IndicatorDataPoints

QuantConnect.Indicators.IndicatorDataPoints

IndicatorDataPoints()

Bases: DynamicData

Collection of indicator data points for a given time

Constructor for initialising the dase data class

current

current: IndicatorDataPoint

The indicator value at a given point

value

value: float

The indicator value at a given point

symbol

symbol: Symbol

Symbol representation for underlying Security

data_type

data_type: MarketDataType

Market Data Type of this data - does it come in individual price packets or is it grouped into OHLC.

time

time: datetime

Current time marker of this data packet.

end_time

end_time: datetime

The end time of this data. Some data covers spans (trade bars) and as such we want to know the entire time span covered

price

price: float

As this is a backtesting platform we'll provide an alias of value as price.

ALL_RESOLUTIONS

ALL_RESOLUTIONS: List[Resolution] = ...

A list of all Resolution

This codeEntityType is protected.

DAILY_RESOLUTION

DAILY_RESOLUTION: List[Resolution] = ...

A list of Resolution.DAILY

This codeEntityType is protected.

MINUTE_RESOLUTION

MINUTE_RESOLUTION: List[Resolution] = ...

A list of Resolution.MINUTE

This codeEntityType is protected.

HIGH_RESOLUTION

HIGH_RESOLUTION: List[Resolution] = ...

A list of high Resolution, including minute, second, and tick.

This codeEntityType is protected.

OPTION_RESOLUTIONS

OPTION_RESOLUTIONS: List[Resolution] = ...

A list of resolutions support by Options

This codeEntityType is protected.

is_fill_forward

is_fill_forward: bool

True if this is a fill forward piece of data

__getitem__

__getitem__(name: str) -> IndicatorDataPoint

Access the historical indicator values per indicator property name

to_string

to_string() -> str

String representation

clone

clone() -> BaseData

Return a new instance clone of this object, used in fill forward

Returns:

Type	Description
BaseData	A clone of the current object.

reader

reader(
    config: SubscriptionDataConfig,
    line: str,
    date: datetime,
    is_live_mode: bool,
) -> BaseData

Reader converts each line of the data source into BaseData objects. Each data type creates its own factory method, and returns a new instance of the object each time it is called. The returned object is assumed to be time stamped in the config.ExchangeTimeZone.

Parameters:

Name	Type	Description	Default
config	SubscriptionDataConfig	Subscription data config setup object	required
line	str	Line of the source document	required
date	datetime	Date of the requested data	required
is_live_mode	bool	true if we're in live mode, false for backtesting mode	required

Returns:

Type	Description
BaseData	Instance of the T:BaseData object generated by this line of the CSV.

requires_mapping

requires_mapping() -> bool

Indicates if there is support for mapping

Returns:

Type	Description
bool	True indicates mapping should be used.

data_time_zone

data_time_zone() -> Any

Specifies the data time zone for this data type. This is useful for custom data types

Returns:

Type	Description
Any	The DateTimeZone of this data type.

default_resolution

default_resolution() -> Resolution

Gets the default resolution for this data and security type

deserialize_message

deserialize_message(serialized: str) -> Iterable[BaseData]

Deserialize the message from the data server

Parameters:

Name	Type	Description	Default
serialized	str	The data server's message	required

Returns:

Type	Description
Iterable[BaseData]	An enumerable of base data, if unsuccessful, returns an empty enumerable.

get_source

get_source(
    config: SubscriptionDataConfig,
    date: datetime,
    is_live_mode: bool,
) -> SubscriptionDataSource

Return the URL string source of the file. This will be converted to a stream

Parameters:

Name	Type	Description	Default
config	SubscriptionDataConfig	Configuration object	required
date	datetime	Date of this source file	required
is_live_mode	bool	true if we're in live mode, false for backtesting mode	required

Returns:

Type	Description
SubscriptionDataSource	String URL of source file.

is_sparse_data

is_sparse_data() -> bool

Indicates that the data set is expected to be sparse

Returns:

Type	Description
bool	True if the data set represented by this type is expected to be sparse.

should_cache_to_security

should_cache_to_security() -> bool

Indicates whether this contains data that should be stored in the security cache

Returns:

Type	Description
bool	Whether this contains data that should be stored in the security cache.

supported_resolutions

supported_resolutions() -> List[Resolution]

Gets the supported resolution for this data and security type

update

update(
    last_trade: float,
    bid_price: float,
    ask_price: float,
    volume: float,
    bid_size: float,
    ask_size: float,
) -> None

Update routine to build a bar/tick from a data update.

Parameters:

Name	Type	Description	Default
last_trade	float	The last trade price	required
bid_price	float	Current bid price	required
ask_price	float	Current asking price	required
volume	float	Volume of this trade	required
bid_size	float	The size of the current bid, if available	required
ask_size	float	The size of the current ask, if available	required

update_ask

update_ask(ask_price: float, ask_size: float) -> None

Updates this base data with the new quote ask information

Parameters:

Name	Type	Description	Default
ask_price	float	The current ask price	required
ask_size	float	The current ask size	required

update_bid

update_bid(bid_price: float, bid_size: float) -> None

Updates this base data with the new quote bid information

Parameters:

Name	Type	Description	Default
bid_price	float	The current bid price	required
bid_size	float	The current bid size	required

update_quote

update_quote(
    bid_price: float,
    bid_size: float,
    ask_price: float,
    ask_size: float,
) -> None

Updates this base data with new quote information

Parameters:

Name	Type	Description	Default
bid_price	float	The current bid price	required
bid_size	float	The current bid size	required
ask_price	float	The current ask price	required
ask_size	float	The current ask size	required

update_trade

update_trade(last_trade: float, trade_size: float) -> None

Updates this base data with a new trade

Parameters:

Name	Type	Description	Default
last_trade	float	The price of the last trade	required
trade_size	float	The quantity traded	required

get_meta_object

get_meta_object(parameter: Any) -> Any

Get the metaObject required for Dynamism.

get_property

get_property(name: str) -> Object

Gets the property's value with the specified name. This is a case-insensitve search.

Parameters:

Name	Type	Description	Default
name	str	The property name to access	required

Returns:

Type	Description
Object	object value of BaseData.

get_storage_dictionary

get_storage_dictionary() -> IDictionary[str, Object]

Gets the storage dictionary Python algorithms need this information since DynamicMetaObject does not work

Returns:

Type	Description
IDictionary[str, Object]	Dictionary that stores the paramenters names and values.

has_property

has_property(name: str) -> bool

Gets whether or not this dynamic data instance has a property with the specified name. This is a case-insensitve search.

Parameters:

Name	Type	Description	Default
name	str	The property name to check for	required

Returns:

Type	Description
bool	True if the property exists, false otherwise.

set_property

set_property(name: str, value: Any) -> Object

Sets the property with the specified name to the value. This is a case-insensitve search.

Parameters:

Name	Type	Description	Default
name	str	The property name to set	required
value	Any	The new property value	required

Returns:

Type	Description
Object	Returns the input value back to the caller.