"""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