mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-10-27 12:40:35 +00:00
1665 lines
47 KiB
Python
1665 lines
47 KiB
Python
"""Helper functions"""
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__docformat__ = "numpy"
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# pylint: disable=too-many-lines
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import argparse
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import logging
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from pathlib import Path
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from typing import List, Union, Optional, Dict
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from datetime import datetime, timedelta, date as d
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import types
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from collections.abc import Iterable
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import os
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import random
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import re
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import sys
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from difflib import SequenceMatcher
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import webbrowser
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import urllib.parse
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import json
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import pytz
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import pandas as pd
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from rich.table import Table
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import iso8601
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import dotenv
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import matplotlib
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import matplotlib.pyplot as plt
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from holidays import US as us_holidays
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from pandas._config.config import get_option
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from pandas.plotting import register_matplotlib_converters
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import pandas.io.formats.format
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import requests
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from screeninfo import get_monitors
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import yfinance as yf
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import numpy as np
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from openbb_terminal.rich_config import console
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from openbb_terminal import feature_flags as obbff
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from openbb_terminal import config_plot as cfgPlot
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from openbb_terminal.core.config.paths import (
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HOME_DIRECTORY,
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USER_ENV_FILE,
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USER_EXPORTS_DIRECTORY,
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)
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from openbb_terminal.core.config import paths
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logger = logging.getLogger(__name__)
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register_matplotlib_converters()
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if cfgPlot.BACKEND is not None:
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matplotlib.use(cfgPlot.BACKEND)
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NO_EXPORT = 0
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EXPORT_ONLY_RAW_DATA_ALLOWED = 1
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EXPORT_ONLY_FIGURES_ALLOWED = 2
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EXPORT_BOTH_RAW_DATA_AND_FIGURES = 3
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MENU_GO_BACK = 0
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MENU_QUIT = 1
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MENU_RESET = 2
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# Command location path to be shown in the figures depending on watermark flag
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command_location = ""
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# pylint: disable=global-statement
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def set_command_location(cmd_loc: str):
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"""Set command location
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Parameters
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----------
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cmd_loc: str
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Command location called by user
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"""
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global command_location
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command_location = cmd_loc
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# pylint: disable=global-statement
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def set_user_data_folder(env_file: str = ".env", path_folder: str = ""):
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"""Set user data folder location
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Parameters
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----------
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env_file : str
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Env file to be updated
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path_folder: str
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Path folder location
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"""
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dotenv.set_key(env_file, "OPENBB_USER_DATA_DIRECTORY", path_folder)
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paths.USER_DATA_DIRECTORY = Path(path_folder)
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def check_path(path: str) -> str:
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"""Check that path file exists
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Parameters
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----------
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path: str
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path of file
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Returns
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-------
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str:
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Ratio of similarity between two strings
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"""
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# Just return empty path because this will be handled outside this function
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if not path:
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return ""
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if path[0] == "~":
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path = path.replace("~", HOME_DIRECTORY.as_posix())
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# Return string of path if such relative path exists
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if os.path.isfile(path):
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return path
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# Return string of path if an absolute path exists
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if os.path.isfile("/" + path):
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return f"/{path}"
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logger.error("The path file '%s' does not exist.", path)
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console.print(f"[red]The path file '{path}' does not exist.\n[/red]")
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return ""
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def parse_and_split_input(an_input: str, custom_filters: List) -> List[str]:
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"""Filter and split the input queue
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Uses regex to filters command arguments that have forward slashes so that it doesn't
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break the execution of the command queue.
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Currently handles unix paths and sorting settings for screener menus.
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Parameters
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----------
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an_input : str
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User input as string
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custom_filters : List
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Additional regular expressions to match
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Returns
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-------
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List[str]
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Command queue as list
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"""
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# Make sure that the user can go back to the root when doing "/"
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if an_input:
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if an_input == "/":
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an_input = "home"
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elif an_input[0] == "/":
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an_input = "home" + an_input
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# everything from ` -f ` to the next known extension
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file_flag = r"(\ -f |\ --file )"
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up_to = r".*?"
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known_extensions = r"(\.xlsx|.csv|.xls|.tsv|.json|.yaml|.ini|.openbb)"
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unix_path_arg_exp = f"({file_flag}{up_to}{known_extensions})"
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# Add custom expressions to handle edge cases of individual controllers
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custom_filter = ""
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for exp in custom_filters:
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if exp is not None:
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custom_filter += f"|{exp}"
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del exp
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slash_filter_exp = f"({unix_path_arg_exp}){custom_filter}"
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filter_input = True
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placeholders: Dict[str, str] = {}
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while filter_input:
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match = re.search(pattern=slash_filter_exp, string=an_input)
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if match is not None:
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placeholder = f"{{placeholder{len(placeholders)+1}}}"
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placeholders[placeholder] = an_input[
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match.span()[0] : match.span()[1] # noqa:E203
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]
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an_input = (
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an_input[: match.span()[0]]
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+ placeholder
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+ an_input[match.span()[1] :] # noqa:E203
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)
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else:
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filter_input = False
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commands = an_input.split("/")
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for command_num, command in enumerate(commands):
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if command == commands[command_num] == commands[-1] == "":
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return list(filter(None, commands))
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matching_placeholders = [tag for tag in placeholders if tag in command]
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if len(matching_placeholders) > 0:
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for tag in matching_placeholders:
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commands[command_num] = command.replace(tag, placeholders[tag])
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return commands
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def log_and_raise(error: Union[argparse.ArgumentTypeError, ValueError]) -> None:
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logger.error(str(error))
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raise error
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def similar(a: str, b: str) -> float:
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"""
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Return a similarity float between string a and string b
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Parameters
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----------
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a: str
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string a
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b: str
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string b
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Returns
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-------
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float:
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Ratio of similarity between two strings
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"""
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return SequenceMatcher(None, a, b).ratio()
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def print_rich_table(
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df: pd.DataFrame,
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show_index: bool = False,
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title: str = "",
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index_name: str = "",
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headers: Union[List[str], pd.Index] = None,
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floatfmt: Union[str, List[str]] = ".2f",
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show_header: bool = True,
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):
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"""Prepare a table from df in rich
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Parameters
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----------
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df: pd.DataFrame
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Dataframe to turn into table
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show_index: bool
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Whether to include index
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title: str
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Title for table
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index_name : str
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Title for index column
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headers: List[str]
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Titles for columns
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floatfmt: Union[str, List[str]]
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Float number formatting specs as string or list of strings. Defaults to ".2f"
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show_header: bool
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Whether to show the header row.
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"""
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if obbff.USE_TABULATE_DF:
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table = Table(title=title, show_lines=True, show_header=show_header)
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if show_index:
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table.add_column(index_name)
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if headers is not None:
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if isinstance(headers, pd.Index):
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headers = list(headers)
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if len(headers) != len(df.columns):
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log_and_raise(
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ValueError("Length of headers does not match length of DataFrame")
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)
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for header in headers:
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table.add_column(str(header))
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else:
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for column in df.columns:
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table.add_column(str(column))
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if isinstance(floatfmt, list):
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if len(floatfmt) != len(df.columns):
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log_and_raise(
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ValueError(
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"Length of floatfmt list does not match length of DataFrame columns."
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)
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)
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if isinstance(floatfmt, str):
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floatfmt = [floatfmt for _ in range(len(df.columns))]
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for idx, values in zip(df.index.tolist(), df.values.tolist()):
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row = [str(idx)] if show_index else []
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row += [
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str(x)
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if not isinstance(x, float) and not isinstance(x, np.float64)
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else (
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f"{x:{floatfmt[idx]}}"
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if isinstance(floatfmt, list)
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else (
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f"{x:.2e}" if 0 < abs(float(x)) <= 0.0001 else f"{x:floatfmt}"
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)
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)
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for idx, x in enumerate(values)
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]
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table.add_row(*row)
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console.print()
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console.print(table)
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else:
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console.print(df.to_string(col_space=0))
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def check_int_range(mini: int, maxi: int):
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"""
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Checks if argparse argument is an int between 2 values.
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Parameters
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----------
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mini: int
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Min value to compare
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maxi: int
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Max value to compare
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Returns
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-------
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int_range_checker:
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Function that compares the three integers
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"""
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# Define the function with default arguments
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def int_range_checker(num: int) -> int:
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"""
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Checks if int is between a high and low value
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Parameters
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----------
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num: int
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Input integer
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Returns
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-------
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num: int
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Input number if conditions are met
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Raises
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-------
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argparse.ArgumentTypeError
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Input number not between min and max values
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"""
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num = int(num)
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if num < mini or num > maxi:
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log_and_raise(
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argparse.ArgumentTypeError(f"Argument must be in range [{mini},{maxi}]")
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)
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return num
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# Return function handle to checking function
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return int_range_checker
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def check_non_negative(value) -> int:
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"""Argparse type to check non negative int"""
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new_value = int(value)
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if new_value < 0:
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log_and_raise(argparse.ArgumentTypeError(f"{value} is negative"))
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return new_value
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def check_terra_address_format(address: str) -> str:
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"""Validate if terra account address has proper format: ^terra1[a-z0-9]{38}$
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Parameters
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----------
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address: str
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terra blockchain account address
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Returns
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-------
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str
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Terra blockchain address or raise argparse exception
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"""
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pattern = re.compile(r"^terra1[a-z0-9]{38}$")
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if not pattern.match(address):
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log_and_raise(
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argparse.ArgumentTypeError(
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f"Terra address: {address} has invalid format. Valid format: ^terra1[a-z0-9]{{38}}$"
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)
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)
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return address
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def check_non_negative_float(value) -> float:
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"""Argparse type to check non negative int"""
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new_value = float(value)
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if new_value < 0:
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log_and_raise(argparse.ArgumentTypeError(f"{value} is negative"))
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return new_value
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def check_positive_list(value) -> List[int]:
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"""Argparse type to return list of positive ints"""
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list_of_nums = value.split(",")
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list_of_pos = []
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for a_value in list_of_nums:
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new_value = int(a_value)
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if new_value <= 0:
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log_and_raise(
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argparse.ArgumentTypeError(f"{value} is an invalid positive int value")
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)
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list_of_pos.append(new_value)
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return list_of_pos
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def check_positive(value) -> int:
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"""Argparse type to check positive int"""
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new_value = int(value)
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if new_value <= 0:
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log_and_raise(
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argparse.ArgumentTypeError(f"{value} is an invalid positive int value")
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)
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return new_value
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def check_positive_float(value) -> float:
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"""Argparse type to check positive int"""
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new_value = float(value)
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if new_value <= 0:
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log_and_raise(
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argparse.ArgumentTypeError(f"{value} is not a positive float value")
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)
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return new_value
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def check_percentage_range(num) -> float:
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"""
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Checks if float is between 0 and 100. If so, return it.
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Parameters
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----------
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num: float
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Input float
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Returns
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-------
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num: float
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Input number if conditions are met
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Raises
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-------
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argparse.ArgumentTypeError
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Input number not between min and max values
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"""
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num = float(num)
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maxi = 100.0
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mini = 0.0
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if num <= mini or num >= maxi:
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log_and_raise(argparse.ArgumentTypeError("Value must be between 0 and 100"))
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return num
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def check_proportion_range(num) -> float:
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"""
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Checks if float is between 0 and 1. If so, return it.
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Parameters
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----------
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num: float
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Input float
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Returns
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-------
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num: float
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Input number if conditions are met
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Raises
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-------
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argparse.ArgumentTypeError
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Input number not between min and max values
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"""
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num = float(num)
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maxi = 1.0
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mini = 0.0
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if num < mini or num > maxi:
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log_and_raise(argparse.ArgumentTypeError("Value must be between 0 and 1"))
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return num
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def valid_date_in_past(s: str) -> datetime:
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"""Argparse type to check date is in valid format"""
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try:
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delta = datetime.now() - datetime.strptime(s, "%Y-%m-%d")
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if delta.days < 1:
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log_and_raise(
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argparse.ArgumentTypeError(
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f"Not a valid date: {s}. Must be earlier than today"
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)
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)
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return datetime.strptime(s, "%Y-%m-%d")
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except ValueError as value_error:
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logging.exception(str(value_error))
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raise argparse.ArgumentTypeError(f"Not a valid date: {s}") from value_error
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|
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def check_list_dates(str_dates: str) -> List[datetime]:
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"""Argparse type to check list of dates provided have a valid format
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Parameters
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----------
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str_dates: str
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string with dates separated by ","
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Returns
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-------
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list_dates: List[datetime]
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List of valid dates
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"""
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list_dates = list()
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if str_dates:
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if "," in str_dates:
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for dt_marker in str_dates.split(","):
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list_dates.append(valid_date(dt_marker))
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else:
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list_dates.append(valid_date(str_dates))
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return list_dates
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|
|
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def valid_date(s: str) -> datetime:
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"""Argparse type to check date is in valid format"""
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try:
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return datetime.strptime(s, "%Y-%m-%d")
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except ValueError as value_error:
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logging.exception(str(value_error))
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raise argparse.ArgumentTypeError(f"Not a valid date: {s}") from value_error
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|
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def valid_repo(repo: str) -> str:
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"""Argparse type to check github repo is in valid format"""
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result = re.search(r"^[a-zA-Z0-9-_.]+\/[a-zA-Z0-9-_.]+$", repo) # noqa: W605
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if not result:
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log_and_raise(
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argparse.ArgumentTypeError(
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f"{repo} is not a valid repo. Valid repo: org/repo"
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)
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)
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return repo
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|
|
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def valid_hour(hr: str) -> int:
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"""Argparse type to check hour is valid with 24-hour notation"""
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|
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new_hr = int(hr)
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if (new_hr < 0) or (new_hr > 24):
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log_and_raise(
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argparse.ArgumentTypeError(f"{hr} doesn't follow 24-hour notion.")
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)
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|
return new_hr
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|
|
|
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|
def plot_view_stock(df: pd.DataFrame, symbol: str, interval: str):
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"""
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|
Plot the loaded stock dataframe
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|
Parameters
|
|
----------
|
|
df: Dataframe
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|
Dataframe of prices and volumes
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symbol: str
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|
Symbol of ticker
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interval: str
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Stock data resolution for plotting purposes
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"""
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df.sort_index(ascending=True, inplace=True)
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bar_colors = ["r" if x[1].Open < x[1].Close else "g" for x in df.iterrows()]
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try:
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fig, ax = plt.subplots(
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2,
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|
1,
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gridspec_kw={"height_ratios": [3, 1]},
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figsize=plot_autoscale(),
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|
dpi=cfgPlot.PLOT_DPI,
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)
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|
except Exception as e:
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|
console.print(e)
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|
console.print(
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|
"Encountered an error trying to open a chart window. Check your X server configuration."
|
|
)
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|
logging.exception("%s", type(e).__name__)
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return
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|
|
# In order to make nice Volume plot, make the bar width = interval
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|
if interval == "1440min":
|
|
bar_width = timedelta(days=1)
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|
title_string = "Daily"
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|
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 obbff.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 = [
|
|
date
|
|
for date in list(all_holidays)
|
|
if all_holidays[date] in market_and_observed_holidays
|
|
]
|
|
|
|
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, round_decimal=3) -> str:
|
|
"""Format a long number"""
|
|
|
|
if isinstance(num, float):
|
|
magnitude = 0
|
|
while abs(num) >= 1000:
|
|
magnitude += 1
|
|
num /= 1000.0
|
|
|
|
string_fmt = f".{round_decimal}f"
|
|
|
|
num_str = int(num) if num.is_integer() else f"{num:{string_fmt}}"
|
|
|
|
return f"{num_str} {' KMBTP'[magnitude]}".strip()
|
|
if isinstance(num, int):
|
|
num = str(num)
|
|
if isinstance(num, str) and num.lstrip("-").isdigit():
|
|
num = int(num)
|
|
num /= 1.0
|
|
magnitude = 0
|
|
while abs(num) >= 1000:
|
|
magnitude += 1
|
|
num /= 1000.0
|
|
|
|
string_fmt = f".{round_decimal}f"
|
|
num_str = int(num) if num.is_integer() else f"{num:{string_fmt}}"
|
|
|
|
return f"{num_str} {' KMBTP'[magnitude]}".strip()
|
|
return num
|
|
|
|
|
|
def lambda_long_number_format_y_axis(df, y_column, ax):
|
|
max_values = df[y_column].values.max()
|
|
|
|
magnitude = 0
|
|
while abs(max_values) >= 1000:
|
|
magnitude += 1
|
|
max_values /= 1000.0
|
|
|
|
magnitude_sym = " KMBTP"[magnitude]
|
|
|
|
# Second y label axis -
|
|
if magnitude_sym == " ":
|
|
ax[2].set_ylabel(f"{y_column}")
|
|
else:
|
|
ax[2].set_ylabel(f"{y_column} [{magnitude_sym}]")
|
|
|
|
divider_map = {" ": 1, "K": 1000, "M": 1000000, "B": 1000000000}
|
|
divider = divider_map[magnitude_sym]
|
|
|
|
ax[2].get_yaxis().set_major_formatter(
|
|
matplotlib.ticker.FuncFormatter(lambda x, _: int(x / divider))
|
|
)
|
|
|
|
|
|
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 the data is inf, -inf, or NaN then simply return '~' because it is either too
|
|
# large, too small, or we do not have data to display for it
|
|
if x in (np.inf, -np.inf, np.nan):
|
|
return " " + "~"
|
|
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, symbol: 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)@{symbol}(?=\b)")
|
|
user = re.compile(r"(?i)@[a-z0-9_]+")
|
|
|
|
tweet = whitespace.sub(" ", tweet)
|
|
tweet = web_address.sub("", tweet)
|
|
tweet = ticker.sub(symbol, 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_simple_args(parser: argparse.ArgumentParser, other_args: List[str]):
|
|
"""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
|
|
|
|
Returns
|
|
-------
|
|
ns_parser:
|
|
Namespace with parsed arguments
|
|
"""
|
|
parser.add_argument(
|
|
"-h", "--help", action="store_true", help="show this help message"
|
|
)
|
|
|
|
if obbff.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 = {
|
|
":openbb": "(🦋)",
|
|
":rocket": "(🚀)",
|
|
":diamond": "(💎)",
|
|
":stars": "(✨)",
|
|
":baseball": "(⚾)",
|
|
":boat": "(⛵)",
|
|
":phone": "(☎)",
|
|
":mercury": "(☿)",
|
|
":hidden": "",
|
|
":sun": "(☼)",
|
|
":moon": "(☾)",
|
|
":nuke": "(☢)",
|
|
":hazard": "(☣)",
|
|
":tunder": "(☈)",
|
|
":king": "(♔)",
|
|
":queen": "(♕)",
|
|
":knight": "(♘)",
|
|
":recycle": "(♻)",
|
|
":scales": "(⚖)",
|
|
":ball": "(⚽)",
|
|
":golf": "(⛳)",
|
|
":piece": "(☮)",
|
|
":yy": "(☯)",
|
|
}
|
|
|
|
flair = (
|
|
flairs[str(obbff.USE_FLAIR)]
|
|
if str(obbff.USE_FLAIR) in flairs
|
|
else str(obbff.USE_FLAIR)
|
|
)
|
|
|
|
set_default_timezone()
|
|
if obbff.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 set_default_timezone() -> None:
|
|
"""Sets a default (America/New_York) timezone if one doesn't exist"""
|
|
|
|
dotenv.load_dotenv(USER_ENV_FILE)
|
|
user_tz = os.getenv("OPENBB_TIMEZONE")
|
|
if not user_tz:
|
|
dotenv.set_key(USER_ENV_FILE, "OPENBB_TIMEZONE", "America/New_York")
|
|
|
|
|
|
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 .env file
|
|
"""
|
|
dotenv.load_dotenv(USER_ENV_FILE)
|
|
user_tz = os.getenv("OPENBB_TIMEZONE")
|
|
if user_tz:
|
|
return user_tz
|
|
return ""
|
|
|
|
|
|
def get_user_timezone_or_invalid() -> str:
|
|
"""Get user timezone if it is a valid one
|
|
|
|
Returns
|
|
-------
|
|
str
|
|
user timezone based on timezone.openbb 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
|
|
"""
|
|
if is_timezone_valid(user_tz):
|
|
dotenv.set_key(USER_ENV_FILE, "OPENBB_TIMEZONE", user_tz)
|
|
console.print("Timezone successfully updated", "\n")
|
|
else:
|
|
console.print("Timezone selected is not valid", "\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 obbff.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 check_file_type_saved(valid_types: List[str] = None):
|
|
"""Provide valid types for the user to be able to select
|
|
|
|
Parameters
|
|
----------
|
|
valid_types: List[str]
|
|
List of valid types to export data
|
|
|
|
Returns
|
|
-------
|
|
check_filenames: Optional[List[str]]
|
|
Function that returns list of filenames to export data
|
|
"""
|
|
|
|
def check_filenames(filenames: str = "") -> str:
|
|
"""Checks if filenames are valid
|
|
|
|
Parameters
|
|
----------
|
|
filenames: str
|
|
filenames to be saved separated with comma
|
|
|
|
Returns
|
|
-------
|
|
str
|
|
valid filenames separated with comma
|
|
"""
|
|
if not filenames or not valid_types:
|
|
return ""
|
|
valid_filenames = list()
|
|
for filename in filenames.split(","):
|
|
if filename.endswith(tuple(valid_types)):
|
|
valid_filenames.append(filename)
|
|
else:
|
|
console.print(
|
|
f"[red]Filename '{filename}' provided is not valid![/red]"
|
|
)
|
|
return ",".join(valid_filenames)
|
|
|
|
return check_filenames
|
|
|
|
|
|
def compose_export_path(func_name: str, dir_path: str) -> Path:
|
|
"""Compose export path for data from the terminal
|
|
|
|
Creates a path to a folder and a filename based on conditions.
|
|
|
|
Parameters
|
|
----------
|
|
func_name : str
|
|
Name of the command that invokes this function
|
|
dir_path : str
|
|
Path of directory from where this function is called
|
|
|
|
Returns
|
|
-------
|
|
Path
|
|
Path variable containing the path of the exported file
|
|
"""
|
|
now = datetime.now()
|
|
# Resolving all symlinks and also normalizing path.
|
|
resolve_path = Path(dir_path).resolve()
|
|
# Getting the directory names from the path. Instead of using split/replace (Windows doesn't like that)
|
|
# check if this is done in a main context to avoid saving with openbb_terminal
|
|
if resolve_path.parts[-2] == "openbb_terminal":
|
|
path_cmd = f"{resolve_path.parts[-1]}"
|
|
else:
|
|
path_cmd = f"{resolve_path.parts[-2]}//{resolve_path.parts[-1]}"
|
|
|
|
default_filename = f"{now.strftime('%Y%m%d_%H%M%S')}_{func_name}"
|
|
|
|
full_path = USER_EXPORTS_DIRECTORY / path_cmd / default_filename
|
|
|
|
return full_path
|
|
|
|
|
|
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_path = compose_export_path(func_name, dir_path)
|
|
export_folder = str(export_path.parent)
|
|
export_filename = export_path.name
|
|
export_path.parent.mkdir(parents=True, exist_ok=True)
|
|
for exp_type in export_type.split(","):
|
|
# In this scenario the path was provided, e.g. --export pt.csv, pt.jpg
|
|
if "." in exp_type:
|
|
saved_path = os.path.join(export_folder, exp_type)
|
|
# In this scenario we use the default filename
|
|
else:
|
|
saved_path = os.path.join(
|
|
export_folder, f"{export_filename}.{exp_type}"
|
|
)
|
|
|
|
if exp_type.endswith("csv"):
|
|
df.to_csv(saved_path)
|
|
elif exp_type.endswith("json"):
|
|
df.to_json(saved_path)
|
|
elif exp_type.endswith("xlsx"):
|
|
df.to_excel(saved_path, index=True, header=True)
|
|
elif exp_type.endswith("png"):
|
|
plt.savefig(saved_path)
|
|
elif exp_type.endswith("jpg"):
|
|
plt.savefig(saved_path)
|
|
elif exp_type.endswith("pdf"):
|
|
plt.savefig(saved_path)
|
|
elif exp_type.endswith("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
|
|
|
|
|
|
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
|
|
|
|
|
|
def handle_error_code(requests_obj, error_code_map):
|
|
"""
|
|
Helper function to handle error code of HTTP requests.
|
|
|
|
Parameters
|
|
----------
|
|
requests_obj: Object
|
|
Request object
|
|
error_code_map: Dict
|
|
Dictionary mapping of HTTP error code and output message
|
|
|
|
"""
|
|
for error_code, error_msg in error_code_map.items():
|
|
if requests_obj.status_code == error_code:
|
|
console.print(error_msg)
|
|
|
|
|
|
def prefill_form(ticket_type, menu, path, command, message):
|
|
"""Pre-fille Google Form and open it in the browser"""
|
|
form_url = "https://openbb.co/support?"
|
|
|
|
params = {
|
|
"type": ticket_type,
|
|
"menu": menu,
|
|
"path": path,
|
|
"command": command,
|
|
"message": message,
|
|
}
|
|
|
|
url_params = urllib.parse.urlencode(params)
|
|
|
|
webbrowser.open(form_url + url_params)
|
|
|
|
|
|
def get_closing_price(ticker, days):
|
|
|
|
"""Get historical close price for n days in past for market asset
|
|
|
|
Parameters
|
|
----------
|
|
ticker : str
|
|
Ticker to get data for
|
|
days : datetime
|
|
No. of days in past
|
|
|
|
Returns
|
|
----------
|
|
data : pd.DataFrame
|
|
Historic close prices for ticker for given days
|
|
"""
|
|
tick = yf.Ticker(ticker)
|
|
df = tick.history(
|
|
start=d.today() - timedelta(days=days),
|
|
interval="1d",
|
|
)["Close"]
|
|
df = df.to_frame().reset_index()
|
|
df = df.rename(columns={0: "Close"})
|
|
df.index.name = "index"
|
|
return df
|
|
|
|
|
|
def camel_case_split(string: str) -> str:
|
|
"""Converts a camel case string to separate words
|
|
|
|
Parameters
|
|
----------
|
|
string : str
|
|
The string to be converted
|
|
|
|
Returns
|
|
----------
|
|
new_string: str
|
|
The formatted string
|
|
"""
|
|
|
|
words = [[string[0]]]
|
|
|
|
for c in string[1:]:
|
|
if words[-1][-1].islower() and c.isupper():
|
|
words.append(list(c))
|
|
else:
|
|
words[-1].append(c)
|
|
|
|
results = ["".join(word) for word in words]
|
|
return " ".join(results).title()
|
|
|
|
|
|
def choice_check_after_action(action=None, choices=None):
|
|
"""return an action class that checks choice after action call
|
|
for argument of argparse.ArgumentParser.add_argument function
|
|
|
|
Parameters
|
|
----------
|
|
action : Union[class, function]
|
|
Action for set args before check choices.
|
|
If action is class, it must implement argparse.Action methods
|
|
If action is function, it takes 4 args(parser, namespace, values, option_string)
|
|
and needs to return value to set dest
|
|
|
|
choices : Union[Iterable, function]
|
|
A container of values that should be allowed.
|
|
If choices is function, it takes 1 args(value) to check and
|
|
return bool that value is allowed or not
|
|
|
|
Returns
|
|
-------
|
|
Class
|
|
Class extended argparse.Action
|
|
"""
|
|
|
|
if isinstance(choices, Iterable):
|
|
|
|
def choice_checker(value):
|
|
return value in choices
|
|
|
|
elif isinstance(choices, types.FunctionType):
|
|
choice_checker = choices
|
|
else:
|
|
raise NotImplementedError("choices argument must be iterable or function")
|
|
|
|
if isinstance(action, type):
|
|
|
|
class ActionClass(action):
|
|
def __call__(self, parser, namespace, values, option_string=None):
|
|
super().__call__(parser, namespace, values, option_string)
|
|
if not choice_checker(getattr(namespace, self.dest)):
|
|
raise ValueError(
|
|
f"{getattr(namespace, self.dest)} is not in {choices}"
|
|
)
|
|
|
|
elif isinstance(action, types.FunctionType):
|
|
|
|
class ActionClass(argparse.Action):
|
|
def __call__(self, parser, namespace, values, option_string=None):
|
|
setattr(
|
|
namespace,
|
|
self.dest,
|
|
action(parser, namespace, values, option_string),
|
|
)
|
|
if not choice_checker(getattr(namespace, self.dest)):
|
|
raise ValueError(
|
|
f"{getattr(namespace, self.dest)} is not in {choices}"
|
|
)
|
|
|
|
else:
|
|
raise NotImplementedError("action argument must be class or function")
|
|
|
|
return ActionClass
|
|
|
|
|
|
def is_valid_axes_count(
|
|
axes: List[plt.Axes],
|
|
n: int,
|
|
custom_text: Optional[str] = None,
|
|
prefix_text: Optional[str] = None,
|
|
suffix_text: Optional[str] = None,
|
|
):
|
|
"""Check if axes list length is equal to n
|
|
and log text if check result is false
|
|
|
|
Parameters
|
|
----------
|
|
|
|
axes: List[plt.Axes]
|
|
External axes (2 axes are expected in the list)
|
|
n: int
|
|
number of expected axes
|
|
custom_text: Optional[str] = None
|
|
custom text to log
|
|
prefix_text: Optional[str] = None
|
|
prefix text to add before text to log
|
|
suffix_text: Optional[str] = None
|
|
suffix text to add after text to log
|
|
"""
|
|
|
|
if len(axes) == n:
|
|
return True
|
|
|
|
if custom_text:
|
|
print_text = custom_text
|
|
else:
|
|
print_text = f"Expected list of {n} axis item{'s' if n>1 else ''}."
|
|
|
|
if prefix_text:
|
|
print_text = f"{prefix_text} {print_text}"
|
|
if suffix_text:
|
|
print_text = f"{suffix_text} {print_text}"
|
|
|
|
logger.error(print_text)
|
|
console.print(f"[red]{print_text}\n[/red]")
|
|
return False
|
|
|
|
|
|
def support_message(s: str) -> str:
|
|
"""Argparse type to check string is in valid format
|
|
for the support command
|
|
"""
|
|
return s.replace('"', "")
|
|
|
|
|
|
def check_list_values(valid_values: List[str]):
|
|
"""
|
|
Get valid values to test arguments given by user
|
|
|
|
Parameters
|
|
----------
|
|
valid_values: List[str]
|
|
List of valid values to be checked
|
|
|
|
Returns
|
|
-------
|
|
check_list_values_from_valid_values_list:
|
|
Function that ensures that the valid values go through and notifies user when value is not valid.
|
|
"""
|
|
|
|
# Define the function with default arguments
|
|
def check_list_values_from_valid_values_list(given_values: str) -> List[str]:
|
|
"""
|
|
Checks if argparse argument is an str with format: value1,value2,value3 and that
|
|
the values value1, value2 and value3 are valid.
|
|
|
|
Parameters
|
|
----------
|
|
given_values: str
|
|
values provided by the user
|
|
|
|
Raises
|
|
-------
|
|
argparse.ArgumentTypeError
|
|
Input number not between min and max values
|
|
"""
|
|
success_values = list()
|
|
|
|
if "," in given_values:
|
|
values_found = [val.strip() for val in given_values.split(",")]
|
|
else:
|
|
values_found = [given_values]
|
|
|
|
for value in values_found:
|
|
# check if the value is valid
|
|
if value in valid_values:
|
|
success_values.append(value)
|
|
else:
|
|
console.print(f"[red]'{value}' is not valid.[/red]")
|
|
|
|
if not success_values:
|
|
log_and_raise(
|
|
argparse.ArgumentTypeError("No correct arguments have been found")
|
|
)
|
|
return success_values
|
|
|
|
# Return function handle to checking function
|
|
return check_list_values_from_valid_values_list
|
|
|
|
|
|
def search_wikipedia(expression: str) -> None:
|
|
"""
|
|
Search wikipedia for a given expression"
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Parameters
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----------
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expression: str
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Expression to search for
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"""
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url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{expression}"
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response = requests.request("GET", url, headers={}, data={})
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if response.status_code == 200:
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response_json = json.loads(response.text)
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res = {
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"title": response_json["title"],
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"url": f"[blue]{response_json['content_urls']['desktop']['page']}[/blue]",
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"summary": response_json["extract"],
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}
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else:
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res = {
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"title": "[red]Not Found[/red]",
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}
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df = pd.json_normalize(res)
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print_rich_table(
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df,
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headers=list(df.columns),
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show_index=False,
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title=f"Wikipedia results for {expression}",
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)
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