Refactor port-> po and pa menus (#748)

* Refactor property weightings

* Refactor pypfopt commands

* refactor pa menu

* Address review comments

* Typo

13 files changed, 1557 insertions, 1188 deletions

diff --git a/gamestonk_terminal/helper_funcs.py b/gamestonk_terminal/helper_funcs.py
index dd8196acdab..5e800a04fdf 100644
--- a/gamestonk_terminal/helper_funcs.py
+++ b/gamestonk_terminal/helper_funcs.py
@@ -27,39 +27,6 @@ if cfgPlot.BACKEND is not None:
     matplotlib.use(cfgPlot.BACKEND)
 
 
-def check_valid_path(path: str) -> str:
-    """Argparse type function to test is path is valid
-
-    Parameters
-    ----------
-    path: str
-        Path supplied
-
-    Returns
-    -------
-    path: str
-        Valid path
-
-    Raises
-    -------
-    argparse.ArgumentTypeError
-        Given path does not exist
-    """
-    if not os.path.exists(
-        os.path.abspath(
-            os.path.join(
-                "gamestonk_terminal",
-                "portfolio",
-                "portfolio_analysis",
-                "portfolios",
-                f"{path}.csv",
-            )
-        )
-    ):
-        raise argparse.ArgumentTypeError("Path does not exist")
-    return path
-
-
 def check_int_range(mini: int, maxi: int):
     """Checks if argparse argument is an int between 2 values.
 
diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py b/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py
index 53f2027fb3a..bba2a3e222f 100644
--- a/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py
+++ b/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py
@@ -1,15 +1,28 @@
+"""Portffolio Analysis Controller"""
 __docformat__ = "numpy"
 
 import argparse
 import os
+from pathlib import Path
+
 import pandas as pd
 from prompt_toolkit.completion import NestedCompleter
 
 from gamestonk_terminal import feature_flags as gtff
-from gamestonk_terminal.helper_funcs import get_flair
+from gamestonk_terminal.helper_funcs import (
+    get_flair,
+    parse_known_args_and_warn,
+)
 from gamestonk_terminal.menu import session
+from gamestonk_terminal.portfolio.portfolio_analysis import (
+    portfolio_model,
+    portfolio_view,
+)
 
-from gamestonk_terminal.portfolio.portfolio_analysis import portfolio_parser
+portfolios_path = os.path.join(os.path.abspath(os.path.dirname(__file__)), "portfolios")
+possible_paths = [
+    Path(port).stem for port in os.listdir(portfolios_path) if port.endswith(".csv")
+]
 
 
 class PortfolioController:
@@ -21,10 +34,15 @@ class PortfolioController:
         "help",
         "q",
         "quit",
+    ]
+    CHOICES_COMMANDS = [
+        "view",
         "load",
         "group",
     ]
 
+    CHOICES += CHOICES_COMMANDS
+
     def __init__(self):
         self.pa_parser = argparse.ArgumentParser(add_help=False, prog="pa")
         self.pa_parser.add_argument("cmd", choices=self.CHOICES)
@@ -33,22 +51,24 @@ class PortfolioController:
 
     def print_help(self):
         """Print help"""
-        print(
-            "https://github.com/GamestonkTerminal/GamestonkTerminal/tree/main/gamestonk_terminal/portfolio_analysis"
-        )
-        print("\nPortfolio Analysis:")
-        print("   cls           clear screen")
-        print("   ?/help        show this menu again")
-        print("   q             quit this menu, and shows back to main menu")
-        print("   quit          quit to abandon program")
-        print("")
-        print("   load          load portfolio from csv file")
-        print("")
-        if self.portfolio_name:
-            print(f"Portfolio: {self.portfolio_name}")
-            print("")
-            print("   group         view holdings by a user input group")
-            print("")
+        help_string = f"""https://github.com/GamestonkTerminal/GamestonkTerminal/tree/main/gamestonk_terminal/portfolio_analysis
+
+>>PORTFOLIO ANALYSIS<<
+
+What would you like to do?
+    cls           clear screen
+    ?/help        show this menu again
+    q             quit this menu, and shows back to main menu
+    quit          quit to abandon program
+
+    view          view available portfolios
+    load          load portfolio from csv file
+
+Portfolio: {self.portfolio_name or None}
+
+    group         view holdings grouped by parameter
+            """
+        print(help_string)
 
     def switch(self, an_input: str):
         """Process and dispatch input
@@ -94,21 +114,153 @@ class PortfolioController:
         """Process Quit command - quit the program"""
         return True
 
+    # TODO: allow loading other files than csv
     def call_load(self, other_args):
-        """Process csv command"""
-        self.portfolio_name, self.portfolio = portfolio_parser.load_csv_portfolio(
-            other_args
+        """Process load command"""
+        parser = argparse.ArgumentParser(
+            prog="load",
+            add_help=False,
+            formatter_class=argparse.ArgumentDefaultsHelpFormatter,
+            description="Function to get portfolio from predefined csv file inside portfolios folder",
+        )
+        parser.add_argument(
+            "-s",
+            "--sector",
+            action="store_true",
+            default=False,
+            help="Add sector to dataframe",
+            dest="sector",
+        )
+        parser.add_argument(
+            "--no_last_price",
+            action="store_false",
+            default=True,
+            help="Don't add last price from yfinance",
+            dest="last_price",
+        )
+        parser.add_argument(
+            "--nan",
+            action="store_true",
+            default=False,
+            help="Show nan entries from csv",
+            dest="show_nan",
+        )
+        parser.add_argument(
+            "-p",
+            "--path",
+            default="my_portfolio",
+            choices=possible_paths,
+            help="Path to csv file",
+            dest="path",
         )
 
-        if self.portfolio_name:
-            print(f"Successfully loaded: {self.portfolio_name}\n")
+        try:
+            ns_parser = parse_known_args_and_warn(parser, other_args)
+            if not ns_parser:
+                return
+
+            self.portfolio_name = ns_parser.path
+            self.portfolio = portfolio_model.load_csv_portfolio(
+                full_path=os.path.join(portfolios_path, ns_parser.path) + ".csv",
+                sector=ns_parser.sector,
+                last_price=ns_parser.last_price,
+                show_nan=ns_parser.show_nan,
+            )
+            if not self.portfolio.empty:
+                print(f"Successfully loaded: {self.portfolio_name}\n")
+
+        except Exception as e:
+            print(e)
 
     def call_group(self, other_args):
         """Process group command"""
-        if self.portfolio_name:
-            portfolio_parser.breakdown_by_group(self.portfolio, other_args)
-        else:
-            print("Please load a portfolio")
+        parser = argparse.ArgumentParser(
+            prog="group",
+            add_help=False,
+            formatter_class=argparse.ArgumentDefaultsHelpFormatter,
+            description="Displays portfolio grouped by a given column",
+        )
+        if other_args and "-" not in other_args[0]:
+            other_args.insert(0, "-g")
+        parser.add_argument(
+            "-g",
+            "--group",
+            type=str,
+            dest="group",
+            default="Ticker",
+            choices=self.portfolio.columns,
+            help="Column to group by",
+        )
+
+        # The following arguments will be used in a later PR for customizable 'reports'
+
+        # The --func flag will need to be tested that it exists for pandas groupby
+        # parser.add_argument("-f",
+        #                     "--func",
+        #                     type=str,
+        #                     dest="function",
+        #                     help="Aggregate function to apply to groups"
+        #                     )
+        # parser.add_argument("-d",
+        #                     "--display",
+        #                     default = None,
+        #                     help = "Columns to display",
+        #                     dest="cols")
+
+        try:
+            ns_parser = parse_known_args_and_warn(parser, other_args)
+            if not ns_parser:
+                return
+
+            if "value" not in self.portfolio.columns:
+                print(
+                    "'value' column not in portfolio.  Either add manually or load without --no_last_price flag\n"
+                )
+                return
+
+            portfolio_view.display_group_holdings(
+                portfolio=self.portfolio, group_column=ns_parser.group
+            )
+
+        except Exception as e:
+            print(e, "\n")
+
+    def call_view(self, other_args):
+        parser = argparse.ArgumentParser(
+            prog="view",
+            add_help=False,
+            formatter_class=argparse.ArgumentDefaultsHelpFormatter,
+            description="Show available portfolios to load.",
+        )
+        parser.add_argument(
+            "-f",
+            "-format",
+            choices=["csv", "all"],
+            help="Format of portfolios to view.  'csv' will show all csv files available, etc.",
+            default="all",
+            dest="file_format",
+        )
+
+        try:
+            ns_parser = parse_known_args_and_warn(parser, other_args)
+            if not ns_parser:
+                return
+
+            available_ports = os.listdir(portfolios_path)
+            if ns_parser.file_format != "all":
+                available_ports = [
+                    port
+                    for port in available_ports
+                    if port.endswith(ns_parser.file_format)
+                ]
+
+            print("\nAvailable Portfolios:\n")
+            for port in available_ports:
+                print(Path(port).stem)
+            print("")
+
+        except Exception as e:
+            print(e, "\n")
 
 
 def menu():
diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_model.py b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_model.py
new file mode 100644
index 00000000000..3301ac697e2
--- /dev/null
+++ b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_model.py
@@ -0,0 +1,62 @@
+"""Portfolio Model"""
+__docformat__ = "numpy"
+
+from tabulate import tabulate
+import pandas as pd
+import yfinance as yf
+import gamestonk_terminal.feature_flags as gtff
+
+# pylint: disable=no-member,unsupported-assignment-operation,unsubscriptable-object
+
+
+def load_csv_portfolio(
+    full_path: str,
+    sector: bool = False,
+    last_price: bool = False,
+    show_nan: bool = True,
+) -> pd.DataFrame:
+    """Loads a csv portfolio into a dataframe and adds sector and last price
+
+    Parameters
+    ----------
+    full_path : str
+        Path to csv portfolio.
+    sector : bool, optional
+        Boolean to indicate getting sector from yfinance , by default False
+    last_price : bool, optional
+        Boolean to indicate getting last price from yfinance, by default False
+    show_nan : bool, optional
+        Boolean to indicate dropping nan values, by default True
+
+    Returns
+    -------
+    pd.DataFrame
+        Dataframe conataining csv portfolio
+    """
+    df = pd.read_csv(full_path)
+
+    if sector:
+        df["sector"] = df.apply(
+            lambda row: yf.Ticker(row.Ticker).info["sector"]
+            if "sector" in yf.Ticker(row.Ticker).info.keys()
+            else "yf Other",
+            axis=1,
+        )
+
+    if last_price:
+        df["last_price"] = df.apply(
+            lambda row: yf.Ticker(row.Ticker)
+            .history(period="1d")["Close"][-1]
+            .round(2),
+            axis=1,
+        )
+        df["value"] = df["Shares"] * df["last_price"]
+
+    if not show_nan:
+        df = df.dropna(axis=1)
+
+    if gtff.USE_TABULATE_DF:
+        print(tabulate(df, tablefmt="fancy_grid", headers=df.columns), "\n")
+    else:
+        print(df.to_string(), "\n")
+    return df
diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_parser.py b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_parser.py
deleted file mode 100644
index 051bb2163b5..00000000000
--- a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_parser.py
+++ /dev/null
@@ -1,179 +0,0 @@
-"""Portfolio parser module"""
-__docformat__ = "numpy"
-
-import os
-import argparse
-from typing import List, Tuple
-from tabulate import tabulate
-import pandas as pd
-import yfinance as yf
-from gamestonk_terminal.helper_funcs import check_valid_path, parse_known_args_and_warn
-
-# pylint: disable=no-member,unsupported-assignment-operation,unsubscriptable-object
-
-
-def load_csv_portfolio(other_args: List[str]) -> Tuple[str, pd.DataFrame]:
-    """Load portfolio from csv
-
-    Parameters
-    ----------
-    other_args: List[str]
-        Argparse arguments
-
-    Returns
-    ----------
-    portfolio_name : str
-        Portfolio name
-    portfolio : pd.DataFrame
-        Portfolio dataframe
-    """
-    parser = argparse.ArgumentParser(
-        prog="load",
-        add_help=False,
-        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
-        description="Function to get portfolio from predefined csv file inside portfolios folder",
-    )
-    parser.add_argument(
-        "-p",
-        "--path",
-        default="my_portfolio",
-        type=check_valid_path,
-        help="Path to csv file",
-        dest="path",
-    )
-    parser.add_argument(
-        "--no_sector",
-        action="store_true",
-        default=False,
-        help="Add sector to dataframe",
-        dest="sector",
-    )
-    parser.add_argument(
-        "--no_last_price",
-        action="store_true",
-        default=False,
-        help="Add last price from yfinance",
-        dest="last_price",
-    )
-    parser.add_argument(
-        "--nan",
-        action="store_true",
-        default=False,
-        help="Show nan entries from csv",
-        dest="show_nan",
-    )
-
-    try:
-        ns_parser = parse_known_args_and_warn(parser, other_args)
-        if not ns_parser:
-            return "", pd.DataFrame()
-
-        full_path = os.path.abspath(
-            os.path.join(
-                "gamestonk_terminal",
-                "portfolio",
-                "portfolio_analysis",
-                "portfolios",
-                f"{ns_parser.path}.csv",
-            )
-        )
-        df = pd.read_csv(full_path)
-
-        if not ns_parser.sector:
-            df["sector"] = df.apply(
-                lambda row: yf.Ticker(row.Ticker).info["sector"]
-                if "sector" in yf.Ticker(row.Ticker).info.keys()
-                else "yf Other",
-                axis=1,
-            )
-
-        if not ns_parser.last_price:
-            df["last_price"] = df.apply(
-                lambda row: yf.Ticker(row.Ticker)
-                .history(period="1d")["Close"][-1]
-                .round(2),
-                axis=1,
-            )
-            df["value"] = df["Shares"] * df["last_price"]
-
-        if not ns_parser.show_nan:
-            df = df.dropna(axis=1)
-
-        print(tabulate(df, tablefmt="fancy_grid", headers=df.columns))
-        print("")
-        return ns_parser.path, df
-
-    except Exception as e:
-        print(e, "\n")
-        return "", pd.DataFrame()
-
-
-def breakdown_by_group(portfolio: pd.DataFrame, other_args: List[str]):
-    """Breakdown of portfolio by a specified group
-
-    Parameters
-    ----------
-    portfolio: pd.DataFrame
-        Dataframe of portfolio generated from menu
-    other_args: List[str]
-        Argparse arguments
-    """
-    parser = argparse.ArgumentParser(
-        prog="groupby",
-        add_help=False,
-        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
-        description="Displays portfolio grouped by a given column",
-    )
-    parser.add_argument(
-        "-g",
-        "--group",
-        type=str,
-        dest="group",
-        default="Ticker",
-        help="Column to group by",
-    )
-
-    # The following arguments will be used in a later PR for customizable 'reports'
-
-    # The --func flag will need to be tested that it exists for pandas groupby
-    # parser.add_argument("-f",
-    #                     "--func",
-    #                     type=str,
-    #                     dest="function",
-    #                     help="Aggregate function to apply to groups"
-    #                     )
-    # parser.add_argument("-d",
-    #                     "--display",
-    #                     default = None,
-    #                     help = "Columns to display",
-    #                     dest="cols")
-
-    try:
-        ns_parser = parse_known_args_and_warn(parser, other_args)
-        if not ns_parser:
-            return
-
-        group_column = ns_parser.group
-        if group_column not in portfolio.columns:
-            print(f"The column {group_column} is not found in your portfolio data")
-            return
-
-        grouped_df = pd.DataFrame(portfolio.groupby(group_column).agg(sum)["value"])
-        print(
-            tabulate(grouped_df, headers=[group_column, "value"], tablefmt="fancy_grid")
-        )
-        print("")
-
-        # The following will be used to display certain columns (i.e show Dollars or Percents)
-        # valid_columns = []
-        # if ns_parser.cols:
-        #     for col in ns_parser.cols:
-        #         if col in portfolio.columns:
-        #             valid_columns.append(col)
-        #         else:
-        #             print(f"{col} not in portfolio columns")
-        # if valid_columns:
-        #     valid_columns = ["Shares"]
-
-    except Exception as e:
-        print(e, "\n")
diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py
new file mode 100644
index 00000000000..b03131ea12c
--- /dev/null
+++ b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py
@@ -0,0 +1,32 @@
+"""Portfolio View"""
+__docformat__ = "numpy"
+
+import pandas as pd
+from tabulate import tabulate
+import gamestonk_terminal.feature_flags as gtff
+
+
+def display_group_holdings(portfolio: pd.DataFrame, group_column: str):
+    """Display portfolio holdings based on grouping
+
+    Parameters
+    ----------
+    portfolio : pd.DataFrame
+        Portfolio dataframe
+    group_column : str
+        Column to group by
+    """
+
+    grouped_df = pd.DataFrame(portfolio.groupby(group_column).agg(sum)["value"])
+    if gtff.USE_TABULATE_DF:
+        print(
+            tabulate(
+                grouped_df,
+                headers=[group_column, "value"],
+                tablefmt="fancy_grid",
+                floatfmt=".2f",
+            ),
+            "\n",
+        )
+    else:
+        print(portfolio.to_string(), "\n")
diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/portfolios/my_portfolio.csv b/gamestonk_terminal/portfolio/portfolio_analysis/portfolios/my_portfolio.csv
index 9123480e064..99482ebce9d 100644
--- a/gamestonk_terminal/portfolio/portfolio_analysis/portfolios/my_portfolio.csv
+++ b/gamestonk_terminal/portfolio/portfolio_analysis/portfolios/my_portfolio.csv
@@ -4,3 +4,4 @@ AMC,420,
 MSFT,3,
 BAC,2,
 O,1,
+AAPL,4
diff --git a/gamestonk_terminal/portfolio/portfolio_controller.py b/gamestonk_terminal/portfolio/portfolio_controller.py
index 2e4116c36d2..8870e39f110 100644
--- a/gamestonk_terminal/portfolio/portfolio_controller.py
+++ b/gamestonk_terminal/portfolio/portfolio_controller.py
@@ -1,3 +1,6 @@
+"""Portfolio Controller"""
+__docformat__ = "numpy"
+
 import argparse
 import os
 
@@ -25,13 +28,6 @@ class PortfolioController:
     ]
 
     CHOICES_MENUS = [
-        "load",
-        "quote",
-        "candle",
-        "view",
-    ]
-
-    CHOICES_MENUS = [
         "bro",
         "pa",
         "po",
diff --git a/gamestonk_terminal/portfolio/portfolio_optimization/optimizer_helper.py b/gamestonk_terminal/portfolio/portfolio_optimization/optimizer_helper.py
index cbd20d60732..a9866b09afd 100644
--- a/gamestonk_terminal/portfolio/portfolio_optimization/optimizer_helper.py
+++ b/gamestonk_terminal/portfolio/portfolio_optimization/optimizer_helper.py
@@ -1,20 +1,9 @@
-""" Portfolio Optimization Helper Functions """
+"""Optimization helpers"""
 __docformat__ = "numpy"
 
 import argparse
-from typing import List
-import math
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-import yfinance as yf
-from pypfopt.efficient_frontier import EfficientFrontier
-from pypfopt import risk_models
-from pypfopt import expected_returns
-from gamestonk_terminal.config_plot import PLOT_DPI
-from gamestonk_terminal import feature_flags as gtff
-from gamestonk_terminal.helper_funcs import plot_autoscale
 
+# These are all the possible yfinance properties
 l_valid_property_infos = [
     "previousClose",
     "regularMarketOpen",
@@ -116,167 +105,3 @@ def check_valid_property_type(aproperty: str) -> str:
         return aproperty
 
     raise argparse.ArgumentTypeError(f"{aproperty} is not a valid info")
-
-
-def process_stocks(list_of_stocks: List[str], period: str = "3mo") -> pd.DataFrame:
-    """Get adjusted closing price for each stock in the list
-
-    Parameters
-    ----------
-    list_of_stocks: List[str]
-        List of tickers to get historical data for
-    period: str
-        Period to get data from yfinance
-
-    Returns
-    -------
-    stock_closes: DataFrame
-        DataFrame containing daily (adjusted) close prices for each stock in list
-    """
-
-    stock_prices = yf.download(
-        list_of_stocks, period=period, progress=False, group_by="ticker"
-    )
-    stock_closes = pd.DataFrame(index=stock_prices.index)
-    for stock in list_of_stocks:
-        stock_closes[stock] = stock_prices[stock]["Adj Close"]
-    return stock_closes
-
-
-def prepare_efficient_frontier(stock_prices: pd.DataFrame):
-    """Take in a dataframe of prices and return an efficient frontier object
-
-    Parameters
-    ----------
-    stock_prices : DataFrame
-        DataFrame where indices are DateTime and columns are stocks
-
-    Returns
-    -------
-    ef: EfficientFrontier
-        EfficientFrontier object
-    """
-
-    mu = expected_returns.mean_historical_return(stock_prices)
-    S = risk_models.sample_cov(stock_prices)
-    ef = EfficientFrontier(mu, S)
-    return ef
-
-
-def display_weights(weights: dict):
-    """Print weights in a nice format
-
-    Parameters
-    ----------
-    weights: dict
-        weights to display.  Keys are stocks.  Values are either weights or values if -v specified
-    """
-
-    if not weights:
-        return
-    weight_df = pd.DataFrame.from_dict(data=weights, orient="index", columns=["value"])
-    if math.isclose(weight_df.sum()["value"], 1, rel_tol=0.1):
-        weight_df["weight"] = (weight_df["value"] * 100).astype(str).apply(
-            lambda s: " " + s[:4] if s.find(".") == 1 else "" + s[:5]
-        ) + " %"
-        print(pd.DataFrame(weight_df["weight"]).to_string(header=False))
-    else:
-        print(weight_df.to_string(header=False))
-
-
-def my_autopct(x):
-    """Function for autopct of plt.pie.  This results in values not being printed in the pie if they are 'too small'"""
-    if x > 4:
-        return f"{x:.2f} %"
-
-    return ""
-
-
-def pie_chart_weights(weights: dict, title_opt: str):
-    """Show a pie chart of holdings
-
-    Parameters
-    ----------
-    weights: dict
-        Weights to display, where keys are tickers, and values are either weights or values if -v specified
-    title: str
-        Title to be used on the plot title
-    """
-    if not weights:
-        return
-
-    init_stocks = list(weights.keys())
-    init_sizes = list(weights.values())
-    stocks = []
-    sizes = []
-    for stock, size in zip(init_stocks, init_sizes):
-        if size > 0:
-            stocks.append(stock)
-            sizes.append(size