I recreated this two years ago which is what turned me on to Alpaca in the first place. It worked fine at the time.

https://hackernoon.com/forecasting-market-movements-using-tensorflow-fb73e614cd06

Then I got distracted for two years. I’m starting again recreating this, but I have no formal programming education so it’s a slog.

I managed to get through a few issues with changes between 2018 and now, but I’m stuck on this particular section of code:

returned_data = api.get_bars(

symbol,

barTimeframe,

start_dt=trainStartDate,

end_dt=evalEndDate).df

```
# Processes all data into numpy arrays for use by talib
timeList = np.array(returned_data.index)
openList = np.array(returned_data.open, dtype=np.float64)
highList = np.array(returned_data.high, dtype=np.float64)
lowList = np.array(returned_data.low, dtype=np.float64)
closeList = np.array(returned_data.close, dtype=np.float64)
volumeList = np.array(returned_data.volume, dtype=np.float64)
```

get_bars is now get_barset - and I’ve managed to make that part work by changing to the below.

api.get_barset(ticker, barTimeframe, limit=None, start=trainStartDate, end=evalEndDate).df

However, only the timeList line beneath it executes, everything else chokes (doesn’t error, just won’t even execute a print statement beneath that line). Any help greatly appreciated.