Multiple Symbols

The same Ticker API that handles one company handles a whole watchlist. Pass a list of symbols and every subsequent call fans out across all of them.

The FAANG example

from yahooquery import Ticker

symbols = ['fb', 'aapl', 'amzn', 'nflx', 'goog']
faang = Ticker(symbols)

faang.summary_detail

The response is a dictionary keyed by symbol — each value has the same shape you’d get from a single-symbol call.

What the response looks like

{
  'fb':   {'regularMarketPrice': ..., 'marketCap': ..., ...},
  'aapl': {'regularMarketPrice': ..., 'marketCap': ..., ...},
  # ... one entry per symbol
}

DataFrames stay tidy too

Methods that return DataFrames — like history() — use a MultiIndex so each symbol’s rows stay grouped:

df = faang.history(period='1mo')
df.loc['aapl']  # just Apple's rows

Practical tips

• Batch aggressively. One multi-symbol Ticker makes fewer round trips than looping over single-symbol Tickers.
• Mix asset types. Stocks, ETFs, indices, currencies, and crypto symbols can share one list.
• Pair with async. For very large lists, enable asynchronous requests to parallelize the calls.