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OpenBB/openbb_terminal/helper_funcs.py
Pratyush Shukla 13283fbfce CI listing quick fix (#6002) 
* BIGGGG LINTING

* fixing lints

* fixing lints

* black

* very ruff

* no export

* fix hedge_view again

* lints

* platform lints

* lints

* black

* black it @hjoaquim

* fix some more linting

---------

Co-authored-by: hjoaquim <h.joaquim@campus.fct.unl.pt>
2024-01-26 17:08:42 +00:00

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"""Helper functions."""
__docformat__ = "numpy"
# pylint: disable=too-many-lines
# IMPORTS STANDARD LIBRARY
# IMPORTS STANDARD
import argparse
import inspect
import io
import json
import logging
import os
import random
import re
import shutil
import sys
import urllib.parse
import webbrowser
from datetime import (
date as d,
datetime,
timedelta,
)
from difflib import SequenceMatcher
from functools import lru_cache
from pathlib import Path
from typing import Dict, List, Optional, Tuple, Union
# IMPORTS THIRDPARTY
import iso8601
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import pandas.io.formats.format
import pandas_ta as ta
import pytz
import requests
import yfinance as yf
from holidays import US as us_holidays
from langchain.chat_models import ChatOpenAI
from llama_index import (
LLMPredictor,
PromptHelper,
ServiceContext,
SimpleDirectoryReader,
StorageContext,
VectorStoreIndex,
load_index_from_storage,
)
from pandas._config.config import get_option
from pandas.plotting import register_matplotlib_converters
from PIL import Image, ImageDraw
from rich.table import Table
from screeninfo import get_monitors
from openbb_terminal import OpenBBFigure, plots_backend
from openbb_terminal.core.config.paths import (
HOME_DIRECTORY,
MISCELLANEOUS_DIRECTORY,
)
from openbb_terminal.core.plots.plotly_ta.ta_class import PlotlyTA
from openbb_terminal.core.session.current_system import get_current_system
# IMPORTS INTERNAL
from openbb_terminal.core.session.current_user import get_current_user
from openbb_terminal.decorators import check_api_key
from openbb_terminal.rich_config import console
logger = logging.getLogger(__name__)
register_matplotlib_converters()
if (
get_current_user().preferences.PLOT_BACKEND is not None
and get_current_user().preferences.PLOT_BACKEND != "None"
):
matplotlib.use(get_current_user().preferences.PLOT_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
GPT_INDEX_DIRECTORY = MISCELLANEOUS_DIRECTORY / "gpt_index/"
GPT_INDEX_VER = 0.4
# Command location path to be shown in the figures depending on watermark flag
command_location = ""
# pylint: disable=R1702,R0912
# pylint: disable=global-statement
def set_command_location(cmd_loc: str):
"""Set command location.
Parameters
----------
cmd_loc: str
Command location called by user
"""
if cmd_loc.split("/")[-1] == "hold":
return
global command_location # noqa
command_location = cmd_loc
def check_path(path: str) -> str:
"""Check that path file exists.
Parameters
----------
path: str
path of file
Returns
-------
str:
Ratio of similarity between two strings
"""
# Just return empty path because this will be handled outside this function
if not path:
return ""
if path[0] == "~":
path = path.replace("~", HOME_DIRECTORY.as_posix())
# Return string of path if such relative path exists
if os.path.isfile(path):
return path
# Return string of path if an absolute path exists
if os.path.isfile("/" + path):
return f"/{path}"
logger.error("The path file '%s' does not exist.", path)
console.print(f"[red]The path file '{path}' does not exist.\n[/red]")
return ""
def parse_and_split_input(an_input: str, custom_filters: List) -> List[str]:
"""Filter and split the input queue.
Uses regex to filters command arguments that have forward slashes so that it doesn't
break the execution of the command queue.
Currently handles unix paths and sorting settings for screener menus.
Parameters
----------
an_input : str
User input as string
custom_filters : List
Additional regular expressions to match
Returns
-------
List[str]
Command queue as list
"""
# Make sure that the user can go back to the root when doing "/"
if an_input and an_input == "/":
an_input = "home"
# everything from ` -f ` to the next known extension
file_flag = r"(\ -f |\ --file )"
up_to = r".*?"
known_extensions = r"(\.(xlsx|csv|xls|tsv|json|yaml|ini|openbb|ipynb))"
unix_path_arg_exp = f"({file_flag}{up_to}{known_extensions})"
# Add custom expressions to handle edge cases of individual controllers
custom_filter = ""
for exp in custom_filters:
if exp is not None:
custom_filter += f"|{exp}"
del exp
slash_filter_exp = f"({unix_path_arg_exp}){custom_filter}"
filter_input = True
placeholders: Dict[str, str] = {}
while filter_input:
match = re.search(pattern=slash_filter_exp, string=an_input)
if match is not None:
placeholder = f"{{placeholder{len(placeholders)+1}}}"
placeholders[placeholder] = an_input[
match.span()[0] : match.span()[1] # noqa:E203
]
an_input = (
an_input[: match.span()[0]]
+ placeholder
+ an_input[match.span()[1] :] # noqa:E203
)
else:
filter_input = False
commands = an_input.split("/")
for command_num, command in enumerate(commands):
if command == commands[command_num] == commands[-1] == "":
return list(filter(None, commands))
matching_placeholders = [tag for tag in placeholders if tag in command]
if len(matching_placeholders) > 0:
for tag in matching_placeholders:
commands[command_num] = command.replace(tag, placeholders[tag])
return commands
def log_and_raise(error: Union[argparse.ArgumentTypeError, ValueError]) -> None:
"""Log and output an error."""
logger.error(str(error))
raise error
def similar(a: str, b: str) -> float:
"""Return a similarity float between string a and string b.
Parameters
----------
a: str
string a
b: str
string b
Returns
-------
float:
Ratio of similarity between two strings
"""
return SequenceMatcher(None, a, b).ratio()
def return_colored_value(value: str):
"""Return the string value with green, yellow, red or white color based on
whether the number is positive, negative, zero or other, respectively.
Parameters
----------
value: str
string to be checked
Returns
-------
value: str
string with color based on value of number if it exists
"""
values = re.findall(r"[-+]?(?:\d*\.\d+|\d+)", value)
# Finds exactly 1 number in the string
if len(values) == 1:
if float(values[0]) > 0:
return f"[green]{value}[/green]"
if float(values[0]) < 0:
return f"[red]{value}[/red]"
if float(values[0]) == 0:
return f"[yellow]{value}[/yellow]"
return f"{value}"
# pylint: disable=too-many-arguments
def print_rich_table( # noqa: PLR0912
df: pd.DataFrame,
show_index: bool = False,
title: str = "",
index_name: str = "",
headers: Optional[Union[List[str], pd.Index]] = None,
floatfmt: Union[str, List[str]] = ".2f",
show_header: bool = True,
automatic_coloring: bool = False,
columns_to_auto_color: Optional[List[str]] = None,
rows_to_auto_color: Optional[List[str]] = None,
export: bool = False,
print_to_console: bool = False,
limit: Optional[int] = 1000,
source: Optional[str] = None,
columns_keep_types: Optional[List[str]] = None,
):
"""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: Union[str, List[str]]
Float number formatting specs as string or list of strings. Defaults to ".2f"
show_header: bool
Whether to show the header row.
automatic_coloring: bool
Automatically color a table based on positive and negative values
columns_to_auto_color: List[str]
Columns to automatically color
rows_to_auto_color: List[str]
Rows to automatically color
export: bool
Whether we are exporting the table to a file. If so, we don't want to print it.
limit: Optional[int]
Limit the number of rows to show.
print_to_console: bool
Whether to print the table to the console. If False and interactive mode is
enabled, the table will be displayed in a new window. Otherwise, it will print to the
console.
source: Optional[str]
Source of the table. If provided, it will be displayed in the header of the table.
columns_keep_types: Optional[List[str]]
Columns to keep their types, i.e. not convert to numeric
"""
if export:
return
current_user = get_current_user()
enable_interactive = (
current_user.preferences.USE_INTERACTIVE_DF and plots_backend().isatty
)
# Make a copy of the dataframe to avoid SettingWithCopyWarning
df = df.copy()
show_index = not isinstance(df.index, pd.RangeIndex) and show_index
# convert non-str that are not timestamp or int into str
# eg) praw.models.reddit.subreddit.Subreddit
for col in df.columns:
if columns_keep_types is not None and col in columns_keep_types:
continue
try:
if not any(
isinstance(df[col].iloc[x], pd.Timestamp)
for x in range(min(10, len(df)))
):
df[col] = pd.to_numeric(df[col], errors="ignore")
except (ValueError, TypeError):
df[col] = df[col].astype(str)
def _get_headers(_headers: Union[List[str], pd.Index]) -> List[str]:
"""Check if headers are valid and return them."""
output = _headers
if isinstance(_headers, pd.Index):
output = list(_headers)
if len(output) != len(df.columns):
log_and_raise(
ValueError("Length of headers does not match length of DataFrame")
)
return output
if enable_interactive and not print_to_console:
df_outgoing = df.copy()
# If headers are provided, use them
if headers is not None:
# We check if headers are valid
df_outgoing.columns = _get_headers(headers)
if show_index and index_name not in df_outgoing.columns:
# If index name is provided, we use it
df_outgoing.index.name = index_name or "Index"
df_outgoing = df_outgoing.reset_index()
for col in df_outgoing.columns:
if col == "":
df_outgoing = df_outgoing.rename(columns={col: " "})
plots_backend().send_table(
df_table=df_outgoing,
title=title,
source=source, # type: ignore
theme=current_user.preferences.TABLE_STYLE,
)
return
df = df.copy() if not limit else df.copy().iloc[:limit]
if automatic_coloring:
if columns_to_auto_color:
for col in columns_to_auto_color:
# checks whether column exists
if col in df.columns:
df[col] = df[col].apply(lambda x: return_colored_value(str(x)))
if rows_to_auto_color:
for row in rows_to_auto_color:
# checks whether row exists
if row in df.index:
df.loc[row] = df.loc[row].apply(
lambda x: return_colored_value(str(x))
)
if columns_to_auto_color is None and rows_to_auto_color is None:
df = df.applymap(lambda x: return_colored_value(str(x)))
if current_user.preferences.USE_TABULATE_DF:
table = Table(title=title, show_lines=True, show_header=show_header)
if show_index:
table.add_column(index_name)
if headers is not None:
headers = _get_headers(headers)
for header in headers:
table.add_column(str(header))
else:
for column in df.columns:
table.add_column(str(column))
if isinstance(floatfmt, list) and 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()):
# remove hour/min/sec from timestamp index - Format: YYYY-MM-DD # make better
row_idx = [str(idx)] if show_index else []
row_idx += [
(
str(x)
if not isinstance(x, float) and not isinstance(x, np.float64)
else (
f"{x:{floatfmt[idx]}}"
if isinstance(floatfmt, list)
else (
f"{x:.2e}"
if 0 < abs(float(x)) <= 0.0001
else f"{x:floatfmt}"
)
)
)
for idx, x in enumerate(values)
]
table.add_row(*row_idx)
console.print(table)
else:
console.print(df.to_string(col_space=0))
def check_int_range(mini: int, maxi: int):
"""Check 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:
"""Check 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 that terra account address has proper format.
Example: ^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_float_list(value) -> List[float]:
"""Argparse type to return list of positive floats."""
list_of_nums = value.split(",")
list_of_pos = []
for a_value in list_of_nums:
new_value = float(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_indicators(string: str) -> List[str]:
"""Check if indicators are valid."""
ta_cls = PlotlyTA()
choices = sorted(
[c.name.replace("plot_", "") for c in ta_cls if c.name != "plot_ma"]
+ ta_cls.ma_mode
)
choices_print = (
f"{'`, `'.join(choices[:10])}`\n `{'`, `'.join(choices[10:20])}"
f"`\n `{'`, `'.join(choices[20:])}"
)
strings = string.split(",")
for s in strings:
if s not in choices:
raise argparse.ArgumentTypeError(
f"\nInvalid choice: {s}, choose from \n `{choices_print}`",
)
return strings
def check_indicator_parameters(args: str, _help: bool = False) -> str:
"""Check if indicators parameters are valid."""
ta_cls = PlotlyTA()
indicators_dict: dict = {}
regex = re.compile(r"([a-zA-Z]+)\[([0-9.,]*)\]")
no_params_regex = re.compile(r"([a-zA-Z]+)")
matches = regex.findall(args)
no_params_matches = no_params_regex.findall(args)
indicators = [m[0] for m in matches]
for match in no_params_matches:
if match not in indicators:
matches.append((match, ""))
if _help:
console.print(
"""[yellow]To pass custom parameters to indicators:[/]
[green]Example:
-i macd[12,26,9],rsi[14],sma[20,50]
-i macd,rsi,sma (uses default parameters)
[yellow]Would pass the following to the indicators:[/]
[green]macd=dict(fast=12, slow=26, signal=9)
rsi=dict(length=14)
sma=dict(length=[20,50])
They must be in the same order as the function parameters.[/]\n"""
)
pop_keys = ["close", "high", "low", "open", "open_", "volume", "talib", "return"]
if matches:
check_indicators(",".join([m[0] for m in matches]))
for match in matches:
indicator, args = match
indicators_dict.setdefault(indicator, {})
if indicator in ["fib", "srlines", "demark", "clenow"]:
if _help:
console.print(
f"[yellow]{indicator}:[/]\n{'':^4}[green]Parameters: None[/]"
)
continue
fullspec = inspect.getfullargspec(getattr(ta, indicator))
kwargs = list(set(fullspec.args) - set(pop_keys))
kwargs.sort(key=fullspec.args.index)
if _help:
console.print(
f"[yellow]{indicator}:[/]\n{'':^4}[green]Parameters: {', '.join(kwargs)}[/]"
)
if indicator in ta_cls.ma_mode:
indicators_dict[indicator]["length"] = check_positive_list(args)
continue
for i, arg in enumerate(args.split(",")):
if arg and len(kwargs) > i:
indicators_dict[indicator][kwargs[i]] = (
float(arg) if "." in arg else int(arg)
)
return json.dumps(indicators_dict)
if not matches:
raise argparse.ArgumentTypeError(
f"Invalid indicator arguments: {args}. \n Example: -i macd[12,26,9],rsi[14]"
)
return args
def check_positive_float(value) -> float:
"""Argparse type to check positive float."""
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_percentage_range(num) -> float:
"""Check if float is between 0 and 100. 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 = 100.0
mini = 0.0
if num <= mini or num >= maxi:
log_and_raise(argparse.ArgumentTypeError("Value must be between 0 and 100"))
return num
def check_proportion_range(num) -> float:
"""Check 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 is_valid_date(s: str) -> bool:
"""Check if date is in valid format."""
try:
datetime.strptime(s, "%Y-%m-%d")
return True
except ValueError:
return False
def valid_repo(repo: str) -> str:
"""Argparse type to check github repo is in valid format."""
result = re.search(r"^[a-zA-Z0-9-_.]+\/[a-zA-Z0-9-_.]+$", repo) # noqa: W605
if not result:
log_and_raise(
argparse.ArgumentTypeError(
f"{repo} is not a valid repo. Valid repo: org/repo"
)
)
return repo
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 lower_str(string: str) -> str:
"""Convert string to lowercase."""
return string.lower()
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) -> Union[str, int, float]:
"""Format a long number."""
if get_current_user().preferences.USE_INTERACTIVE_DF:
return num
if num == float("inf"):
return "inf"
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()
and not num.lstrip("-").startswith("0")
and not is_valid_date(num)
):
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 revert_lambda_long_number_format(num_str: str) -> Union[float, str]:
"""
Revert the formatting of a long number if the input is a formatted number, otherwise return the input as is.
Parameters
----------
num_str : str
The number to remove the formatting.
Returns
-------
Union[float, str]
The number as float (with no formatting) or the input as is.
"""
magnitude_dict = {
"K": 1000,
"M": 1000000,
"B": 1000000000,
"T": 1000000000000,
"P": 1000000000000000,
}
# Ensure the input is a string and not empty
if not num_str or not isinstance(num_str, str):
return num_str
num_as_list = num_str.strip().split()
# If the input string is a number parse it as float
if (
len(num_as_list) == 1
and num_as_list[0].replace(".", "").replace("-", "").isdigit()
and not is_valid_date(num_str)
):
return float(num_str)
# If the input string is a formatted number with magnitude
if (
len(num_as_list) == 2
and num_as_list[1] in magnitude_dict
and num_as_list[0].replace(".", "").replace("-", "").isdigit()
):
num, unit = num_as_list
magnitude = magnitude_dict.get(unit)
if magnitude:
return float(num) * magnitude
# Return the input string as is if it's not a formatted number
return num_str
def lambda_long_number_format_y_axis(df, y_column, ax):
"""Format long number that goes onto Y axis."""
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:
"""Clean 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:
"""Get the next stock market day.
Checks against weekends and holidays.
"""
n_days = 0
l_pred_days = []
years: list = []
holidays: list = []
if isinstance(last_stock_day, datetime):
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)
else:
while n_days < n_next_days:
l_pred_days.append(last_stock_day + 1 + n_days)
n_days += 1
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]
intraday = not granularity >= timedelta(days=1)
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
"""
date_format = "%b %d %H:%M" if is_intraday(df) else "%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):
"""Get 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 else tweet["text"]
return {"created_at": s_datetime, "text": s_text}
def clean_tweet(tweet: str, symbol: str) -> str:
"""Clean 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 # noqa: S311
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"):
"""Apply 'Justify' text alignment."""
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):
"""Join text."""
# 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 lambda_financials_colored_values(val: str) -> str:
"""Add a color to a value."""
# We don't want to do the color stuff in interactive mode
if get_current_user().preferences.USE_INTERACTIVE_DF:
return val
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:
"""Match 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
AVAILABLE_FLAIRS = {
":openbb": "(🦋)",
":bug": "(🐛)",
":rocket": "(🚀)",
":diamond": "(💎)",
":stars": "(✨)",
":baseball": "(⚾)",
":boat": "(⛵)",
":phone": "(☎)",
":mercury": "(☿)",
":hidden": "",
":sun": "(☼)",
":moon": "(☾)",
":nuke": "(☢)",
":hazard": "(☣)",
":tunder": "(☈)",
":king": "(♔)",
":queen": "(♕)",
":knight": "(♘)",
":recycle": "(♻)",
":scales": "(⚖)",
":ball": "(⚽)",
":golf": "(⛳)",
":piece": "(☮)",
":yy": "(☯)",
}
def get_flair() -> str:
"""Get a flair icon."""
current_user = get_current_user() # pylint: disable=redefined-outer-name
current_flair = str(current_user.preferences.FLAIR)
flair = AVAILABLE_FLAIRS.get(current_flair, current_flair)
if (
current_user.preferences.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 .env file
"""
return get_current_user().preferences.TIMEZONE
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 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."""
try:
screens = get_monitors() # Get all available monitors
except Exception:
return None
if screens:
current_user = get_current_user()
if (
len(screens) - 1 < current_user.preferences.MONITOR
): # Check to see if chosen monitor is detected
monitor = 0
console.print(
f"Could not locate monitor {current_user.preferences.MONITOR}, using primary monitor."
)
else:
monitor = current_user.preferences.MONITOR
main_screen = screens[monitor] # Choose what monitor to get
return (main_screen.width, main_screen.height)
return None
def plot_autoscale():
"""Autoscale plot."""
current_user = get_current_user()
screen_info = get_screeninfo()
if current_user.preferences.USE_PLOT_AUTOSCALING and screen_info:
x, y = screen_info # Get screen size
# account for ultrawide monitors
if x / y > 1.5:
x = x * 0.4
x = ((x) * current_user.preferences.PLOT_WIDTH_PERCENTAGE * 10**-2) / (
current_user.preferences.PLOT_DPI
) # Calculate width
if current_user.preferences.PLOT_HEIGHT_PERCENTAGE == 100: # If full height
y = y - 60 # Remove the height of window toolbar
y = ((y) * current_user.preferences.PLOT_HEIGHT_PERCENTAGE * 10**-2) / (
current_user.preferences.PLOT_DPI
)
else: # If not autoscale, use size defined in config_plot.py
x = current_user.preferences.PLOT_WIDTH / (current_user.preferences.PLOT_DPI)
y = current_user.preferences.PLOT_HEIGHT / (current_user.preferences.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: Optional[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:
"""Check 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!\nPlease use one of the following file types:"
f"{','.join(valid_types)}[/red]\n"
)
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')}_{path_cmd}_{func_name}"
full_path = get_current_user().preferences.USER_EXPORTS_DIRECTORY / default_filename
return full_path
def ask_file_overwrite(file_path: Path) -> Tuple[bool, bool]:
"""Helper to provide a prompt for overwriting existing files.
Returns two values, the first is a boolean indicating if the file exists and the
second is a boolean indicating if the user wants to overwrite the file.
"""
# Jeroen asked for a flag to overwrite no matter what
current_user = get_current_user()
if current_user.preferences.FILE_OVERWRITE:
return False, True
if get_current_system().TEST_MODE:
return False, True
if file_path.exists():
overwrite = input("\nFile already exists. Overwrite? [y/n]: ").lower()
if overwrite == "y":
file_path.unlink(missing_ok=True)
# File exists and user wants to overwrite
return True, True
# File exists and user does not want to overwrite
return True, False
# File does not exist
return False, True
def save_to_excel(df, saved_path, sheet_name, start_row=0, index=True, header=True):
"""Saves a Pandas DataFrame to an Excel file.
Args:
df: A Pandas DataFrame.
saved_path: The path to the Excel file to save to.
sheet_name: The name of the sheet to save the DataFrame to.
start_row: The row number to start writing the DataFrame at.
index: Whether to write the DataFrame index to the Excel file.
header: Whether to write the DataFrame header to the Excel file.
"""
overwrite_options = {
"o": "replace",
"a": "overlay",
"n": "new",
}
if not saved_path.exists():
with pd.ExcelWriter(saved_path, engine="openpyxl") as writer:
df.to_excel(writer, sheet_name=sheet_name, index=index, header=header)
else:
with pd.ExcelFile(saved_path) as reader:
overwrite_option = "n"
if sheet_name in reader.sheet_names:
overwrite_option = input(
"\nSheet already exists. Overwrite/Append/New? [o/a/n]: "
).lower()
start_row = 0
if overwrite_option == "a":
existing_df = pd.read_excel(saved_path, sheet_name=sheet_name)
start_row = existing_df.shape[0] + 1
with pd.ExcelWriter(
saved_path,
mode="a",
if_sheet_exists=overwrite_options[overwrite_option],
engine="openpyxl",
) as writer:
df.to_excel(
writer,
sheet_name=sheet_name,
startrow=start_row,
index=index,
header=False if overwrite_option == "a" else header,
)
# This is a false positive on pylint and being tracked in pylint #3060
# pylint: disable=abstract-class-instantiated
def export_data(
export_type: str,
dir_path: str,
func_name: str,
df: pd.DataFrame = pd.DataFrame(),
sheet_name: Optional[str] = None,
figure: Optional[OpenBBFigure] = None,
margin: bool = True,
) -> 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
sheet_name : str
If provided. The name of the sheet to save in excel file
figure : Optional[OpenBBFigure]
Figure object to save as image file
margin : bool
Automatically adjust subplot parameters to give specified padding.
"""
if export_type:
saved_path = compose_export_path(func_name, dir_path).resolve()
saved_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 = saved_path.with_name(exp_type)
# In this scenario we use the default filename
else:
if ".OpenBB_openbb_terminal" in saved_path.name:
saved_path = saved_path.with_name(
saved_path.name.replace(
".OpenBB_openbb_terminal", "OpenBBTerminal"
)
)
saved_path = saved_path.with_suffix(f".{exp_type}")
exists, overwrite = False, False
is_xlsx = exp_type.endswith("xlsx")
if sheet_name is None and is_xlsx or not is_xlsx:
exists, overwrite = ask_file_overwrite(saved_path)
if exists and not overwrite:
existing = len(list(saved_path.parent.glob(saved_path.stem + "*")))
saved_path = saved_path.with_stem(f"{saved_path.stem}_{existing + 1}")
df = df.replace(
{
r"\[yellow\]": "",
r"\[/yellow\]": "",
r"\[green\]": "",
r"\[/green\]": "",
r"\[red\]": "",
r"\[/red\]": "",
r"\[magenta\]": "",
r"\[/magenta\]": "",
},
regex=True,
)
df = df.applymap(revert_lambda_long_number_format)
if exp_type.endswith("csv"):
df.to_csv(saved_path)
elif exp_type.endswith("json"):
df.reset_index(drop=True, inplace=True)
df.to_json(saved_path)
elif exp_type.endswith("xlsx"):
# since xlsx does not support datetimes with timezones we need to remove it
df = remove_timezone_from_dataframe(df)
if sheet_name is None: # noqa: SIM223
df.to_excel(
saved_path,
index=True,
header=True,
)
else:
save_to_excel(df, saved_path, sheet_name)
elif saved_path.suffix in [".jpg", ".pdf", ".png", ".svg"]:
if figure is None:
console.print("No plot to export.")
continue
figure.show(export_image=saved_path, margin=margin)
else:
console.print("Wrong export file specified.")
continue
console.print(f"Saved file: {saved_path}")
if figure is not None:
figure._exported = True # pylint: disable=protected-access
def get_rf() -> float:
"""Use 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 = request(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 # noqa: S605,S607
def excel_columns() -> List[str]:
"""Return 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):
"""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-fill Google Form and open it in the browser."""
form_url = "https://my.openbb.co/app/terminal/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:
"""Convert 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 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
print_text = (
custom_text
if custom_text
else 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]:
"""Check if argparse argument is an str format.
Ensure that 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()
values_found = (
[val.strip() for val in given_values.split(",")]
if "," in given_values
else [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.
Parameters
----------
expression: str
Expression to search for
"""
url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{expression}"
response = requests.request("GET", url, headers={}, data={})
if response.status_code == 200:
response_json = json.loads(response.text)
res = {
"title": response_json["title"],
"url": f"{response_json['content_urls']['desktop']['page']}",
"summary": response_json["extract"],
}
else:
res = {
"title": "[red]Not Found[/red]",
}
df = pd.json_normalize(res)
print_rich_table(
df,
headers=list(df.columns),
show_index=False,
title=f"Wikipedia results for {expression}",
)
def screenshot() -> None:
"""Screenshot the terminal window or the plot window.
Parameters
----------
terminal_window_target: bool
Target the terminal window
"""
try:
if plt.get_fignums():
img_buf = io.BytesIO()
plt.savefig(img_buf, format="png")
shot = Image.open(img_buf)
screenshot_to_canvas(shot, plot_exists=True)
else:
console.print("No plots found.\n")
except Exception as err:
console.print(f"Cannot reach window - {err}\n")
def screenshot_to_canvas(shot, plot_exists: bool = False):
"""Frame image to OpenBB canvas.
Parameters
----------
shot
Image to frame with OpenBB Canvas
plot_exists: bool
Variable to say whether the image is a plot or screenshot of terminal
"""
WHITE_LINE_WIDTH = 3
OUTSIDE_CANVAS_WIDTH = shot.width + 4 * WHITE_LINE_WIDTH + 5
OUTSIDE_CANVAS_HEIGHT = shot.height + 4 * WHITE_LINE_WIDTH + 5
UPPER_SPACE = 40
BACKGROUND_WIDTH_SLACK = 150
BACKGROUND_HEIGHT_SLACK = 150
background = Image.open(
Path(os.path.abspath(__file__), "../../images/background.png")
)
logo = Image.open(
Path(os.path.abspath(__file__), "../../images/openbb_horizontal_logo.png")
)
try:
if plot_exists:
HEADER_HEIGHT = 0
RADIUS = 8
background = background.resize(
(
shot.width + BACKGROUND_WIDTH_SLACK,
shot.height + BACKGROUND_HEIGHT_SLACK,
)
)
x = int((background.width - OUTSIDE_CANVAS_WIDTH) / 2)
y = UPPER_SPACE
white_shape = (
(x, y),
(x + OUTSIDE_CANVAS_WIDTH, y + OUTSIDE_CANVAS_HEIGHT),
)
img = ImageDraw.Draw(background)
img.rounded_rectangle(
white_shape,
fill="black",
outline="white",
width=WHITE_LINE_WIDTH,
radius=RADIUS,
)
background.paste(shot, (x + WHITE_LINE_WIDTH + 5, y + WHITE_LINE_WIDTH + 5))
# Logo
background.paste(
logo,
(
int((background.width - logo.width) / 2),
UPPER_SPACE
+ OUTSIDE_CANVAS_HEIGHT
+ HEADER_HEIGHT
+ int(
(
background.height
- UPPER_SPACE
- OUTSIDE_CANVAS_HEIGHT
- HEADER_HEIGHT
- logo.height
)
/ 2
),
),
logo,
)
background.show(title="screenshot")
except Exception:
console.print("Shot failed.")
@lru_cache
def load_json(path: Path) -> Dict[str, str]:
"""Load a dictionary from a json file path.
Parameter
----------
path : Path
The path for the json file
Returns
-------
Dict[str, str]
The dictionary loaded from json
"""
try:
with open(path) as file:
return json.load(file)
except Exception as e:
console.print(
f"[red]Failed to load preferred source from file: "
f"{get_current_user().preferences.USER_DATA_SOURCES_FILE}[/red]"
)
console.print(f"[red]{e}[/red]")
return {}
def list_from_str(value: str) -> List[str]:
"""Convert a string to a list.
Parameter
---------
value : str
The string to convert
Returns
-------
new_value: List[str]
The list of strings
"""
if value:
return value.split(",")
return []
def str_date_to_timestamp(date: str) -> int:
"""Transform string date to timestamp
Parameters
----------
start_date : str
Initial date, format YYYY-MM-DD
Returns
-------
date_ts : int
Initial date timestamp (e.g., 1_614_556_800)
"""
date_ts = int(
datetime.strptime(date + " 00:00:00+0000", "%Y-%m-%d %H:%M:%S%z").timestamp()
)
return date_ts
def check_start_less_than_end(start_date: str, end_date: str) -> bool:
"""Check if start_date is equal to end_date.
Parameters
----------
start_date : str
Initial date, format YYYY-MM-DD
end_date : str
Final date, format YYYY-MM-DD
Returns
-------
bool
True if start_date is not equal to end_date, False otherwise
"""
if start_date is None or end_date is None:
return False
if start_date == end_date:
console.print("[red]Start date and end date cannot be the same.[/red]")
return True
if start_date > end_date:
console.print("[red]Start date cannot be greater than end date.[/red]")
return True
return False
# Write an abstract helper to make requests from a url with potential headers and params
def request(
url: str, method: str = "get", timeout: int = 0, **kwargs
) -> requests.Response:
"""Abstract helper to make requests from a url with potential headers and params.
Parameters
----------
url : str
Url to make the request to
method : str
HTTP method to use. Choose from:
delete, get, head, patch, post, put, by default "get"
timeout : int
How many seconds to wait for the server to send data
Returns
-------
requests.Response
Request response object
Raises
------
ValueError
If invalid method is passed
"""
method = method.lower()
if method not in ["delete", "get", "head", "patch", "post", "put"]:
raise ValueError(f"Invalid method: {method}")
current_user = get_current_user()
# We want to add a user agent to the request, so check if there are any headers
# If there are headers, check if there is a user agent, if not add one.
# Some requests seem to work only with a specific user agent, so we want to be able to override it.
headers = kwargs.pop("headers", {})
timeout = timeout or current_user.preferences.REQUEST_TIMEOUT
if "User-Agent" not in headers:
headers["User-Agent"] = get_user_agent()
func = getattr(requests, method)
return func(
url,
headers=headers,
timeout=timeout,
**kwargs,
)
def remove_timezone_from_dataframe(df: pd.DataFrame) -> pd.DataFrame:
"""
Remove timezone information from a dataframe.
Parameters
----------
df : pd.DataFrame
The dataframe to remove timezone information from
Returns
-------
pd.DataFrame
The dataframe with timezone information removed
"""
date_cols = []
index_is_date = False
# Find columns and index containing date data
if (
df.index.dtype.kind == "M"
and hasattr(df.index.dtype, "tz")
and df.index.dtype.tz is not None
):
index_is_date = True
for col, dtype in df.dtypes.items():
if dtype.kind == "M" and hasattr(df.index.dtype, "tz") and dtype.tz is not None:
date_cols.append(col)
# Remove the timezone information
for col in date_cols:
df[col] = df[col].dt.date
if index_is_date:
index_name = df.index.name
df.index = df.index.date
df.index.name = index_name
return df
@check_api_key(["API_OPENAI_KEY"])
def query_LLM_local(query_text, gpt_model):
current_user = get_current_user()
os.environ["OPENAI_API_KEY"] = current_user.credentials.API_OPENAI_KEY
# check if index exists
index_path = GPT_INDEX_DIRECTORY / f"index_{GPT_INDEX_VER}.json"
old_index_paths = [
str(x) for x in GPT_INDEX_DIRECTORY.glob("index_*.json") if x != index_path
]
# define LLM
llm_predictor = LLMPredictor(llm=ChatOpenAI(temperature=0.5, model_name=gpt_model))
# define prompt helper
prompt_helper = PromptHelper(context_window=4096, num_output=256)
service_context = ServiceContext.from_defaults(
llm_predictor=llm_predictor, prompt_helper=prompt_helper
)
if os.path.exists(index_path):
# rebuild storage context
storage_context = StorageContext.from_defaults(persist_dir=index_path)
index = load_index_from_storage(
service_context=service_context, storage_context=storage_context
)
else:
# If the index file doesn't exist or is of incorrect version, generate a new one
# First, remove old version(s), if any
for path in old_index_paths:
if os.path.isfile(path):
os.remove(path)
elif os.path.isdir(path):
shutil.rmtree(path)
# Then, generate and save new index
# import from print console and say generating index, this might take a while
console.print("Generating index, this might take a while....\n")
# read in documents
documents = SimpleDirectoryReader(GPT_INDEX_DIRECTORY / "data/").load_data()
index = VectorStoreIndex.from_documents(
documents, service_context=service_context
)
# save to disk
console.print("Saving index to disk....\n")
index.storage_context.persist(index_path)
current_date = datetime.now().astimezone(pytz.timezone("America/New_York"))
prompt_string = f"""From the cli argparse help text above, provide the terminal
command for {query_text}. If relevant, use the examples as guidance.
Provide the exact command along with the parent command with a "/" separation to get that information,
and nothing else including any explanation. Don't add any other word such as 'Command to get', 'Answer'
or the likes. If you do not know, reply "I don't know"
Current date: {current_date.strftime("%Y-%m-%d")}
Current day of the week: {current_date.strftime("%A")}
Remember:
1. It is very important to provide the full path of the command including the parent command and loading
the particular target before running any subsequent commands
2. If you are asked about dates or times, load the target dates, times span during the "load" command
before running any subsequent commands. replace all <> with the actual dates and times. The date format should
be YYYY-MM-DD. If there is no date included in the query, do not specify any.
3. Country names should be snake case and lower case. example: united_states.
4. Always use a comma to separate between countries and no spaces: example: united_states,italy,spain
5. Always use "load" command first before running any subsequent commands. example:
stocks/load <symbol>/ ....
crypto/load <symbol>/ .... etc.
6. Do not include --export unless the request asks for the data to be exported or saved to a specific file type.
7. Do not make up any subcommands or options for the specific command.
8. Do not provide anything that could be interpreted as investment advice.
9. Any request asking for options refers to stocks/options.
Only do what is asked and only provide a single command string, never more than one.
"""
# try to get the response from the index
try:
query_engine = index.as_query_engine()
response = query_engine.query(prompt_string)
return response.response, response.source_nodes
except Exception as e:
# check if the error has the following "The model: `gpt-4` does not exist"
if "The model: `gpt-4` does not exist" in str(e):
console.print(
"[red]You do not have access to GPT4 model with your API key."
" Please try again with valid API Access.[/red]"
)
return None
console.print(f"[red]Something went wrong with the query. {e}[/red]")
return None, None
def query_LLM_remote(query_text: str):
"""Query askobb on gpt-3.5 turbo hosted model
Parameters
----------
query_text : str
Query string for askobb
"""
url = "https://api.openbb.co/askobb"
data = {"prompt": query_text, "accessToken": get_current_user().profile.token}
ask_obbrequest_data = request(url, method="POST", json=data, timeout=15).json()
if "error" in ask_obbrequest_data:
console.print(f"[red]{ask_obbrequest_data['error']}[/red]")
return None, None
return ask_obbrequest_data["response"], ask_obbrequest_data["source_nodes"]
def check_valid_date(date_string) -> bool:
""" "Helper to see if we can parse the string to a date"""
try:
# Try to parse the string with strptime()
datetime.strptime(
date_string, "%Y-%m-%d"
) # Use the format your dates are expected to be in
return True # If it can be parsed, then it is a valid date string
except ValueError: # strptime() throws a ValueError if the string can't be parsed
return False
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