Merge pull request #193 from Mohammad-Tayyab-Frequenz/update-release-notes

docs: update-release-notes

Author: Mohammad-Tayyab-Frequenz

RELEASE_NOTES.md

@@ -1,13 +1,9 @@
 # Tooling Library for Notebooks Release Notes
 
 ## Summary
-
-<!-- Here goes a general summary of what this release is about -->
+This release standardizes energy reporting with a new suite of metric definitions, visualization helpers, and a schema-based ColumnMapper for consistent data handling. It also introduces breaking changes to MicrogridConfig to support schema-based loading and adds official support for Python 3.13.
 
 ## Upgrading
-
-<!-- Here goes notes on how to upgrade from previous versions, including deprecations and what they should be replaced with -->
-
 - `MicrogridConfig`: Switch to schema-based loading of microgrid config files and updates to the config class:
    - Remove unused nested field `assets` and replace by its contents `pv`, `wind`, `battery`.
    - Make `meta` and `ctype` public fields.
@@ -16,24 +12,15 @@
 - Add `src/frequenz/lib/notebooks/reporting/schema_mapping.yaml` to your deployment so notebooks can load the canonical column definitions via `ColumnMapper`.
 
 ## New Features
-
-<!-- Here goes the main new features and examples or instructions on how to use them -->
-
 - Introduced `frequenz.lib.notebooks.reporting.metrics.reporting_metrics` with first-class definitions for production excess, battery charging share, grid feed-in, self-consumption, self-consumption share, and inferred consumption; the schema now documents each metric via an `implementation` tag.
 - Added `frequenz.lib.notebooks.reporting.utils.helpers.add_energy_flows()` (plus supporting helpers) that aggregates raw production/consumption columns and appends the derived flows the reporting notebook needs.
 - Published a locale-aware `ColumnMapper` utility that reads the YAML schema so notebooks can seamlessly move between raw API headers, canonical identifiers, and localized display labels.
-- plot_time_series() can auto-pivot long-format inputs, honor a desired legend/trace order, and optionally fill selected traces while keeping Plotly colors consistent through a shared palette builder; also defaults to numeric columns only to avoid spurious traces (src/frequenz/lib/notebooks/reporting/plotter.py (lines 15-163)).
-- Added reusable long_to_wide() and build_color_map() helpers so notebooks can pivot categorical telemetry and reuse the canonical color scheme without duplicating logic (src/frequenz/lib/notebooks/reporting/utils/helpers.py (lines 216-311)).
-- Added a default mapping loading to the `ColumnMapper` utility function.
-- Added `grid_consumption` function in the `reporting_metrics.py`.
+- plot_time_series() can auto-pivot long-format inputs, add a desired legend/trace order, and optionally fill selected traces while keeping Plotly colors consistent through a shared palette builder; also defaults to numeric columns only to avoid spurious traces.
+- Added reusable `long_to_wide()` and `build_color_map()` helpers so notebooks can pivot categorical telemetry and reuse the canonical color scheme without duplicating logic.
 - Added `create_energy_report_df()` to convert raw microgrid exports into timezone-aware, canonical energy-report tables with derived grid/battery KPIs and labeled component columns, letting dashboards bind to a consistent schema without bespoke glue.
 - Introduced the `reporting_nb_functions` toolkit so notebooks can build overview tables, melt component selections, compute energy-mix summaries, and aggregate KPIs (production totals, self-consumption share, grid import peaks) for stakeholder-ready reporting pages.
 - Expanded the reporting helper utilities with YAML config loading, German number formatting, timezone conversion, component labeling, energy-report column selection, and robust energy-flow derivations so multiple notebooks can reuse the same preprocessing primitives.
 - Published `Reporting NB.ipynb` example that wires the mapper, helper utilities, and KPI builders together in a ready-to-run reporting notebook.
 
 ## Bug Fixes
-- `frequenz.lib.notebooks.reporting.utils.helpers.add_energy_flows()` now infers consumption totals from existing data when explicit consumption columns are missing, preventing inconsistent outputs in notebook pipelines that only provide grid and production inputs.
-- `frequenz.lib.notebooks.reporting.metrics.consumption()` reindexes optional production/battery inputs and raises a warning when inferred consumption turns negative so sign-convention issues are surfaced immediately.
-- plot_energy_pie_chart() now accepts the same color_dict overrides as the time-series view, ensuring doughnut slices reuse the canonical colors instead of Plotly’s defaults and keeping legends consistent across charts (src/frequenz/lib/notebooks/reporting/plotter.py (lines 166-200)).
-
-<!-- Here goes notable bug fixes that are worth a special mention or explanation -->
+- `plot_energy_pie_chart()` now accepts the same color_dict overrides as the time-series view, ensuring doughnut slices reuse the canonical colors instead of Plotly’s defaults and keeping legends consistent across charts.