def test_get_ticker_details_sequential_requests(self):
stocks = Screener(filters=[
'sh_curvol_o300', 'ta_highlow52w_b0to10h', 'ind_stocksonly',
'sh_outstanding_o1000'
])
ticker_details = stocks.get_ticker_details()
count = 0
for _ in ticker_details:
count += 1
assert len(stocks) == count == len(ticker_details)
def test_get_ticker_details_sequential_requests(self):
""" Tests that `get_ticker_details` method returns correct number of ticker details. """
stocks = Screener(filters=[
"sh_curvol_o300",
"ta_highlow52w_b0to10h",
"ind_stocksonly",
"sh_outstanding_o1000",
])
ticker_details = stocks.get_ticker_details()
count = 0
for _ in ticker_details:
count += 1
assert len(stocks) == count == len(ticker_details)
#!/usr/bin/python3
from finviz.screener import Screener
# Get dict of available filters
# filters dict contains the corresponding filter tags
filters = Screener.load_filter_dict()
some_filters = [filters["PEG"]["Under 1"], filters["Exchange"]["AMEX"]]
stock_list = Screener(filters=some_filters, order="ticker")
print(stock_list)
# Use raw filter tags in a list
# filters = ['geo_usa']
filters = ["idx_sp500"] # Shows companies in the S&P500
print("Screening stocks...")
stock_list = Screener(filters=filters, order="ticker")
print(stock_list)
print("Retrieving stock data...")
stock_data = stock_list.get_ticker_details()
print(stock_data)
# Export the screener results to CSV file
stock_list.to_csv("sp500.csv")
# Create a SQLite database
# stock_list.to_sqlite("sp500.sqlite")
from finviz.helper_functions.save_data import export_to_db, export_to_csv
from finviz.screener import Screener
from finviz.main_func import *
import pandas as pd
import yfinance as yf
from datetime import datetime, timedelta, date
#filters = []
#filters = ['geo_usa']
filters = ['fa_div_pos'] # Shows companies in the S&P500
print("Filtering stocks..")
stock_list = Screener(filters=filters, order='ticker')
print("Parsing every stock..")
stock_list.get_ticker_details()
#df = pd.DataFrame(data=stock_list)
#print(df.head())
# Export the screener results to CSV file
stock_list.to_csv(r'C:/Users/Jacob Steenhuysen/Downloads/all_world_yields6.csv')
df = pd.read_csv(r'C:/Users/Jacob Steenhuysen/Downloads/all_world_yields6.csv')
