opendsm

library1.2.7pypypiunverified

OpenDSM provides standard methods for predicting building energy usage, supporting hourly, daily, and billing models with clustering and baseline metrics. Current version 1.2.7, requires Python >=3.10, and is actively maintained on GitHub.

data ai-ml

pip install opendsm

github ↗package ↗homepage ↗docs ↗

INSTALL

IMPORT

SIG · OPENDSM

opendsm

datapythonv1.2.7

Install

39.1s avg

Import

—

Disk

1062MB

Pass rate

5/ 10

Env Coverage5 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v1.2.7 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

build_error

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 39.1s · import 0.000s · 982MB

1062MB installed

● package 1062MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

OpenDSM

✓ from opendsm import OpenDSM

✗ from opendsm import OpenDSM

Quickstart example loading hourly data and fitting an hourly model.

from opendsm import OpenDSM from opendsm.hourly import HourlyModel import pandas as pd # Create sample hourly energy usage data import numpy as np dates = pd.date_range('2023-01-01', periods=8760, freq='H') energy = np.random.rand(8760) * 100 temp = np.random.rand(8760) * 35 df = pd.DataFrame({'energy': energy, 'temperature': temp}, index=dates) # Initialize OpenDSM with a project name project = OpenDSM('my_project') # Add data project.add_data(df, energy_column='energy', temperature_column='temperature') # Run hourly model model = HourlyModel(project) model.fit() print(model.results())

Debug

Known issues

breakingIn v1.2.0, the logging interface changed to a modern logger. If you previously configured logging via the old interface, you must update your code to use the new logging module from opendsm.logger.

fix

Use from opendsm.logger import logger and configure via logger.setLevel(...) instead of direct logging calls.

affects: >=1.2.0

breakingDaily and billing models now use BaselineMetrics natively in v1.2.0. If you relied on custom metric calculations, you may need to update your code to use the BaselineMetrics class.

fix

Use from opendsm.metrics import BaselineMetrics to access metrics.

affects: >=1.2.0

deprecatedThe old 'from_series' method for daily data class instantiation has a bug fixed in v1.2.6. If you were using it before, upgrade to v1.2.6+ to avoid issues.

fix

Upgrade to v1.2.6: pip install opendsm>=1.2.6

affects: <1.2.6

gotchaSpectral clustering results may not be deterministic across runs unless you set the seed via the clustering settings. Use seed=42 or similar.

fix

Set seed in clustering_settings: clustering_settings = {'seed': 42}.

affects: >=1.2.4

gotchaData sufficiency can be modified via a settings dictionary but this is intended for R&D; defaults may differ from production standards.

fix

Documentation for data sufficiency settings is limited; use with caution.

affects: >=1.2.0

Upgrade

Version history

1.2.7latest on PyPI · released Feb 11, 2026

Audit

Dependencies

pandasrequiredCore data manipulation

numpyrequiredNumerical operations

scikit-learnrequiredClustering and regression models

matplotliboptionalPlotting

Agent activity

2 hits · last 30 days

node

Resources

githubhttp://github.com/opendsm/opendsm ↗

packagehttps://pypi.org/project/opendsm/ ↗

homepagehttps://lfenergy.org/projects/opendsm ↗

docshttps://opendsm.energy ↗