mirror of
https://github.com/OpenBB-finance/OpenBB.git
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141dd68e68
* Removed prints * FIxed typing * FIxed typing * Fixed typing * Fixed typing * Fixed typing * Fixed typing * Fixed typing * Fix * Reverted stuff
339 lines
9.2 KiB
Python
339 lines
9.2 KiB
Python
"""Portfolio Helper"""
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__docformat__ = "numpy"
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import csv
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import logging
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import os
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from datetime import date, datetime
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from pathlib import Path
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from typing import List
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import pandas as pd
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import yfinance as yf
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from dateutil.relativedelta import relativedelta
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from openbb_terminal.core.session.current_user import get_current_user
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from openbb_terminal.portfolio.statics import REGIONS
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from openbb_terminal.rich_config import console
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logger = logging.getLogger(__name__)
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# pylint: disable=too-many-return-statements, too-many-lines, too-many-statements, consider-iterating-dictionary
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# pylint: disable=C0302
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now = datetime.now()
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PERIODS_DAYS = {
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"mtd": (now - datetime(now.year, now.month, 1)).days,
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"qtd": (
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now
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- datetime(
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now.year,
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1 if now.month < 4 else 4 if now.month < 7 else 7 if now.month < 10 else 10,
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1,
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)
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).days,
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"ytd": (now - datetime(now.year, 1, 1)).days,
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"all": 1,
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"3m": 3 * 21,
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"6m": 6 * 21,
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"1y": 12 * 21,
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"3y": 3 * 12 * 21,
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"5y": 5 * 12 * 21,
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"10y": 10 * 12 * 21,
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}
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DEFAULT_HOLDINGS_PATH = (
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get_current_user().preferences.USER_PORTFOLIO_DATA_DIRECTORY / "holdings"
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)
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def is_ticker(ticker: str) -> bool:
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"""Determine whether a string is a valid ticker
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Parameters
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----------
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ticker : str
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The string to be tested
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Returns
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-------
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bool
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Whether the string is a ticker
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"""
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item = yf.Ticker(ticker)
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return "previousClose" in item.fast_info
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# TODO: Is this being used anywhere?
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def beta_word(beta: float) -> str:
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"""Describe a beta
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Parameters
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----------
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beta : float
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The beta for a portfolio
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Returns
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-------
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str
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The description of the beta
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"""
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if abs(1 - beta) > 3:
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part = "extremely "
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elif abs(1 - beta) > 2:
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part = "very "
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elif abs(1 - beta) > 1:
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part = ""
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else:
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part = "moderately "
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return part + "high" if beta > 1 else "low"
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def clean_name(name: str) -> str:
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"""Clean a name to a ticker
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Parameters
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----------
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name : str
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The value to be cleaned
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Returns
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-------
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str
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A cleaned value
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"""
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return name.replace("beta_", "").upper()
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def filter_df_by_period(df: pd.DataFrame, period: str = "all") -> pd.DataFrame:
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"""Filter dataframe by selected period
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Parameters
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----------
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df: pd.DataFrame
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Dataframe to be filtered in terms of time
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period : str
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Period in which to filter dataframe.
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Possible choices are: mtd, qtd, ytd, 3m, 6m, 1y, 3y, 5y, 10y, all
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Returns
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-------
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pd.DataFrame
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A cleaned value
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"""
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if period == "mtd":
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return df[df.index.strftime("%Y-%m") == datetime.now().strftime("%Y-%m")]
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if period == "qtd":
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if datetime.now().month < 4:
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return df[
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df.index.strftime("%Y-%m") < f"{datetime.now().strftime('%Y')}-04"
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]
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if datetime.now().month < 7:
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return df[
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(df.index.strftime("%Y-%m") >= f"{datetime.now().strftime('%Y')}-04")
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& (df.index.strftime("%Y-%m") < f"{datetime.now().strftime('%Y')}-07")
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]
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if datetime.now().month < 10:
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return df[
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(df.index.strftime("%Y-%m") >= f"{datetime.now().strftime('%Y')}-07")
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& (df.index.strftime("%Y-%m") < f"{datetime.now().strftime('%Y')}-10")
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]
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return df[df.index.strftime("%Y-%m") >= f"{datetime.now().strftime('%Y')}-10"]
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if period == "ytd":
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return df[df.index.strftime("%Y") == datetime.now().strftime("%Y")]
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period_dict = {
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"3m": relativedelta(months=3),
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"6m": relativedelta(months=6),
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"1y": relativedelta(years=1),
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"3y": relativedelta(years=3),
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"5y": relativedelta(years=5),
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"10y": relativedelta(years=10),
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}
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if period in period_dict:
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return df[df.index >= (datetime.now() - period_dict[period])]
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return df
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def make_equal_length(df1: pd.DataFrame, df2: pd.DataFrame):
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"""Filter dataframe by selected period
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Parameters
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----------
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df1: pd.DataFrame
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The first DataFrame that needs to be compared.
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df2: pd.DataFrame
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The second DataFrame that needs to be compared.
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Returns
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-------
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df1 and df2
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Both DataFrames returned
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"""
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# Match the DataFrames so they share a similar length
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if isinstance(df1, pd.Series):
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df1 = df1.to_frame()
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if isinstance(df2, pd.Series):
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df2 = df2.to_frame()
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df2.columns = [str(i) + "2" for i in df2.columns]
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df_merged = df1.join(df2, how="outer")
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df_merged = df_merged.fillna(0)
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df1 = df_merged[df1.columns]
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df2 = df_merged[df2.columns]
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df2.columns = [i[:-1] for i in df2.columns]
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return df1.iloc[:, 0], df2.iloc[:, 0]
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def get_region_from_country(country: str) -> str:
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"""Get region from country
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Parameters
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----------
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country: str
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The country to assign region.
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Returns
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-------
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str
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Region to which country belongs.
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"""
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return REGIONS[country]
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def get_info_update_file(ticker: str, file_path: Path, writemode: str) -> List[str]:
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"""Get info (Sector, Industry, Country and Region) from ticker and save information in file to access later.
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Parameters
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----------
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ticker: str
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The ticker to get information.
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file_path: str
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The file to save information.
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writemode: str
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The mode to write into the file, 'w' or 'a'.
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Returns
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-------
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List[str]
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List with ticker information.
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"""
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# Pull ticker info from yf
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yf_ticker_info = yf.Ticker(ticker).info
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if "sector" in yf_ticker_info:
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# Ticker has valid sector
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# Replace the dash to UTF-8 readable
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ticker_info_list = [
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yf_ticker_info["sector"],
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yf_ticker_info["industry"].replace("—", "-"),
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yf_ticker_info["country"],
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get_region_from_country(yf_ticker_info["country"]),
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]
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with open(file_path, writemode, newline="") as f:
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writer = csv.writer(f)
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if writemode == "a":
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# file already has data, so just append
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writer.writerow([ticker] + ticker_info_list)
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else:
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# file did not exist or as empty, so write headers first
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writer.writerow(["Ticker", "Sector", "Industry", "Country", "Region"])
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writer.writerow([ticker] + ticker_info_list)
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f.close()
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return ticker_info_list
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# Ticker does not have a valid sector
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console.print(f"F:{ticker}", end="")
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return ["", "", "", ""]
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def get_info_from_ticker(ticker: str) -> list:
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"""Get info (Sector, Industry, Country and Region) from ticker.
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Parameters
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----------
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ticker: str
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The ticker to get information.
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Returns
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-------
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List[str]
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List with ticker information.
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"""
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filename = "tickers_info.csv"
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file_path = Path(
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str(get_current_user().preferences.USER_PORTFOLIO_DATA_DIRECTORY), filename
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)
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if file_path.is_file() and os.stat(file_path).st_size > 0:
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# file exists and is not empty, so append if necessary
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ticker_info_df = pd.read_csv(file_path)
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df_row = ticker_info_df.loc[ticker_info_df["Ticker"] == ticker]
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if len(df_row) > 0:
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# ticker is in file, just return it
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ticker_info_list = list(df_row.iloc[0].drop("Ticker"))
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return ticker_info_list
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# ticker is not in file, go get it
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ticker_info_list = get_info_update_file(ticker, file_path, "a")
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return ticker_info_list
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# file does not exist or is empty, so write it
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ticker_info_list = get_info_update_file(ticker, file_path, "w")
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return ticker_info_list
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def get_start_date_from_period(period: str) -> date:
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"""Get start date of a time period based on the period string.
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Parameters
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----------
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period: str
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Period to get start date from (e.g. 10y, 3m, etc.)
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Returns
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-------
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date
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Start date of the period.
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"""
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if period == "10y":
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start_date = date.today() + relativedelta(years=-10)
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elif period == "5y":
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start_date = date.today() + relativedelta(years=-5)
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elif period == "3y":
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start_date = date.today() + relativedelta(years=-3)
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elif period == "1y":
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start_date = date.today() + relativedelta(years=-1)
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elif period == "6m":
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start_date = date.today() + relativedelta(months=-6)
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elif period == "3m":
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start_date = date.today() + relativedelta(months=-3)
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elif period == "ytd":
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start_date = date(date.today().year, 1, 1)
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elif period == "qtd":
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cm = date.today().month
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if 3 >= cm >= 1:
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start_date = date(date.today().year, 1, 1)
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elif 6 >= cm >= 4:
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start_date = date(date.today().year, 4, 1)
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elif 9 >= cm >= 7:
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start_date = date(date.today().year, 7, 1)
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elif 12 >= cm >= 10:
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start_date = date(date.today().year, 10, 1)
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else:
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console.print("Error")
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elif period == "mtd":
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cur_month = date.today().month
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cur_year = date.today().year
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start_date = date(cur_year, cur_month, 1)
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return start_date
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