converting pinescript indicators

[A Former User]

Hi

I have worked on converting a Pinescript indicator to backtrader.

I will describe some findings in the process, give some tips, show a example and so on.

variables
in pinescript, variables seem to work like lines in backtrader. So for every variable used in the script I have added a line:

pinescript:

setupCountUp = na

backtrader ind.__init__:

self.setup_sell = bt.LineNum(float('nan'))

conditions
to use methods like barssince, valuewhen from pinescript, which allows conditions like: setupCountUp == self.p.setup_bars the easiest method I found is to use numpy for this.

1. convert a line to a numpy array (using get(size=SIZE) to not work on complete line but only a defined range of data)

def line2arr(line, size=-1):
    if size <= 0:
        return np.array(line.array)
    else:
        return np.array(line.get(size=size))

2. provide methods which works as methods from pinescript: so I wrote the methods I needed.

def na(val):
    return val != val

def nz(x, y=None):
    if isinstance(x, np.generic):
        return x.fillna(y or 0)
    if x != x:
        if y is not None:
            return y
        return 0
    return x

def barssince(condition, occurrence=0):
    cond_len = len(condition)
    occ = 0
    since = 0
    res = float('nan')
    while cond_len - (since+1) >= 0:
        cond = condition[cond_len-(since+1)]
        if cond and not cond != cond:
            if occ == occurrence:
                res = since
                break
            occ += 1
        since += 1
    return res

def valuewhen(condition, source, occurrence=0):
    res = float('nan')
    since = barssince(condition, occurrence)
    if since is not None:
        res = source[-(since+1)]
    return res

rewriting

the process of rewriting the pinescript in python using backtrader was simple after this. basically it can be split up to:

1. look for vars, params, signals used in pinescript
2. define vars, params, signal in indicator
3. strip all plot related code from pinescript
4. rewrite pinescript code in indicators next method

plotting

since i only want to have signals as lines in indicator, I did not set all vars used in pinescript in the lines dict, but in init. So I had a better control of what the indicator is plotting. But the indicator had more values then just the signals, so how to handle them?
The solution was a observer, which takes care of plotting all other information, the indicator has. Here you can setup all the plot related code from pinescript.

some remaining issues

maybe some of you guys know answers for this:

Questions:

• is it possible to create lines with conditions (outside of __init__) like: self.line1 > val ?
• is there a way to get something like barssince, valuewhen natively in backtrader?

Issues:

• the code is not very good, since a lot of the code can be done better in python, but if you don't want to fiddle to much with it, this should be fine
• refactoring would make the code better readable

I hope, this will help some of you!
I will post the code of a indicator, observer and the pinescript methods in a next post below.

[A Former User]

below there is code for the indicator from:
https://www.tradingview.com/script/t08BkTIg-TD-Sequential/

[A Former User]

pinescript.py

import numpy as np


def line2arr(line, size=-1):
    '''
    Creates an numpy array from a backtrader line

    This method wraps the lines array in numpy. This can
    be used for conditions.
    '''
    if size <= 0:
        return np.array(line.array)
    else:
        return np.array(line.get(size=size))


def na(val):
    '''
    RETURNS
    true if x is not a valid number (x is NaN), otherwise false.
    '''
    return val != val


def nz(x, y=None):
    '''
    RETURNS
    Two args version: returns x if it's a valid (not NaN) number, otherwise y
    One arg version: returns x if it's a valid (not NaN) number, otherwise 0
    ARGUMENTS
    x (val) Series of values to process.
    y (float) Value that will be inserted instead of all NaN values in x series.
    '''
    if isinstance(x, np.generic):
        return x.fillna(y or 0)
    if x != x:
        if y is not None:
            return y
        return 0
    return x


def barssince(condition, occurrence=0):
    '''
    Impl of barssince

    RETURNS
    Number of bars since condition was true.
    REMARKS
    If the condition has never been met prior to the current bar, the function returns na.
    '''
    cond_len = len(condition)
    occ = 0
    since = 0
    res = float('nan')
    while cond_len - (since+1) >= 0:
        cond = condition[cond_len-(since+1)]
        # check for nan cond != cond == True when nan
        if cond and not cond != cond:
            if occ == occurrence:
                res = since
                break
            occ += 1
        since += 1
    return res


def valuewhen(condition, source, occurrence=0):
    '''
    Impl of valuewhen
    + added occurrence

    RETURNS
    Source value when condition was true
    '''
    res = float('nan')
    since = barssince(condition, occurrence)
    if since is not None:
        res = source[-(since+1)]
    return res

[A Former User]

indicator.py

import backtrader as bt
from utils.pinescript import line2arr, barssince, valuewhen, na, nz


class TDSequentialInd(bt.Indicator):

    '''
    TD Sequential

    This indicator implements a flexible rendition of TD Sequentials
    Reference: DeMark Indicators by Jason Perl

    based on:
    https://www.tradingview.com/script/t08BkTIg-TD-Sequential/
    http://practicaltechnicalanalysis.blogspot.com/2013/01/tom-demark-sequential.html


    TD Indicators:
    - TD Price Flips (setup_count_up/setup_count_down = 1)
    - TD Setup count up (self.setup_count_up)
    - TD Setup count down (self.setup_count_down)
    - TD Sell Setup (self.setup_sell: price, self.l.setup_sell: signal)
    - TD Sell Setup perfected (self.setup_sell_perf: price, self.l.setup_sell_perf: signal), can be deferred
    - TD Buy Setup (self.setup_buy: price, self.l.setup_buy: signal)
    - TD Buy Setup perfected (self.setup_buy_perf: price, self.l.setup_buy_perf: signal), can be deferred
    - TD Setup Trend support (self.setup_trend_support)
    - TD Setup Trend resistance (self.setup_trend_resistance)
    - TD Countdown up (self.countdown_up)
    - TD Countdown down (self.countdown_down)
    - TD Sell Countdown qualify bar (self.countdown_count_up_imp == self.p.countdown_qual_bar)
    - TD Sell Countdown deferred (self.countdown_sell_defer: price, self.l.countdown_sell_defer: signal)
    - TD Sell Countdown (self.countdown_sell: price, self.l.countdown_sell: signal)
    - TD Buy Countdown qualify bar (self.countdown_count_down_imp == self.p.countdown_qual_bar)
    - TD Buy Countdown deferred (self.countdown_buy_defer: price, self.l.countdown_buy_defer: signal)
    - TD Buy Countdown (self.countdown_buy: price, self.l.countdown_buy: signal)
    - TD Countdown Recycling (self.countdown_count_up_recycle: price, self.l.countdown_count_up_recycle: signal,
                             self.countdown_count_down_recycle: price, self.l.countdown_count_down_recycle: signal)
        Note: Only one aspect of recycling is implemented where,
            if Setup Up/Down Count == 2 * 'Setup: Bars', then the
            present Countdown is cancelled.
            Trend momentum has intensified.
    - TD Risk Level (self.risk_level)
    '''

    DATA_CANDLES = 200  # use up to 200 candles for analysis

    '''
    setupIsPerfected = 2
    setupIsDeferred = 1
    '''
    SETUP_IS_PERFECTED = 2
    SETUP_IS_DEFERRED = 1
    '''
    cntdwnIsQualified = 2
    cntdwnIsDeferred = 1
    '''
    COUNTDOWN_IS_QUALIFIED = 2
    COUNTDOWN_IS_DEFERRED = 1

    plotinfo = dict(subplot=True)

    lines = (
        'setup_sell',                   # sell setup
        'setup_buy',                    # buy setup
        'setup_sell_perf',              # sell setup perfected
        'setup_buy_perf',               # buy setup perfected
        'countdown_sell',               # sell countdown
        'countdown_buy',                # buy countdown
        'countdown_sell_defer',
        'countdown_buy_defer',
        'countdown_count_up_recycle',
        'countdown_count_down_recycle',
    )

    params = dict(
        # data source to use, either close, hgih or low (Default: close)
        data_source='close',
        # the last Setup count (traditionally 9).
        setup_bars=9,
        # defines the previous bar to compare for counting (traditionally 4).
        setup_lookback_bars=4,
        # defines the previous count to evaluate for a perfected setup
        # (this count and the next). Traditionally 3, i.e compare
        # count 6 and 7 to count 8 or count 9.
        setup_perf_lookback=3,
        # If enabled, allow >= or <= in price comparisons.
        setup_equal_enable=False,
        # If disabled, only look back to the beginning of
        # this Buy/Sell Setup event
        # to find trends, low(support for Sell) or high(resistance for Buy)
        # If enabled, look back beyond this Buy/Sell Setup event to
        # the previous Setup event of the same kind.
        setup_trend_extend=False,
        # the last Countdown count (traditionally 13).
        # Called the Buy/Sell Countdown event in this code, i.e. the
        # last up/down count becomes the Buy/Sell Countdown event.
        countdown_bars=13,
        # define previous bar to compare for counting (traditionally 2).
        countdown_lookback_bars=2,
        # the bar in the Countdown sequence used to qualifiy the price
        # of the Buy/Sell Countdown event(traditionally 8).
        # If a countdown event doesn't qualify, counting continues.
        # Note: If the Qualifier Bar is set >= "countdown_lookback_bars",
        # qualification is disabled. Countdown events are still
        # determined, just not qualified.
        countdown_qual_bar=8,
        # Use aggressive comparison. E.g. for Sell Countdown,
        # instead of "Price: Source" >= high of "countdown_lookback_bars",
        # use high >= high of "countdown_lookback_bars". Disabled by default.
        countdown_aggressive=False,
    )

    def __init__(self):
        super().__init__()
        self.addminperiod(self.p.setup_lookback_bars + 1)

        # data source to use
        if self.p.data_source == 'high':
            self.source = self.data_high
        elif self.p.data_source == 'low':
            self.source = self.data_low
        else:
            self.source = self.data_close

        # setup prices
        self.setup_price_up = (
            self.source(0) > self.source(-self.p.setup_lookback_bars))
        self.setup_price_down = (
            self.source(0) < self.source(-self.p.setup_lookback_bars))
        self.setup_price_equal = (
            self.source(0) == self.source(-self.p.setup_lookback_bars))

        # countdown prices
        if self.p.countdown_aggressive:
            self.countdown_price_up = (
                self.data_high(0)
                >= self.data_high(-self.p.countdown_lookback_bars))
            self.countdown_price_down = (
                self.data_low(0)
                <= self.data_low(-self.p.countdown_lookback_bars))
        else:
            self.countdown_price_up = (
                self.source(0)
                >= self.data_high(-self.p.countdown_lookback_bars))
            self.countdown_price_down = (
                self.source(0)
                <= self.data_low(-self.p.countdown_lookback_bars))

        # indicators
        self.tr = bt.ind.TrueRange()

        # values
        self.setup_sell = bt.LineNum(float('nan'))
        self.setup_buy = bt.LineNum(float('nan'))
        self.setup_count_up = bt.LineNum(float('nan'))
        self.setup_count_down = bt.LineNum(float('nan'))
        self.setup_sell_perf_price = bt.LineNum(float('nan'))
        self.setup_sell_perf_mask = bt.LineNum(float('nan'))
        self.setup_sell_perf = bt.LineNum(float('nan'))
        self.setup_buy_perf_price = bt.LineNum(float('nan'))
        self.setup_buy_perf_mask = bt.LineNum(float('nan'))
        self.setup_buy_perf = bt.LineNum(float('nan'))
        self.setup_sell_count = bt.LineNum(float('nan'))
        self.setup_buy_count = bt.LineNum(float('nan'))
        self.setup_trend_support = bt.LineNum(float('nan'))
        self.setup_trend_resistance = bt.LineNum(float('nan'))
        self.countdown_count_up = bt.LineNum(float('nan'))
        self.countdown_count_down = bt.LineNum(float('nan'))
        self.countdown_count_up_imp = bt.LineNum(float('nan'))
        self.countdown_count_down_imp = bt.LineNum(float('nan'))
        self.countdown_count_up_recycle = bt.LineNum(float('nan'))
        self.countdown_count_down_recycle = bt.LineNum(float('nan'))
        self.countdown_sell = bt.LineNum(float('nan'))
        self.countdown_sell_defer = bt.LineNum(float('nan'))
        self.countdown_sell_qual_price = bt.LineNum(float('nan'))
        self.countdown_sell_qual_mask = bt.LineNum(float('nan'))
        self.countdown_sell_qual_mask_imp = bt.LineNum(float('nan'))
        self.countdown_buy = bt.LineNum(float('nan'))
        self.countdown_buy_defer = bt.LineNum(float('nan'))
        self.countdown_buy_qual_price = bt.LineNum(float('nan'))
        self.countdown_buy_qual_mask = bt.LineNum(float('nan'))
        self.countdown_buy_qual_mask_imp = bt.LineNum(float('nan'))
        self.risk_level = bt.LineNum(float('nan'))

    def next(self):

        #
        # ---- TD Setups ----------------------------
        #

        if self.p.setup_equal_enable:
            if (self.setup_price_up[0]
                or (self.setup_count_up[-1]
                    and self.setup_price_equal[0])):
                self.setup_count_up[0] = nz(self.setup_count_up[-1]) + 1
            if (self.setup_price_down[0]
                or (self.setup_count_down[-1]
                    and self.setup_price_equal[0])):
                self.setup_count_down[0] = nz(self.setup_count_down[-1]) + 1
        else:
            if self.setup_price_up[0]:
                self.setup_count_up[0] = nz(self.setup_count_up[-1]) + 1
            if self.setup_price_down[0]:
                self.setup_count_down[0] = nz(self.setup_count_down[-1]) + 1

        if self.setup_count_up[0] == self.p.setup_bars:
            setupCountUp = line2arr(self.setup_count_up, self.DATA_CANDLES)
            priceSource = line2arr(self.source, self.DATA_CANDLES)
            self.setup_sell[0] = valuewhen(
                setupCountUp == self.p.setup_bars,
                priceSource,
                0)

        if self.setup_count_down[0] == self.p.setup_bars:
            setupCountDown = line2arr(self.setup_count_down, self.DATA_CANDLES)
            priceSource = line2arr(self.source, self.DATA_CANDLES)
            self.setup_buy[0] = valuewhen(
                setupCountDown == self.p.setup_bars,
                priceSource,
                0)

        self.setup_sell_count[0] = barssince(
            line2arr(self.setup_sell, self.DATA_CANDLES))
        self.setup_buy_count[0] = barssince(
            line2arr(self.setup_buy, self.DATA_CANDLES))
        if self.setup_count_up[0] == self.p.setup_bars:
            val = None
            setupCountUp = line2arr(self.setup_count_up, self.DATA_CANDLES)
            high = line2arr(self.data.high, self.DATA_CANDLES)
            cond1 = valuewhen(
                setupCountUp == (self.p.setup_bars
                                 - self.p.setup_perf_lookback),
                high, 0)
            cond2 = valuewhen(
                setupCountUp == (self.p.setup_bars
                                 - self.p.setup_perf_lookback + 1),
                high, 0)
            if (cond1 >= cond2):
                val = cond1
            else:
                val = cond2
            self.setup_sell_perf_price[0] = val
        else:
            self.setup_sell_perf_price[0] = nz(self.setup_sell_perf_price[-1])

        if self.setup_count_down[0] == self.p.setup_bars:
            val = None
            setupCountDown = line2arr(self.setup_count_down, self.DATA_CANDLES)
            low = line2arr(self.data.high, self.DATA_CANDLES)
            cond1 = valuewhen(
                setupCountDown == (self.p.setup_bars
                                   - self.p.setup_perf_lookback),
                low, 0)
            cond2 = valuewhen(
                setupCountDown == (self.p.setup_bars
                                   - self.p.setup_perf_lookback + 1),
                low, 0)
            if cond1 >= cond2:
                val = cond1
            else:
                val = cond2
            self.setup_buy_perf_price[0] = val
        else:
            self.setup_buy_perf_price[0] = nz(self.setup_buy_perf_price[-1])

        if not (nz(self.setup_sell_perf_mask[-1])
                >= self.SETUP_IS_PERFECTED or (not na(self.setup_buy[0]))):
            val = None
            if self.setup_count_up[0] == self.p.setup_bars:
                high = line2arr(self.data_high, self.DATA_CANDLES)
                setupCountUp = line2arr(
                    self.setup_count_up, self.DATA_CANDLES)
                if (
                    (valuewhen(setupCountUp == (self.p.setup_bars-1), high, 0)
                        >= self.setup_sell_perf_price[0])
                    or (valuewhen(setupCountUp == self.p.setup_bars, high, 0)
                        >= self.setup_sell_perf_price[0])):
                    val = self.SETUP_IS_PERFECTED
                else:
                    val = self.SETUP_IS_DEFERRED
            elif not na(self.setup_sell_perf_mask[-1]):
                if self.data_high[0] >= self.setup_sell_perf_price[0]:
                    val = self.SETUP_IS_PERFECTED
                else:
                    val = self.setup_sell_perf_mask[-1]
            if val is not None:
                self.setup_sell_perf_mask[0] = val

        if not (nz(self.setup_buy_perf_mask[-1])
                >= self.SETUP_IS_PERFECTED or (not na(self.setup_sell[0]))):
            val = None
            if self.setup_count_down[0] == self.p.setup_bars:
                low = line2arr(self.data_low, self.DATA_CANDLES)
                setupCountDown = line2arr(
                    self.setup_count_down, self.DATA_CANDLES)
                if (
                    (valuewhen(setupCountDown == (self.p.setup_bars-1), low, 0)
                        <= self.setup_buy_perf_price[0]) or
                    (valuewhen(setupCountDown == self.p.setup_bars, low, 0)
                        <= self.setup_buy_perf_price[0])):
                    val = self.SETUP_IS_PERFECTED
                else:
                    val = self.SETUP_IS_DEFERRED
            elif not na(self.setup_sell_perf_mask[-1]):
                if self.data_low[0] >= self.setup_sell_perf_price[0]:
                    val = self.SETUP_IS_PERFECTED
                else:
                    val = self.setup_buy_perf_mask[-1]
            if val is not None:
                self.setup_buy_perf_mask[0] = val

        if self.setup_sell_perf_mask[0] == self.SETUP_IS_PERFECTED:
            self.setup_sell_perf[0] = self.source[0]
        if self.setup_buy_perf_mask[0] == self.SETUP_IS_PERFECTED:
            self.setup_buy_perf[0] = self.source[0]
        if self.setup_sell[0]:
            if self.p.setup_trend_extend and self.setup_sell_count[-1] > 0:
                extend = int((
                    ((self.setup_sell_count[-1]
                      - (self.setup_sell_count[-1] % self.p.setup_bars))
                     / self.p.setup_bars)
                    + 1) * self.p.setup_bars)
                self.setup_trend_support[0] = min(
                    self.data_low.get(size=extend))
            else:
                self.setup_trend_support[0] = min(
                    self.data_low.get(size=self.p.setup_bars))
        else:
            self.setup_trend_support[0] = nz(self.setup_trend_support[-1])

        if self.setup_buy[0]:
            if self.p.setup_trend_extend and self.setup_buy_count[-1] > 0:
                extend = int((
                    ((self.setup_buy_count[-1]
                      - (self.setup_buy_count[-1] % self.p.setup_bars))
                     / self.p.setup_bars)
                    + 1) * self.p.setup_bars)
                self.setup_trend_resistance[0] = max(
                    self.data_high.get(size=extend))
            else:
                self.setup_trend_resistance[0] = max(
                    self.data_high.get(size=self.p.setup_bars))
        else:
            self.setup_trend_resistance[0] = nz(self.setup_trend_resistance[-1])

        if self.setup_count_up[0] == (2 * self.p.setup_bars):
            setupCountUp = line2arr(self.setup_count_up, self.DATA_CANDLES)
            priceSource = line2arr(self.source, self.DATA_CANDLES)
            self.countdown_count_up_recycle[0] = (
                valuewhen(
                    (setupCountUp == (2 * self.p.setup_bars)),
                    priceSource,
                    0)
            )
        if self.setup_count_down[0] == (2 * self.p.setup_bars):
            setupCountDown = line2arr(self.setup_count_down, self.DATA_CANDLES)
            priceSource = line2arr(self.source, self.DATA_CANDLES)
            self.countdown_count_down_recycle[0] = (
                valuewhen(
                    (setupCountDown == (2 * self.p.setup_bars)),
                    priceSource,
                    0)
            )

        if na(self.countdown_price_up[0]):
            self.countdown_count_up[0] = self.countdown_count_up[-1]
        else:
            val = None
            if not (
                    (not na(self.setup_buy[0])
                        or (self.source[0] < self.setup_trend_support[0]))
                    or (not na(self.countdown_count_up_recycle[0]))):
                if not na(self.setup_sell[0]):
                    if self.countdown_price_up[0]:
                        val = 1
                    else:
                        val = 0
                elif not na(self.countdown_count_up[-1]):
                    if self.countdown_price_up[0]:
                        val = self.countdown_count_up[-1] + 1
                    else:
                        val = self.countdown_count_up[-1]
            if val is not None:
                self.countdown_count_up[0] = val
        if na(self.countdown_price_down[0]):
            self.countdown_count_down[0] = self.countdown_count_down[-1]
        else:
            val = None
            if not (
                    (not na(self.setup_sell[0])
                        or (self.source[0] > self.setup_trend_resistance[0]))
                    or (not na(self.countdown_count_down_recycle[0]))):
                if not na(self.setup_buy[0]):
                    if self.countdown_price_down[0]:
                        val = 1
                    else:
                        val = 0
                elif not na(self.countdown_count_down[-1]):
                    if self.countdown_price_down[0]:
                        val = self.countdown_count_down[-1] + 1
                    else:
                        val = self.countdown_count_down[-1]
            if val is not None:
                self.countdown_count_down[0] = val

        if self.countdown_price_up[0]:
            self.countdown_count_up_imp[0] = self.countdown_count_up[0]
        if self.countdown_price_down[0]:
            self.countdown_count_down_imp[0] = self.countdown_count_down[0]
    
        if self.p.countdown_qual_bar < self.p.countdown_bars:

            if self.countdown_count_up_imp[0] == self.p.countdown_qual_bar:
                cntdwnCountUpImp = line2arr(
                    self.countdown_count_up_imp,
                    self.DATA_CANDLES)
                priceSource = line2arr(
                    self.source,
                    self.DATA_CANDLES)
                self.countdown_sell_qual_price[0] = valuewhen(
                    cntdwnCountUpImp == self.p.countdown_qual_bar,
                    priceSource,
                    0)
            else:
                self.countdown_sell_qual_price[0] = self.countdown_sell_qual_price[-1]

            if self.countdown_count_down_imp[0] == self.p.countdown_qual_bar:
                cntdwnCountDownImp = line2arr(
                    self.countdown_count_down_imp,
                    self.DATA_CANDLES)
                priceSource = line2arr(
                    self.source,
                    self.DATA_CANDLES)
                self.countdown_buy_qual_price[0] = valuewhen(
                    cntdwnCountDownImp == self.p.countdown_qual_bar,
                    priceSource,
                    0)
            else:
                self.countdown_buy_qual_price[0] = self.countdown_buy_qual_price[-1]

            if not ((nz(self.countdown_sell_qual_mask[-1])
                     >= self.COUNTDOWN_IS_QUALIFIED)
                    or na(self.countdown_count_up[-1])):
                val = None
                cntdwnCountUpImp = line2arr(
                    self.countdown_count_up_imp, self.DATA_CANDLES)
                high = line2arr(self.data_high, self.DATA_CANDLES)
                if self.countdown_count_up_imp[0] == self.p.countdown_bars:
                    if (valuewhen(
                            cntdwnCountUpImp == self.p.countdown_bars,
                            high,
                            0)) >= self.countdown_sell_qual_price[0]:
                        val = self.COUNTDOWN_IS_QUALIFIED
                    else:
                        val = self.COUNTDOWN_IS_DEFERRED
                elif not na(self.countdown_sell_qual_mask[-1]):
                    if self.countdown_count_up_imp[0] > self.p.countdown_bars:
                        if (valuewhen(
                                cntdwnCountUpImp > self.p.countdown_bars,
                                high,
                                0)) >= self.countdown_sell_qual_price[0]:
                            val = self.COUNTDOWN_IS_QUALIFIED
                        else:
                            val = self.countdown_sell_qual_mask[-1]
                    else:
                        val = self.countdown_sell_qual_mask[-1]
                if val is not None:
                    self.countdown_sell_qual_mask[0] = val

            if not ((nz(self.countdown_buy_qual_mask[-1])
                     >= self.COUNTDOWN_IS_QUALIFIED)
                    or na(self.countdown_count_down[-1])):
                val = None
                cntdwnCountDownImp = line2arr(
                    self.countdown_count_down_imp, self.DATA_CANDLES)
                low = line2arr(self.data_low, self.DATA_CANDLES)
                if self.countdown_count_down_imp[0] == self.p.countdown_bars:
                    if (valuewhen(
                            cntdwnCountDownImp == self.p.countdown_bars,
                            low,
                            0)) <= self.countdown_buy_qual_price[0]:
                        val = self.COUNTDOWN_IS_QUALIFIED
                    else:
                        val = self.COUNTDOWN_IS_DEFERRED
                elif not na(self.countdown_buy_qual_mask[-1]):
                    if self.countdown_count_down_imp[0] > self.p.countdown_bars:
                        if (valuewhen(
                                cntdwnCountDownImp > self.p.countdown_bars,
                                low,
                                0)) <= self.countdown_buy_qual_price[0]:
                            val = self.COUNTDOWN_IS_QUALIFIED
                        else:
                            val = self.countdown_buy_qual_mask[-1]
                    else:
                        val = self.countdown_buy_qual_mask[-1]
                if val is not None:
                    self.countdown_buy_qual_mask[0] = val
        else:
            if self.countdown_count_up[0] == self.p.countdown_bars:
                self.countdown_sell_qual_mask[0] = self.COUNTDOWN_IS_QUALIFIED
            if self.countdown_count_down[0] == self.p.countdown_bars:
                self.countdown_buy_qual_mask[0] = self.COUNTDOWN_IS_QUALIFED

        if self.countdown_count_up_imp[0]:
            self.countdown_sell_qual_mask_imp[0] = self.countdown_sell_qual_mask[0]
        if self.countdown_count_down_imp[0]:
            self.countdown_buy_qual_mask_imp[0] = self.countdown_buy_qual_mask[0]
        if self.countdown_sell_qual_mask_imp[0] == self.COUNTDOWN_IS_QUALIFIED:
            cntdwnSellQualMaskImp = line2arr(
                self.countdown_sell_qual_mask_imp, self.DATA_CANDLES)
            priceSource = line2arr(
                self.source, self.DATA_CANDLES)
            self.countdown_sell[0] = valuewhen(
                cntdwnSellQualMaskImp == self.COUNTDOWN_IS_QUALIFIED,
                priceSource,
                0)
        if self.countdown_sell_qual_mask_imp[0] == self.COUNTDOWN_IS_DEFERRED:
            cntdwnSellQualMaskImp = line2arr(
                self.countdown_sell_qual_mask_imp, self.DATA_CANDLES)
            priceSource = line2arr(
                self.source, self.DATA_CANDLES)
            self.countdown_sell_defer[0] = valuewhen(
                cntdwnSellQualMaskImp == self.COUNTDOWN_IS_DEFERRED,
                priceSource,
                0)
    
        if self.countdown_buy_qual_mask_imp[0] == self.COUNTDOWN_IS_QUALIFIED:
            cntdwnBuyQualMaskImp = line2arr(
                self.countdown_buy_qual_mask_imp, self.DATA_CANDLES)
            priceSource = line2arr(
                self.source, self.DATA_CANDLES)
            self.countdown_buy[0] = valuewhen(
                cntdwnBuyQualMaskImp == self.COUNTDOWN_IS_QUALIFIED,
                priceSource,
                0)
        if self.countdown_buy_qual_mask_imp[0] == self.COUNTDOWN_IS_DEFERRED:
            cntdwnBuyQualMaskImp = line2arr(
                self.countdown_buy_qual_mask_imp, self.DATA_CANDLES)
            priceSource = line2arr(
                self.source, self.DATA_CANDLES)
            self.countdown_buy_defer[0] = valuewhen(
                cntdwnBuyQualMaskImp == self.COUNTDOWN_IS_DEFERRED,
                priceSource,
                0)

        if self.setup_sell[0] or self.countdown_count_up_recycle[0]:
            high = line2arr(self.data_high, self.p.setup_bars)
            tr = line2arr(self.tr, self.p.setup_bars)
            highest = max(high)
            self.risk_level[0] = highest + valuewhen(high == highest, tr, 0)
        elif self.setup_buy[0] or self.countdown_count_down_recycle[0]:
            low = line2arr(self.data_low, self.p.setup_bars)
            tr = line2arr(self.tr, self.p.setup_bars)
            lowest = min(low)
            self.risk_level[0] = lowest - valuewhen(low == lowest, tr, 0)
        elif self.countdown_sell[0]:
            high = line2arr(self.data_high, self.p.countdown_bars)
            tr = line2arr(self.tr, self.p.countdown_bars)
            highest = max(high)
            self.risk_level[0] = highest + valuewhen(high == highest, tr, 0)
        elif self.countdown_buy[0]:
            low = line2arr(self.data_low, self.p.countdown_bars)
            tr = line2arr(self.tr, self.p.countdown_bars)
            lowest = min(low)
            self.risk_level[0] = lowest - valuewhen(low == lowest, tr, 0)
        else:
            self.risk_level[0] = nz(self.risk_level[-1], self.data_low[0])


        # setup_sell
        self.l.setup_sell[0] = 0
        if not na(self.setup_sell[0]):
            self.l.setup_sell[0] = 1
        # setup_buy
        self.l.setup_buy[0] = 0
        if not na(self.setup_buy[0]):
            self.l.setup_buy[0] = 1
        # setup_sell_perf
        self.l.setup_sell_perf[0] = 0
        if not na(self.setup_sell_perf[0]):
            self.l.setup_sell_perf[0] = 1
        # setup_buy_perf
        self.l.setup_buy_perf[0] = 0
        if not na(self.setup_buy_perf[0]):
            self.l.setup_buy_perf[0] = 1
        # countdown_sell
        self.l.countdown_sell[0] = 0
        if not na(self.countdown_sell[0]):
            self.l.countdown_sell[0] = 1
        # countdown_buy
        self.l.countdown_buy[0] = 0
        if not na(self.countdown_buy[0]):
            self.l.countdown_buy[0] = 1
        # countdown_sell_defer
        self.l.countdown_sell_defer[0] = 0
        if not na(self.countdown_sell_defer[0]):
            self.l.countdown_sell_defer[0] = 1
        # countdown_buy_defer
        self.l.countdown_buy_defer[0] = 0
        if not na(self.countdown_buy_defer[0]):
            self.l.countdown_buy_defer[0] = 1
        # countdown_count_up_recycle
        self.l.countdown_count_up_recycle[0] = 0
        if not na(self.countdown_count_up_recycle[0]):
            self.l.countdown_count_up_recycle[0] = 1
        # countdown_count_down_recycle
        self.l.countdown_count_down_recycle[0] = 0
        if not na(self.countdown_count_down_recycle[0]):
            self.l.countdown_count_down_recycle[0] = 1

[A Former User]

observer.py

import backtrader as bt


class TDSequentialObs(bt.observers.Observer):

    plotinfo = dict(plot=True,
                    subplot=False,
                    plotlegend=False,
                    plotlinelegend=False,
                    plotlinelabels=False,
                    plotvaluetags=False,
                    plotlinevalues=True,
                    plotabove=True,
                    plotname="TD Sequential",)

    lines = (
        'seq_up',               # up count marker
        'seq_down',             # down count marker
        's_buy',                # setup buy marker
        's_sell',               # setup sell marker
        's_buy_perf',           # setup buy perf markerr
        's_sell_perf',          # setup sell perf marker
        's_buy_perf_price',
        's_sell_perf_price',
        's_trend_support',
        's_trend_resistance',
        'cd_seq_up',            # countdown up marker
        'cd_seq_down',          # countdown down marker
        'cd_buy',               # countdown buy marker
        'cd_sell',              # countdown sell marker
        'cd_buy_defer',         # countdown buy defer marker
        'cd_sell_defer',        # countdown sell defer marker
        'cd_cnt_up_recycle',    # countdown up recycle marker
        'cd_cnt_down_recycle',  # countdown down recycle marker
        'risk_level'
    )

    plotlines = dict(
        seq_up=dict(
            marker='*', markersize=4.0, color='black', ls='',),
        seq_down=dict(
            marker='*', markersize=4.0, color='black', ls='',),
        s_buy=dict(
            marker='2', markersize=5.0, color='green',),
        s_sell=dict(
            marker='1', markersize=5.0, color='maroon',),
        s_buy_perf=dict(
            marker='^', markersize=5.0, color='green',),
        s_sell_perf=dict(
            marker='v', markersize=5.0, color='maroon',),
        cd_seq_up=dict(
            marker='*', markersize=5.0, color='blue', ls='',),
        cd_seq_down=dict(
            marker='*', markersize=5.0, color='blue', ls='',),
        cd_buy=dict(
            marker='^', markersize=10.0, color='green',),
        cd_sell=dict(
            marker='v', markersize=10.0, color='maroon',),
        cd_buy_defer=dict(
            marker='$D$', markersize=5.0, color='red', ls='',),
        cd_sell_defer=dict(
            marker='$D$', markersize=5.0, color='red', ls='',),
        cd_count_up_recycle=dict(
            marker='$R$', markersize=5.0, color='blue', ls='',),
        cd_count_down_recycle=dict(
            marker='$R$', markersize=5.0, color='blue', ls='',),
        risk_level=dict(lw=2.0, ls='--',),
    )

    params = dict(
        td_seq=None,
        bardist=0.0006,
        plot_setup_count=True,
        plot_setup_signals=True,
        plot_setup_tdst=True,
        plot_countdown_count=True,
        plot_countdown_signals=True,
        plot_risk_level=True
    )

    def __init__(self):
        self.td_seq = self.p.td_seq
        self.countdown_up_prev = None
        self.countdown_down_prev = None

    def _plotlabel(self):
        return [None]

    def _get_line(self, name):
        line = getattr(self.lines, name, False)
        return line

    def next(self):
        # setup signals
        if self.p.plot_setup_signals:
            # setup buy / sell signal
            if self.td_seq.l.setup_buy[0]:
                self.l.s_buy[0] = self.data_low[0] - (3 * self.p.bardist)
            if self.td_seq.l.setup_sell[0]:
                self.l.s_sell[0] = self.data_high[0] + (3 * self.p.bardist)
            # setup perfected buy / sell signal
            if self.td_seq.l.setup_buy_perf[0]:
                self.l.s_buy_perf[0] = self.data_low[0] - (4 * self.p.bardist)
            if self.td_seq.l.setup_sell_perf[0]:
                self.l.s_sell_perf[0] = self.data_high[0] + (4 * self.p.bardist)

        # setup count
        if self.p.plot_setup_count:
            # setup count up sequence
            if self.td_seq.setup_count_up[0] > 0:
                self.l.seq_up[0] = self.data_low[0] + self.p.bardist
            # setup count down sequence
            if self.td_seq.setup_count_down[0] > 0:
                self.l.seq_down[0] = self.data_high[0] - self.p.bardist

        # setup trend support / resistance (TDST)
        if self.p.plot_setup_tdst:
            self.l.s_trend_support[0] = self.td_seq.setup_trend_support[0]
            self.l.s_trend_resistance[0] = self.td_seq.setup_trend_resistance[0]

        # countdown count
        if self.p.plot_countdown_count:
            # countdown count up sequence
            if self.td_seq.countdown_count_up_imp[0] >= 0:
                if self.td_seq.countdown_count_up_imp[0] != self.countdown_up_prev:
                    self.l.cd_seq_up[0] = self.data_low[0] + (2 * self.p.bardist)
                self.countdown_up_prev = self.td_seq.countdown_count_up_imp[0]
            # countdown count down sequence
            if self.td_seq.countdown_count_down_imp[0] >= 0:
                if self.td_seq.countdown_count_down_imp[0] != self.countdown_down_prev:
                    self.l.cd_seq_down[0] = self.data_high[0] - (2 * self.p.bardist)
                self.countdown_down_prev = self.td_seq.countdown_count_down_imp[0]

        # countdown signals
        if self.p.plot_countdown_signals:
            # countdown_buy/sell
            if self.td_seq.l.countdown_buy[0]:
                self.l.cd_buy[0] = self.data_low[0] - (4 * self.p.bardist)
            if self.td_seq.l.countdown_sell[0]:
                self.l.cd_sell[0] = self.data_high[0] + (4 * self.p.bardist)

            # countdown_buy_defer/sell_defer
            if self.td_seq.l.countdown_buy_defer[0]:
                self.l.cd_buy_defer[0] = self.data_low[0] - (3 * self.p.bardist)
            if self.td_seq.l.countdown_sell_defer[0]:
                self.l.cd_sell_defer[0] = self.data_high[0] + (3 * self.p.bardist)

            # countdown_up_recycle/down_recycle
            if self.td_seq.l.countdown_count_up_recycle[0]:
                self.l.cd_cnt_up_recycle[0] = self.data_low[0] + (3 * self.p.bardist)
            if self.td_seq.l.countdown_count_down_recycle[0]:
                self.l.cd_cnt_down_recycle[0] = self.data_high[0] - (3 * self.p.bardist)

        # risk level
        if self.p.plot_risk_level:
            self.l.risk_level[0] = self.td_seq.risk_level[0]

[A Former User]

strategy.py

class StrategyTDSequential(bt.Strategy):

    def __init__(self):
        '''Initialization '''
        self.td_seq = TDSequentialInd()
        self._addobserver(
            False,
            TDSequentialObs,
            self.data,
            td_seq=self.td_seq,
            plot_setup_signals=True,
            plot_setup_count=True,
            plot_setup_tdst=True,
            plot_countdown_signals=True,
            plot_countdown_count=True,
            plot_risk_level=True)
    

[A Former User]

I had to strip all comments from the indicator since it was too big to post, if anyone is interested in complete code, just send me a message.

[Wayne Filkins]

Hello, I just started with backtrader recently and have a noob question. I'm not really converting pine script (that was the original plan though) but I have been programming in pine for about 2 years so i'm very used to it. I'm trying to program in a similar way using backtrader.

This is probably super simple for you guys, but how does one make a variable in backtrader which acts like open/high/low/close whereas you can reference its' current candle value as var[0] and 10 candles back would be var[-10] and so on? I thought I could do it as a line, but when I try to set myLine[0] it doesn't let me. I need to be able to set its' current value and change it, and have that change apply to it when you reference it using myLine[-1] and myLine[-2] etc. while moving through the candles. Any insight would really be helpful because these docs are very extensive (which I very much appreciate) but the terminology gets confusing and i'm having trouble figuring this out. Once I solve this I can create most of my strategy very quickly because I can then program like i'm using pine. Thanks in advance for any help or advice anyone can offer.

[A Former User]

@Wayne-Filkins check out the code above, there is an example how to do this.

it would be this, what you want, I think:

self.line = bt.LineNum(float('nan'))

without the need to define the lines dict.

Also check out the pinescript.py where I added some methods from pinescript.

[Wayne Filkins]

Yes if I had scrolled further in your code blocks I probably would have figured that out. Hadn't had coffee yet haha. I saw some of the functions you made like nz() and barssince(). This is something I was wanting to do but would probably take me forever so really thankful you are sharing them!

[Wayne Filkins]

@dasch Hey man if you have a minute, i'm trying to get bases (basically like looking 50 candles back and comparing that candle to the 50 before it and 50 after it to see if it's the lowest) and it's not quite working. I declared the base in init() with:

self.base = bt.LineNum(float('1.0'))

So basically in next() it starts out as 1, and I loop through the last 100 candles to try to compare to see if any are lower, and if any are lower it changes it to 0 (so it's not a pivot). This is the code in next():

        for i in range(-2 * 50, -1):
            if self.datalow[-2 * 50] in locals():
                if self.datalow[i] < self.datalow[-1 * 50]:
                    self.base = 0.0

        if self.base == 1.0:
            print("we have a pivot!")

So yeah basically i'm trying to compare the last 100 candles to close[-50], and do this on every iteration of next(). Any idea why this isn't working? self.base just stays as 1.0 the whole time. Thanks in advance for anyone who can help with this!

[Wayne Filkins]

@dasch I did all that in strategy.py. Do I have to make an indicator.py and observer.py too to do stuff like this?

[Wayne Filkins]

@dasch NM I got it figured out! base didn't have [0] on it, and the thing that was really messing it up was the "in locals()" thing wasn't working so I had to do a counter so that it didn't get the out of range error on the first 50 candles, since you know it can't look back 50 candles at the beginning if there aren't that many. Had to do that stuff a lot in pine script, always had a bunch of various counters lol. Do you know how I can plot these base/pivots with a dot on the low of the candle?

[Wayne Filkins]

@dasch Can you send the complete code so I can see the comments? It's pretty confusing. Idk how to send a message on this goofy platform though

[A Former User]

Sure, send me an email. Mine email is in my profile.

[jcgeraldi]

@dasch
sorry to write in an old post. I need to convert an indicator that I use to python. but I'm having difficulty in the valuewhen function. I saw that you have a lot of experience in this. Would you be able to help me or else do the service for me. Sorry for my english, I'm from Brazil

[run-out]

@jcgeraldi His email is in his profile.