Skip to main content

Type-safe Pydantic models for all EnergyPlus IDF objects

Project description

idfpy

PyPI Python 3.12+ License: MIT EnergyPlus 26.1 Autoupdate Ask DeepWiki

Type-safe Pydantic models for all EnergyPlus IDF object types, plus IDF file read/write and simulation execution, optimized for LLM tool calling and IDE auto-completion.

Auto-generated from Energy+.schema.epJSON version 26.1.0.

Features

  • 859 object types as Pydantic v2 models with full validation
  • 275 reference types with cross-object validation
  • Forward navigationsurface.zone resolves a reference field to the target object
  • Reverse navigationzone.referencing("Lights") finds all objects that reference a given object
  • Reference validationidf.validate() batch-checks all cross-object references for existence and type compatibility
  • Extension plugin systemsurface.area, .normal, .centroid via auto-discovered geometry mixins with full IDE support
  • Case-insensitive Literal field matching (EnergyPlus IDF is case-insensitive)
  • Extensible field support (vertices, schedule data, etc.)
  • IDF read/write with positional field ordering
  • epJSON read/write with auto-detection by file extension
  • to_dict() / from_dict() for in-memory dict conversion (ideal for LLM tool calls)
  • EnergyPlus simulation execution with ExpandObjects support
  • Accepts both snake_case and original EnergyPlus schema key names

Why idfpy over eppy?

idfpy eppy
No EnergyPlus IDD required at runtime
Type-safe field validation ✅ Pydantic v2
epJSON read/write
Cross-reference validation ✅ 275 ref groups
Forward/reverse navigation ✅ 2849 properties
Surface geometry (area/normal) ✅ ext plugin
to_dict() / from_dict() for LLM
Dependencies 4 (pydantic, jinja2, loguru, typer) 12+ (lxml, pyparsing...)

Installation

pip install idfpy

Quick Start

from pathlib import Path
from idfpy import IDF
from idfpy.models import Version, Building, Zone

# Create an IDF
idf = IDF()
idf.add(Version())
idf.add(Building(name='MyBuilding', north_axis=0.0))
idf.add(Zone(name='Zone1'))

# Save as IDF
idf.save(Path('output.idf'))

# Save as epJSON
idf.save(Path('output.epjson'), output_type='epjson')

# Load (auto-detects format by extension)
idf = IDF.load(Path('existing.idf'))      # IDF format
idf = IDF.load(Path('existing.epjson'))    # epJSON format

# Run simulation
from idfpy.sim import simulate

result = simulate(Path('output.idf'), weather=Path('weather.epw'), output_dir=Path('results/'))
print(result.success)  # True / False

In-memory dict conversion

from pathlib import Path
from idfpy import IDF

idf = IDF.load(Path('model.idf'))

# IDF → dict (epJSON structure)
data = idf.to_dict()
# {
#   "Building": {"MyBuilding": {"north_axis": 0.0, "terrain": "Suburbs"}},
#   "Zone": {"Zone1": {"direction_of_relative_north": 0.0}},
#   ...
# }

# dict → IDF
idf = IDF.from_dict(data)

Object navigation

Every reference field generates a @property for forward navigation. Reverse navigation is available via referencing(). All query methods (get / has / all_of_type / remove) accept either an EnergyPlus type string, a Python class name, or the model class itself — passing the class preserves precise typing in your IDE.

from pathlib import Path
from idfpy import IDF
from idfpy.models import BuildingSurfaceDetailed, Zone

idf = IDF.load(Path('model.idf'))

# Forward navigation — resolve reference to target object
surface = idf.get(BuildingSurfaceDetailed, 'Wall1')   # → BuildingSurfaceDetailed | None
surface.zone_name        # "Zone1" (raw string, always works)
surface.zone             # Zone object (resolved via IDF)
surface.construction     # Construction object

# Reverse navigation — find all objects referencing a given object
zone = idf.get(Zone, 'Zone1')
zone.referencing(BuildingSurfaceDetailed)       # → [Wall1, Wall2, ...]
zone.referencing('Lights')                       # → [OfficeLights, ...]

# Chained navigation
zone.referencing(BuildingSurfaceDetailed)[0].construction

Strict type-name validation (default)

Query methods raise UnknownObjectTypeError when the type name cannot be resolved — this surfaces typos immediately instead of returning an empty result. Pass strict=False for the legacy silent behavior.

from idfpy import UnknownObjectTypeError

try:
    idf.get('BuildingSurface:detailed', 'Wall1')   # note the lowercase 'd'
except UnknownObjectTypeError as e:
    print(e)   # → Unknown object type: 'BuildingSurface:detailed'. ...

# Opt-in legacy silent behavior
idf.get('BuildingSurface:detailed', 'Wall1', strict=False)  # → None

Reference validation

from idfpy import IDF, RefValidationError

idf = IDF.load(Path('model.idf'))

# Batch check all cross-object references
errors = idf.validate()
for e in errors:
    print(e)
# [missing] Lights/OffLights.schedule_name: "BadSched" not found in any of [ScheduleNames]

# Or raise on first broken reference set
try:
    idf.validate_or_raise()
except RefValidationError as exc:
    print(f"{len(exc.errors)} broken reference(s)")

Real-world Example

from pathlib import Path
from idfpy import IDF

# Load a DOE reference building
idf = IDF.load(Path("LargeOffice.idf"))

# Modify all exterior walls' insulation
for con_name, con in idf.all_of_type('Construction').items():
    layer = con.outside_layer_ref
    if layer and hasattr(layer, "conductivity"):
        print(f"{con.name}: k={layer.conductivity} W/m·K")

# Validate all references
errors = idf.validate()
print(f"{len(errors)} broken references")

Geometry extensions

Surface models include geometry properties via the built-in ext.geometry plugin — area, normal vector, and centroid are computed from vertices using Newell's method, with full IDE autocompletion.

from idfpy import IDF
from pathlib import Path

idf = IDF.load(Path('model.idf'))

surface = idf.get('BuildingSurface:Detailed', 'Wall1')
surface.area               # 30.0 (m²)
surface.normal             # (0.0, -1.0, 0.0) — outward unit normal
surface.centroid           # (5.0, 0.0, 1.5)
surface.vertices_as_tuples # [(0,0,3), (0,0,0), (10,0,0), (10,0,3)]

window = idf.get('FenestrationSurface:Detailed', 'Win1')
window.area                # 16.0 (m²)

Supported surface types: BuildingSurface:Detailed, FenestrationSurface:Detailed, Floor:Detailed, RoofCeiling:Detailed, Wall:Detailed, Shading:Building:Detailed, Shading:Site:Detailed, Shading:Zone:Detailed.

Creating custom plugins

Extensions live in idfpy/ext/ as sub-packages. Each plugin exposes a MIXIN_MAP that the code generator auto-discovers:

# idfpy/ext/thermal/__init__.py
from .mixins import ThermalPropertyMixin

MIXIN_MAP: dict[str, type] = {
    'BuildingSurfaceDetailed': ThermalPropertyMixin,
}
# idfpy/ext/thermal/mixins.py
class ThermalPropertyMixin:
    @property
    def u_value(self) -> float:
        """Compute U-value from construction layers."""
        ...

After adding a plugin, re-run idfpy codegen to regenerate models — the mixin is injected into the class hierarchy and IDE autocompletion works immediately.

Container mutation

from idfpy.models import Zone

idf.remove(Zone, 'Zone1')     # unbinds + unregisters references
idf.remove('Zone', 'Zone1')   # string form (EnergyPlus or Python class name)

License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

idfpy-26.1.0.post5.tar.gz (619.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

idfpy-26.1.0.post5-py3-none-any.whl (633.9 kB view details)

Uploaded Python 3

File details

Details for the file idfpy-26.1.0.post5.tar.gz.

File metadata

  • Download URL: idfpy-26.1.0.post5.tar.gz
  • Upload date:
  • Size: 619.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for idfpy-26.1.0.post5.tar.gz
Algorithm Hash digest
SHA256 e6c57d6f2dc7a52a0a6824c600f954e959f8067cbe5f990e8b33d1ee9e59311c
MD5 76544cc9135f19c4715c4216c82a39f7
BLAKE2b-256 083073aaa7a521e41f5cbfda1cbee719da8347c5fd797a0d4cd001883befe176

See more details on using hashes here.

Provenance

The following attestation bundles were made for idfpy-26.1.0.post5.tar.gz:

Publisher: release-version.yml on ITOTI-Y/idfpy

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file idfpy-26.1.0.post5-py3-none-any.whl.

File metadata

  • Download URL: idfpy-26.1.0.post5-py3-none-any.whl
  • Upload date:
  • Size: 633.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for idfpy-26.1.0.post5-py3-none-any.whl
Algorithm Hash digest
SHA256 d658c87f0567b75523e17c176760f6e321f7a75adafb747392140974866d2f47
MD5 ad52f311961ae3a9f52810000eea6681
BLAKE2b-256 727f927805118070eb05a5250cdd84ca6810c068aa6d2e694828610aed66ac42

See more details on using hashes here.

Provenance

The following attestation bundles were made for idfpy-26.1.0.post5-py3-none-any.whl:

Publisher: release-version.yml on ITOTI-Y/idfpy

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page