Files
OpenBB/openbb_terminal/common/behavioural_analysis/finnhub_view.py
montezdesousa 02901f1473 Trim command output spaces (#3424)
* first round of removing spaces

* remove more print statemnts

* remove more spaces

* bullbear color

* spacc color

* improve stalker readability

* delete more spaces

* reddit colors

* rever hood

* flake8

* forgot this one

* fix econometrics tests

* fix econometrics tests

* fix more tests

Co-authored-by: James Maslek <jmaslek11@gmail.com>
2022-11-16 11:47:24 +00:00

62 lines
1.8 KiB
Python

"""Finnhub View"""
__docformat__ = "numpy"
import logging
import os
import pandas as pd
from openbb_terminal.common.behavioural_analysis import finnhub_model
from openbb_terminal.decorators import log_start_end
from openbb_terminal.helper_funcs import export_data
from openbb_terminal.rich_config import console
from openbb_terminal.decorators import check_api_key
logger = logging.getLogger(__name__)
@log_start_end(log=logger)
@check_api_key(["API_FINNHUB_KEY"])
def display_sentiment_stats(ticker: str, export: str = ""):
"""
Prints Sentiment stats which displays buzz, news score, articles last week, articles weekly average,
bullish vs bearish percentages, sector average bullish percentage, and sector average news score
Parameters
----------
ticker : str
Ticker to get sentiment stats
export : str
Format to export data
"""
d_stats = finnhub_model.get_sentiment_stats(ticker)
print(d_stats)
if d_stats.empty:
return
if d_stats:
console.print(
f"""
Buzz: {round(100*d_stats['buzz']['buzz'],2)} %
News Score: {round(100*d_stats['companyNewsScore'],2)} %
Articles Last Week: {d_stats['buzz']['articlesInLastWeek']}
Articles Weekly Average: {d_stats['buzz']['weeklyAverage']}
Bullish: {round(100*d_stats['sentiment']['bullishPercent'],2)} %
Bearish: {round(100*d_stats['sentiment']['bearishPercent'],2)} %
Sector Average Bullish: {round(100*d_stats['sectorAverageBullishPercent'],2)}
Sector Average News Score: {round(100*d_stats['sectorAverageNewsScore'],2)} %"""
)
export_data(
export,
os.path.dirname(os.path.abspath(__file__)),
"stats",
pd.DataFrame(d_stats),
)
else:
console.print("No sentiment stats found.")