QuantConnect/Lean · error · ValueError
Unexpected distribution: {distribution}
Error message
Unexpected distribution: {distribution} What it means
Per-row sanity check on the AAPL dividend history: every distribution value must be non-zero. A zero distribution indicates malformed dividend data (a dividend row with a 0 amount) or a deserialization bug that zeroed the distribution field.
Source
Thrown at Algorithm.Python/HistoryAuxiliaryDataRegressionAlgorithm.py:50
if len(multi_symbol_request) != 12:
raise ValueError(f"Unexpected multi symbol dividend count: {len(multi_symbol_request)}")
# continuous future mapping requests
sp500 = Symbol.create(Futures.Indices.SP_500_E_MINI, SecurityType.FUTURE, Market.CME)
continuous_future_open_interest_mapping = self.history(SymbolChangedEvent, sp500, datetime(2007, 1, 1), datetime(2012, 1, 1), data_mapping_mode = DataMappingMode.OPEN_INTEREST)
if len(continuous_future_open_interest_mapping) != 9:
raise ValueError(f"Unexpected continuous future mapping event count: {len(continuous_future_open_interest_mapping)}")
continuous_future_last_trading_day_mapping = self.history(SymbolChangedEvent, sp500, datetime(2007, 1, 1), datetime(2012, 1, 1), data_mapping_mode = DataMappingMode.LAST_TRADING_DAY)
if len(continuous_future_last_trading_day_mapping) != 9:
raise ValueError(f"Unexpected continuous future mapping event count: {len(continuous_future_last_trading_day_mapping)}")
dividend = self.history(Dividend, aapl, 360)
self.debug(str(dividend))
if len(dividend) != 6:
raise ValueError(f"Unexpected dividend count: {len(dividend)}")
for distribution in dividend.distribution:
if distribution == 0:
raise ValueError(f"Unexpected distribution: {distribution}")
split = self.history(Split, aapl, 360)
self.debug(str(split))
if len(split) != 2:
raise ValueError(f"Unexpected split count: {len(split)}")
for splitfactor in split.splitfactor:
if splitfactor == 0:
raise ValueError(f"Unexpected splitfactor: {splitfactor}")
symbol = Symbol.create("BTCUSD", SecurityType.CRYPTO_FUTURE, Market.BINANCE)
margin_interest = self.history(MarginInterestRate, symbol, 24 * 3, Resolution.HOUR)
self.debug(str(margin_interest))
if len(margin_interest) != 8:
raise ValueError(f"Unexpected margin interest count: {len(margin_interest)}")
for interestrate in margin_interest.interestrate:
if interestrate == 0:
raise ValueError(f"Unexpected interestrate: {interestrate}")
View on GitHub (pinned to d2c3659f87)
Solutions
- Inspect AAPL factor file rows in the window for zero or malformed distribution values.
- Trace Dividend.Distribution population in the dividend reader/factor provider.
- Correct or remove the bad data row and re-run.
Example fix
# before: malformed factor row {time; priceFactor; splitFactor; 0 distribution}
# after: corrected distribution value
{20200713;1.0;1.0;0.205} Defensive patterns
Strategy: validation
Validate before calling
div = self.history(Dividend, aapl, 360)
bad = [d for d in div.distribution if d == 0]
if bad:
self.debug(f"zero dividend distributions: {len(bad)}") Type guard
def has_nonzero_distributions(div_history) -> bool:
return all(d != 0 for d in div_history.distribution) Prevention
- Sanity-check auxiliary values, not just row counts.
- Validate factor-file rows before relying on them.
- Reject zero distributions at parse time in custom data readers.
When it happens
Trigger: Iterating dividend.distribution, a value equals 0.0.
Common situations: A factor file row has a zero/blank distribution that was parsed as 0; a dividend refactor changed how Distribution is populated; data corruption.
Related errors
- Unexpected multi symbol dividend count: {len(multi_symbol_re
- Unexpected dividend count: {len(dividend)}
- Unexpected splitfactor: {splitfactor}
- Unexpected continuous future mapping event count: {len(conti
- Unexpected continuous future mapping event count: {len(conti
AI-assisted analysis of QuantConnect/Lean@d2c3659f87 (2026-08-13).
Data as JSON: /api/errors/ae92b06c40988459.
Report an issue: GitHub.