I'll just list the two bugs I know as of now, and if you have any recommendations for refactoring my code let me know I'll go ahead and list out the few known issues as of now.
- yfinance is not appending the
dividendYield
to my dict, I did make sure that their is an actual Dividend Yield for those Symbols.
TypeError: can only concatenate str (not "Tag") to str
which I assume is something to do with how it parsing through the xml, and it ran into a tag so I am not able to create the expander, I thought I could solve it with this if statement, but instead I just don't get any expander at all.
with st.expander("Expand for stocks news"):
for heading in fin_headings:
if heading == str:
st.markdown("* " + heading)
else:
pass
Full code for main.py:
import requests
import spacy
import pandas as pd
import yfinance as yf
import streamlit as st
from bs4 import BeautifulSoup
st.title("Fire stocks :fire:")
nlp = spacy.load("en_core_web_sm")
def extract_rss(rss_link):
# Parses xml, and extracts the headings.
headings = []
response1 = requests.get(
"http://feeds.marketwatch.com/marketwatch/marketpulse/")
response2 = requests.get(rss_link)
parse1 = BeautifulSoup(response1.content, features="xml")
parse2 = BeautifulSoup(response2.content, features="xml")
headings1 = parse1.findAll('title')
headings2 = parse2.findAll('title')
headings = headings1 + headings2
return headings
def stock_info(headings):
# Get the entities from each heading, link it with nasdaq data // if possible, and Extract market data with yfinance.
stock_dict = {
'Org': [],
'Symbol': [],
'currentPrice': [],
'dayHigh': [],
'dayLow': [],
'forwardPE': [],
'dividendYield': []
}
stocks_df = pd.read_csv("./data/nasdaq_screener_1658383327100.csv")
for title in headings:
doc = nlp(title.text)
for ent in doc.ents:
try:
if stocks_df['Name'].str.contains(ent.text).sum():
symbol = stocks_df[stocks_df['Name'].str.contains(
ent.text)]['Symbol'].values[0]
org_name = stocks_df[stocks_df['Name'].str.contains(
ent.text)]['Name'].values[0]
# Recieve info from yfinance
stock_info = yf.Ticker(symbol).info
print(symbol)
stock_dict['Org'].append(org_name)
stock_dict['Symbol'].append(symbol)
stock_dict['currentPrice'].append(
stock_info['currentPrice'])
stock_dict['dayHigh'].append(stock_info['dayHigh'])
stock_dict['dayLow'].append(stock_info['dayLow'])
stock_dict['forwardPE'].append(stock_info['forwardPE'])
stock_dict['dividendYield'].append(
stock_info['dividendYield'])
else:
# If name can't be found pass.
pass
except:
# Don't raise an error.
pass
output_df = pd.DataFrame.from_dict(stock_dict, orient='index')
output_df = output_df.transpose()
return output_df
# Add input field input field
user_input = st.text_input(
"Add rss link here", "https://www.investing.com/rss/news.rss")
# Get financial headlines
fin_headings = extract_rss(user_input)
print(fin_headings)
# Output financial info
output_df = stock_info(fin_headings)
output_df.drop_duplicates(inplace=True, subset='Symbol')
st.dataframe(output_df)
with st.expander("Expand for stocks news"):
for heading in fin_headings:
if heading == str:
st.markdown("* " + heading)
else:
pass
from Python Streamlit, and yfinance issues
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