Strikes

Get a list of available strike prices for an underlying symbol.

Making Requests

Use the strikes() method on the options resource to fetch strike prices. The method supports multiple output formats:

Output Format	Return Type	Description
DATAFRAME	pandas.DataFrame or polars.DataFrame	Returns a DataFrame with strike prices (default).
INTERNAL	OptionsStrikes or OptionsStrikesHumanReadable	Returns an OptionsStrikes object. When use_human_readable=True, returns an OptionsStrikesHumanReadable object 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.

strikes

def strikes(
    symbol: str,
    *,
    expiration: str | datetime.datetime = None,
    date: str | datetime.datetime = None,
    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,
) -> OptionsStrikes | OptionsStrikesHumanReadable | dict | str | MarketDataClientErrorResult

Fetches available strike prices for a given symbol. The symbol parameter can be passed as the first positional argument or as a keyword argument. All other parameters must be keyword-only.

Parameters

• symbol (str)

  The underlying stock symbol for which to fetch strike prices.

• expiration (str | datetime.datetime, optional)

  Filter by expiration date.

• date (str | datetime.datetime, optional)

  Historical date for the strike 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 feed mode to use. See Settings for details.

• filename (str | Path, optional)

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

Returns

• OptionsStrikes | OptionsStrikesHumanReadable | dict | str | MarketDataClientErrorResult

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

Example (DataFrame)

from marketdata.client import MarketDataClient

client = MarketDataClient()

# Get options strikes as DataFrame (default)
# symbol can be passed positionally or as keyword
df = client.options.strikes("AAPL")
# or
df = client.options.strikes(symbol="AAPL")

print(df)

Example (Internal)

from marketdata.client import MarketDataClient
from marketdata.input_types.base import OutputFormat

client = MarketDataClient()

# Get options strikes as internal object
strikes = client.options.strikes("AAPL", output_format=OutputFormat.INTERNAL)

# Access strike prices
# Strikes are stored as dynamic fields based on expiration dates
# Access them via __dict__ or getattr
print(f"Updated: {strikes.updated}")
# Example: Access strikes for a specific expiration date
# The field names are expiration dates in format "YYYY-MM-DD"
for key, value in strikes.__dict__.items():
    if key not in ["s", "updated"]:
        print(f"{key}: {value}")

Example (JSON)

from marketdata.client import MarketDataClient
from marketdata.input_types.base import OutputFormat

client = MarketDataClient()

# Get options strikes as JSON
strikes = client.options.strikes("AAPL", output_format=OutputFormat.JSON)

print(strikes)

Example (CSV)

from marketdata.client import MarketDataClient
from marketdata.input_types.base import OutputFormat
from pathlib import Path

client = MarketDataClient()

# Get options strikes as CSV
csv_file = client.options.strikes(
    "AAPL",
    output_format=OutputFormat.CSV,
    filename=Path("strikes.csv")
)

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

Example (Human Readable)

from marketdata.client import MarketDataClient
from marketdata.input_types.base import OutputFormat

client = MarketDataClient()

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

# Access strike prices and date
print(f"Date: {strikes.Date}")
# Strikes are stored as dynamic fields based on expiration dates
# Access them via getattr or __dict__

OptionsStrikes

@dataclass
class OptionsStrikes:
    s: str
    updated: datetime.datetime
    # Dynamic fields: expiration dates as keys (e.g., "2024-01-20": list[float])

OptionsStrikes represents strike prices for options, with dynamic fields based on expiration dates. Each expiration date becomes a field containing a list of strike prices.

Properties

• s (str): Status indicator ("ok" for successful responses).
• updated (datetime.datetime): The time when the data was last updated (automatically converted from timestamp).
• Dynamic fields: Each expiration date (in format "YYYY-MM-DD") becomes a field containing a list of strike prices (list[float]).

Notes

• The updated field is automatically converted to a datetime.datetime object from a Unix timestamp.
• Strike prices are organized by expiration date, with each expiration date as a field name.
• Access strikes using getattr() or __dict__ (e.g., getattr(strikes, "2024-01-20")).

OptionsStrikesHumanReadable

@dataclass
class OptionsStrikesHumanReadable:
    Date: datetime.datetime
    # Dynamic fields: expiration dates as keys (e.g., "2024-01-20": list[float])

OptionsStrikesHumanReadable represents strike prices in human-readable format with capitalized field names and formatted values.

Properties

• Date (datetime.datetime): The time when the data was last updated (automatically converted from timestamp).
• Dynamic fields: Each expiration date (in format "YYYY-MM-DD") becomes a field containing a list of strike prices (list[float]).

Notes

• The Date field is automatically converted to a datetime.datetime object from a Unix timestamp.
• Strike prices are organized by expiration date, with each expiration date as a field name.
• Access strikes using getattr() or __dict__ (e.g., getattr(strikes, "2024-01-20")).
• Field names use capitalized format (e.g., Date instead of updated).