Convert Pine Script into Python

Question

I am just wondering how to convert the PineScript dev() function into Python code. Is my interpretation correct?

Pine Scripts Example is the following:

plot(dev(close, 10))
// the same on pine
pine_dev(source, length) =>
 mean = sma(source, length)
 sum = 0.0
 for i = 0 to length - 1
 val = source[i]
 sum := sum + abs(val - mean)
 dev = sum/length
plot(pine_dev(close, 10))

My Python code is the following:

df["SMA_highest"] = ta.sma(df["Close"], 10)
df["dev_abs_highest"] = (df["Close"] - df["SMA_highest"]).abs()
df["dev_cumsum_highest"] = df["dev_abs_highest"].rolling(window=10).sum()
df["DEV_SMA_highest"] = df["dev_cumsum_highest"] / 10

What do I need to adjust in the Python code to have the same result as in the Pine Script?

Thanks for any hints :)

• Mike Tung: We aren't here to do your work for you. Please present a Minimal, Verifiables, Complete Example that we can help you with.

Answer 1

I was looking for the same script too and did not find a ready-to-go solution. So I implemented myself. Unfortunately I did not test it completely because the stock prices between yfinance and TradingView differ a little bit, so the result differs a little bit too.

 diffavg = stock[columnname].rolling(days).apply(pine_dev)
 def pine_dev(column):
 summ = 0.0
 mean = column.mean() 
 length = len(column)
 for i in range(0, length):
 summ = summ + abs( column[i] - mean )
 
 ret_val = summ / length
 return ret_val

Basically I use the rolling function and if you apply a function to this, you get all Values from the rolling timeframe in the function.