Merge branch 'develop' into hotfix/4833

README.md

@@ -80,7 +80,7 @@ If you wish to install the OpenBB Terminal or the OpenBB SDK, please use one of
 |:-|:-|
 |[PyPI](https://docs.openbb.co/terminal/installation/pypi)|If you wish to use the OpenBB SDK in Python or Jupyter Notebooks|
 |[Source](https://docs.openbb.co/terminal/installation/source)|If you wish to contribute to the development of the OpenBB Terminal|
-nbsp;|
+<!-- nbsp;| -->
 
 ## 2. Contributing
 

openbb_terminal/core/models/system_model.py

@@ -27,7 +27,7 @@ class SystemModel(BaseModel):
     PLATFORM: str = str(platform.platform())
 
     # OpenBB section
-    VERSION = "3.0.0"
+    VERSION: str = "3.0.0"
 
     # Logging section
     LOGGING_APP_ID: str = "REPLACE_ME"

openbb_terminal/core/plots/plotly_ta/plugins/volatility_plugin.py

@@ -84,11 +84,10 @@ def plot_bbands(self, fig: OpenBBFigure, df_ta: pd.DataFrame, inchart_index: int
             secondary_y=self.show_volume,
         )
         bbands_text = (
-            columns_regex(df_ta, "BBL")[0]
-            .replace("BBL_", "BB")
-            .replace("_", ",")
-            .split(".")[0]
+            columns_regex(df_ta, "BBL")[0].replace("BBL_", "BB").replace("_", ",")
         )
+        if float(bbands_text.split(",")[1]) % 1 == 0:
+            bbands_text = bbands_text.split(".")[0]
         fig.add_annotation(
             xref="paper",
             yref="paper",

openbb_terminal/core/sdk/controllers/stocks_sdk_controller.py

@@ -260,7 +260,7 @@ def options(self):
 
         Attributes:
             `chains`: Get Option Chain For A Stock.  No greek data is returned\n
-            `dte`: Gets days to expiration from yfinance option date\n
+            `dte`: Returns a new column containing the DTE as an integer, including 0.\n
             `eodchain`: Get full EOD option date across all expirations\n
             `expirations`: Get Option Chain Expirations\n
             `generate_data`: Gets x values, and y values before and after premiums\n

openbb_terminal/core/sdk/models/stocks_sdk_model.py

@@ -449,7 +449,7 @@ class StocksOptions(Category):
 
     Attributes:
         `chains`: Get Option Chain For A Stock.  No greek data is returned\n
-        `dte`: Gets days to expiration from yfinance option date\n
+        `dte`: Returns a new column containing the DTE as an integer, including 0.\n
         `eodchain`: Get full EOD option date across all expirations\n
         `expirations`: Get Option Chain Expirations\n
         `generate_data`: Gets x values, and y values before and after premiums\n
@@ -477,7 +477,7 @@ class StocksOptions(Category):
     def __init__(self):
         super().__init__()
         self.chains = lib.stocks_options_sdk_helper.get_full_option_chain
-        self.dte = lib.stocks_options_yfinance_model.get_dte
+        self.dte = lib.stocks_options_helpers.get_dte
         self.eodchain = lib.stocks_options_intrinio_model.get_full_chain_eod
         self.expirations = lib.stocks_options_sdk_helper.get_option_expirations
         self.generate_data = lib.stocks_options_yfinance_model.generate_data

openbb_terminal/core/sdk/sdk_init.py

@@ -472,6 +472,7 @@
     intrinio_model as stocks_options_intrinio_model,
     intrinio_view as stocks_options_intrinio_view,
     nasdaq_model as stocks_options_nasdaq_model,
+    op_helpers as stocks_options_helpers,
     options_sdk_helper as stocks_options_sdk_helper,
     options_view as stocks_options_view,
     tradier_model as stocks_options_tradier_model,

openbb_terminal/core/sdk/trail_map.csv

@@ -503,7 +503,7 @@ stocks.ins.stats,stocks_insider_sdk_helper.stats,
 stocks.load,stocks_helper.load,
 stocks.news,common_ultima_newsmonitor_model.get_news,
 stocks.options.chains,stocks_options_sdk_helper.get_full_option_chain,
-stocks.options.dte,stocks_options_yfinance_model.get_dte,
+stocks.options.dte,stocks_options_helpers.get_dte,
 stocks.options.eodchain,stocks_options_intrinio_model.get_full_chain_eod,
 stocks.options.expirations,stocks_options_sdk_helper.get_option_expirations,
 stocks.options.generate_data,stocks_options_yfinance_model.generate_data,

openbb_terminal/helper_funcs.py

@@ -612,7 +612,7 @@ def check_indicator_parameters(args: str, _help: bool = False) -> str:
 
 
 def check_positive_float(value) -> float:
-    """Argparse type to check positive int."""
+    """Argparse type to check positive float."""
     new_value = float(value)
     if new_value <= 0:
         log_and_raise(

openbb_terminal/stocks/fundamental_analysis/business_insider_model.py

@@ -3,7 +3,6 @@
 
 import json
 import logging
-import re
 from typing import Tuple
 
 import pandas as pd
@@ -193,120 +192,61 @@ def get_estimates(symbol: str) -> Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame
         "lxml",
     )
 
-    l_estimates_year_header = list()
-    l_estimates_quarter_header = list()
-    for estimates_header in text_soup_market_business_insider.findAll(
-        "th", {"class": "table__th text-right"}
-    ):
-        s_estimates_header = estimates_header.text.strip()
-        if s_estimates_header.isdigit():
-            l_estimates_year_header.append(s_estimates_header)
-        elif ("in %" not in s_estimates_header) and ("Job" not in s_estimates_header):
-            l_estimates_quarter_header.append(s_estimates_header)
-
-    l_estimates_year_metric = list()
-    for estimates_year_metric in text_soup_market_business_insider.findAll(
-        "td", {"class": "table__td black"}
-    ):
-        l_estimates_year_metric.append(estimates_year_metric.text)
-
-    l_estimates_quarter_metric = list()
-    for estimates_quarter_metric in text_soup_market_business_insider.findAll(
-        "td", {"class": "table__td font-color-dim-gray"}
-    ):
-        l_estimates_quarter_metric.append(estimates_quarter_metric.text)
-
-    d_metric_year = dict()
-    d_metric_quarter_earnings = dict()
-    d_metric_quarter_revenues = dict()
-    l_metrics = list()
-    n_metrics = 0
-    b_year = True
-    for idx, metric_value in enumerate(
-        text_soup_market_business_insider.findAll(
-            "td", {"class": "table__td text-right"}
-        )
-    ):
-        if b_year:
-            # YEAR metrics
-            l_metrics.append(metric_value.text.strip())
-
-            # Check if we have processed all year metrics
-            if n_metrics > len(l_estimates_year_metric) - 1:
-                b_year = False
-                n_metrics = 0
-                l_metrics = list()
-                idx_y = idx
-
-            # Add value to dictionary
-            if (idx + 1) % len(l_estimates_year_header) == 0:
-                d_metric_year[l_estimates_year_metric[n_metrics]] = l_metrics
-                l_metrics = list()
-                n_metrics += 1
-
-        if not b_year:
-            # QUARTER metrics
-            l_metrics.append(metric_value.text.strip())
-
-            # Check if we have processed all quarter metrics
-            if n_metrics > len(l_estimates_quarter_metric) - 1:
-                break
-
-            # Add value to dictionary
-            if (idx - idx_y + 1) % len(l_estimates_quarter_header) == 0:
-                if n_metrics < 4:
-                    d_metric_quarter_earnings[
-                        l_estimates_quarter_metric[n_metrics]
-                    ] = l_metrics
-                else:
-                    d_metric_quarter_revenues[
-                        l_estimates_quarter_metric[n_metrics - 4]
-                    ] = l_metrics
-                l_metrics = list()
-                n_metrics += 1
-
-    df_year_estimates = pd.DataFrame.from_dict(
-        d_metric_year, orient="index", columns=l_estimates_year_header
-    )
-    df_year_estimates.index.name = "YEARLY ESTIMATES"
-    df_quarter_earnings = pd.DataFrame.from_dict(
-        d_metric_quarter_earnings,
-        orient="index",
-        columns=l_estimates_quarter_header,
+    # Get all tables and convert them to list of pandas dataframes
+    tables = text_soup_market_business_insider.find_all("table")
+    list_df = pd.read_html(str(tables))
+
+    # Get year estimates
+    df_year_estimates = list_df[3]
+    l_year_estimates_columns = df_year_estimates.columns.tolist()
+    l_year_estimates_columns[0] = "YEARLY ESTIMATES"
+    df_year_estimates.columns = l_year_estimates_columns
+    df_year_estimates.set_index("YEARLY ESTIMATES", inplace=True)
+
+    df_quarter = list_df[4]
+    date_row = dict()
+
+    # Get quarter earnings estimates
+    df_quarter_earnings = df_quarter.iloc[0:5, :].reset_index(drop=True).copy()
+    df_quarter_earnings.drop(index=0, inplace=True)
+    l_quarter_earnings_columns = df_quarter_earnings.columns.tolist()
+    l_quarter_earnings_columns[0] = "QUARTER EARNINGS ESTIMATES"
+    date_row["QUARTER EARNINGS ESTIMATES"] = "Date"
+
+    # Adding Date info to add to dataframe
+    for col in l_quarter_earnings_columns[1:]:
+        key = col.split("ending")[0].strip()
+        value = col[col.find("ending") :].strip()
+        date_row[key] = value
+
+    df_quarter_earnings.columns = date_row.keys()
+    date_row = pd.DataFrame(date_row, index=[0])
+    df_quarter_earnings = pd.concat([date_row, df_quarter_earnings]).reset_index(
+        drop=True
     )
-    # df_quarter_earnings.index.name = 'Earnings'
-    df_quarter_revenues = pd.DataFrame.from_dict(
-        d_metric_quarter_revenues,
-        orient="index",
-        columns=l_estimates_quarter_header,
+    df_quarter_earnings.set_index("QUARTER EARNINGS ESTIMATES", inplace=True)
+
+    # Setting date_row to empty dict object
+    date_row = dict()
+
+    # Get quarter revenues estimates
+    df_quarter_revenues = df_quarter.iloc[5:, :].reset_index(drop=True).copy()
+    df_quarter_revenues.drop(index=0, inplace=True)
+    l_quarter_revenues_columns = df_quarter_revenues.columns.tolist()
+    l_quarter_revenues_columns[0] = "QUARTER REVENUES ESTIMATES"
+    date_row["QUARTER REVENUES ESTIMATES"] = "Date"
+
+    # Adding Date info to add to dataframe
+    for col in l_quarter_revenues_columns[1:]:
+        key = col.split("ending")[0].strip()
+        value = col[col.find("ending") :].strip()
+        date_row[key] = value
+
+    df_quarter_revenues.columns = date_row.keys()
+    date_row = pd.DataFrame(date_row, index=[0])
+    df_quarter_revenues = pd.concat([date_row, df_quarter_revenues]).reset_index(
+        drop=True
     )
-    # df_quarter_revenues.index.name = 'Revenues'
-
-    if not df_quarter_earnings.empty:
-        l_quarter = list()
-        l_date = list()
-        for quarter_title in df_quarter_earnings.columns:
-            l_quarter.append(re.split("  ending", quarter_title)[0])
-            if len(re.split("  ending", quarter_title)) == 2:
-                l_date.append(
-                    "ending " + re.split("  ending", quarter_title)[1].strip()
-                )
-            else:
-                l_date.append("-")
-
-        df_quarter_earnings.index.name = "QUARTER EARNINGS ESTIMATES"
-        df_quarter_earnings.columns = l_quarter
-        df_quarter_earnings.loc["Date"] = l_date
-        df_quarter_earnings = df_quarter_earnings.reindex(
-            ["Date", "No. of Analysts", "Average Estimate", "Year Ago", "Publish Date"]
-        )
-
-    if not df_quarter_revenues.empty:
-        df_quarter_revenues.index.name = "QUARTER REVENUES ESTIMATES"
-        df_quarter_revenues.columns = l_quarter
-        df_quarter_revenues.loc["Date"] = l_date
-        df_quarter_revenues = df_quarter_revenues.reindex(
-            ["Date", "No. of Analysts", "Average Estimate", "Year Ago", "Publish Date"]
-        )
+    df_quarter_revenues.set_index("QUARTER REVENUES ESTIMATES", inplace=True)
 
     return df_year_estimates, df_quarter_earnings, df_quarter_revenues

openbb_terminal/stocks/fundamental_analysis/business_insider_view.py

@@ -215,7 +215,7 @@ def display_estimates(
         df_quarter_revenues,
     ) = business_insider_model.get_estimates(symbol)
 
-    if estimate == "annualearnings":
+    if estimate == "annual_earnings":
         print_rich_table(
             df_year_estimates,
             headers=list(df_year_estimates.columns),
@@ -231,7 +231,7 @@ def display_estimates(
             sheet_name,
         )
 
-    elif estimate == "quarterearnings":
+    elif estimate == "quarter_earnings":
         print_rich_table(
             df_quarter_earnings,
             headers=list(df_quarter_earnings.columns),
@@ -247,7 +247,7 @@ def display_estimates(
             sheet_name,
         )
 
-    elif estimate == "annualrevenue":
+    elif estimate == "quarter_revenues":
         print_rich_table(
             df_quarter_revenues,
             headers=list(df_quarter_revenues.columns),

openbb_terminal/stocks/fundamental_analysis/fa_controller.py

@@ -92,7 +92,7 @@ class FundamentalAnalysisController(StockBaseController):
     PATH = "/stocks/fa/"
 
     SHRS_CHOICES = ["major", "institutional", "mutualfund"]
-    ESTIMATE_CHOICES = ["annualrevenue", "annualearnings", "quarterearnings"]
+    ESTIMATE_CHOICES = ["annual_earnings", "quarter_earnings", "quarter_revenues"]
     CHOICES_GENERATION = True
 
     def __init__(
@@ -1858,7 +1858,7 @@ def call_est(self, other_args: List[str]):
             help="Estimates to get",
             dest="estimate",
             choices=self.ESTIMATE_CHOICES,
-            default="annualearnings",
+            default="annual_earnings",
         )
         ns_parser = self.parse_known_args_and_warn(
             parser, other_args, EXPORT_ONLY_RAW_DATA_ALLOWED

openbb_terminal/stocks/options/op_helpers.py

@@ -19,7 +19,6 @@
 # pylint: disable=too-many-arguments
 
 
-@log_start_end(log=logger)
 def get_strikes(
     min_sp: float, max_sp: float, current_price: float
 ) -> Tuple[float, float]:
@@ -58,7 +57,6 @@ def get_loss_at_strike(strike: float, chain: pd.DataFrame) -> float:
     return loss
 
 
-@log_start_end(log=logger)
 def calculate_max_pain(chain: pd.DataFrame) -> Union[int, float]:
     """Returns the max pain for a given call/put dataframe
 
@@ -104,7 +102,6 @@ def convert(orig: str, to: str) -> float:
     raise ValueError("Invalid to format, please use '%' or ','.")
 
 
-@log_start_end(log=logger)
 def rn_payoff(x: str, df: pd.DataFrame, put: bool, delta: int, rf: float) -> float:
     """The risk neutral payoff for a stock
     Parameters
@@ -594,3 +591,19 @@ def Vomma(self, change):
             * norm.pdf(self.d1)
             / self._sigma
         )
+
+
+def get_dte(chain: pd.DataFrame) -> pd.DataFrame:
+    """
+    Returns a new column containing the DTE as an integer, including 0.
+    Requires the chain to have the column labeled as, expiration.
+    """
+    if "expiration" not in chain.columns:
+        raise ValueError("No column labeled 'expiration' was found.")
+
+    now = datetime.now()
+    temp = pd.DatetimeIndex(chain.expiration)
+    temp_ = (temp - now).days + 1
+    chain["dte"] = temp_
+
+    return chain

openbb_terminal/stocks/technical_analysis/ta_controller.py

@@ -30,6 +30,7 @@
     EXPORT_ONLY_RAW_DATA_ALLOWED,
     check_indicator_parameters,
     check_positive,
+    check_positive_float,
     check_positive_list,
     valid_date,
 )
@@ -1159,7 +1160,7 @@ def call_bbands(self, other_args: List[str]):
             "--std",
             action="store",
             dest="n_std",
-            type=check_positive,
+            type=check_positive_float,
             default=2,
             help="std",
         )