mirror of
https://github.com/OpenBB-finance/OpenBB.git
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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>
100 lines
2.6 KiB
Python
100 lines
2.6 KiB
Python
""" Fidelity Model """
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__docformat__ = "numpy"
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import logging
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from typing import Tuple
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import pandas as pd
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from bs4 import BeautifulSoup
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from pandas.core.frame import DataFrame
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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 get_orders() -> Tuple[str, DataFrame]:
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"""Returns Fidelity orders in a Dataframe
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Returns
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-------
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Tuple[str, DataFrame]
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First value in the tuple is a Fidelity orders header
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Fidelity orders Dataframe with the following columns -
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Symbol, Buy / Sell Ratio, Price Change, Company, # Buy Orders, # Sell Orders
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"""
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url_orders = (
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"https://eresearch.fidelity.com/eresearch/gotoBL/fidelityTopOrders.jhtml"
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)
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text_soup_url_orders = BeautifulSoup(
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request(url_orders, headers={"User-Agent": get_user_agent()}).text, "lxml"
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)
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l_orders = []
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l_orders_vals = []
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idx = 0
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order_list = text_soup_url_orders.findAll(
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"td",
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{"class": ["second", "third", "fourth", "fifth", "sixth", "seventh", "eight"]},
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)
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for an_order in order_list:
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if ((idx + 1) % 3 == 0) or ((idx + 1) % 4 == 0) or ((idx + 1) % 6 == 0):
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if not an_order:
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l_orders_vals.append("")
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else:
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try:
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l_orders_vals.append(an_order.contents[1])
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except IndexError:
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l_orders_vals.append("0")
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elif (idx + 1) % 5 == 0:
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s_orders = str(an_order)
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l_orders_vals.append(
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s_orders[
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s_orders.find('title="') + len('title="') : s_orders.find('"/>')
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]
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)
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else:
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l_orders_vals.append(an_order.text.strip())
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idx += 1
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# Add value to dictionary
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if (idx + 1) % 8 == 0:
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l_orders.append(l_orders_vals)
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l_orders_vals = []
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idx = 0
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df_orders = pd.DataFrame(
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l_orders,
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columns=[
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"Symbol",
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"Company",
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"Price Change",
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"# Buy Orders",
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"Buy / Sell Ratio",
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"# Sell Orders",
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"Latest News",
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],
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)
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df_orders = df_orders[
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[
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"Symbol",
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"Buy / Sell Ratio",
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"Price Change",
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"Company",
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"# Buy Orders",
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"# Sell Orders",
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"Latest News",
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]
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]
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order_header = text_soup_url_orders.findAll("span", {"class": "source"})[
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0
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].text.capitalize()
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return order_header, df_orders
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