY environment variable is used
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aggs = client.get_aggs(
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"AAPL",
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1,
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"day",
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"2019-01-01",
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"2023-02-16",
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limit=50000,
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)
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# print(aggs)
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data = []
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# writing data
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for agg in aggs:
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# verify this is an agg
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if isinstance(agg, Agg):
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# verify this is an int
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if isinstance(agg.timestamp, int):
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new_record = {
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"date": agg.timestamp,
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"open": agg.open,
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"high": agg.high,
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"low": agg.low,
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"close": agg.close,
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"volume": agg.volume,
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}
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data.append(new_record)
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values = [[v for k, v in d.items()] for d in data]
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# json_data = json.dumps(data)
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# print(json_data)
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class handler(http.server.SimpleHTTPRequestHandler):
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def do_GET(self):
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if self.path == "/data":
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self.send_response(200)
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self.send_header("Content-type", "application/json")
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self.end_headers()
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json_data = json.dumps(values)
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self.wfile.write(json_data.encode())
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else:
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self.send_response(200)
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self.send_header("Content-type", "text/html")
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self.end_headers()
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self.wfile.write(html.encode())
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# handle ctrl-c KeyboardInterrupt to exit the program gracefully
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try:
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while True:
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# run http server
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with socketserver.TCPServer(("", PORT), handler) as httpd:
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print("serving at port", PORT)
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httpd.serve_forever()
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pass
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except KeyboardInterrupt:
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print("\nExiting gracefully...")
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# traceback.print_exc()

‎examples/rest/stocks-grouped_daily_bars.py‎

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client = RESTClient() # POLYGON_API_KEY environment variable is used
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grouped = client.get_grouped_daily_aggs(
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"2023-02-07",
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"2023-02-16",
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)
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# print(grouped)

‎examples/rest/stocks-tickers.py‎

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client = RESTClient() # POLYGON_API_KEY environment variable is used
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tickers = []
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for t in client.list_tickers(limit=1000):
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for t in client.list_tickers(market="stocks", type="CS", active=True, limit=1000):
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tickers.append(t)
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print(tickers)

‎examples/rest/stocks-trades_extra.py‎

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if isinstance(t, Trade):
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# verify these are float
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if isinstance(t.price, float) and isinstance(t.size, float):
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if isinstance(t.price, float) and isinstance(t.size, int):
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money += t.price * t.size
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‎examples/websocket/stocks-ws.py‎

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Original file line numberDiff line numberDiff line change
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from polygon.websocket.models import WebSocketMessage
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from typing import List
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client = WebSocketClient("N_4QqOFs3X_pCHeIJjW4pCETSOBerS4_") # api_key is used
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# client = WebSocketClient("XXXXXX") # hardcoded api_key is used
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client = WebSocketClient() # POLYGON_API_KEY environment variable is used
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# docs
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# https://polygon.io/docs/stocks/ws_stocks_am
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# https://polygon-api-client.readthedocs.io/en/latest/WebSocket.html#
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# aggregates
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# client.subscribe("AM.*") # aggregates (per minute)
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# client.subscribe("A.*") # aggregates (per second)
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# aggregates (per minute)
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# client.subscribe("AM.*") # all aggregates
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# client.subscribe("AM.TSLA") # single ticker
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# aggregates (per second)
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client.subscribe("A.*") # all aggregates
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# client.subscribe("A.TSLA") # single ticker
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# trades
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# client.subscribe("T.*") # all trades
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# client.subscribe("T.TSLA", "T.UBER") # limited trades
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# client.subscribe("T.*") # all trades
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# client.subscribe("T.TSLA", "T.UBER") # multiple tickers
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# quotes
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# client.subscribe("Q.*") # all quotes
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# client.subscribe("Q.TSLA", "Q.UBER") # limited quotes
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# client.subscribe("Q.*") # all quotes
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# client.subscribe("Q.TSLA", "Q.UBER") # multiple tickers
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def handle_msg(msgs: List[WebSocketMessage]):

‎examples/websocket/stocks-ws_extra.py‎

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@@ -1,11 +1,11 @@
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from polygon import WebSocketClient
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from polygon.websocket.models import WebSocketMessage
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from polygon.websocket.models import WebSocketMessage, EquityTrade
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from typing import List
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from typing import Dict
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from datetime import datetime
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import time
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import threading
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# docs
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# https://polygon.io/docs/stocks/ws_stocks_am
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# https://polygon-api-client.readthedocs.io/en/latest/WebSocket.html#
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# program then prints the map, which gives a readout of the top stocks
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# traded in the past 5 seconds.
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# aggregates
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# client.subscribe("AM.*") # aggregates (per minute)
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# client.subscribe("A.*") # aggregates (per second)
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# trades
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# client.subscribe("T.*") # all trades
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# client.subscribe("T.TSLA", "T.UBER") # limited trades
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# quotes
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# client.subscribe("Q.*") # all quotes
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# client.subscribe("Q.TSLA", "Q.UBER") # limited quotes
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def run_websocket_client():
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# client = WebSocketClient("XXXXXX") # hardcoded api_key is used
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string_map: Dict[str, int]
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string_map = {} #
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cash_traded = float(0)
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def handle_msg(msgs: List[WebSocketMessage]):
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for m in msgs:
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# print(m)
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# verify this is a string
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if isinstance(m, str):
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if type(m) == EquityTrade:
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if m.symbol in string_map:
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string_map[m.symbol] += 1
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else:
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string_map[m.symbol] = 1
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# verify this is a string
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if isinstance(m.symbol, str):
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if m.symbol in string_map:
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string_map[m.symbol] += 1
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else:
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string_map[m.symbol] = 1
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# print messages
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# client.run(handle_msg)
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# verify these are float
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if isinstance(m.price, float) and isinstance(m.size, int):
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global cash_traded
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cash_traded += m.price * m.size
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# print(cash_traded)
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def top_function():
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# start timer
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start_time = time.time()
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sorted_string_map = sorted(string_map.items(), key=lambda x: x[1], reverse=True)
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print("\033c", end="") # ANSI escape sequence to clear the screen
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for index, item in sorted_string_map[:10]:
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for index, item in sorted_string_map[:25]:
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print("{:<15}{:<15}".format(index, item))
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string_map.clear() # clear map for next loop
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# end timer
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end_time = time.time()
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# print stats
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print()
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# current time
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current_time = datetime.now()
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print(f"Time: {current_time}")
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# how many tickers seen
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ticker_count = len(sorted_string_map)
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print(f"Tickers seen: {ticker_count}")
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# how many trades seen
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trade_count = 0
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for index, item in sorted_string_map:
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trade_count += item
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print(f"Trades seen: {trade_count}")
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# cash traded
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global cash_traded
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formatted_number = "{:,.2f}".format(cash_traded)
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print("Roughly " + formatted_number + " cash changed hands")
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# performance?
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print(f"Time taken: {end_time - start_time:.6f} seconds")
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# clear map and cash for next loop
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string_map.clear()
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cash_traded = 0
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def run_function_periodically():

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