System.InvalidCastException: Specified cast is not valid OR Runtime Error: Specified cast is not valid by Garyha

Garyha INVESTOR

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System.InvalidCastException: Specified cast is not valid.

Runtime Error: Specified cast is not valid.

Why?

[backtest doesn't show up on the list, will have to paste here instead of attach]

# System.InvalidCastException: Specified cast is not valid.

# Runtime Error: Specified cast is not valid.



import pandas as pd



class Zoo(QCAlgorithm):

    def Initialize(self):

        self.SetStartDate(2017,10,1)

        self.SetEndDate(2017,11,1)

        self.SetCash(100000)

        self.averages = {}

        self.AddUniverse(self.CoarseSelection)



    def CoarseSelection(c, coarse):

        columns = ['Price', 'HasFundamentalData']

        data_df = pd.DataFrame.from_records(

            [[getattr(s, name) for name in columns] for s in coarse],

            index = [s for s in coarse], columns = columns, coerce_float=True)

        data_df = data_df.query("(Price > .50) and (Price < .60) and HasFundamentalData").nsmallest(99, 'Price')

        diffs   = pd.Series({})

        for cf in data_df.index:

            sym = cf.Symbol

            if sym not in c.averages:

                c.averages[sym] = SymbolData(sym)  # initialize

            c.averages[sym].update(cf)  # Update the SymbolData object with current EOD price?

            sma1 = c.averages[sym].sma1.Current.Value ; sma1 = float(sma1) if sma1 else 0.0

            sma2 = c.averages[sym].sma2.Current.Value ; sma2 = float(sma2) if sma2 else 0.0

            diff = sma1 - sma2

            if not diff: continue

            z = str(sym) # to avoid diffs[sym] = diff ... 'object is not callable' (another confusing error)

            diffs[z] = diff

        '''

        if len(diffs.index): c.Log(diffs.size)

        And another confusing error:

            Runtime Error: Trying to dynamically access a method that does not exist throws a TypeError exception. 

            To prevent the exception, ensure each parameter type matches those required by the Log method. 

            Please checkout the API documentation. at CoarseSelection in main.py:line 32

            TypeError : No method matches given arguments for Log (Open Stacktrace)

        Huh? len() or .size ????  Expected any of these would work fine ...

        c.Log(diffs)  c.Log(len(diffs))  c.Log(diffs.size)  

        '''

        c.Log(diffs)

        return list(diffs.index)



class SymbolData(object):

    def __init__(self, symbol):

        self.symbol = symbol

        self.sma1 = SimpleMovingAverage(3)

        self.sma2 = SimpleMovingAverage(10)

        self.is_ready = False

    def update(self, value):

        self.is_ready = self.sma1.Update(value.EndTime, value.Price) and self.sma2.Update(value.EndTime, value.Price)

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Garyha

Accepted Answer

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Alexandre Catarino

garyha, I would advice you to avoid using pandas.DataFrame and pandas.Series for such simple filtering and sorting operations. It is slower and consumes more memory than simple list operations:

def CoarseSelection(c, coarse):



    # Filter coarse fundamental universe by price range and has fundamental data

    coarse = [ cf for cf in coarse if cf.Price > .5 and cf.Price < .6 and cf.HasFundamentalData ]

    # get the 99 smallest coarse fundamental universe by price

    coarse = sorted(coarse, key = lambda cf: cf.Price)[:99]



    diff = {}



    for cf in coarse:

        symbol = cf.Symbol

        if symbol not in c.averages:

            c.averages[symbol] = SymbolData(symbol)

        c.averages[symbol].update(cf)

        sma1 = c.averages[symbol].sma1.Current.Value

        sma2 = c.averages[symbol].sma2.Current.Value

        diff[symbol] = sma1 - sma2



    return list(diff.keys())

It is also an known issue that using Symbol objects as pandas.Index doesn't work as we would expect, therefore you needed to convert it into str `z = str(sym)`. At this point, you have a string and this method should return a list of Symbol...

In your code snippet, there is also a question about an exception thrown my this statement:
`c.Log(diffs.size)`:
The Log method accepts string or a non-native python object: it means that int, float, double, etc must be passed as a string: `c.Log(str(diffs.size))` or `c.Log(f"{diffs.size}")`.

Garyha

423 ,

I like that first line for trimming coarse, simple:

coarse = [ s for s in coarse if s.Price > 5.00 and s.Price < 10.00 and s.HasFundamentalData ]

A little more info on the error 'Specified cast is not valid'.

My return looked like ['DCIX UTEYWBKJIC11', 'ZBB TTK3TR0978MD', 'SYMX TXB02K4DOLLX']

In Alexandre's code using a dictionary, the symbol variable prior to it looks like DCIX UTEYWBKJIC11 but then those apparently land as keys in the dictionary like <QuantConnect.Symbol object at 0x7f2335874a58>, pointers or references.

Alexandre Catarino

The issue is that z = str(sym) will return the string value of the Symbol object: "DCIX UTEYWBKJIC11", for example.
list(diffs.index) is a list of string where it should be a list of Symbol.

Garyha INVESTOR

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