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Improved readability and removed unnecessary functionality
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README.md

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## finviz-api
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`finviz-api` is compatible with Python 3.6+ only
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[![PyPI version](https://badge.fury.io/py/finviz.svg)](https://badge.fury.io/py/finviz)
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[![GitHub stars](https://img.shields.io/github/stars/mariostoev/finviz.svg)](https://github.com/mariostoev/finviz/stargazers)
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[![Downloads](https://pepy.tech/badge/finviz)](https://pepy.tech/project/finviz)
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[![HitCount](http://hits.dwyl.io/mariostoev/finviz.svg)](http://hits.dwyl.io/mariostoev/finviz)
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`finviz` is compatible with Python 3.5+ only
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**What is Finviz?**
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Any quotes data displayed on finviz.com is delayed by 15 minutes for NASDAQ, and 20 minutes for NYSE and AMEX. This API should **NOT** be used for live trading, it's main purpuse is financial analysis, research and data scraping.
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### Install the current release using PyPi
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pip install finviz
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### Using Screener()
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from finviz import Screener
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from finviz.screener import Screener
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tickers = ['AAPL', 'ATVI', 'TSLA']
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filters = ['exch_nasd', 'cap_large'] # Shows companies in NASDAQ with Market Cap from $10bln. to $200bln.
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filters = ['exch_nasd', 'cap_large'] # Shows companies in NASDAQ with a market cap from $10bln. to $200bln.
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order = '-price' # Orders the results by price descending
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stocks = Screener(filters, order, rows=50) # Get the first 50 results
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# Export the screener results to .csv
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stocks.to_csv()
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Screener(tickers, filters, order, rows=37)
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Screener.to_csv()
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# Create a SQLite database
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stocks.to_sqlite()
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# Creates screener_results.csv file in the current directory
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# Print the database into the console
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stocks.display_db()
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### Download results as a chart
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stocks.get_charts(period='m', chart_type='c', size='l', ta=False) # Monthly, Candles, Large, No Technical Analysis
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# period='d' > daily
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# period='w' > weekly
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# period='m' > monthly
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# chart_type='c' > candle
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# chart_type='l' > lines
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# size='m' > small
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# size='l' > large
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# ta=True > display technical analysis
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# ta=False > ignore technical analysis
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Below, you can see all of the possible arguments that can be passed through Screener():
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| filters | list | ['exch_nasd', 'cap_large'] | None |
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| order | string | '-price' | None |
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| signal | string | 'ta_topgainers' | None |
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| dir | string | 'C:/User/Desktop/data' | Current Directory |
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| table | string | 'Performance' | 'Overview' |
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| rows | int | 43 | Maximum |
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| rows | string | 43 | Maximum |
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