🚀 v0.6.0 - (no changes — released for platform consistency)

(no changes — released for platform consistency)

🚀 v0.5.0 - EnergyDataModel

EnergyDataModel is an open-source Python library for representing energy systems as plain data classes — assets, areas, grid topology, and time-series declarations — under a single Element root with stable UUID identity.

It gives energy engineers and energy data scientists object-oriented building blocks for portfolios, sites, and equipment that compose into trees, serialize losslessly to JSON, and round-trip into EnergyDB without losing any structural state.

🌳 The Element Model

Everything in EnergyDataModel inherits from a single root, Element, which carries identity (id: UUID, name), a list of attached TimeSeries declarations, an optional shapely geometry, and an extra dict for ad-hoc JSON-scalar fields.

Three sibling subtrees specialize Element, plus an Asset mixin:

• 🟢 Node — graph vertices (equipment, areas, sensors, grid topology points). Adds members and tz.
• 🔗 Edge — directed relationships between two nodes (lines, transformers, interconnectors). Adds from_element, to_element, directed.
• 📦 Collection — logical groupings (Portfolio, Site, Region, …). Adds members and tz. Not a graph vertex.
• 🏷️ Asset — cross-cutting mixin marking physical equipment, mixed into Node via NodeAsset and into Edge via EdgeAsset.

System-structural classes (containers, areas, networks, bases) live flat at edm.X. Technology-specific equipment lives under sub-namespaces — edm.solar.PVSystem, edm.wind.WindTurbine, edm.grid.Line, edm.battery.Battery, edm.hydro.HydroPowerPlant, edm.heatpump.HeatPump, edm.building.House, edm.weather.TemperatureSensor.

✨ Key Features

• UUID7 identity: every Element gets a stable UUID7 at construction — survives renames, JSON round-trips, and (when paired with EnergyDB) sits as the row primary key in PostgreSQL.
• Lossless JSON round-trip: element.to_json() / Element.from_json() for any registered subclass. Subclasses self-register via Element.__init_subclass__ — no decorator required.
• User extensibility: subclass edm.NodeAsset (or edm.grid.EdgeAsset, or edm.Element) and your class is auto-registered. Add ad-hoc scalar fields via the extra: dict[str, JSONScalar] bag without subclassing.
• Cross-tree references: Reference[T] points at another Element by UUID, resolved lazily via an Index (dict[UUID, Element] built once, O(1) lookup). JSON wire format is {"__ref__": "<uuid>"} — single-pass deserialize, no two-pass walk.
• Edge endpoint widening: Edge.from_element / to_element accept Element | UUID | Reference at construction; __post_init__ normalizes everything to Reference.
• GeoJSON export: element.to_geojson() walks the tree and emits a FeatureCollection of leaves with shapely geometry.
• Energy vocabulary: Quantity / Kind / Scope enums and build_metric() for dotted metric strings (electricity.demand.area), plus convenience constructors (electricity_supply(), spot_price(), grid_frequency(), …) that return metadata-only TimeSeries.
• Tree display & navigation: print(element) / element.to_tree() renders the hierarchy as an indented tree; element.children() exposes a uniform walk across all node-bearing types.
• Interactive class explorer: a Cytoscape-rendered class graph (56 classes, 50 edges) is auto-rebuilt with every docs build — pan, zoom, click any class to inspect its fields and parents.

🛠️ Getting Started

Install via pip:

pip install energydatamodel

import energydatamodel as edm
from shapely.geometry import Point

pvsystem = edm.solar.PVSystem(name="PV-1", capacity=2400, surface_azimuth=180, surface_tilt=25)
windturbine = edm.wind.WindTurbine(name="WT-1", capacity=3200, hub_height=120, rotor_diameter=100)
battery = edm.battery.Battery(name="B-1", storage_capacity=1000, max_charge=500, max_discharge=500)

site = edm.Site(name="Site-1", geometry=Point(12.8, 55.5), members=[pvsystem, windturbine, battery])
portfolio = edm.Portfolio(name="My Portfolio", members=[site])

js = portfolio.to_json()
restored = edm.Portfolio.from_json(js)

Try it instantly in Colab — no install needed:

📚 Resources

• Documentation: https://docs.energydatamodel.org
• Class explorer: https://docs.energydatamodel.org/en/latest/class_hierarchy.html
• Community: Join us on Slack
• License: MIT

Full Changelog: https://github.com/rebase-energy/EnergyDataModel/commits/v0.5.0

Are you using EnergyDataModel in your work? We'd love to hear your feedback. Open an issue or join our Slack community to help us build a shared vocabulary for energy systems.

🚀 v0.2.0 — EnergyDataModel

EnergyDataModel is an open-source Python library for representing energy systems as plain data classes — assets, areas, grid topology, and time-series declarations — under a single Element root with stable UUID identity.

It gives energy engineers and energy data scientists object-oriented building blocks for portfolios, sites, and equipment that compose into trees, serialize losslessly to JSON, and round-trip into EnergyDB without losing any structural state.

🌳 The Element Model

Everything in EnergyDataModel inherits from a single root, Element, which carries identity (id: UUID, name), a list of attached TimeSeries declarations, an optional shapely geometry, and an extra dict for ad-hoc JSON-scalar fields.

Three sibling subtrees specialize Element, plus an Asset mixin:

• 🟢 Node — graph vertices (equipment, areas, sensors, grid topology points). Adds members and tz.
• 🔗 Edge — directed relationships between two nodes (lines, transformers, interconnectors). Adds from_element, to_element, directed.
• 📦 Collection — logical groupings (Portfolio, Site, Region, …). Adds members and tz. Not a graph vertex.
• 🏷️ Asset — cross-cutting mixin marking physical equipment, mixed into Node via NodeAsset and into Edge via EdgeAsset.

System-structural classes (containers, areas, networks, bases) live flat at edm.X. Technology-specific equipment lives under sub-namespaces — edm.solar.PVSystem, edm.wind.WindTurbine, edm.grid.Line, edm.battery.Battery, edm.hydro.HydroPowerPlant, edm.heatpump.HeatPump, edm.building.House, edm.weather.TemperatureSensor.

✨ Key Features

• UUID7 identity: every Element gets a stable UUID7 at construction — survives renames, JSON round-trips, and (when paired with EnergyDB) sits as the row primary key in PostgreSQL.
• Lossless JSON round-trip: element.to_json() / Element.from_json() for any registered subclass. Subclasses self-register via Element.__init_subclass__ — no decorator required.
• User extensibility: subclass edm.NodeAsset (or edm.grid.EdgeAsset, or edm.Element) and your class is auto-registered. Add ad-hoc scalar fields via the extra: dict[str, JSONScalar] bag without subclassing.
• Cross-tree references: Reference[T] points at another Element by UUID, resolved lazily via an Index (dict[UUID, Element] built once, O(1) lookup). JSON wire format is {"__ref__": "<uuid>"} — single-pass deserialize, no two-pass walk.
• Edge endpoint widening: Edge.from_element / to_element accept Element | UUID | Reference at construction; __post_init__ normalizes everything to Reference.
• GeoJSON export: element.to_geojson() walks the tree and emits a FeatureCollection of leaves with shapely geometry.
• Energy vocabulary: Quantity / Kind / Scope enums and build_metric() for dotted metric strings (electricity.demand.area), plus convenience constructors (electricity_supply(), spot_price(), grid_frequency(), …) that return metadata-only TimeSeries.
• Tree display & navigation: print(element) / element.to_tree() renders the hierarchy as an indented tree; element.children() exposes a uniform walk across all node-bearing types.
• Interactive class explorer: a Cytoscape-rendered class graph (56 classes, 50 edges) is auto-rebuilt with every docs build — pan, zoom, click any class to inspect its fields and parents.

🛠️ Getting Started

Install via pip:

pip install energydatamodel

import energydatamodel as edm
from shapely.geometry import Point

pvsystem = edm.solar.PVSystem(name="PV-1", capacity=2400, surface_azimuth=180, surface_tilt=25)
windturbine = edm.wind.WindTurbine(name="WT-1", capacity=3200, hub_height=120, rotor_diameter=100)
battery = edm.battery.Battery(name="B-1", storage_capacity=1000, max_charge=500, max_discharge=500)

site = edm.Site(name="Site-1", geometry=Point(12.8, 55.5), members=[pvsystem, windturbine, battery])
portfolio = edm.Portfolio(name="My Portfolio", members=[site])

js = portfolio.to_json()
restored = edm.Portfolio.from_json(js)

Try it instantly in Colab — no install needed:

📚 Resources

• Documentation: https://docs.energydatamodel.org
• Class explorer: https://docs.energydatamodel.org/en/latest/class_hierarchy.html
• Community: Join us on Slack
• License: MIT

Full Changelog: https://github.com/rebase-energy/EnergyDataModel/commits/v0.2.0

Are you using EnergyDataModel in your work? We'd love to hear your feedback. Open an issue or join our Slack community to help us build a shared vocabulary for energy systems.

v0.1.0 Test Release

bump versions

Source-Commit: 145278d7e98230eaabc5b3928885515ec1e3337c

v0.0.6 Test Release

bump libs versions

Source-Commit: 423758a7abf8257a8aba57ec9d1703e07111326c

v0.0.5 Test Release

Bump version from 0.0.4 to 0.0.5

v0.0.4 Test Release

Bump version from 0.0.3 to 0.0.4