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')