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https://github.com/jpawlowski/hass.tibber_prices.git
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refactor(logging): remove verbose debug logging from price enrichment
Removed excessive debug logging in enrich_price_info_with_differences(): - Deleted per-interval "Processing" messages (cluttered logs) - Kept boundary INFO messages (enrichment start/skip counts) - Removed unused variable expected_intervals_24h - Removed unused parameter day_label from _process_price_interval() Impact: Cleaner logs, no functional changes. Reduces log volume during price data processing.
This commit is contained in:
Julian Pawlowski
parent
2449c28a88
commit
e04e38d09f
1 changed files with 8 additions and 79 deletions
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@ -146,25 +146,11 @@ def calculate_trailing_average_for_interval(
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matching_prices.append(float(total_price))
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if not matching_prices:
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_LOGGER.debug(
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"No prices found in 24-hour lookback window for interval starting at %s (lookback: %s to %s)",
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interval_start,
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lookback_start,
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interval_start,
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)
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return None
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# CRITICAL: Warn if we have less than 24 hours of data (partial average)
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# 24 hours = 96 intervals (4 per hour)
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expected_intervals_24h = 96
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if len(matching_prices) < expected_intervals_24h:
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_LOGGER.debug(
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"Partial trailing average: only %d intervals available (expected %d for full 24h) "
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"for interval starting at %s",
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len(matching_prices),
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expected_intervals_24h,
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interval_start,
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)
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# Note: This is expected for intervals in the first 24h window
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# Calculate and return the average
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return sum(matching_prices) / len(matching_prices)
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@ -251,7 +237,6 @@ def _process_price_interval(
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all_prices: list[dict[str, Any]],
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threshold_low: float,
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threshold_high: float,
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day_label: str,
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) -> None:
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"""
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Process a single price interval and add difference and rating_level.
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@ -284,14 +269,9 @@ def _process_price_interval(
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rating_level = calculate_rating_level(difference, threshold_low, threshold_high)
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price_interval["rating_level"] = rating_level
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else:
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# Set to None if we couldn't calculate
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# Set to None if we couldn't calculate (expected for intervals in first 24h)
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price_interval["difference"] = None
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price_interval["rating_level"] = None
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_LOGGER.debug(
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"Could not calculate trailing average for %s interval %s",
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day_label,
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starts_at,
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)
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def enrich_price_info_with_differences(
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@ -343,19 +323,13 @@ def enrich_price_info_with_differences(
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earliest_start = starts_at
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if earliest_start is None:
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_LOGGER.debug("No valid timestamps found in intervals - skipping enrichment")
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# No valid intervals - return as-is
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return all_intervals
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# Calculate the 24-hour boundary from earliest data
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# Only intervals starting at or after this boundary have full 24h lookback
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enrichment_boundary = earliest_start + timedelta(hours=24)
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_LOGGER.debug(
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"Enrichment boundary: earliest_start=%s, boundary=%s (skip first 24h)",
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earliest_start,
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enrichment_boundary,
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)
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# Process intervals (modifies in-place)
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# CRITICAL: Only enrich intervals that start >= 24h after earliest data
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enriched_count = 0
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@ -372,15 +346,9 @@ def enrich_price_info_with_differences(
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skipped_count += 1
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continue
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_process_price_interval(price_interval, all_intervals, threshold_low, threshold_high, "enriched")
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_process_price_interval(price_interval, all_intervals, threshold_low, threshold_high)
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enriched_count += 1
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_LOGGER.debug(
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"Enrichment complete: %d intervals enriched, %d intervals skipped (within first 24h or invalid)",
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enriched_count,
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skipped_count,
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)
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return all_intervals
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@ -593,12 +561,8 @@ def _calculate_lookahead_volatility_factor(
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"""
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if len(all_intervals) < lookahead_intervals:
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_LOGGER.debug(
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"Insufficient data for volatility calculation: need %d intervals, have %d - using factor 1.0",
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lookahead_intervals,
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len(all_intervals),
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)
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return 1.0 # Fallback: no adjustment
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# Insufficient data - use default factor (no adjustment)
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return 1.0
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# Extract prices from next N intervals
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lookahead_prices = [
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@ -608,7 +572,7 @@ def _calculate_lookahead_volatility_factor(
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]
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if not lookahead_prices:
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_LOGGER.debug("No valid prices in lookahead period - using factor 1.0")
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# No valid prices - use default factor
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return 1.0
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# Use the same volatility calculation as volatility sensors (coefficient of variation)
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@ -630,17 +594,6 @@ def _calculate_lookahead_volatility_factor(
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else: # VOLATILITY_VERY_HIGH (should not occur with our thresholds, but handle it)
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factor = VOLATILITY_FACTOR_INSENSITIVE # 1.4 → Less sensitive (filter noise)
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_LOGGER.debug(
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"Volatility analysis: intervals=%d, prices=%d, "
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"level=%s, thresholds=(moderate:%.0f%%, high:%.0f%%), factor=%.2f",
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lookahead_intervals,
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len(lookahead_prices),
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volatility_level,
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volatility_threshold_moderate,
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volatility_threshold_high,
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factor,
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)
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return factor
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@ -691,8 +644,7 @@ def calculate_price_trend( # noqa: PLR0913 - All parameters are necessary for v
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"""
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if current_interval_price == 0:
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# Avoid division by zero
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_LOGGER.debug("Current price is zero - returning stable trend")
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# Avoid division by zero - return stable trend
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return "stable", 0.0
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# Apply volatility adjustment if enabled and data available
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@ -707,18 +659,6 @@ def calculate_price_trend( # noqa: PLR0913 - All parameters are necessary for v
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effective_rising = threshold_rising * volatility_factor
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effective_falling = threshold_falling * volatility_factor
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_LOGGER.debug(
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"Trend threshold adjustment: base_rising=%.1f%%, base_falling=%.1f%%, "
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"lookahead_intervals=%d, volatility_factor=%.2f, "
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"effective_rising=%.1f%%, effective_falling=%.1f%%",
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threshold_rising,
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threshold_falling,
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lookahead_intervals,
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volatility_factor,
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effective_rising,
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effective_falling,
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)
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# Calculate percentage difference from current to future
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# CRITICAL: Use abs() for negative prices to get correct percentage direction
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# Example: current=-10, future=-5 → diff=5, pct=5/abs(-10)*100=+50% (correctly shows rising)
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@ -736,15 +676,4 @@ def calculate_price_trend( # noqa: PLR0913 - All parameters are necessary for v
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else:
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trend = "stable"
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_LOGGER.debug(
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"Trend calculation: current=%.4f, future_avg=%.4f, diff=%.1f%%, "
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"threshold_rising=%.1f%%, threshold_falling=%.1f%%, trend=%s",
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current_interval_price,
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future_average,
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diff_pct,
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effective_rising,
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effective_falling,
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trend,
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)
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return trend, diff_pct
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