/debug-algorithm - QuantConnect Cross-Language Debugging

Invoked on a runtime error or a 0-order backtest. Work top to bottom. Find the real cause; never hide it. Same rules for main.py and main.cs.

0. Never add error-hiding patterns

Never introduce pytry/exceptcstry/catch or pyhasattr/getattr/setattr/isinstancecsreflection. They hide the exact failure. If existing code wraps the failing region in one, remove it, re-run, read the real exception, then continue. Only add an if check to skip a known, expected case (such as a header line) by testing that exact condition. Adding a check just to make a crash or 0 trades go away is not a fix; fix the cause.

1. Shorten the backtest, then find the failure type

Record the original pyset_start_date/set_end_datecsSetStartDate/SetEndDate and universe, then shrink both: the smallest window that still reproduces the failure (runtime error: a span around the error date; 0 trades: 3 to 6 months), and the universe to a small fixed symbol list or tight filter. Only after the fix gives non-zero orders with no runtime error, restore the original dates and universe and run ONE final full-period backtest to confirm. Match the failure type:

• Runtime exception -> Section 2.
• 0 orders / flat equity -> Section 3.

2. Runtime exception

Read the actual message and line; never guess.

• Unknown property or method / AttributeError / "no attribute" -> Section 4.
• KeyNotFound / "wasn't found in the DataDictionary": find WHY the key is absent first. Custom/alt data (add_data) has its OWN symbol (the return value), not the equity symbol; reading alt data with the equity symbol is the usual cause. Key by add_data(...).symbol; field names from the QC docs page (Section 4), never getattr. Skipping a wrong key with a check just turns the crash into 0 trades (Section 3). symbol in data is right only for a real fillforward gap on a correct key.
• None / null price: seed_initial_prices only looks back 3 days; keep only securities where security.price is set.
• Insufficient buying power: reduce exposure, then derivative sizing, then raise free_portfolio_value_percentage; add liquidate_existing_holdings=True; if a 9:00 schedule still fails, move it to 9, 31 (sizes on intraday price).

3. 0 trades / 0 orders

Stop at the first that applies. NEVER add or tighten a check here.

1. Selection too strict OR too loose (the usual flat equity / silent-fail cause).
   • Too strict: a long chain of if ...: continue checks drops every candidate, so set_holdings runs with an empty list -> 0 orders / flat equity.
   • Too loose: the filter passes a very large set (e.g. 1000+) into an equal-weight set_holdings; LEAN cannot size that many positions and silently places no orders. Measure with self.log(...) in the rebalance/filter: log the count passing each check and the final selected count. Find the one check responsible, then loosen or tighten just it. Common cause: data an earlier bug left empty (e.g. a signal dict from the Section 2 wrong-symbol bug), or thresholds too strict to ever happen together. Logging rules: never set_runtime_statistic or the Object Store; never self.log in on_data or an often-firing scheduled event (it floods); if unavoidable there, gate it to the first N calls with a counter.
2. Schedule / frequency mismatch:
   • Daily-resolution data with an intraday TimeRule (e.g. time_rules.after_market_open) fires before the daily bar is delivered, so the rebalance reads stale/empty data. With daily data schedule via self.date_rules... + self.time_rules.at(8, 0); use an intraday TimeRule only with minute/hour data.
   • Rebalance reads self._universe.selected on a different/earlier frequency than the universe updates, so it sees an empty set. Align both to the same DateRule, or drive the rebalance from on_securities_changed.
3. Universe empty / wrong Universe.UNCHANGED return (only a filter that just stores symbols and selects nothing returns it; a real selection returns a list).
4. Securities dropped for missing price (see Section 2).
5. Indicators never ready: automatic_indicator_warm_up = True set BEFORE any factory call; feed manual indicators/consolidators in initialize via a history loop; warm-up length fits the rebalance frequency (weekly 14d, monthly or slower 45d). Futures/continuous contracts need this.

4. Unknown property or method

Do not find a property or method by pyhasattr/getattrcsreflection. Find the real property/field name on the dataset's or type's QC docs page, then use it directly. Quick rules:

• Alt-data fields (headline, body, sentiment, etc.) come from that dataset's page, never from getattr guessing.
• Comparing indicators: use indicator.current.value. Direct object comparison only works when both are the same indicator type; different types (or an indicator vs a sub-indicator) need the explicit .current.value. Previous value: indicator.previous.value, not .window[0].
• Fundamental data missing: np.isnan(value), never != 0.
• Yesterday's daily OHLC: security.session (set .size; index [1] is yesterday). Change one access at a time, then re-run.

5. Checklist

1. No banned pattern (Section 0).
2. Original dates + universe recorded before shrinking.
3. Fix targets the real exception line, not a guess.
4. Alt/custom data keyed by the add_data symbol; presence checks only for real fillforward gaps.
5. Unknown properties/fields taken from the QC docs page, not guessed.
6. No check added/tightened to mask 0 trades; cause found via self.log; selection not so large set_holdings silently no-ops (Section 3).
7. Universe and rebalance same frequency; schedule matches data (daily not on an intraday TimeRule, DateRule symbol subscribed); indicators warmed; no buying-power rejection.
8. Original period + universe restored; ONE final backtest confirms non-zero orders and no error.