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Data Collector

Gathering data is the foundation of many Python applications. This section explores various methods of data acquisition, from official APIs to web scraping.

Disclaimer: Using official APIs is always the most reliable and ethical method. Excessive crawling can cause system damage and may lead to legal issues. This information is for educational purposes only.

Modules

1. Collectors

Practical examples of data acquisition:

• APIs: Stock data (yfinance), Crypto (Binance), Trends (Google).
• Scraping: Sports data (NFL, Premier League), Weather (Windy).

2. Theory

Essential concepts and terminology for data collection and processing.

3. Data Storage

Methods for persisting collected data:

• Plain text and JSON files.
• Relational databases (SQLite, SQLAlchemy).

4. Post-Processing

What to do with the data after collection:

• Technical analysis (Bollinger Bands, MACD, etc.).
• Reporting (Word, Excel, Gmail).
• Automation (Telegram bots).