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data ¤

BackTestDataFeed ¤

BackTestDataFeed(
    data: DataFrame,
    name: str,
    timeframe: str | int | Timedelta | None = None,
    meta: dict | None = None,
    since: int | str | Timestamp | None = None,
    to: int | str | Timestamp | None = None,
    **kwargs
)

Bases: DataFeed

BackTest DataFeed

Parameters:

  • data (DataFrame) –

    description

  • name (str) –

    description

  • timeframe (str | int | Timedelta | None, default: None ) –

    description. Defaults to None.

  • meta (dict | None, default: None ) –

    description. Defaults to None.

  • since (int | str | Timestamp | None, default: None ) –

    Drop data before since. Defaults to None.

  • to (int | str | Timestamp | None, default: None ) –

    Drop data after to. Defaults to None.

Source code in lettrade/exchange/backtest/data.py 
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def __init__(
    self,
    data: pd.DataFrame,
    name: str,
    timeframe: str | int | pd.Timedelta | None = None,
    meta: dict | None = None,
    since: int | str | pd.Timestamp | None = None,
    to: int | str | pd.Timestamp | None = None,
    **kwargs,
) -> None:
    """_summary_

    Args:
        data (pd.DataFrame): _description_
        name (str): _description_
        timeframe (str | int | pd.Timedelta | None, optional): _description_. Defaults to None.
        meta (dict | None, optional): _description_. Defaults to None.
        since (int | str | pd.Timestamp | None, optional): Drop data before since. Defaults to None.
        to (int | str | pd.Timestamp | None, optional): Drop data after to. Defaults to None.
    """
    if timeframe is None:
        timeframe = self._find_timeframe(data)
        logger.info("DataFeed %s auto detect timeframe %s", name, timeframe)
    super().__init__(
        data=data,
        name=name,
        timeframe=timeframe,
        meta=meta,
        **kwargs,
    )
    if since is not None or to is not None:
        self.drop(since=since, to=to)

i property ¤

i: indicator

Alias to lettrade.indicator and using in DataFeed by call: DataFeed.i.indicator_name()

is_main property ¤

is_main: bool

Property to check DataFeed is main DataFeed or not

l instance-attribute ¤

l: LetDataFeedWrapper

LetTrade DataFeed wrapper using to manage index pointer of DataFeed

meta property ¤

meta: dict

Property to get metadata of DataFeed

name property ¤

name: str

Property to get name of DataFeed

now property ¤

now: Timestamp

Property to get current index value of DataFeed

timeframe property ¤

timeframe: TimeFrame

Property to get timeframe of DataFeed

bar ¤

bar(i: int = 0) -> Timestamp

Get current pd.Timestamp value of DataFeed

Parameters:

  • i (int, default: 0 ) –

    Index. Defaults to 0.

Returns:

  • Timestamp –

    pd.Timestamp: description

Source code in lettrade/data/data.py 
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def bar(self, i: int = 0) -> pd.Timestamp:
    """Get current pd.Timestamp value of DataFeed

    Args:
        i (int, optional): Index. Defaults to 0.

    Returns:
        pd.Timestamp: _description_
    """
    return self.l.index[i]

copy ¤

copy(deep: bool = False, **kwargs) -> DataFeed

summary

Parameters:

  • deep (bool, default: False ) –

    description. Defaults to False.

Returns:

Source code in lettrade/data/data.py 
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def copy(self, deep: bool = False, **kwargs) -> "DataFeed":
    """_summary_

    Args:
        deep (bool, optional): _description_. Defaults to False.

    Returns:
        DataFeed: _description_
    """
    df = super().copy(deep=deep)
    df = self.__class__(
        data=df,
        name=self.name,
        timeframe=self.timeframe,
        meta=self.meta.copy(),
        **kwargs,
    )
    return df

drop ¤

drop(
    *args,
    since: int | str | Timestamp | None = None,
    to: int | str | Timestamp | None = None,
    **kwargs
) -> None

summary

Parameters:

  • since (int | str | Timestamp | None, default: None ) –

    description. Defaults to None.

  • to (int | str | Timestamp | None, default: None ) –

    description. Defaults to None.

Raises:

Source code in lettrade/data/data.py 
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def drop(
    self,
    *args,
    since: int | str | pd.Timestamp | None = None,
    to: int | str | pd.Timestamp | None = None,
    **kwargs,
) -> None:
    """_summary_

    Args:
        since (int | str | pd.Timestamp | None, optional): _description_. Defaults to None.
        to (int | str | pd.Timestamp | None, optional): _description_. Defaults to None.

    Raises:
        RuntimeError: _description_
    """
    if since is None and to is None:
        super().drop(*args, **kwargs)
        return

    condiction = None

    # Since
    if since is not None:
        if isinstance(since, int):
            loc = self.l.index[since]
        elif isinstance(since, str):
            loc = pd.to_datetime(since, utc=True)
        elif isinstance(since, pd.Timestamp):
            loc = since
        else:
            raise RuntimeError(f"DataFeed.drop since {since} is invalid")
        condiction = self.index < loc

    # To
    if to is not None:
        if isinstance(to, int):
            loc = self.l.index[to]
        elif isinstance(to, str):
            loc = pd.to_datetime(to, utc=True)
        elif isinstance(to, pd.Timestamp):
            loc = to
        else:
            raise RuntimeError(f"DataFeed.drop to {to} is invalid")

        if condiction is None:
            condiction = self.index > loc
        else:
            condiction = condiction | (self.index > loc)

    index = self[condiction].index
    super().drop(index=index, inplace=True)
    self.l.reset()

    if __debug__:
        logger.debug("BackTestDataFeed %s dropped %s rows", self.name, len(index))

push ¤

push(
    rows: list[list[int | float]],
    unit: str | None = None,
    utc: bool = True,
    **kwargs
)

Push new rows to DataFeed

Parameters:

  • rows (list[list[int | float]]) –

    list of rows [["timestamp", "open price", "high price"...]]

  • unit (str | None, default: None ) –

    pandas.Timestamp parsing unit. Defaults to None.

  • utc (bool, default: True ) –

    description. Defaults to True.

Source code in lettrade/data/data.py 
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def push(
    self,
    rows: list[list[int | float]],
    unit: str | None = None,
    utc: bool = True,
    **kwargs,
):
    """Push new rows to DataFeed

    Args:
        rows (list[list[int | float]]): list of rows `[["timestamp", "open price", "high price"...]]`
        unit (str | None, optional): pandas.Timestamp parsing unit. Defaults to None.
        utc (bool, optional): _description_. Defaults to True.
    """
    for row in rows:
        dt = pd.to_datetime(row[0], unit=unit, utc=utc, **kwargs)
        self.at[
            dt,
            (
                "open",
                "high",
                "low",
                "close",
                "volume",
            ),
        ] = (
            row[1],  # open
            row[2],  # high
            row[3],  # low
            row[4],  # close
            row[5],  # volume
        )

    if __debug__:
        logger.debug("[%s] Update bar: \n%s", self.name, self.tail(len(rows)))

CSVBackTestDataFeed ¤

CSVBackTestDataFeed(
    path: str | None = None,
    csv: dict | None = None,
    name: str | None = None,
    timeframe: str | int | Timedelta | None = None,
    meta: dict | None = None,
    data: DataFeed | None = None,
    **kwargs: dict
)

Bases: BackTestDataFeed

Implement help to load DataFeed from csv file

Parameters:

  • path (str | None, default: None ) –

    Path to csv file. Defaults to None.

  • csv (dict | None, default: None ) –

    Reflect of pandas.read_csv() parameters. Defaults to None.

  • name (str | None, default: None ) –

    description. Defaults to None.

  • timeframe (str | int | Timedelta | None, default: None ) –

    description. Defaults to None.

  • meta (dict | None, default: None ) –

    description. Defaults to None.

  • data (DataFeed | None, default: None ) –

    description. Defaults to None.

  • **kwargs (dict, default: {} ) –

    DataFeed dict parameters

Source code in lettrade/exchange/backtest/data.py 
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def __init__(
    self,
    path: str | None = None,
    csv: dict | None = None,
    name: str | None = None,
    timeframe: str | int | pd.Timedelta | None = None,
    meta: dict | None = None,
    data: DataFeed | None = None,
    **kwargs: dict,
) -> None:
    """_summary_

    Args:
        path (str | None, optional): Path to csv file. Defaults to None.
        csv (dict | None, optional): Reflect of `pandas.read_csv()` parameters. Defaults to None.
        name (str | None, optional): _description_. Defaults to None.
        timeframe (str | int | pd.Timedelta | None, optional): _description_. Defaults to None.
        meta (dict | None, optional): _description_. Defaults to None.
        data (DataFeed | None, optional): _description_. Defaults to None.
        **kwargs (dict): [DataFeed](../../data/data.md#lettrade.data.data.DataFeed) dict parameters
    """
    if name is None:
        name = _path_to_name(path)

    if data is None:
        csv_params = dict(
            index_col=0,
            parse_dates=["datetime"],
            delimiter=",",
            header=0,
        )
        if csv is not None:
            csv_params.update(**csv)

        data = pd.read_csv(path, **csv_params)

        if not isinstance(data.index, pd.DatetimeIndex):
            data.index = data.index.astype("datetime64[ns, UTC]")

    super().__init__(
        data=data,
        name=name,
        timeframe=timeframe,
        meta=meta,
        **kwargs,
    )

i property ¤

i: indicator

Alias to lettrade.indicator and using in DataFeed by call: DataFeed.i.indicator_name()

is_main property ¤

is_main: bool

Property to check DataFeed is main DataFeed or not

l instance-attribute ¤

l: LetDataFeedWrapper

LetTrade DataFeed wrapper using to manage index pointer of DataFeed

meta property ¤

meta: dict

Property to get metadata of DataFeed

name property ¤

name: str

Property to get name of DataFeed

now property ¤

now: Timestamp

Property to get current index value of DataFeed

timeframe property ¤

timeframe: TimeFrame

Property to get timeframe of DataFeed

bar ¤

bar(i: int = 0) -> Timestamp

Get current pd.Timestamp value of DataFeed

Parameters:

  • i (int, default: 0 ) –

    Index. Defaults to 0.

Returns:

  • Timestamp –

    pd.Timestamp: description

Source code in lettrade/data/data.py 
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def bar(self, i: int = 0) -> pd.Timestamp:
    """Get current pd.Timestamp value of DataFeed

    Args:
        i (int, optional): Index. Defaults to 0.

    Returns:
        pd.Timestamp: _description_
    """
    return self.l.index[i]

copy ¤

copy(deep: bool = False, **kwargs) -> DataFeed

summary

Parameters:

  • deep (bool, default: False ) –

    description. Defaults to False.

Returns:

Source code in lettrade/data/data.py 
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def copy(self, deep: bool = False, **kwargs) -> "DataFeed":
    """_summary_

    Args:
        deep (bool, optional): _description_. Defaults to False.

    Returns:
        DataFeed: _description_
    """
    df = super().copy(deep=deep)
    df = self.__class__(
        data=df,
        name=self.name,
        timeframe=self.timeframe,
        meta=self.meta.copy(),
        **kwargs,
    )
    return df

drop ¤

drop(
    *args,
    since: int | str | Timestamp | None = None,
    to: int | str | Timestamp | None = None,
    **kwargs
) -> None

summary

Parameters:

  • since (int | str | Timestamp | None, default: None ) –

    description. Defaults to None.

  • to (int | str | Timestamp | None, default: None ) –

    description. Defaults to None.

Raises:

Source code in lettrade/data/data.py 
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def drop(
    self,
    *args,
    since: int | str | pd.Timestamp | None = None,
    to: int | str | pd.Timestamp | None = None,
    **kwargs,
) -> None:
    """_summary_

    Args:
        since (int | str | pd.Timestamp | None, optional): _description_. Defaults to None.
        to (int | str | pd.Timestamp | None, optional): _description_. Defaults to None.

    Raises:
        RuntimeError: _description_
    """
    if since is None and to is None:
        super().drop(*args, **kwargs)
        return

    condiction = None

    # Since
    if since is not None:
        if isinstance(since, int):
            loc = self.l.index[since]
        elif isinstance(since, str):
            loc = pd.to_datetime(since, utc=True)
        elif isinstance(since, pd.Timestamp):
            loc = since
        else:
            raise RuntimeError(f"DataFeed.drop since {since} is invalid")
        condiction = self.index < loc

    # To
    if to is not None:
        if isinstance(to, int):
            loc = self.l.index[to]
        elif isinstance(to, str):
            loc = pd.to_datetime(to, utc=True)
        elif isinstance(to, pd.Timestamp):
            loc = to
        else:
            raise RuntimeError(f"DataFeed.drop to {to} is invalid")

        if condiction is None:
            condiction = self.index > loc
        else:
            condiction = condiction | (self.index > loc)

    index = self[condiction].index
    super().drop(index=index, inplace=True)
    self.l.reset()

    if __debug__:
        logger.debug("BackTestDataFeed %s dropped %s rows", self.name, len(index))

push ¤

push(
    rows: list[list[int | float]],
    unit: str | None = None,
    utc: bool = True,
    **kwargs
)

Push new rows to DataFeed

Parameters:

  • rows (list[list[int | float]]) –

    list of rows [["timestamp", "open price", "high price"...]]

  • unit (str | None, default: None ) –

    pandas.Timestamp parsing unit. Defaults to None.

  • utc (bool, default: True ) –

    description. Defaults to True.

Source code in lettrade/data/data.py 
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def push(
    self,
    rows: list[list[int | float]],
    unit: str | None = None,
    utc: bool = True,
    **kwargs,
):
    """Push new rows to DataFeed

    Args:
        rows (list[list[int | float]]): list of rows `[["timestamp", "open price", "high price"...]]`
        unit (str | None, optional): pandas.Timestamp parsing unit. Defaults to None.
        utc (bool, optional): _description_. Defaults to True.
    """
    for row in rows:
        dt = pd.to_datetime(row[0], unit=unit, utc=utc, **kwargs)
        self.at[
            dt,
            (
                "open",
                "high",
                "low",
                "close",
                "volume",
            ),
        ] = (
            row[1],  # open
            row[2],  # high
            row[3],  # low
            row[4],  # close
            row[5],  # volume
        )

    if __debug__:
        logger.debug("[%s] Update bar: \n%s", self.name, self.tail(len(rows)))

YFBackTestDataFeed ¤

YFBackTestDataFeed(
    name: str,
    ticker: str,
    since: str,
    to: str | None = None,
    period: str | None = None,
    interval: str = "1d",
    **kwargs
)

Bases: BackTestDataFeed

YahooFinance DataFeed

Parameters:

  • name (str) –

    description

  • ticker (str) –

    description

  • since (str) –

    description

  • to (str | None, default: None ) –

    description. Defaults to None.

  • period (str | None, default: None ) –

    description. Defaults to None.

  • interval (str, default: '1d' ) –

    description. Defaults to "1d".

Source code in lettrade/exchange/backtest/data.py 
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def __init__(
    self,
    name: str,
    ticker: str,
    since: str,
    to: str | None = None,
    period: str | None = None,
    interval: str = "1d",
    **kwargs,
) -> None:
    """_summary_

    Args:
        name (str): _description_
        ticker (str): _description_
        since (str): _description_
        to (str | None, optional): _description_. Defaults to None.
        period (str | None, optional): _description_. Defaults to None.
        interval (str, optional): _description_. Defaults to "1d".
    """
    params = dict(
        start=since,
        end=to,
        period=period,
        interval=interval,
    )

    # Download
    import yfinance as yf

    df = yf.download(ticker, **params)

    # Parse to lettrade datafeed
    from .extra.yfinance import yf_parse

    df = yf_parse(df)

    # Metadata
    meta = dict(yf=dict(ticker=ticker, **params))

    super().__init__(
        name=name,
        meta=meta,
        data=df,
        **kwargs,
    )

i property ¤

i: indicator

Alias to lettrade.indicator and using in DataFeed by call: DataFeed.i.indicator_name()

is_main property ¤

is_main: bool

Property to check DataFeed is main DataFeed or not

l instance-attribute ¤

l: LetDataFeedWrapper

LetTrade DataFeed wrapper using to manage index pointer of DataFeed

meta property ¤

meta: dict

Property to get metadata of DataFeed

name property ¤

name: str

Property to get name of DataFeed

now property ¤

now: Timestamp

Property to get current index value of DataFeed

timeframe property ¤

timeframe: TimeFrame

Property to get timeframe of DataFeed

bar ¤

bar(i: int = 0) -> Timestamp

Get current pd.Timestamp value of DataFeed

Parameters:

  • i (int, default: 0 ) –

    Index. Defaults to 0.

Returns:

  • Timestamp –

    pd.Timestamp: description

Source code in lettrade/data/data.py 
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def bar(self, i: int = 0) -> pd.Timestamp:
    """Get current pd.Timestamp value of DataFeed

    Args:
        i (int, optional): Index. Defaults to 0.

    Returns:
        pd.Timestamp: _description_
    """
    return self.l.index[i]

copy ¤

copy(deep: bool = False, **kwargs) -> DataFeed

summary

Parameters:

  • deep (bool, default: False ) –

    description. Defaults to False.

Returns:

Source code in lettrade/data/data.py 
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def copy(self, deep: bool = False, **kwargs) -> "DataFeed":
    """_summary_

    Args:
        deep (bool, optional): _description_. Defaults to False.

    Returns:
        DataFeed: _description_
    """
    df = super().copy(deep=deep)
    df = self.__class__(
        data=df,
        name=self.name,
        timeframe=self.timeframe,
        meta=self.meta.copy(),
        **kwargs,
    )
    return df

drop ¤

drop(
    *args,
    since: int | str | Timestamp | None = None,
    to: int | str | Timestamp | None = None,
    **kwargs
) -> None

summary

Parameters:

  • since (int | str | Timestamp | None, default: None ) –

    description. Defaults to None.

  • to (int | str | Timestamp | None, default: None ) –

    description. Defaults to None.

Raises:

Source code in lettrade/data/data.py 
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def drop(
    self,
    *args,
    since: int | str | pd.Timestamp | None = None,
    to: int | str | pd.Timestamp | None = None,
    **kwargs,
) -> None:
    """_summary_

    Args:
        since (int | str | pd.Timestamp | None, optional): _description_. Defaults to None.
        to (int | str | pd.Timestamp | None, optional): _description_. Defaults to None.

    Raises:
        RuntimeError: _description_
    """
    if since is None and to is None:
        super().drop(*args, **kwargs)
        return

    condiction = None

    # Since
    if since is not None:
        if isinstance(since, int):
            loc = self.l.index[since]
        elif isinstance(since, str):
            loc = pd.to_datetime(since, utc=True)
        elif isinstance(since, pd.Timestamp):
            loc = since
        else:
            raise RuntimeError(f"DataFeed.drop since {since} is invalid")
        condiction = self.index < loc

    # To
    if to is not None:
        if isinstance(to, int):
            loc = self.l.index[to]
        elif isinstance(to, str):
            loc = pd.to_datetime(to, utc=True)
        elif isinstance(to, pd.Timestamp):
            loc = to
        else:
            raise RuntimeError(f"DataFeed.drop to {to} is invalid")

        if condiction is None:
            condiction = self.index > loc
        else:
            condiction = condiction | (self.index > loc)

    index = self[condiction].index
    super().drop(index=index, inplace=True)
    self.l.reset()

    if __debug__:
        logger.debug("BackTestDataFeed %s dropped %s rows", self.name, len(index))

push ¤

push(
    rows: list[list[int | float]],
    unit: str | None = None,
    utc: bool = True,
    **kwargs
)

Push new rows to DataFeed

Parameters:

  • rows (list[list[int | float]]) –

    list of rows [["timestamp", "open price", "high price"...]]

  • unit (str | None, default: None ) –

    pandas.Timestamp parsing unit. Defaults to None.

  • utc (bool, default: True ) –

    description. Defaults to True.

Source code in lettrade/data/data.py 
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def push(
    self,
    rows: list[list[int | float]],
    unit: str | None = None,
    utc: bool = True,
    **kwargs,
):
    """Push new rows to DataFeed

    Args:
        rows (list[list[int | float]]): list of rows `[["timestamp", "open price", "high price"...]]`
        unit (str | None, optional): pandas.Timestamp parsing unit. Defaults to None.
        utc (bool, optional): _description_. Defaults to True.
    """
    for row in rows:
        dt = pd.to_datetime(row[0], unit=unit, utc=utc, **kwargs)
        self.at[
            dt,
            (
                "open",
                "high",
                "low",
                "close",
                "volume",
            ),
        ] = (
            row[1],  # open
            row[2],  # high
            row[3],  # low
            row[4],  # close
            row[5],  # volume
        )

    if __debug__:
        logger.debug("[%s] Update bar: \n%s", self.name, self.tail(len(rows)))