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Connect financial data providers to Python and research applications

Compare company fundamentals visually with historical stock valuations

Research and backtest quantitative strategies in notebooks and code

Create reusable chart conditions and filter stock watchlists

Explore international macroeconomic datasets and projection vintages

Calculate portfolio returns from a complete transaction history

Study an exploratory Python engine for historical equities tests

Move from global stock screens to financials and valuation models

iPhone expense accounts that can also serve as budget envelopes

PDF-to-spreadsheet conversion with layout and OCR tools

Environments for training AI and agents that handle recurring engineering work

Develop and compare trading strategies in a Windows backtesting workspace

Interpret options sweeps and equity prints, with new subscriptions currently paused

License financial datasets for personal research or commercial products

Move between portfolio views and a configurable trading workspace

Study Indian stocks through market screens and portfolio analysis

Research markets through connected data, news and analytics

Add entity, theme and sentiment features to financial-text research

Move from stock screens to charts and portfolio views

Compare company research with options strategy simulations

Retrieve stock history and filing data as JSON

Choose Python research and backtesting engines for the task

Run configurable pricing, risk and valuation-adjustment studies

Compare options transactions with market-positioning estimates and disclosures