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chargelog: fix calc energy mix #3185

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Merged
LKuemmel merged 2 commits into from
Mar 10, 2026
Merged

chargelog: fix calc energy mix #3185

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eb3d014
chargelog: fix calc energy mix
LKuemmel Mar 6, 2026
607d81b
fix
LKuemmel Mar 6, 2026
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14 changes: 10 additions & 4 deletions packages/control/chargelog/chargelog.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,8 +10,7 @@
from control import data
from dataclass_utils import asdict
from helpermodules.measurement_logging.process_log import (
FILE_ERRORS, CalculationType, _analyse_energy_source,
_process_entries, analyse_percentage, get_log_from_date_until_now, get_totals)
FILE_ERRORS, CalculationType, _analyse_energy_source, _process_entries, get_totals)
from helpermodules.pub import Pub
from helpermodules import timecheck
from helpermodules.utils.json_file_handler import write_and_check
Expand Down Expand Up @@ -203,6 +202,13 @@ def _get_range_charged(log_data, charging_ev) -> float:
return None


def _calc_power_source_percentages(log_data) -> Dict[str, float]:
power_source = {}
for source in ENERGY_SOURCES:
power_source[source] = log_data.charged_energy_by_source[source] / log_data.imported_since_mode_switch
Comment on lines +206 to +208
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Copilot AI Mar 6, 2026

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_calc_power_source_percentages can raise ZeroDivisionError when log_data.imported_since_mode_switch is 0/0.0 (e.g., export-only sessions, or very small imports that were rounded to 0.0 in _create_entry). Right now this is only handled indirectly via get_value_or_default, which will emit a full exception log for a normal/expected scenario. Consider explicitly guarding on imported_since_mode_switch <= 0 and returning the zero-dict without raising, and optionally rounding the ratios (e.g., to 4 decimals) to keep the JSON output stable/consistent with other energy-mix calculations.

Suggested change
power_source = {}
for source in ENERGY_SOURCES:
power_source[source] = log_data.charged_energy_by_source[source] / log_data.imported_since_mode_switch
"""Calculate share of each energy source in imported energy.
Returns a dict mapping each source to its fraction of the total imported
energy since the last mode switch. If the imported energy is zero or
negative (e.g. export-only session), all fractions are returned as 0.0.
"""
# Avoid ZeroDivisionError in export-only or zero-import sessions.
if getattr(log_data, "imported_since_mode_switch", 0) <= 0:
return {source: 0.0 for source in ENERGY_SOURCES}
total_imported = log_data.imported_since_mode_switch
power_source: Dict[str, float] = {}
for source in ENERGY_SOURCES:
# Use .get to be robust if a source key is missing.
charged_by_source = log_data.charged_energy_by_source.get(source, 0.0)
ratio = charged_by_source / total_imported
# Round to keep JSON output stable/consistent with other energy-mix calculations.
power_source[source] = round(ratio, 4)

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return power_source


def save_data(chargepoint, charging_ev):
""" json-Objekt für den Log-Eintrag erstellen, an die Datei anhängen und die Daten, die sich auf den Ladevorgang
beziehen, löschen.
Expand Down Expand Up @@ -245,8 +251,8 @@ def _create_entry(chargepoint, charging_ev):
# log_data.imported_since_mode_switch / (duration / 3600)
power = get_value_or_default(lambda: round(log_data.imported_since_mode_switch / (time_charged / 3600), 2))
calc_energy_costs(chargepoint, True)
energy_source = get_value_or_default(lambda: analyse_percentage(get_log_from_date_until_now(
log_data.timestamp_mode_switch)["totals"])["energy_source"])
energy_source = get_value_or_default(lambda: _calc_power_source_percentages(log_data), {
source: 0 for source in ENERGY_SOURCES})
Comment on lines +254 to +255
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Copilot AI Mar 6, 2026

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The energy-mix for the charge log entry now comes from charged_energy_by_source / imported_since_mode_switch, which is a behavioral change from using the measurement-log totals. Since this file already has unit tests for cost/source calculations (chargelog_test.py), please add coverage for the new log-entry mix calculation (including edge cases like imported_since_mode_switch == 0 and small rounded values) to prevent regressions.

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costs = round(log_data.costs, 2)

new_entry = {
Expand Down