Stock Screener, S&P 500, Python, EODHD API, Streamlit

Build a real-time S&P 500 stock screener with Python, EODHD API, and Streamlit. View historical prices, candlestick charts & fundamental data.

Published · Updated · Methodology: Technical Indicators

Part of: Candlestick Patterns

  • Methodology: Technical Indicators
  • Content type: educational
  • Timeframes: Daily, Weekly, Monthly
  • Markets: S&P 500, Stocks

Indicators used

  • Candlestick Chart

Source video

Decoded from: 📈¿Cómo Construir un Stock Screener de Acciones del S&P 500 en Python con EODHD API? by PythonIA — watch the original

Key timestamps:

  • 0:20 - Introduction to the application
  • 0:50 - EODHD API description
  • 1:50 - Screener functionality overview
  • 2:00 - Price table data (Open, High, Low, Close, Volume)
  • 2:15 - Candlestick chart interaction
  • 2:30 - Timeframe selection (Daily, Weekly, Monthly)
  • 2:45 - Fundamental data display (Market Cap, PER, EPS, Revenue, Enterprise Value)
  • 3:00 - Export to Excel functionality
  • 3:30 - Importing libraries (Streamlit, Requests, Pandas, Beautiful Soup)
  • 3:45 - Web scraping Wikipedia for S&P 500 symbols
  • 4:30 - EODHD API key and documentation
  • 5:00 - Stock data function (historical End of Day API)
  • 5:30 - Fundamentals data function
  • 6:00 - Building the Streamlit UI elements
  • 7:00 - Time period mapping for API (Daily, Weekly, Monthly)
  • 7:30 - Calling get_stock_data and displaying results
  • 8:00 - Candlestick chart creation
  • 8:15 - Displaying fundamental data
  • 8:30 - Export to Excel button
  • 8:45 - Running the Streamlit application
  • 9:15 - Demonstration with Microsoft stock
  • 10:00 - Exported Excel data review

Strategy overview

Candlestick charts encode each period's open, high, low and close into a single readable shape, which is why they remain the default visual language for screening price action. This entry, however, is not about reading a specific pattern — it is about building the tool that lets you read patterns across an entire index. The source video walks through constructing a stock screener for the S&P 500 in Python, using the EODHD API for market data and Streamlit for the interface.

The video, "¿Cómo Construir un Stock Screener de Acciones del S&P 500 en Python con EODHD API?" from the Spanish-language channel PythonIA, is structured as an application build rather than a trading lesson. It opens with a tour of the finished app, explains where the price data comes from, and then demonstrates the screener in use: an OHLCV price table, an interactive candlestick chart, and a switch between daily, weekly and monthly views of the same symbol. The emphasis throughout is on the plumbing — data source, rendering, timeframe handling — not on when to buy or sell.

That makes this a useful entry for a different reason than most in the catalogue. No entry or exit conditions are defined here, so there is nothing to backtest as a strategy; what the video offers is the scanning layer that a rule-based approach normally sits on top of. Traders who currently screen manually, or who depend on a hosted platform's filters, will find this a template for owning that step themselves — including the multi-timeframe candlestick view that makes a shortlist worth reviewing by eye.

Topics

stock screener · s&p 500 · python trading strategy · eodhd api · streamlit app · technical indicators · daily timeframe · candlestick chart · stock market analysis · quantitative finance · stock data api · market data

Frequently asked questions

What is a stock screener and why build one in Python?

A stock screener filters a universe of symbols — here the S&P 500 — down to a shortlist worth inspecting. Building one in Python with a market-data API and a framework like Streamlit means you control the data source, the filters and the charts, instead of working within a hosted platform's fixed options.

Does this video teach a trading strategy with entry and exit rules?

No. It is a build tutorial for a screening application, not a rule set. It covers how the app pulls price data, displays OHLCV values and renders interactive candlestick charts, but it does not define signal conditions, position sizing or exits.

Why does the screener offer daily, weekly and monthly candlestick views?

Switching timeframes on the same symbol lets you check whether what looks meaningful on a daily chart still holds on a weekly or monthly one. It is a standard sanity check when reviewing a shortlist, and the video demonstrates it as part of the screener's chart interaction.

What role does the EODHD API play in the build?

It is the market-data provider the application queries for end-of-day price history, which then feeds both the price table and the candlestick chart. The video devotes an early segment to describing the API before showing the screener functionality it powers.

About this strategy page

This trading strategy was decoded by Strategy Decoder's AI from a public YouTube trading video and turned into a structured, reviewable specification. In the interactive app this page shows the full entry and exit logic, risk management settings, the indicators involved with their parameters, AlgoWizard-compatible logic and a Pine Script export ready for TradingView backtesting — plus an automated backtest verdict when one has been computed for this strategy.

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