Deribit

Fetch market and static data from Deribit API.

You can import the module via

from quantflow.data.deribit import Deribit

quantflow.data.deribit.Deribit dataclass

Deribit(url='https://www.deribit.com/api/v2')

Bases: AioHttpClient

Deribit API client

Example

from quantflow.data.deribit import Deribit

deribit = Deribit()

url class-attribute instance-attribute

url = 'https://www.deribit.com/api/v2'

get_book_summary_by_instrument async

get_book_summary_by_instrument(instrument_name, **kw)

Get the book summary for a given instrument.

PARAMETER	DESCRIPTION
instrument_name	Instrument name TYPE: str

Source code in quantflow/data/deribit.py

async def get_book_summary_by_instrument(
    self,
    instrument_name: Annotated[str, Doc("Instrument name")],
    **kw: Any,
) -> list[dict]:
    """Get the book summary for a given instrument."""
    kw.update(params=dict(instrument_name=instrument_name), callback=self.to_result)
    return cast(
        list[dict],
        await self.get_path("public/get_book_summary_by_instrument", **kw),
    )

get_book_summary_by_currency async

get_book_summary_by_currency(
    currency, *, kind=None, base=None, **kw
)

Get the book summary for a given currency.

For linear futures/options, the currency parameter should be set to "usdc" and the base parameter should be set to the underlying currency (e.g. "btc" or "eth").

PARAMETER	DESCRIPTION
currency	Currency TYPE: str
kind	Optional instrument kind TYPE: InstrumentKind | None DEFAULT: None
base	Optional base currency for linear futures/options TYPE: str | None DEFAULT: None

Source code in quantflow/data/deribit.py

async def get_book_summary_by_currency(
    self,
    currency: Annotated[str, Doc("Currency")],
    *,
    kind: Annotated[InstrumentKind | None, Doc("Optional instrument kind")] = None,
    base: Annotated[
        str | None, Doc("Optional base currency for linear futures/options")
    ] = None,
    **kw: Any,
) -> list[dict]:
    """Get the book summary for a given currency.

    For linear futures/options, the `currency` parameter should be set to "usdc"
    and the `base` parameter should be set to the underlying
    currency (e.g. "btc" or "eth").
    """
    kw.update(
        params=compact_dict(currency=currency, kind=kind), callback=self.to_result
    )
    data = cast(
        list[dict], await self.get_path("public/get_book_summary_by_currency", **kw)
    )
    if base:
        base = base.upper()
        data = [d for d in data if d["base_currency"] == base]
    return data

get_instruments async

get_instruments(
    currency, *, kind=None, expired=None, base=None, **kw
)

Get the list of instruments for a given currency.

PARAMETER	DESCRIPTION
currency	Currency TYPE: str
kind	Optional instrument kind TYPE: InstrumentKind | None DEFAULT: None
expired	Include expired instruments TYPE: bool | None DEFAULT: None
base	Optional base currency for linear futures/options TYPE: str | None DEFAULT: None

Source code in quantflow/data/deribit.py

async def get_instruments(
    self,
    currency: Annotated[str, Doc("Currency")],
    *,
    kind: Annotated[InstrumentKind | None, Doc("Optional instrument kind")] = None,
    expired: Annotated[bool | None, Doc("Include expired instruments")] = None,
    base: Annotated[
        str | None, Doc("Optional base currency for linear futures/options")
    ] = None,
    **kw: Any,
) -> list[dict]:
    """Get the list of instruments for a given currency."""
    kw.update(
        params=compact_dict(currency=currency, kind=kind, expired=expired),
        callback=self.to_result,
    )
    data = cast(list[dict], await self.get_path("public/get_instruments", **kw))
    if base:
        base = base.upper()
        data = [d for d in data if d["base_currency"] == base]
    return data

get_volatility async

get_volatility(currency, **kw)

Provides information about historical volatility for given cryptocurrency

PARAMETER	DESCRIPTION
currency	Currency TYPE: str

Source code in quantflow/data/deribit.py

async def get_volatility(
    self,
    currency: Annotated[str, Doc("Currency")],
    **kw: Any,
) -> pd.DataFrame:
    """Provides information about historical volatility for given cryptocurrency"""
    kw.update(params=dict(currency=currency), callback=self.to_df)
    return await self.get_path("public/get_historical_volatility", **kw)

volatility_surface_loader async

volatility_surface_loader(
    currency,
    *,
    ref_date=None,
    inverse=True,
    exclude_open_interest=None,
    exclude_volume=None
)

Create a VolSurfaceLoader for a given crypto-currency by fetching the book summaries and instrument definitions and passing them to loader_from_book

PARAMETER	DESCRIPTION
currency	Currency TYPE: str
ref_date	Reference date for the yield curves; defaults to now TYPE: datetime | None DEFAULT: None
inverse	Whether to use inverse or linear options. Inverse options are priced in the base currency, while linear options are priced in USD. TYPE: bool DEFAULT: True
exclude_open_interest	Exclude options with open interest below this threshold TYPE: Number | None DEFAULT: None
exclude_volume	Exclude options with volume below this threshold TYPE: Number | None DEFAULT: None

Source code in quantflow/data/deribit.py

async def volatility_surface_loader(
    self,
    currency: Annotated[str, Doc("Currency")],
    *,
    ref_date: Annotated[
        datetime | None,
        Doc("Reference date for the yield curves; defaults to now"),
    ] = None,
    inverse: Annotated[
        bool,
        Doc(
            "Whether to use inverse or linear options. Inverse options are priced "
            "in the base currency, while linear options are priced in USD."
        ),
    ] = True,
    exclude_open_interest: Annotated[
        Number | None,
        Doc("Exclude options with open interest below this threshold"),
    ] = None,
    exclude_volume: Annotated[
        Number | None, Doc("Exclude options with volume below this threshold")
    ] = None,
) -> VolSurfaceLoader:
    """Create a [VolSurfaceLoader][quantflow.options.surface.VolSurfaceLoader]
    for a given crypto-currency by fetching the book summaries and
    instrument definitions and passing them to
    [loader_from_book][quantflow.data.deribit.Deribit.loader_from_book]"""
    if inverse:
        futures = await self.get_book_summary_by_currency(
            currency=currency, kind=InstrumentKind.FUTURE
        )
        options = await self.get_book_summary_by_currency(
            currency=currency, kind=InstrumentKind.OPTION
        )
        instruments = await self.get_instruments(currency=currency)
    else:
        futures = await self.get_book_summary_by_currency(
            currency="usdc", kind=InstrumentKind.FUTURE, base=currency
        )
        options = await self.get_book_summary_by_currency(
            currency="usdc", kind=InstrumentKind.OPTION, base=currency
        )
        instruments = await self.get_instruments(currency="usdc", base=currency)
    return self.loader_from_book(
        futures,
        options,
        instruments,
        currency=currency,
        ref_date=ref_date,
        inverse=inverse,
        exclude_open_interest=exclude_open_interest,
        exclude_volume=exclude_volume,
    )

loader_from_book classmethod

loader_from_book(
    futures,
    options,
    instruments,
    *,
    currency,
    ref_date=None,
    inverse=True,
    exclude_open_interest=None,
    exclude_volume=None
)

Build a VolSurfaceLoader from Deribit book summaries and instrument definitions.

Useful for rebuilding a loader from recorded data without network access.

PARAMETER	DESCRIPTION
futures	Futures book summary entries TYPE: list[dict]
options	Options book summary entries TYPE: list[dict]
instruments	Instrument definitions TYPE: list[dict]
currency	Currency TYPE: str
ref_date	Reference date for the yield curves; defaults to now TYPE: datetime | None DEFAULT: None
inverse	Whether to use inverse or linear options. Inverse options are priced in the base currency, while linear options are priced in USD. TYPE: bool DEFAULT: True
exclude_open_interest	Exclude options with open interest below this threshold TYPE: Number | None DEFAULT: None
exclude_volume	Exclude options with volume below this threshold TYPE: Number | None DEFAULT: None

Source code in quantflow/data/deribit.py

@classmethod
def loader_from_book(
    cls,
    futures: Annotated[list[dict], Doc("Futures book summary entries")],
    options: Annotated[list[dict], Doc("Options book summary entries")],
    instruments: Annotated[list[dict], Doc("Instrument definitions")],
    *,
    currency: Annotated[str, Doc("Currency")],
    ref_date: Annotated[
        datetime | None,
        Doc("Reference date for the yield curves; defaults to now"),
    ] = None,
    inverse: Annotated[
        bool,
        Doc(
            "Whether to use inverse or linear options. Inverse options are priced "
            "in the base currency, while linear options are priced in USD."
        ),
    ] = True,
    exclude_open_interest: Annotated[
        Number | None,
        Doc("Exclude options with open interest below this threshold"),
    ] = None,
    exclude_volume: Annotated[
        Number | None, Doc("Exclude options with volume below this threshold")
    ] = None,
) -> VolSurfaceLoader:
    """Build a [VolSurfaceLoader][quantflow.options.surface.VolSurfaceLoader]
    from Deribit book summaries and instrument definitions.

    Useful for rebuilding a loader from recorded data without network
    access."""
    loader = VolSurfaceLoader(
        asset=currency,
        ref_date=ref_date or utcnow(),
        exclude_open_interest=to_decimal_or_none(exclude_open_interest),
        exclude_volume=to_decimal_or_none(exclude_volume),
    )
    instrument_map = {i["instrument_name"]: i for i in instruments}
    min_tick_size = Decimal("inf")
    for entry in futures:
        bid_ = entry["bid_price"]
        ask_ = entry["ask_price"]
        if bid_ and ask_:
            name = entry["instrument_name"]
            if (meta := instrument_map.get(name)) is None:
                continue
            tick_size = to_decimal(meta["tick_size"])
            min_tick_size = min(min_tick_size, tick_size)
            bid = round_to_step(bid_, tick_size)
            ask = round_to_step(ask_, tick_size)
            if meta["settlement_period"] == "perpetual":
                loader.add_spot(
                    DefaultVolSecurity.spot(),
                    bid=bid,
                    ask=ask,
                    open_interest=to_decimal(entry["open_interest"]),
                    volume=to_decimal(entry["volume_usd"]),
                )
            else:
                maturity = pd.to_datetime(
                    meta["expiration_timestamp"],
                    unit="ms",
                    utc=True,
                ).to_pydatetime()
                loader.add_forward(
                    DefaultVolSecurity.forward(),
                    maturity=maturity,
                    bid=bid,
                    ask=ask,
                    open_interest=to_decimal(entry["open_interest"]),
                    volume=to_decimal(entry["volume_usd"]),
                )
    loader.tick_size_forwards = min_tick_size

    min_tick_size = Decimal("inf")
    for entry in options:
        if (bid_ := entry["bid_price"]) and (ask_ := entry["ask_price"]):
            name = entry["instrument_name"]
            if (meta := instrument_map.get(name)) is None:
                continue
            tick_size = to_decimal(meta["tick_size"])
            min_tick_size = min(min_tick_size, tick_size)
            loader.add_option(
                DefaultVolSecurity.option(),
                strike=round_to_step(meta["strike"], tick_size),
                maturity=pd.to_datetime(
                    meta["expiration_timestamp"],
                    unit="ms",
                    utc=True,
                ).to_pydatetime(),
                option_type=(
                    OptionType.CALL
                    if meta["option_type"] == "call"
                    else OptionType.PUT
                ),
                bid=round_to_step(bid_, tick_size),
                ask=round_to_step(ask_, tick_size),
                open_interest=to_decimal(entry["open_interest"]),
                volume=to_decimal(entry["volume_usd"]),
                inverse=inverse,
            )
    loader.tick_size_options = min_tick_size
    return loader

get_path async

get_path(path, **kw)

PARAMETER	DESCRIPTION
path	API path TYPE: str

Source code in quantflow/data/deribit.py

async def get_path(
    self,
    path: Annotated[str, Doc("API path")],
    **kw: Any,
) -> dict:
    return await self.get(f"{self.url}/{path}", **kw)

to_result async

to_result(response)

PARAMETER	DESCRIPTION
response	HTTP response object TYPE: HttpResponse

Source code in quantflow/data/deribit.py

async def to_result(
    self,
    response: Annotated[HttpResponse, Doc("HTTP response object")],
) -> list[dict]:
    data = await response.json()
    if "error" in data:
        raise HttpResponseError(response, data["error"])
    return cast(list[dict], data["result"])

to_df async

to_df(response)

PARAMETER	DESCRIPTION
response	HTTP response object TYPE: HttpResponse

Source code in quantflow/data/deribit.py

async def to_df(
    self,
    response: Annotated[HttpResponse, Doc("HTTP response object")],
) -> pd.DataFrame:
    data = await self.to_result(response)
    df = pd.DataFrame(data, columns=["timestamp", "volatility"])
    df["timestamp"] = pd.to_datetime(df["timestamp"], unit="ms")
    return df