Prices (Python SDK)

• Last updated Sep 3, 2026
• View as Markdown

Retrieve stock prices for any supported stock symbol.

Making Requests

Use the prices() method on the stocks resource to fetch stock prices. The method supports multiple output formats:

Output Format	Return Type	Description
DATAFRAME	pandas.DataFrame or polars.DataFrame	Returns a DataFrame with prices indexed by symbol (default).
INTERNAL	list[StockPrice] or list[StockPricesHumanReadable]	Returns a list of StockPrice objects. When use_human_readable=True, returns a list of StockPricesHumanReadable objects with capitalized field names.
JSON	dict	Returns the raw JSON response as a dictionary.
CSV	str	Writes CSV data to file and returns the filename string.

prices

def prices(
    symbols: list[str] | str,
    *,
    output_format: OutputFormat = OutputFormat.DATAFRAME,
    date_format: DateFormat = None,
    columns: list[str] = None,
    add_headers: bool = None,
    use_human_readable: bool = False,
    mode: Mode = None,
    filename: str | Path = None,
) -> list[StockPrice] | list[StockPricesHumanReadable] | dict | str | MarketDataClientErrorResult

Fetches stock prices for one or more symbols. The symbols parameter can be passed as the first positional argument or as a keyword argument. All other parameters must be keyword-only.

Parameters

• symbols (list[str] | str)

  A single symbol string or a list of symbol strings for which to fetch prices.

• output_format (OutputFormat, optional)

  The format of the returned data. Defaults to OutputFormat.DATAFRAME. See Settings for details.

• date_format (DateFormat, optional)

  The date format to use in the response. Defaults to DateFormat.UNIX. See Settings for details.

• columns (optional)

  Specify which columns to include in the response. See Settings for details.

• add_headers (optional)

  Whether to include headers in the response. See Settings for details.

• use_human_readable (optional)

  Whether to use human-readable format for values. Only applies when output_format=OutputFormat.INTERNAL. See Settings for details.

• mode (Mode, optional)

  The data mode to use. See Settings for details.

• filename (str | Path, optional)

  File path for CSV output (only used with output_format=OutputFormat.CSV).

Returns

• list[StockPrice] | list[StockPricesHumanReadable] | dict | str | MarketDataClientErrorResult

  The prices data in the requested format, or a MarketDataClientErrorResult if an error occurred.

Example (DataFrame)

from marketdata import MarketDataClient

client = MarketDataClient()

# Get stock prices as DataFrame (default)
# symbols can be passed positionally or as keyword
df = client.stocks.prices("AAPL")
# or
df = client.stocks.prices(symbols="AAPL")

# Get prices for multiple symbols
df = client.stocks.prices(["AAPL", "MSFT"])

print(df)

Example (Internal)

from marketdata import MarketDataClient, OutputFormat

client = MarketDataClient()

# Get stock prices as internal objects
prices = client.stocks.prices("AAPL", output_format=OutputFormat.INTERNAL)

# Access individual price properties
for price in prices:
    print(f"Symbol: {price.symbol}")
    print(f"Mid: {price.mid}")
    print(f"Change: {price.change}")
    print(f"Change Percent: {price.changepct}")
    print(f"Updated: {price.updated}")

Example (JSON)

from marketdata import MarketDataClient, OutputFormat

client = MarketDataClient()

# Get stock prices as JSON
prices = client.stocks.prices(["AAPL", "MSFT"], output_format=OutputFormat.JSON)

print(prices)

Example (CSV)

from marketdata import MarketDataClient, OutputFormat
from pathlib import Path

client = MarketDataClient()

# Get stock prices as CSV
csv_file = client.stocks.prices(
    ["AAPL", "MSFT"],
    output_format=OutputFormat.CSV,
    filename=Path("prices.csv")
)

print(f"CSV file saved to: {csv_file}")

Example (Human Readable)

from marketdata import MarketDataClient, OutputFormat

client = MarketDataClient()

# Get stock prices in human-readable format
prices = client.stocks.prices(
    "AAPL",
    output_format=OutputFormat.INTERNAL,
    use_human_readable=True
)

for price in prices:
    print(f"Symbol: {price.Symbol}")
    print(f"Mid: {price.Mid}")
    print(f"Change Price: {price.Change_Price}")
    print(f"Change Percent: {price.Change_Percent}")
    print(f"Date: {price.Date}")

StockPrice

@dataclass
class StockPrice:
    s: str
    symbol: str
    mid: float
    change: float
    changepct: float
    updated: datetime.datetime

StockPrice represents a single stock price, encapsulating various details such as prices and timestamps.

Properties

• s (str): Status indicator ("ok" for successful responses).
• symbol (str): The stock symbol.
• mid (float): The mid price calculated between the ask and bid prices.
• change (float): The price change.
• changepct (float): The percentage change in price.
• updated (datetime.datetime): The time when the price was last updated (automatically converted from timestamp).

Notes

• The updated field is automatically converted to a datetime.datetime object from a Unix timestamp.

StockPricesHumanReadable

@dataclass
class StockPricesHumanReadable:
    Symbol: str
    Mid: float
    Change_Price: float
    Change_Percent: float
    Date: datetime.datetime

StockPricesHumanReadable represents a stock price in human-readable format with capitalized field names and formatted values.

Properties

• Symbol (str): The stock symbol.
• Mid (float): The mid price calculated between the ask and bid prices.
• Change_Price (float): The price change.
• Change_Percent (float): The percentage change in price.
• Date (datetime.datetime): The time when the price was last updated (automatically converted from timestamp).

Notes

• The Date field is automatically converted to a datetime.datetime object from a Unix timestamp.
• Field names use capitalized format with underscores (e.g., Change_Price instead of change).