util package#

Submodules#

util.afterhours module#

util.afterhours.afterHours()[source]#

Simple code to check if the current time is after hours in the US. Source: https://www.reddit.com/r/algotrading/comments/9x9xho/python_code_to_check_if_market_is_open_in_your/

Returns:

True if it is currently after-hours, False otherwise.

Return type:

bool

util.cg_data module#

util.confirm_stock module#

util.db module#

util.disc_util module#

util.earnings_scraper module#

util.exchange_data module#

util.formatting module#

util.formatting.format_change(change)[source]#

Converts a float to a string with a plus sign if the float is positive, and a minus sign if the float is negative.

Parameters:

change (float) – The percentual change of an asset.

Returns:

The formatted change.

Return type:

str

async util.formatting.format_embed(og_df, type, source)[source]#

Formats the dataframe to an embed.

Parameters:
  • df (pd.DataFrame) – A dataframe with the columns: Symbol Price % Change Volume

  • type (str) – The type used in the title of the embed

  • source (str) – The source used for this data

Returns:

A Discord embed containing the formatted data

Return type:

discord.Embed

util.formatting.format_embed_length(data)[source]#

If the length of the data is greater than 1024 characters, it will be shortened to that amount.

Parameters:

data (list) – The list containing the description for an embed.

Returns:

The shortened description.

Return type:

list

util.formatting.human_format(number, absolute=False, decimals=0)[source]#

Takes a number and returns a human readable string. Taken from: https://stackoverflow.com/questions/579310/formatting-long-numbers-as-strings-in-python/45846841.

Parameters:
  • number (float) – The number to be formatted.

  • absolute (bool) – If True, the number will be converted to its absolute value.

  • decimals (int) – The number of decimals to be used.

Returns:

The formatted number as a string.

Return type:

str

util.get_tweet module#

util.parse_tweet module#

util.sentiment_analyis module#

util.ticker_classifier module#

util.trades_msg module#

util.tv_data module#

util.tv_symbols module#

util.tweet_embed module#

util.vars module#

util.yf_data module#

Module contents#