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https://github.com/OpenBB-finance/OpenBB.git
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2cb229f35e
* spacing before and after rich tables * fix menus to have standard UI * fix tests * fix tests * fix tests
112 lines
3.1 KiB
Python
112 lines
3.1 KiB
Python
"""Cramer View"""
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__docformat__ = "numpy"
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import os
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from typing import Optional, List
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import logging
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import matplotlib.pyplot as plt
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from matplotlib.dates import DateFormatter
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import yfinance
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import pandas as pd
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import openbb_terminal.config_plot as cfp
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from openbb_terminal.config_terminal import theme
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from openbb_terminal.helper_funcs import (
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print_rich_table,
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export_data,
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plot_autoscale,
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is_valid_axes_count,
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)
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from openbb_terminal.stocks.behavioural_analysis import cramer_model
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from openbb_terminal.rich_config import console
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from openbb_terminal.decorators import log_start_end
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logger = logging.getLogger(__name__)
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@log_start_end(log=logger)
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def display_cramer_daily(inverse: bool = True, export: str = ""):
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"""Display Jim Cramer daily recommendations
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Parameters
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----------
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inverse:bool
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Flag to include inverse recommendation
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export:str
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Format to export data
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"""
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recs = cramer_model.get_cramer_daily(inverse)
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if recs.empty:
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console.print("[red]Error getting request.\n[/red]")
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return
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date = recs.Date[0]
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recs = recs.drop(columns=["Date"])
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print_rich_table(recs, title=f"Jim Cramer Recommendations for {date}")
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export_data(export, os.path.dirname(os.path.abspath(__file__)), "cramer", recs)
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@log_start_end(log=logger)
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def display_cramer_ticker(
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ticker: str,
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raw: bool = True,
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export: str = "",
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external_axes: Optional[List[plt.Axes]] = None,
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):
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"""Display ticker close with Cramer recommendations
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Parameters
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----------
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ticker: str
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Stock ticker
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raw: bool
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Display raw data
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export: str
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Format to export data
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external_axes: Optional[List[plt.Axes]] = None,
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External axes to plot on
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"""
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df = cramer_model.get_cramer_ticker(ticker)
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if df.empty:
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console.print(f"No recommendations found for {ticker}.\n")
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return
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df["Date"] = pd.to_datetime(df["Date"].apply(lambda x: x + "/2022"))
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if external_axes is None:
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_, ax = plt.subplots(figsize=plot_autoscale(), dpi=cfp.PLOT_DPI)
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elif is_valid_axes_count(external_axes, 1):
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(ax,) = external_axes
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else:
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return
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close_prices = yfinance.download(ticker, start="2022-01-01", progress=False)[
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"Adj Close"
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]
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ax.plot(close_prices)
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color_map = {"Buy": theme.up_color, "Sell": theme.down_color}
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for name, group in df.groupby("Recommendation"):
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ax.scatter(group.Date, group.Price, color=color_map[name], s=150, label=name)
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ax.set_title(f"{ticker.upper()} Close With Cramer Recommendations")
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theme.style_primary_axis(ax)
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ax.legend(loc="best", scatterpoints=1)
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# Overwrite default dote formatting
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ax.xaxis.set_major_formatter(DateFormatter("%m/%d"))
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ax.set_xlabel("Date")
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if external_axes is None:
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theme.visualize_output()
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if raw:
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df["Date"] = df["Date"].apply(lambda x: x.strftime("%Y-%m-%d"))
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print_rich_table(df, title=f"Jim Cramer Recommendations for {ticker}")
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export_data(export, os.path.dirname(os.path.abspath(__file__)), df, "jctr")
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