OpenBB/gamestonk_terminal/helper_funcs.py

"""Helper functions"""
__docformat__ = "numpy"
# pylint: disable=too-many-lines
import argparse
import logging
from typing import List, Union
from datetime import datetime, timedelta
import os
import random
import re
import sys
import pytz
import pandas as pd
from rich.table import Table
import iso8601

import matplotlib
import matplotlib.pyplot as plt
from holidays import US as us_holidays
from pandas._config.config import get_option
from pandas.plotting import register_matplotlib_converters
import pandas.io.formats.format
import requests
from screeninfo import get_monitors

from gamestonk_terminal.rich_config import console
from gamestonk_terminal import feature_flags as gtff
from gamestonk_terminal import config_plot as cfgPlot

logger = logging.getLogger(__name__)

register_matplotlib_converters()
if cfgPlot.BACKEND is not None:
    matplotlib.use(cfgPlot.BACKEND)

NO_EXPORT = 0
EXPORT_ONLY_RAW_DATA_ALLOWED = 1
EXPORT_ONLY_FIGURES_ALLOWED = 2
EXPORT_BOTH_RAW_DATA_AND_FIGURES = 3

MENU_GO_BACK = 0
MENU_QUIT = 1
MENU_RESET = 2


def log_and_raise(error: Union[argparse.ArgumentTypeError, ValueError]) -> None:
    logger.error(str(error))
    raise error


def print_rich_table(
    df: pd.DataFrame,
    show_index: bool = False,
    title: str = "",
    index_name: str = "",
    headers: Union[List[str], pd.Index] = None,
    floatfmt: Union[str, List[str]] = ".2f",
):
    """Prepare a table from df in rich

    Parameters
    ----------
    df: pd.DataFrame
        Dataframe to turn into table
    show_index: bool
        Whether to include index
    title: str
        Title for table
    index_name : str
        Title for index column
    headers: List[str]
        Titles for columns
    floatfmt: str
        String to
    """

    if gtff.USE_TABULATE_DF:
        table = Table(title=title, show_lines=True)

        if show_index:
            table.add_column(index_name)

        if headers is not None:
            if isinstance(headers, pd.Index):
                headers = list(headers)
            if len(headers) != len(df.columns):
                log_and_raise(
                    ValueError("Length of headers does not match length of DataFrame")
                )
            for header in headers:
                table.add_column(str(header))
        else:
            for column in df.columns:
                table.add_column(str(column))

        if isinstance(floatfmt, list):
            if len(floatfmt) != len(df.columns):
                log_and_raise(
                    ValueError(
                        "Length of floatfmt list does not match length of DataFrame columns."
                    )
                )
        if isinstance(floatfmt, str):
            floatfmt = [floatfmt for _ in range(len(df.columns))]

        for idx, values in zip(df.index.tolist(), df.values.tolist()):
            row = [str(idx)] if show_index else []
            row += [
                str(x) if not isinstance(x, float) else f"{x:{floatfmt[idx]}}"
                for idx, x in enumerate(values)
            ]
            table.add_row(*row)
        console.print(table)
    else:
        console.print(df.to_string())


def check_int_range(mini: int, maxi: int):
    """
    Checks if argparse argument is an int between 2 values.

    Parameters
    ----------
    mini: int
        Min value to compare
    maxi: int
        Max value to compare

    Returns
    -------
    int_range_checker:
        Function that compares the three integers
    """

    # Define the function with default arguments
    def int_range_checker(num: int) -> int:
        """
        Checks if int is between a high and low value

        Parameters
        ----------
        num: int
            Input integer

        Returns
        -------
        num: int
            Input number if conditions are met

        Raises
        -------
        argparse.ArgumentTypeError
            Input number not between min and max values
        """
        num = int(num)
        if num < mini or num > maxi:
            log_and_raise(
                argparse.ArgumentTypeError(f"Argument must be in range [{mini},{maxi}]")
            )
        return num

    # Return function handle to checking function
    return int_range_checker


def check_non_negative(value) -> int:
    """Argparse type to check non negative int"""
    new_value = int(value)
    if new_value < 0:
        log_and_raise(argparse.ArgumentTypeError(f"{value} is negative"))
    return new_value


def check_terra_address_format(address: str) -> str:
    """Validate if terra account address has proper format: ^terra1[a-z0-9]{38}$

    Parameters
    ----------
    address: str
        terra blockchain account address
    Returns
    -------
    str
        Terra blockchain address or raise argparse exception
    """

    pattern = re.compile(r"^terra1[a-z0-9]{38}$")
    if not pattern.match(address):
        log_and_raise(
            argparse.ArgumentTypeError(
                f"Terra address: {address} has invalid format. Valid format: ^terra1[a-z0-9]{{38}}$"
            )
        )
    return address


def check_non_negative_float(value) -> float:
    """Argparse type to check non negative int"""
    new_value = float(value)
    if new_value < 0:
        log_and_raise(argparse.ArgumentTypeError(f"{value} is negative"))
    return new_value


def check_positive_list(value) -> List[int]:
    """Argparse type to return list of positive ints"""
    list_of_nums = value.split(",")
    list_of_pos = []
    for a_value in list_of_nums:
        new_value = int(a_value)
        if new_value <= 0:
            log_and_raise(
                argparse.ArgumentTypeError(f"{value} is an invalid positive int value")
            )
        list_of_pos.append(new_value)
    return list_of_pos


def check_positive(value) -> int:
    """Argparse type to check positive int"""
    new_value = int(value)
    if new_value <= 0:
        log_and_raise(
            argparse.ArgumentTypeError(f"{value} is an invalid positive int value")
        )
    return new_value


def check_positive_float(value) -> float:
    """Argparse type to check positive int"""
    new_value = float(value)
    if new_value <= 0:
        log_and_raise(
            argparse.ArgumentTypeError(f"{value} is not a positive float value")
        )
    return new_value


def check_proportion_range(num) -> float:
    """
    Checks if float is between 0 and 1. If so, return it.

    Parameters
    ----------
    num: float
        Input float
    Returns
    -------
    num: float
        Input number if conditions are met
    Raises
    -------
    argparse.ArgumentTypeError
        Input number not between min and max values
    """
    num = float(num)
    maxi = 1.0
    mini = 0.0
    if num < mini or num > maxi:
        log_and_raise(argparse.ArgumentTypeError("Value must be between 0 and 1"))
    return num


def valid_date_in_past(s: str) -> datetime:
    """Argparse type to check date is in valid format"""
    try:
        delta = datetime.now() - datetime.strptime(s, "%Y-%m-%d")
        if delta.days < 1:
            log_and_raise(
                argparse.ArgumentTypeError(
                    f"Not a valid date: {s}. Must be earlier than today"
                )
            )
        return datetime.strptime(s, "%Y-%m-%d")
    except ValueError as value_error:
        logging.exception(str(value_error))
        raise argparse.ArgumentTypeError(f"Not a valid date: {s}") from value_error


def check_list_dates(str_dates: str) -> List[datetime]:
    """Argparse type to check list of dates provided have a valid format

    Parameters
    ----------
    str_dates: str
        string with dates separated by ","

    Returns
    -------
    list_dates: List[datetime]
        List of valid dates
    """
    list_dates = list()
    if str_dates:
        if "," in str_dates:
            for dt_marker in str_dates.split(","):
                list_dates.append(valid_date(dt_marker))
        else:
            list_dates.append(valid_date(str_dates))

    return list_dates


def valid_date(s: str) -> datetime:
    """Argparse type to check date is in valid format"""
    try:
        return datetime.strptime(s, "%Y-%m-%d")
    except ValueError as value_error:
        logging.exception(str(value_error))
        raise argparse.ArgumentTypeError(f"Not a valid date: {s}") from value_error


def valid_hour(hr: str) -> int:
    """Argparse type to check hour is valid with 24-hour notation"""

    new_hr = int(hr)

    if (new_hr < 0) or (new_hr > 24):
        log_and_raise(
            argparse.ArgumentTypeError(f"{hr} doesn't follow 24-hour notion.")
        )
    return new_hr


def plot_view_stock(df: pd.DataFrame, symbol: str, interval: str):
    """
    Plot the loaded stock dataframe
    Parameters
    ----------
    df: Dataframe
        Dataframe of prices and volumes
    symbol: str
        Symbol of ticker
    interval: str
        Stock data resolution for plotting purposes

    """
    df.sort_index(ascending=True, inplace=True)
    bar_colors = ["r" if x[1].Open < x[1].Close else "g" for x in df.iterrows()]

    try:
        fig, ax = plt.subplots(
            2,
            1,
            gridspec_kw={"height_ratios": [3, 1]},
            figsize=plot_autoscale(),
            dpi=cfgPlot.PLOT_DPI,
        )
    except Exception as e:
        console.print(e)
        console.print(
            "Encountered an error trying to open a chart window. Check your X server configuration."
        )
        logging.exception("%s", type(e).__name__)
        return

    # In order to make nice Volume plot, make the bar width = interval
    if interval == "1440min":
        bar_width = timedelta(days=1)
        title_string = "Daily"
    else:
        bar_width = timedelta(minutes=int(interval.split("m")[0]))
        title_string = f"{int(interval.split('m')[0])} min"

    ax[0].yaxis.tick_right()
    if "Adj Close" in df.columns:
        ax[0].plot(df.index, df["Adj Close"], c=cfgPlot.VIEW_COLOR)
    else:
        ax[0].plot(df.index, df["Close"], c=cfgPlot.VIEW_COLOR)
    ax[0].set_xlim(df.index[0], df.index[-1])
    ax[0].set_xticks([])
    ax[0].yaxis.set_label_position("right")
    ax[0].set_ylabel("Share Price ($)")
    ax[0].grid(axis="y", color="gainsboro", linestyle="-", linewidth=0.5)

    ax[0].spines["top"].set_visible(False)
    ax[0].spines["left"].set_visible(False)
    ax[1].bar(
        df.index, df.Volume / 1_000_000, color=bar_colors, alpha=0.8, width=bar_width
    )
    ax[1].set_xlim(df.index[0], df.index[-1])
    ax[1].yaxis.tick_right()
    ax[1].yaxis.set_label_position("right")
    ax[1].set_ylabel("Volume (1M)")
    ax[1].grid(axis="y", color="gainsboro", linestyle="-", linewidth=0.5)
    ax[1].spines["top"].set_visible(False)
    ax[1].spines["left"].set_visible(False)
    ax[1].set_xlabel("Time")
    fig.suptitle(
        symbol + " " + title_string,
        size=20,
        x=0.15,
        y=0.95,
        fontfamily="serif",
        fontstyle="italic",
    )
    if gtff.USE_ION:
        plt.ion()
    fig.tight_layout(pad=2)
    plt.setp(ax[1].get_xticklabels(), rotation=20, horizontalalignment="right")

    plt.show()
    console.print("")


def us_market_holidays(years) -> list:
    """Get US market holidays"""
    if isinstance(years, int):
        years = [
            years,
        ]
    # https://www.nyse.com/markets/hours-calendars
    market_holidays = [
        "Martin Luther King Jr. Day",
        "Washington's Birthday",
        "Memorial Day",
        "Independence Day",
        "Labor Day",
        "Thanksgiving",
        "Christmas Day",
    ]
    #   http://www.maa.clell.de/StarDate/publ_holidays.html
    good_fridays = {
        2010: "2010-04-02",
        2011: "2011-04-22",
        2012: "2012-04-06",
        2013: "2013-03-29",
        2014: "2014-04-18",
        2015: "2015-04-03",
        2016: "2016-03-25",
        2017: "2017-04-14",
        2018: "2018-03-30",
        2019: "2019-04-19",
        2020: "2020-04-10",
        2021: "2021-04-02",
        2022: "2022-04-15",
        2023: "2023-04-07",
        2024: "2024-03-29",
        2025: "2025-04-18",
        2026: "2026-04-03",
        2027: "2027-03-26",
        2028: "2028-04-14",
        2029: "2029-03-30",
        2030: "2030-04-19",
    }
    market_and_observed_holidays = market_holidays + [
        holiday + " (Observed)" for holiday in market_holidays
    ]
    all_holidays = us_holidays(years=years)
    valid_holidays = []
    for date in list(all_holidays):
        if all_holidays[date] in market_and_observed_holidays:
            valid_holidays.append(date)
    for year in years:
        new_Year = datetime.strptime(f"{year}-01-01", "%Y-%m-%d")
        if new_Year.weekday() != 5:  # ignore saturday
            valid_holidays.append(new_Year.date())
        if new_Year.weekday() == 6:  # add monday for Sunday
            valid_holidays.append(new_Year.date() + timedelta(1))
    for year in years:
        valid_holidays.append(datetime.strptime(good_fridays[year], "%Y-%m-%d").date())
    return valid_holidays


def lambda_long_number_format(num) -> str:
    """Format a long number"""
    if isinstance(num, float):
        magnitude = 0
        while abs(num) >= 1000:
            magnitude += 1
            num /= 1000.0
        num_str = int(num) if num.is_integer() else f"{num:.3f}"
        return f"{num_str} {' KMBTP'[magnitude]}".strip()
    if isinstance(num, int):
        num = str(num)
    if num.lstrip("-").isdigit():
        num = int(num)
        num /= 1.0
        magnitude = 0
        while abs(num) >= 1000:
            magnitude += 1
            num /= 1000.0
        num_str = int(num) if num.is_integer() else f"{num:.3f}"
        return f"{num_str} {' KMBTP'[magnitude]}".strip()
    return num


def lambda_clean_data_values_to_float(val: str) -> float:
    """Cleans data to float based on string ending"""
    # Remove any leading or trailing parentheses and spaces
    val = val.strip("( )")
    if val == "-":
        val = "0"

    # Convert percentage to decimal
    if val.endswith("%"):
        return float(val[:-1]) / 100.0
    if val.endswith("B"):
        return float(val[:-1]) * 1_000_000_000
    if val.endswith("M"):
        return float(val[:-1]) * 1_000_000
    if val.endswith("K"):
        return float(val[:-1]) * 1000
    return float(val)


def lambda_int_or_round_float(x) -> str:
    """Format int or round float"""
    if (x - int(x) < -sys.float_info.epsilon) or (x - int(x) > sys.float_info.epsilon):
        return " " + str(round(x, 2))

    return " " + str(int(x))


def divide_chunks(data, n):
    """Split into chunks"""
    # looping till length of data
    for i in range(0, len(data), n):
        yield data[i : i + n]  # noqa: E203


def get_next_stock_market_days(last_stock_day, n_next_days) -> list:
    """Gets the next stock market day. Checks against weekends and holidays"""
    n_days = 0
    l_pred_days = []
    years: list = []
    holidays: list = []
    while n_days < n_next_days:
        last_stock_day += timedelta(hours=24)
        year = last_stock_day.date().year
        if year not in years:
            years.append(year)
            holidays += us_market_holidays(year)
        # Check if it is a weekend
        if last_stock_day.date().weekday() > 4:
            continue
        # Check if it is a holiday
        if last_stock_day.strftime("%Y-%m-%d") in holidays:
            continue
        # Otherwise stock market is open
        n_days += 1
        l_pred_days.append(last_stock_day)

    return l_pred_days


def is_intraday(df: pd.DataFrame) -> bool:
    """Check if the data granularity is intraday.

    Parameters
    ----------
    df : pd.DataFrame
        Price data

    Returns
    -------
    bool
        True if data is intraday
    """
    granularity = df.index[1] - df.index[0]
    if granularity >= timedelta(days=1):
        intraday = False
    else:
        intraday = True
    return intraday


def reindex_dates(df: pd.DataFrame) -> pd.DataFrame:
    """Reindex dataframe to exclude non-trading days.

    Resets the index of a df to an integer and prepares the 'date' column to become
    x tick labels on a plot.

    Parameters
    ----------
    df : pd.DataFrame
        Source dataframe

    Returns
    -------
    pd.DataFrame
        Reindexed dataframe
    """
    if is_intraday(df):
        date_format = "%b %d %H:%M"
    else:
        date_format = "%Y-%m-%d"
    reindexed_df = df.reset_index()
    reindexed_df["date"] = reindexed_df["date"].dt.strftime(date_format)
    return reindexed_df


def get_data(tweet):
    """Gets twitter data from API request"""
    if "+" in tweet["created_at"]:
        s_datetime = tweet["created_at"].split(" +")[0]
    else:
        s_datetime = iso8601.parse_date(tweet["created_at"]).strftime(
            "%Y-%m-%d %H:%M:%S"
        )

    s_text = tweet["full_text"] if "full_text" in tweet.keys() else tweet["text"]
    return {"created_at": s_datetime, "text": s_text}


def clean_tweet(tweet: str, s_ticker: str) -> str:
    """Cleans tweets to be fed to sentiment model"""
    whitespace = re.compile(r"\s+")
    web_address = re.compile(r"(?i)http(s):\/\/[a-z0-9.~_\-\/]+")
    ticker = re.compile(rf"(?i)@{s_ticker}(?=\b)")
    user = re.compile(r"(?i)@[a-z0-9_]+")

    tweet = whitespace.sub(" ", tweet)
    tweet = web_address.sub("", tweet)
    tweet = ticker.sub(s_ticker, tweet)
    tweet = user.sub("", tweet)

    return tweet


def get_user_agent() -> str:
    """Get a not very random user agent"""
    user_agent_strings = [
        "Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10.10; rv:86.1) Gecko/20100101 Firefox/86.1",
        "Mozilla/5.0 (Windows NT 6.1; WOW64; rv:86.1) Gecko/20100101 Firefox/86.1",
        "Mozilla/5.0 (Macintosh; Intel Mac OS X 10.10; rv:82.1) Gecko/20100101 Firefox/82.1",
        "Mozilla/5.0 (Macintosh; Intel Mac OS X 10.13; rv:86.0) Gecko/20100101 Firefox/86.0",
        "Mozilla/5.0 (Windows NT 10.0; WOW64; rv:86.0) Gecko/20100101 Firefox/86.0",
        "Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10.10; rv:83.0) Gecko/20100101 Firefox/83.0",
        "Mozilla/5.0 (Windows NT 6.1; WOW64; rv:84.0) Gecko/20100101 Firefox/84.0",
    ]

    return random.choice(user_agent_strings)  # nosec


def text_adjustment_init(self):
    """Adjust text monkey patch for Pandas"""
    self.ansi_regx = re.compile(r"\x1B[@-_][0-?]*[ -/]*[@-~]")
    self.encoding = get_option("display.encoding")


def text_adjustment_len(self, text):
    """Get the length of the text adjustment"""
    # return compat.strlen(self.ansi_regx.sub("", text), encoding=self.encoding)
    return len(self.ansi_regx.sub("", text))


def text_adjustment_justify(self, texts, max_len, mode="right"):
    """Justify text"""
    justify = (
        str.ljust
        if (mode == "left")
        else str.rjust
        if (mode == "right")
        else str.center
    )
    out = []
    for s in texts:
        escapes = self.ansi_regx.findall(s)
        if len(escapes) == 2:
            out.append(
                escapes[0].strip()
                + justify(self.ansi_regx.sub("", s), max_len)
                + escapes[1].strip()
            )
        else:
            out.append(justify(s, max_len))
    return out


# pylint: disable=unused-argument
def text_adjustment_join_unicode(self, lines, sep=""):
    """Join Unicode"""
    try:
        return sep.join(lines)
    except UnicodeDecodeError:
        # sep = compat.text_type(sep)
        return sep.join([x.decode("utf-8") if isinstance(x, str) else x for x in lines])


# pylint: disable=unused-argument
def text_adjustment_adjoin(self, space, *lists, **kwargs):
    """Adjoin"""
    # Add space for all but the last column:
    pads = ([space] * (len(lists) - 1)) + [0]
    max_col_len = max(len(col) for col in lists)
    new_cols = []
    for col, pad in zip(lists, pads):
        width = max(self.len(s) for s in col) + pad
        c = self.justify(col, width, mode="left")
        # Add blank cells to end of col if needed for different col lens:
        if len(col) < max_col_len:
            c.extend([" " * width] * (max_col_len - len(col)))
        new_cols.append(c)

    rows = [self.join_unicode(row_tup) for row_tup in zip(*new_cols)]
    return self.join_unicode(rows, sep="\n")


# https://github.com/pandas-dev/pandas/issues/18066#issuecomment-522192922
def patch_pandas_text_adjustment():
    """Set pandas text adjustment settings"""
    pandas.io.formats.format.TextAdjustment.__init__ = text_adjustment_init
    pandas.io.formats.format.TextAdjustment.len = text_adjustment_len
    pandas.io.formats.format.TextAdjustment.justify = text_adjustment_justify
    pandas.io.formats.format.TextAdjustment.join_unicode = text_adjustment_join_unicode
    pandas.io.formats.format.TextAdjustment.adjoin = text_adjustment_adjoin


def parse_known_args_and_warn(
    parser: argparse.ArgumentParser,
    other_args: List[str],
    export_allowed: int = NO_EXPORT,
    raw: bool = False,
    limit: int = 0,
):
    """Parses list of arguments into the supplied parser

    Parameters
    ----------
    parser: argparse.ArgumentParser
        Parser with predefined arguments
    other_args: List[str]
        List of arguments to parse
    export_allowed: int
        Choose from NO_EXPORT, EXPORT_ONLY_RAW_DATA_ALLOWED,
        EXPORT_ONLY_FIGURES_ALLOWED and EXPORT_BOTH_RAW_DATA_AND_FIGURES
    raw: bool
        Add the --raw flag
    limit: int
        Add a --limit flag with this number default
    Returns
    -------
    ns_parser:
        Namespace with parsed arguments
    """
    parser.add_argument(
        "-h", "--help", action="store_true", help="show this help message"
    )
    if export_allowed > NO_EXPORT:
        choices_export = []
        help_export = "Does not export!"

        if export_allowed == EXPORT_ONLY_RAW_DATA_ALLOWED:
            choices_export = ["csv", "json", "xlsx"]
            help_export = "Export raw data into csv, json, xlsx"
        elif export_allowed == EXPORT_ONLY_FIGURES_ALLOWED:
            choices_export = ["png", "jpg", "pdf", "svg"]
            help_export = "Export figure into png, jpg, pdf, svg "
        else:
            choices_export = ["csv", "json", "xlsx", "png", "jpg", "pdf", "svg"]
            help_export = "Export raw data into csv, json, xlsx and figure into png, jpg, pdf, svg "

        parser.add_argument(
            "--export",
            choices=choices_export,
            default="",
            type=str,
            dest="export",
            help=help_export,
        )

    if raw:
        parser.add_argument(
            "--raw",
            dest="raw",
            action="store_true",
            default=False,
            help="Flag to display raw data",
        )
    if limit > 0:
        parser.add_argument(
            "-l",
            "--limit",
            dest="limit",
            default=limit,
            help="Number of entries to show in data.",
            type=int,
        )

    if gtff.USE_CLEAR_AFTER_CMD:
        system_clear()

    try:
        (ns_parser, l_unknown_args) = parser.parse_known_args(other_args)
    except SystemExit:
        # In case the command has required argument that isn't specified
        console.print("")
        return None

    if ns_parser.help:
        txt_help = parser.format_help()
        console.print(f"[help]{txt_help}[/help]")
        return None

    if l_unknown_args:
        console.print(f"The following args couldn't be interpreted: {l_unknown_args}")

    return ns_parser


def lambda_financials_colored_values(val: str) -> str:
    """Add a color to a value"""
    if val == "N/A" or str(val) == "nan":
        val = "[yellow]N/A[/yellow]"
    elif sum(c.isalpha() for c in val) < 2:
        if "%" in val and "-" in val or "%" not in val and "(" in val:
            val = f"[red]{val}[/red]"
        elif "%" in val:
            val = f"[green]{val}[/green]"
    return val


def check_ohlc(type_ohlc: str) -> str:
    """Check that data is in ohlc"""
    if bool(re.match("^[ohlca]+$", type_ohlc)):
        return type_ohlc
    raise argparse.ArgumentTypeError("The type specified is not recognized")


def lett_to_num(word: str) -> str:
    """Matches ohlca to integers"""
    replacements = [("o", "1"), ("h", "2"), ("l", "3"), ("c", "4"), ("a", "5")]
    for (a, b) in replacements:
        word = word.replace(a, b)
    return word


def get_flair() -> str:
    """Get a flair icon"""
    flairs = {
        ":rocket": "(🚀🚀)",
        ":diamond": "(💎💎)",
        ":stars": "(✨)",
        ":baseball": "(⚾)",
        ":boat": "(⛵)",
        ":phone": "(☎)",
        ":mercury": "(☿)",
        ":hidden": "",
        ":sun": "(☼)",
        ":moon": "(☾)",
        ":nuke": "(☢)",
        ":hazard": "(☣)",
        ":tunder": "(☈)",
        ":king": "(♔)",
        ":queen": "(♕)",
        ":knight": "(♘)",
        ":recycle": "(♻)",
        ":scales": "(⚖)",
        ":ball": "(⚽)",
        ":golf": "(⛳)",
        ":piece": "(☮)",
        ":yy": "(☯)",
    }

    flair = flairs[gtff.USE_FLAIR] if gtff.USE_FLAIR in flairs else gtff.USE_FLAIR
    if gtff.USE_DATETIME and get_user_timezone_or_invalid() != "INVALID":
        dtime = datetime.now(pytz.timezone(get_user_timezone())).strftime(
            "%Y %b %d, %H:%M"
        )

        # if there is no flair, don't add an extra space after the time
        if flair == "":
            return f"{dtime}"

        return f"{dtime} {flair}"

    return flair


def is_timezone_valid(user_tz: str) -> bool:
    """Check whether user timezone is valid

    Parameters
    ----------
    user_tz: str
        Timezone to check for validity

    Returns
    -------
    bool
        True if timezone provided is valid
    """
    return user_tz in pytz.all_timezones


def get_user_timezone() -> str:
    """Get user timezone if it is a valid one

    Returns
    -------
    str
        user timezone based on timezone.gst file
    """
    filename = os.path.join(
        os.path.dirname(os.path.abspath(__file__)),
        "timezone.gst",
    )
    if os.path.isfile(filename):
        with open(filename) as f:
            return f.read()
    return ""


def get_user_timezone_or_invalid() -> str:
    """Get user timezone if it is a valid one

    Returns
    -------
    str
        user timezone based on timezone.gst file or INVALID
    """
    user_tz = get_user_timezone()
    if is_timezone_valid(user_tz):
        return f"{user_tz}"
    return "INVALID"


def replace_user_timezone(user_tz: str) -> None:
    """Replace user timezone

    Parameters
    ----------
    user_tz: str
        User timezone to set
    """
    filename = os.path.join(
        os.path.dirname(os.path.abspath(__file__)),
        "timezone.gst",
    )
    if os.path.isfile(filename):
        with open(filename, "w") as f:
            if is_timezone_valid(user_tz):
                if f.write(user_tz):
                    console.print("Timezone successfully updated", "\n")
                else:
                    console.print("Timezone not set successfully", "\n")
            else:
                console.print("Timezone selected is not valid", "\n")
    else:
        console.print("timezone.gst file does not exist", "\n")


def str_to_bool(value) -> bool:
    """Match a string to a boolean value"""
    if isinstance(value, bool):
        return value
    if value.lower() in {"false", "f", "0", "no", "n"}:
        return False
    if value.lower() in {"true", "t", "1", "yes", "y"}:
        return True
    raise ValueError(f"{value} is not a valid boolean value")


def get_screeninfo():
    """Get screeninfo"""
    screens = get_monitors()  # Get all available monitors
    if len(screens) - 1 < cfgPlot.MONITOR:  # Check to see if chosen monitor is detected
        monitor = 0
        console.print(
            f"Could not locate monitor {cfgPlot.MONITOR}, using primary monitor."
        )
    else:
        monitor = cfgPlot.MONITOR
    main_screen = screens[monitor]  # Choose what monitor to get

    return (main_screen.width, main_screen.height)


def plot_autoscale():
    """Autoscale plot"""

    if gtff.USE_PLOT_AUTOSCALING:
        x, y = get_screeninfo()  # Get screen size
        x = ((x) * cfgPlot.PLOT_WIDTH_PERCENTAGE * 10**-2) / (
            cfgPlot.PLOT_DPI
        )  # Calculate width
        if cfgPlot.PLOT_HEIGHT_PERCENTAGE == 100:  # If full height
            y = y - 60  # Remove the height of window toolbar
        y = ((y) * cfgPlot.PLOT_HEIGHT_PERCENTAGE * 10**-2) / (cfgPlot.PLOT_DPI)
    else:  # If not autoscale, use size defined in config_plot.py
        x = cfgPlot.PLOT_WIDTH / (cfgPlot.PLOT_DPI)
        y = cfgPlot.PLOT_HEIGHT / (cfgPlot.PLOT_DPI)
    return x, y


def get_last_time_market_was_open(dt):
    """Get last time the US market was open"""
    # Check if it is a weekend
    if dt.date().weekday() > 4:
        dt = get_last_time_market_was_open(dt - timedelta(hours=24))

    # Check if it is a holiday
    if dt.strftime("%Y-%m-%d") in us_holidays():
        dt = get_last_time_market_was_open(dt - timedelta(hours=24))

    dt = dt.replace(hour=21, minute=0, second=0)

    return dt


def export_data(
    export_type: str, dir_path: str, func_name: str, df: pd.DataFrame = pd.DataFrame()
) -> None:
    """Export data to a file.

    Parameters
    ----------
    export_type : str
        Type of export between: csv,json,xlsx,xls
    dir_path : str
        Path of directory from where this function is called
    func_name : str
        Name of the command that invokes this function
    df : pd.Dataframe
        Dataframe of data to save
    """
    if export_type:
        export_dir = dir_path.replace("gamestonk_terminal", "exports")

        now = datetime.now()
        full_path = os.path.abspath(
            os.path.join(
                export_dir,
                f"{func_name}_{now.strftime('%Y%m%d_%H%M%S')}",
            )
        )

        if "," not in export_type:
            export_type += ","

        for exp_type in export_type.split(","):
            if exp_type:
                saved_path = f"{full_path}.{exp_type}"

                if exp_type == "csv":
                    df.to_csv(saved_path)
                elif exp_type == "json":
                    df.to_json(saved_path)
                elif exp_type in "xlsx":
                    df.to_excel(saved_path, index=True, header=True)
                elif exp_type == "png":
                    plt.savefig(saved_path)
                elif exp_type == "jpg":
                    plt.savefig(saved_path)
                elif exp_type == "pdf":
                    plt.savefig(saved_path)
                elif exp_type == "svg":
                    plt.savefig(saved_path)
                else:
                    console.print("Wrong export file specified.\n")

                console.print(f"Saved file: {saved_path}\n")


def get_rf() -> float:
    """
    Uses the fiscaldata.gov API to get most recent T-Bill rate

    Returns
    -------
    rate : float
        The current US T-Bill rate
    """
    try:
        base = "https://api.fiscaldata.treasury.gov/services/api/fiscal_service"
        end = "/v2/accounting/od/avg_interest_rates"
        filters = "?filter=security_desc:eq:Treasury Bills&sort=-record_date"
        response = requests.get(base + end + filters)
        latest = response.json()["data"][0]
        return round(float(latest["avg_interest_rate_amt"]) / 100, 8)
    except Exception:
        return 0.02


class LineAnnotateDrawer:
    """Line drawing class."""

    def __init__(self, ax: matplotlib.axes = None):
        self.ax = ax

    def draw_lines_and_annotate(self):
        # ymin, _ = self.ax.get_ylim()
        # xmin, _ = self.ax.get_xlim()
        # self.ax.plot(
        #     [xmin, xmin],
        #     [ymin, ymin],
        #     lw=0,
        #     color="white",
        #     label="X - leave interactive mode\nClick twice for annotation",
        # )
        # self.ax.legend(handlelength=0, handletextpad=0, fancybox=True, loc=2)
        # self.ax.figure.canvas.draw()
        """Draw lines."""
        console.print(
            "Click twice for annotation.\nClose window to keep using terminal.\n"
        )

        while True:
            xy = plt.ginput(2)
            # Check whether the user has closed the window or not
            if not plt.get_fignums():
                console.print("")
                return

            if len(xy) == 2:
                x = [p[0] for p in xy]
                y = [p[1] for p in xy]

                if (x[0] == x[1]) and (y[0] == y[1]):
                    txt = input("Annotation: ")
                    self.ax.annotate(txt, (x[0], y[1]), ha="center", va="center")
                else:
                    self.ax.plot(x, y)

                self.ax.figure.canvas.draw()


def system_clear():
    """Clear screen"""
    os.system("cls||clear")  # nosec


def excel_columns() -> List[str]:
    """
    Returns potential columns for excel

    Returns
    -------
    letters : List[str]
        Letters to be used as excel columns
    """
    letters = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M"]
    letters += ["N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "X", "Y", "Z"]

    opts = (
        [f"{x}" for x in letters]
        + [f"{x}{y}" for x in letters for y in letters]
        + [f"{x}{y}{z}" for x in letters for y in letters for z in letters]
    )
    return opts