finviz_api

Finviz makes the URL simple to implement in the code (just add the ticker symbol after http://finviz.com/quote.ashx?t=) although it comes with several limitations I won't describe here that makes it a harder task than it is and that's the reason I used Mario Stoev unofficial API as it was rather easy and intuitive to use and didn't involve many installs like in other API's out there. So this is what you need to do to connect to the API First, you need to install Finviz API pip install finviz Then import relevant dependencies  from finviz.screener import Screener

from typing import List, Dict from sklearn import logger

from stocks_finviz.get_finviz_filtered_list import find_filters_symbols # This one you'll need to create of your own You'll need to add your parameters as you would do on the Finviz website. This can be quite tricky as several parameters have the same name and their names convention change when you send them through the API. In order to have all options available with this API, I took all the filters from here and added them as JSON to a file called finviz_filters.py. Without this file you cannot resolve the filter name Finviz API expects to get. Say you want to find stocks that answer the following parameters: Industry=Stocks only (ex-Funds), Country=USA Market Cap=-Small (under $2bln)

All you need to do is to add them as an input parameter like the following: input_filters=Industry,Stocks only (ex-Funds),Country,USA, Market Cap,-Small (under $2bln) And with the following methods: def convert_to_dict(lst): lst = lst.split(',') res_dct = {lst[i]: lst[i + 1] for i in range(0, len(lst), 2)} return res_dct def get_filters(filters): # type: (List[Dict]) -> List[str] """ get name filters for screener :param filters: list of dict :return: str filters values """

if isinstance(filters, str):
    filters = [filters]

if len(filters) == 0:
    logger.info('No filters')
    return

filtered_results = find_filters_symbols(filters)

if filtered_results:
    logger.info(f'The following filters are found: {filtered_results}')
    return filtered_results
else:
    logger.warning('No filtered results from finviz screener')
    return

You'll end up with something like this: filters = convert_to_dict(input_filters) filters_finviz = get_filters(filters) print(filters_finviz) ['ind_stocksonly', 'geo_usa', 'fa_eps5years_pos', 'ta_volatility_wo10', 'sh_relvol_o1', 'sh_outstanding_u20', 'sh_float_u20'] Which is what the Finviz screener expects to get. From here the road is easy, you need to call the API, add the relevant filters you want and save it to a CSV or SQL DB export_path = YOUR PATH file_name = YOUR FILE NAME try: stock_list = Screener(filters=filters_finviz, table='Performance', order='price') except Exception as e: print(f'No stocks after screening. {e}') stock_list = None

Either use finviz built in to_csv

stock_list.to_csv("stock.csv")

Or use pandas to_excel

stock_df = pd.DataFrame(stock_list.data) stock_df.to_excel(export_path+file_name, sheetname='filtered_stocks', index=False) # You might need to use xlsxwriter

Or create a SQLite database

stock_list.to_sqlite("stock.sqlite3") If you would like the entire code for this article, you can visit this GitHub. I hope this article will prove useful to your endeavors in the future. Thank you so much for reading!