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Merge branch 'development' into experimental
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‎.github/workflows/ci.yml

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@@ -12,9 +12,9 @@ jobs:
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name: Format
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v1
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- uses: actions/setup-python@v2
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- uses: pre-commit/action@v2.0.0
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- uses: actions/checkout@v3
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- uses: actions/setup-python@v3
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- uses: pre-commit/action@v3.0.0
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with:
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extra_args: --hook-stage manual --all-files
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@@ -24,13 +24,13 @@ jobs:
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strategy:
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fail-fast: false
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matrix:
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python-version: [ "3.7", "3.8", "3.9", "3.10", "3.11" ]
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python-version: [ "3.7", "3.8", "3.9", "3.10", "3.11", "3.12"]
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runs-on: [ubuntu-latest, macos-latest, windows-latest]
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steps:
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- uses: actions/checkout@v2
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- uses: actions/checkout@v3
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v2
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uses: actions/setup-python@v3
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with:
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python-version: ${{ matrix.python-version }}
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run: |
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pip list
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- name: Run some examples
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- name: Run simple examples
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run: |
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cd examples
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python document.py
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cd test
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python test.py
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## Test NeuroML example
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- name: Test NeuroML examples
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if: ${{ matrix.python-version != '3.7'}}
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run: |
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cd ../neuroml2
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cd examples/neuroml2
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python neuroml2_spec.py
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pip install pyneuroml
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# Note: NeuroML files will be validated with OMV below
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- name: Test SBML examples
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if: ${{ matrix.python-version != '3.7'}}
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run: |
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# Requires: pip install pyneuroml
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pynml -validate hello_world_neuroml.net.nml
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pynml -validate TestNeuroML.xml
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cd examples/sbml
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./regenerateAndTest.sh
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- name: Run pytest
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run: |
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cd examples
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python Example1.py
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- name: Install MDF
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run: |
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python arrays.py -run # test one example
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- name: Build Documentation
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if: ${{ matrix.python-version != '3.7'}}
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run: |
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# Note: contributors generation below fails on py 3.7 due to pandas version...
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pip install .[docs]
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cd docs
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python generate.py
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make clean
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make html
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- name: Install and test with OMV
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if: ${{ matrix.runs-on != 'windows-latest' }}
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run: |
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# Note: OMV not well tested on Windows...
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pip install git+https://github.com/OpenSourceBrain/osb-model-validation
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pip install scipy sympy matplotlib cython pandas tables
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# Run OMV tests on all engines
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cd examples
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omv all -V
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omv list -V # list installed engines
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- name: Final version info
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run: |
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pip list

‎.github/workflows/static.yml

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# Simple workflow for deploying static content to GitHub Pages
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name: Deploy static content to Pages
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on:
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# Runs on pushes targeting the default branch
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push:
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branches: ["main"]
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# Allows you to run this workflow manually from the Actions tab
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workflow_dispatch:
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# Sets permissions of the GITHUB_TOKEN to allow deployment to GitHub Pages
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permissions:
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contents: read
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pages: write
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id-token: write
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# Allow only one concurrent deployment, skipping runs queued between the run in-progress and latest queued.
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# However, do NOT cancel in-progress runs as we want to allow these production deployments to complete.
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concurrency:
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group: "pages"
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cancel-in-progress: false
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jobs:
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# Single deploy job since we're just deploying
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deploy:
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environment:
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name: github-pages
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url: ${{ steps.deployment.outputs.page_url }}
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runs-on: ubuntu-latest
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steps:
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- name: Checkout
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uses: actions/checkout@v3
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: 3.9
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- name: Install package
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run: |
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python -m pip install --upgrade pip
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pip install .[dev]
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- name: List packages so far
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run: |
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pip list
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- name: Build Documentation
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run: |
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pip install .[docs]
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cd docs
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python generate.py
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python contributors.py
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cd sphinx
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make clean
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make html
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- name: Setup Pages
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uses: actions/configure-pages@v3
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- name: Upload artifact
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uses: actions/upload-pages-artifact@v2
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with:
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# Upload just docs
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path: 'docs/sphinx/build/html'
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- name: Deploy to GitHub Pages
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id: deployment
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uses: actions/deploy-pages@v2

‎.gitignore

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.idea/
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/examples/document.specification.bson
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/examples/neuroml2/hello_world.v.dat
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/examples/sbml/example_sbml_test.xml

‎README.md

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# Modelspec
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3-
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[![Continuous builds](https://github.com/ModECI/modelspec/actions/workflows/ci.yml/badge.svg)](https://github.com/ModECI/modelspec/actions/workflows/ci.yml) [![PyPI](https://img.shields.io/pypi/v/modelspec)](https://pypi.org/project/modelspec/)
54

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7-
Functionality for specifying the structure of models & enabling automatic serialization to them (e.g. in JSON and YAML format).
5+
Functionality for specifying the allowed structure of models, facilitating the creation of APIs in Python for handling the models & enabling automatic serialization of instances of them (e.g. in JSON and YAML format).
86

97
This package is being used by [NeuroMLlite](https://github.com/NeuroML/NeuroMLlite) & [MDF](https://github.com/ModECI/MDF).
108

‎docs/contributors.py

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len_per_info = len(per_info)
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empty_list = []
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max_tries = 100
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2022
for i in range(len_per_info):
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url = per_info[i]
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print(url)
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data = requests.get(url=url)
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requests_status = "unknown"
25-
while (requests_status == "unknown") or (requests_status == "unsuccessful"):
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while max_tries > 0 and (
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(requests_status == "unknown") or (requests_status == "unsuccessful")
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):
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if data.status_code == 200:
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requests_status = "successful"
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print(" Received: %s" % data.json())
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empty_list.append(data.json())
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else:
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# handle failure on requests to the url for mac os
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requests_status = "unsuccessful"
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print(f"Failed to get data from: {url}")
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# make request again to get data from the url
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data = requests.get(url=url)
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max_tries -= 1
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df1 = pd.DataFrame(empty_list)
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df1["name"] = df1["name"].fillna("")
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name = df1["name"]
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login = df1["login"]
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url_html = df1["html_url"]
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url_id = df1["id"]
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if len(empty_list) > 0:
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df1 = pd.DataFrame(empty_list)
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df1["name"] = df1["name"].fillna(df1["login"])
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name = df1["name"]
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login = df1["login"]
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url_html = df1["html_url"]
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url_id = df1["id"]
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login_html = list(zip(name, login, url_html))
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zip_dict = dict(zip(url_id, login_html))
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login_html = list(zip(name, login, url_html))
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zip_dict = dict(zip(url_id, login_html))
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file = "sphinx/source/api/Contributors.md"
47-
with open(file, "w") as f:
48-
print(
49-
textwrap.dedent(
50-
"""\
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(Modelspec:contributors)=
53+
file = "sphinx/source/api/Contributors.md"
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with open(file, "w") as f:
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print(
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textwrap.dedent(
57+
"""\
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(Modelspec:contributors)=
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# Modelspec contributors
60+
# Modelspec contributors
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This page list names and Github profiles of contributors to Modelspec, listed in no particular order.
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This page is generated periodically, most recently on {}.""".format(
57-
date.today()
58-
)
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),
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file=f,
61-
)
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This page list names and Github profiles of contributors to Modelspec, listed in no particular order.
63+
This page is generated periodically, most recently on {}.""".format(
64+
date.today()
65+
)
66+
),
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file=f,
68+
)
6269

63-
print("", file=f)
70+
print("", file=f)
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65-
for key, val in zip_dict.items():
66-
print("- {} ([@{}]({}))".format(val[0], val[1], val[2]), file=f)
72+
for key, val in zip_dict.items():
73+
print("- {} ([@{}]({}))".format(val[0], val[1], val[2]), file=f)

‎docs/sphinx/source/api/Contributors.md

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# Modelspec contributors
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This page list names and Github profiles of contributors to Modelspec, listed in no particular order.
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This page is generated periodically, most recently on 2023-07-05.
6+
This page is generated periodically, most recently on 2023-12-13.
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88
- Padraig Gleeson ([@pgleeson](https://github.com/pgleeson))
9+
- Manifest Chakalov ([@mqnifestkelvin](https://github.com/mqnifestkelvin))
910
- David Turner ([@davidt0x](https://github.com/davidt0x))
11+
- Peace Ododo ([@Onoyiza](https://github.com/Onoyiza))
1012
- Parikshit Singh Rathore ([@parikshit14](https://github.com/parikshit14))
11-
- Katherine Mantel ([@kmantel](https://github.com/kmantel))
13+
- Ankur Sinha ([@sanjayankur31](https://github.com/sanjayankur31))
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- kmantel ([@kmantel](https://github.com/kmantel))

‎docs/sphinx/source/api/Introduction.md

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# Modelspec
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[![Continuous builds](https://github.com/ModECI/modelspec/actions/workflows/ci.yml/badge.svg)](https://github.com/ModECI/modelspec/actions/workflows/ci.yml) [![PyPI](https://img.shields.io/pypi/v/modelspec)](https://pypi.org/project/modelspec/)
54

6-
7-
Functionality for specifying the structure of models & enabling automatic serialization to them (e.g. in JSON and YAML format).
5+
Functionality for specifying the allowed structure of models, facilitating the creation of APIs in Python for handling the models & enabling automatic serialization of instances of them (e.g. in JSON and YAML format).
86

97
This package is being used by [NeuroMLlite](https://github.com/NeuroML/NeuroMLlite) & [MDF](https://github.com/ModECI/MDF).
108

‎docs/sphinx/source/api/Quickstart.md

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### Simple example
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A basic example which illustrates how to create the specification for a document(model) and create serialized instances can be found [here](examples/README).
18+
A basic example which illustrates how to create the specification for a document (i.e. the model definition for a document) and create serialized instances can be found [here](examples/README).
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### Serialization formats
2121

22-
Python scripts can be used to generate the specification of a type of model(e.g. [this](https://github.com/ModECI/modelspec/blob/main/examples/document.py)), but the models are saved in standardized format in either text based [JSON](https://github.com/ModECI/modelspec/blob/main/examples/document.json) or [YAML](https://github.com/ModECI/modelspec/blob/main/examples/document.yaml) formats or in binary [BSON](https://github.com/ModECI/modelspec/blob/main/examples/document.bson) format. Support for XML serialization is under development.
22+
Python scripts can be used to generate the specification of a type of model (e.g. [this](https://github.com/ModECI/modelspec/blob/main/examples/document.py)), but the models are saved in standardized format in either text based ([JSON](https://github.com/ModECI/modelspec/blob/main/examples/document.json) or [YAML](https://github.com/ModECI/modelspec/blob/main/examples/document.yaml)) formats or in binary ([BSON](https://github.com/ModECI/modelspec/blob/main/examples/document.bson)) format. Support for [XML](https://github.com/ModECI/modelspec/blob/main/examples/document.xml) serialization has recently been added.
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2424
### Current formats using modelspec
2525

26-
#### MDF
26+
#### MDF (Model Description Format)
2727

28-
MDF uses modelspec to create the structure of its models and convert the models into serialized formats such as JSON, YAML, and BSON.
28+
[ModECI's MDF](https://modeci.org/quickstart) uses modelspec to create the structure of its models and convert the models into serialized formats such as JSON, YAML, and BSON.
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3030
#### NeuroML
3131

32-
NeuroMLlite uses modelspec to create the structure of its models and convert the models into serialize formats such as JSON, YAML, and BSON.
32+
[NeuroMLlite](https://github.com/NeuroML/NeuroMLlite) uses modelspec to create the structure of its models and convert the models into serialize formats such as JSON, YAML, and BSON.
33+
The XML serialisation of modelspec will be useful for integrating NeuroML 2 files into the framework, see [here](https://github.com/ModECI/modelspec/tree/main/examples/neuroml2).

‎docs/sphinx/source/api/examples/document.bson

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‎docs/sphinx/source/api/examples/document.json

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{
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"MyBook": {
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"title": "My life in Python",
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"ISBN": 123,
45
"sections": {
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"Abstract": {
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"paragraphs": [

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