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eb2c11060d
* bump * Initial function write * Delete this line from yaml * Changed all the main things - Need help on tests * pylint errors * Tests v0 * Tests v1 * Tests v2 --------- Co-authored-by: andrewkenreich <andrew.kenreich@gmail.com>
93 lines
2.7 KiB
Python
93 lines
2.7 KiB
Python
"""WSJ model"""
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__docformat__ = "numpy"
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import logging
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import pandas as pd
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from openbb_terminal.decorators import log_start_end
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from openbb_terminal.helper_funcs import get_user_agent, request
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logger = logging.getLogger(__name__)
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@log_start_end(log=logger)
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def etf_movers(sort_type: str = "gainers", export: bool = False) -> pd.DataFrame:
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"""
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Scrape data for top etf movers.
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Parameters
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----------
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sort_type: str
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Data to get. Can be "gainers", "decliners" or "active"
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Returns
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-------
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etfmovers: pd.DataFrame
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Datafame containing the name, price, change and the volume of the etf
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"""
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if sort_type.lower() == "gainers":
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url = (
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"https://www.wsj.com/market-data/mutualfunds-etfs/etfmovers?id=%7B%22application"
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"%22%3A%22WSJ%22%2C%22etfMover%22%3A%22leaders%22%2C%22count%22%3A25%7D&type="
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"mdc_etfmovers"
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)
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elif sort_type.lower() == "decliners":
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url = (
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"https://www.wsj.com/market-data/mutualfunds-etfs/etfmovers?id=%7B%22application"
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"%22%3A%22WSJ%22%2C%22etfMover%22%3A%22laggards%22%2C%22count%22%3A25%7D&type="
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"mdc_etfmovers"
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)
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elif sort_type.lower() == "active":
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url = (
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"https://www.wsj.com/market-data/mutualfunds-etfs/etfmovers?id=%7B%22application"
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"%22%3A%22WSJ%22%2C%22etfMover%22%3A%22most_active%22%2C%22count%22%3A25%7D&type="
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"mdc_etfmovers"
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)
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else:
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url = ""
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if url:
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data = request(url, headers={"User-Agent": get_user_agent()}).json()
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symbol, name, last_price, net_change, percent_change, volume = (
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[],
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[],
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[],
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[],
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[],
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[],
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)
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for entry in data["data"]["instruments"]:
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symbol.append(entry["ticker"])
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name.append(entry["name"])
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last_price.append(entry["lastPrice"])
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net_change.append(entry["priceChange"])
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percent_change.append(entry["percentChange"])
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volume.append(entry["formattedVolume"])
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if export:
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etfmovers = pd.DataFrame(
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{
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" ": symbol,
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"Name": name,
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"Price": last_price,
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"Chg": net_change,
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"%Chg": percent_change,
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"Vol": volume,
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}
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)
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else:
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etfmovers = pd.DataFrame(
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{
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" ": name,
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"Price": last_price,
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"Chg": net_change,
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"%Chg": percent_change,
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"Vol": volume,
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}
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)
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return etfmovers
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return pd.DataFrame()
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