A curated list of open technology projects to sustain a stable climate, energy supply, biodiversity and natural resources.

pyrealm

Providing an integrated toolbox for modelling plant productivity, growth and demography using Python.
https://github.com/ImperialCollegeLondon/pyrealm

Category: Biosphere
Sub Category: Plants and Vegetation

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Repository metadata

Development of the pyrealm package, providing an integrated toolbox for modelling plant productivity, growth and demography using Python.

README.md


PyPI - Version
PyPI - Python Version
DOI
Documentation Status
codecov
Test and build
pre-commit.ci status

The pyrealm package provides a toolbox implementing some key models for estimating
plant productivity, growth and demography in Python. The outputs of different models
can be then easily fed into other models within pyrealm to allow productivity
estimates to be fed forward into estimation of net primary productivity, growth and
ultimately plant community demography.

The pyrealm package currently includes:

  • The P Model for estimating optimal rates of plant photosynthesis given the balance
    between carbon capture and water loss. This includes recent extensions to incorporate
    the effects of water stress, slow acclimation processes, models of C3/C4 competition
    and carbon isotope fractionation.
  • The SPLASH model for calculating soil moisture and actual evapotranspiration.
  • Initial components of a demography module for modelling plant functional types,
    cohorts, communities and canopies, including allocation calculations using the T
    Model.
  • A suite of core physics functions and other utilities used to support the modules
    above.

For more details, see the package website:
https://pyrealm.readthedocs.io/.

Version 2.0.0 development

New functionality being implemented after version 1.0.0 has lead to some immediate
breaking changes in the API, for example in the handling of quantum yield settings in
the class signatures for the PModel and SubdailyPModel. As the package uses
semantic versioning, these changes to the API require that new
releases be made under a new major version.

We will be publishing a series of "release candidates" of the 2.0.0 package. These will
be used to identify issues with the current API and try to stabilise a new API. The
content of version 2.0.0 is not yet finalised, so these release candidates may also add
new functionality.

We recommend that you update to the most recent release candidate of version 2.0.0. The
documentation now includes a migration
guide
to help update
existing code.

Using pyrealm

The pyrealm package requires Python 3 and the currently supported Python versions are:
3.10, 3.11 and 3.12. We make released package versions available via
PyPi and also generate DOIs for each release via
Zenodo. You can install the most recent
release using pip:

pip install pyrealm

You can now get started using pyrealm. For example, to calculate the estimated gross
primary productivity of a C3 plant in a location, start a Python interpreter, using
python, python3 or ipython depending on your installation, and run:

import numpy as np
from pyrealm.pmodel import PModelEnvironment, PModel

# Calculate the photosynthetic environment given the conditions
env = PModelEnvironment(
    tc=np.array([20]), vpd=np.array([1000]),
    co2=np.array([400]), patm=np.array([101325.0],
    fapar=1, ppfd=300)
)

# Calculate the predictions of the P Model for a C3 plant
pmodel_c3 = PModel(env)

# Report the GPP in micrograms of carbon per m2 per second.
pmodel_c3.gpp

This should give the following output:

array([76.42544948])

The package website provides worked examples of using pyrealm, for example to:

These worked examples also show how pyrealm can be used within Python scripts or
Jupyter notebooks and how to use pyrealm with large datasets loaded using
numpy or xarray with
pyrealm classes and functions.

Citing pyrealm

The pyrealm repository can be cited following the information in the citation
file
. If you are using pyrealm in research, it is better to cite the
DOI of the specific release from Zenodo.

Developing pyrealm

If you are interested in contributing to the development of pyrealm, please read the
guide for contributors. Please do also read the code of
conduct
for contributing to this project.

Support and funding

Development of the pyrealm package has been supported by the following grants and
institutions:

Citation (CITATION.cff)

cff-version: 1.2.0
title: pyrealm
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: C. David L.
    family-names: Orme
    email: [email protected]
    affiliation: Department of Life Sciences, Imperial College London
    orcid: 'https://orcid.org/0000-0002-7005-1394'
  - given-names: Alienor
    family-names: Lavergne
    email: [email protected]
    affiliation: Department of Life Sciences, Imperial College London
  - given-names: Vivienne
    family-names: Groner
    email: [email protected]
    affiliation: Department of Life Sciences, Imperial College London
  - given-names: Marion
    family-names: Weinzierl
    email: [email protected]
    affiliation: Institute of Computing for Climate Science, University of Cambridge
  - given-names: Tianzhang
    family-names: Cai
    email: [email protected]
    affiliation: Institute of Computing for Climate Science, University of Cambridge
  - given-names: Surbhi
    family-names: Goel
    email: [email protected]
    affiliation: Institute of Computing for Climate Science, University of Cambridge
  - given-names: Alexander
    family-names: Smith
    email: [email protected]
    affiliation: Institute of Computing for Climate Science, University of Cambridge
  - given-names: James
    family-names: Emberton
    email: [email protected]
    affiliation: Institute of Computing for Climate Science, University of Cambridge
  - given-names: Amy
    family-names: Pike
    email: [email protected]
    affiliation: Institute of Computing for Climate Science, University of Cambridge

repository-code: 'https://github.com/ImperialCollegeLondon/pyrealm'
url: 'https://pyrealm.readthedocs.io'
repository: 'https://pypi.org/project/pyrealm/'
abstract: >-
  The pyrealm package provides an integrated set of Python 3
  modules for modelling plant productivity, growth and
  demography and the estimation of growing conditions.
license: MIT


Owner metadata


GitHub Events

Total
Last Year

Committers metadata

Last synced: 5 days ago

Total Commits: 1,925
Total Committers: 13
Avg Commits per committer: 148.077
Development Distribution Score (DDS): 0.259

Commits in past year: 835
Committers in past year: 9
Avg Commits per committer in past year: 92.778
Development Distribution Score (DDS) in past year: 0.341

Name Email Commits
David Orme d****e 1427
James Emberton j****n@g****m 146
tztsai 1****4@q****m 88
MarionBWeinzierl m****5@c****k 70
pre-commit-ci[bot] 6****] 60
TZCai 1****9@1****m 39
Surbhi Goel s****7@g****m 38
Sally s****n@g****m 17
Alexander Smith a****x@g****m 15
arne s****e@g****m 13
Amy Pike a****e@h****k 6
vgro v****o 5
github-actions[bot] 4****] 1

Committer domains:


Issue and Pull Request metadata

Last synced: 1 day ago

Total issues: 256
Total pull requests: 252
Average time to close issues: about 2 months
Average time to close pull requests: 14 days
Total issue authors: 13
Total pull request authors: 13
Average comments per issue: 1.07
Average comments per pull request: 1.92
Merged pull request: 220
Bot issues: 0
Bot pull requests: 46

Past year issues: 146
Past year pull requests: 142
Past year average time to close issues: 19 days
Past year average time to close pull requests: 12 days
Past year issue authors: 9
Past year pull request authors: 10
Past year average comments per issue: 0.89
Past year average comments per pull request: 2.11
Past year merged pull request: 124
Past year bot issues: 0
Past year bot pull requests: 31

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/ImperialCollegeLondon/pyrealm

Top Issue Authors

  • davidorme (185)
  • MarionBWeinzierl (25)
  • j-emberton (17)
  • tztsai (7)
  • surbhigoel77 (6)
  • AmyOctoCat (3)
  • a-smith-github (3)
  • arne-exe (2)
  • sjavis (2)
  • sallymatson (2)
  • mondus (2)
  • Syuizen (1)
  • VallesMarinerisExplorer (1)

Top Pull Request Authors

  • davidorme (147)
  • pre-commit-ci[bot] (31)
  • tztsai (17)
  • MarionBWeinzierl (16)
  • github-actions[bot] (15)
  • j-emberton (9)
  • surbhigoel77 (5)
  • AmyOctoCat (4)
  • Alielav (4)
  • a-smith-github (1)
  • arne-exe (1)
  • sjavis (1)
  • sallymatson (1)

Top Issue Labels

  • bug (38)
  • enhancement (33)
  • rse (33)
  • code review (13)
  • documentation (13)
  • roadmap (11)
  • core devs (9)
  • meta (9)
  • icebox (3)
  • outreach (1)
  • duplicate (1)
  • question (1)
  • testing (1)

Top Pull Request Labels

  • enhancement (14)
  • rse (7)
  • code review (2)
  • roadmap (2)
  • documentation (2)
  • core devs (1)
  • testing (1)

Package metadata

pypi.org: pyrealm

Python tools for modelling plant productivity and demography.

  • Homepage: https://pyrealm.readthedocs.io/
  • Documentation: https://pyrealm.readthedocs.io/
  • Licenses: MIT
  • Latest release: 1.0.0 (published 10 months ago)
  • Last Synced: 2025-04-26T13:39:43.949Z (1 day ago)
  • Versions: 24
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 2,406 Last month
  • Rankings:
    • Dependent packages count: 10.052%
    • Forks count: 15.314%
    • Average: 17.149%
    • Stargazers count: 18.46%
    • Downloads: 20.28%
    • Dependent repos count: 21.642%
  • Maintainers (1)

Dependencies

requirements.txt pypi
  • netCDF4 *
  • pre-commit *
  • pytest *
  • pyyaml *
.github/workflows/pre-commit_autoupdate.yaml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
  • browniebroke/pre-commit-autoupdate-action main composite
  • peter-evans/create-pull-request v3 composite
.github/workflows/pyrealm_ci.yaml actions
  • abatilo/actions-poetry v2.1.6 composite
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
  • pre-commit/action v3.0.0 composite
poetry.lock pypi
  • 131 dependencies
pyproject.toml pypi
  • Bottleneck ^1.3.5
  • dacite ^1.6.0
  • numpy ^1.16.5
  • python >=3.9,<3.11
  • scipy ^1.7.3
  • tabulate ^0.8.10

Score: 14.794152420380565