forked from enviPath/enviPy
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12 Commits
871448dde8
...
develop-ba
| Author | SHA1 | Date | |
|---|---|---|---|
| 67aa3731cb | |||
| 0033513d99 | |||
| fedd1b5280 | |||
| 2d3dca6a75 | |||
| ada270aa3c | |||
| 093daa5ecf | |||
| f4f284925a | |||
| ca6e926b30 | |||
| 2504d7045b | |||
| 032ebc30a2 | |||
| 703f377b7f | |||
| 7639b23e4e |
62
.gitea/workflows/build-image.yaml
Normal file
62
.gitea/workflows/build-image.yaml
Normal file
@ -0,0 +1,62 @@
|
||||
name: Build Docker Image
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|
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# Trigger when a PR to main/develop is completed.
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on:
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pull_request:
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branches:
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- main
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- develop
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types:
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- closed
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|
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jobs:
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build-and-push:
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if: ${{ github.event.pull_request.merged == true }}
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runs-on: ubuntu-latest
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steps:
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# Fetch the repository content for the Docker build context.
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- name: Checkout repository
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uses: actions/checkout@v4
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# Enable Buildx for BuildKit features (incl. SSH mount support).
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@v3
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# Authenticate against the container registry before pushing images.
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- name: Log in to container registry
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uses: docker/login-action@v3
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with:
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registry: git.envipath.com
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username: ${{ secrets.CI_REGISTRY_USER }}
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password: ${{ secrets.CI_REGISTRY_PASSWORD }}
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|
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# Generate image tags/labels:
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# - PRs targeting main get "latest" and "main-sha"
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# - PRs targeting develop get "dev" and "dev-sha"
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- name: Extract metadata
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id: meta
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uses: docker/metadata-action@v5
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with:
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images: git.envipath.com/envipath/envipy
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tags: |
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type=raw,value=latest,enable=${{ github.event.pull_request.base.ref == 'main' }}
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type=sha,prefix=main-,enable=${{ github.event.pull_request.base.ref == 'main' }}
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type=raw,value=dev,enable=${{ github.event.pull_request.base.ref == 'develop' }}
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type=sha,prefix=dev-,enable=${{ github.event.pull_request.base.ref == 'develop' }}
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# Load SSH key so Docker can pull private git+ssh dependencies during build.
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- name: Setup SSH for private git dependencies
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uses: webfactory/ssh-agent@v0.9.0
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with:
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ssh-private-key: ${{ secrets.ENVIPY_CI_PRIVATE_KEY }}
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# Build and push the production image; forward SSH agent without registry cache reuse.
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- name: Build and push Docker image
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uses: docker/build-push-action@v5
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with:
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context: .
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file: Dockerfile
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push: true
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ssh: default
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tags: ${{ steps.meta.outputs.tags }}
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labels: ${{ steps.meta.outputs.labels }}
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@ -60,6 +60,10 @@ COPY tests tests
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COPY utilities utilities
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COPY manage.py .
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# Used to run migrations etc
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COPY entrypoint.sh entrypoint.sh
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RUN chmod +x entrypoint.sh
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# Install frontend deps
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COPY package.json pnpm-lock.yaml pnpm-workspace.yaml ./
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@ -81,6 +85,7 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
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libxext6 \
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libfontconfig1 \
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nano \
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openjdk-21-jre-headless \
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&& rm -rf /var/lib/apt/lists/*
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RUN useradd -ms /bin/bash django
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@ -102,4 +107,5 @@ USER django
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EXPOSE 8000
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CMD ["gunicorn", "envipath.wsgi:application", "--bind", "0.0.0.0:8000", "--workers", "3"]
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ENTRYPOINT ["/app/entrypoint.sh"]
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CMD ["gunicorn", "envipath.wsgi:application", "--bind", "0.0.0.0:8000", "--workers", "8"]
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120
bayer/views.py
120
bayer/views.py
@ -8,7 +8,7 @@ from django.shortcuts import redirect
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from bayer.models import PESCompound
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from epdb.logic import PackageManager
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from epdb.models import Pathway, Node
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from epdb.models import Pathway, Node, Group
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from epdb.views import _anonymous_or_real, error
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from utilities.decorators import package_permission_required
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@ -18,6 +18,23 @@ Package = s.GET_PACKAGE_MODEL()
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logger = logging.getLogger(__name__)
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def has_secret_group(user):
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"""
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Determines if the specified user belongs to any secret group.
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This function checks whether the given user is a member of any group
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that is marked as secret.
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|
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Args:
|
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user: The user for whom the check is performed.
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Returns:
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bool: True if the user belongs to at least one secret group,
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False otherwise.
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"""
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return Group.objects.filter(secret=True, user_member=user).exists()
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@package_permission_required()
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def create_pes(request, package_uuid):
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current_user = _anonymous_or_real(request)
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@ -38,7 +55,7 @@ def create_pes(request, package_uuid):
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if pes_link:
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try:
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pes_data = fetch_pes(request, pes_link)
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pes_data = fetch_pes(request, pes_link, current_user)
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except ValueError as e:
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return error(
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request,
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@ -98,7 +115,7 @@ def create_pes_node(request, package_uuid, pathway_uuid):
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if pes_link:
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try:
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pes_data = fetch_pes(request, pes_link)
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pes_data = fetch_pes(request, pes_link, current_user)
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except ValueError as e:
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return error(
|
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request,
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@ -157,53 +174,82 @@ def create_pes_node(request, package_uuid, pathway_uuid):
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return HttpResponseNotAllowed(["POST"])
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def fetch_pes(request, pes_url) -> dict:
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from epauth.views import get_access_token_from_request
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token = get_access_token_from_request(request)
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def get_application_token(prod: bool) -> str:
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scope = f"{s.PROD_PES_SCOPE if prod else s.NON_PROD_PES_SCOPE}/.default"
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if token is None:
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token = pes_url.split('/')[-1] == 'dummy'
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url = f"https://login.microsoftonline.com/{s.MS_TENANT_ID}/oauth2/v2.0/token"
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data = {
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"grant_type": "client_credentials",
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"client_id": s.MS_ENTRA_CLIENT_ID,
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"client_secret": s.MS_ENTRA_CLIENT_SECRET,
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"scope": scope,
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}
|
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|
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if token:
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for k, v in s.PES_API_MAPPING.items():
|
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if pes_url.startswith(k):
|
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pes_id = pes_url.split('/')[-1]
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||||
try:
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response = requests.post(url, data=data)
|
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response.raise_for_status()
|
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return response.json()["access_token"]
|
||||
except requests.exceptions.HTTPError as e:
|
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logger.error(f"Could not fetch application token: {e}")
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raise ValueError(f"Could not fetch application token!")
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|
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if pes_id == 'dummy':
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import json
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res_data = json.load(open(s.BASE_DIR / "fixtures/pes.json"))
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|
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def fetch_pes(request, pes_url, user) -> dict:
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for k, v in s.PES_API_MAPPING.items():
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if pes_url.startswith(k):
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prod = "cropkey-np" not in pes_url
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|
||||
pes_id = pes_url.split('/')[-1]
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||||
|
||||
if pes_id == 'dummy':
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import json
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res_data = json.load(open(s.BASE_DIR / "fixtures/pes.json"))
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res_data["pes_url"] = pes_url
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return res_data
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else:
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headers = {
|
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"accept": "*/*",
|
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"authorization": "Bearer " + get_application_token(prod),
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}
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||||
|
||||
# Restrict request if user is not part of any secret group
|
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if not has_secret_group(user):
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headers["app-classification-level-restriction"] = "restrict-pes-secret-structure-access"
|
||||
|
||||
|
||||
params = {"pes_reg_entity_corporate_id": pes_id}
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||||
|
||||
res = requests.get(v, headers=headers, params=params, proxies=s.PROXIES or None)
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||||
|
||||
try:
|
||||
res.raise_for_status()
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pes_data = res.json()
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|
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# Handle missing response
|
||||
if "detail" in pes_data and "The following PES Reg Entities Corporate Ids could not be found" in pes_data["detail"]:
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raise ValueError(f"PES with id {pes_id} not found")
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|
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# Ensure we have a entity
|
||||
if len(pes_data) == 0:
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raise ValueError(f"PES with id {pes_id} not found")
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|
||||
res_data = pes_data[0]
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||||
res_data["pes_url"] = pes_url
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||||
return res_data
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||||
else:
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headers = {"Authorization": f"Bearer {token['access_token']}"}
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||||
params = {"pes_reg_entity_corporate_id": pes_id}
|
||||
|
||||
res = requests.get(v, headers=headers, params=params, proxies=s.PROXIES or None)
|
||||
except requests.exceptions.HTTPError as e:
|
||||
raise ValueError(f"Error fetching PES with id {pes_id}: {e}")
|
||||
|
||||
try:
|
||||
res.raise_for_status()
|
||||
pes_data = res.json()
|
||||
|
||||
if len(pes_data) == 0:
|
||||
raise ValueError(f"PES with id {pes_id} not found")
|
||||
|
||||
res_data = pes_data[0]
|
||||
res_data["pes_url"] = pes_url
|
||||
return res_data
|
||||
|
||||
except requests.exceptions.HTTPError as e:
|
||||
raise ValueError(f"Error fetching PES with id {pes_id}: {e}")
|
||||
else:
|
||||
raise ValueError(f"Unknown URL {pes_url}")
|
||||
else:
|
||||
raise ValueError("Could not fetch access token from request.")
|
||||
raise ValueError(f"Unknown URL {pes_url}")
|
||||
|
||||
|
||||
def visualize_pes(request):
|
||||
pes_link = request.GET.get('pesLink')
|
||||
|
||||
if pes_link:
|
||||
pes_data = fetch_pes(request, pes_link)
|
||||
pes_data = fetch_pes(request, pes_link, request.user)
|
||||
|
||||
representations = pes_data.get('representations')
|
||||
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
import enum
|
||||
from typing import Any, Dict
|
||||
from abc import ABC, abstractmethod
|
||||
|
||||
from envipy_additional_information import EnviPyModel
|
||||
@ -69,6 +70,12 @@ class Plugin(ABC):
|
||||
|
||||
|
||||
class Property(Plugin):
|
||||
def parameters(self) -> Dict[str, Any]:
|
||||
"""
|
||||
Returns the parameters of the PropertyPlugin.
|
||||
"""
|
||||
return {}
|
||||
|
||||
@classmethod
|
||||
@abstractmethod
|
||||
def requires_rule_packages(cls) -> bool:
|
||||
@ -300,6 +307,12 @@ class Classifier(Plugin):
|
||||
"""
|
||||
pass
|
||||
|
||||
def parameters(self) -> Dict[str, Any]:
|
||||
"""
|
||||
Returns the parameters of the ClassifierPlugin.
|
||||
"""
|
||||
return {}
|
||||
|
||||
@abstractmethod
|
||||
def build(self, eP: EnviPyDTO, *args, **kwargs) -> BuildResult | None:
|
||||
"""
|
||||
|
||||
9
entrypoint.sh
Normal file
9
entrypoint.sh
Normal file
@ -0,0 +1,9 @@
|
||||
#!/bin/bash
|
||||
set -e
|
||||
|
||||
if [ "${SKIP_DJANGO_SETUP:-false}" != "true" ]; then
|
||||
python manage.py migrate --no-input
|
||||
python manage.py collectstatic --no-input
|
||||
fi
|
||||
|
||||
exec "$@"
|
||||
@ -9,7 +9,7 @@ from django.shortcuts import redirect
|
||||
|
||||
from epdb.logic import UserManager, GroupManager
|
||||
from epdb.models import Group
|
||||
from epdb.views import get_remote_address
|
||||
from epdb.views import get_remote_address, error
|
||||
|
||||
auth_log = logging.getLogger("auth")
|
||||
|
||||
@ -72,6 +72,15 @@ def entra_callback(request):
|
||||
|
||||
claims = result["id_token_claims"]
|
||||
|
||||
if claims.get("roles") is None or claims.get("roles") == [] or "envipath_registered_user" not in claims.get("roles"):
|
||||
auth_log.error(f"Login attempt by {get_remote_address(request)} failed due to missing role")
|
||||
return error(
|
||||
request,
|
||||
"Login Failed",
|
||||
"The user is not authenticated. A reason for this might be a missing assignment to the respective enviPath group.",
|
||||
403,
|
||||
)
|
||||
|
||||
user_name = claims.get("name")
|
||||
# preferred_username is a fallback for 2nd CWID
|
||||
user_email = claims.get("emailaddress", claims.get("email", claims.get("preferred_username")))
|
||||
|
||||
@ -72,6 +72,10 @@ def get_cached_jwks(tenant_id: str, force=False) -> Dict:
|
||||
return jwks
|
||||
|
||||
|
||||
def get_package_for_read(user, package_uuid):
|
||||
return PackageManager.get_package_by_id(user, package_uuid)
|
||||
|
||||
|
||||
def get_package_for_write(user, package_uuid):
|
||||
p = PackageManager.get_package_by_id(user, package_uuid)
|
||||
if not PackageManager.writable(user, p):
|
||||
@ -885,7 +889,7 @@ def create_package_compound(
|
||||
from bayer.models import PESCompound
|
||||
|
||||
try:
|
||||
pes_data = fetch_pes(request, c.pesLink)
|
||||
pes_data = fetch_pes(request, c.pesLink, request.user)
|
||||
except ValueError as e:
|
||||
return 400, {"message": f"Could not fetch PES data for {c.pesLink}"}
|
||||
|
||||
@ -2010,7 +2014,7 @@ def add_pathway_node(request, package_uuid, pathway_uuid, n: Form[CreateNode]):
|
||||
from bayer.models import PESCompound
|
||||
|
||||
try:
|
||||
pes_data = fetch_pes(request, n.pesLink)
|
||||
pes_data = fetch_pes(request, n.pesLink, request.user)
|
||||
except ValueError as e:
|
||||
return 400, {"message": f"Could not fetch PES data for {n.pesLink}"}
|
||||
|
||||
@ -2430,3 +2434,42 @@ def predict(request, np: Form[NonPersistent]):
|
||||
return 403, {
|
||||
"message": f"Getting Setting with id {np.setting_url} failed due to insufficient rights!"
|
||||
}
|
||||
|
||||
|
||||
##########
|
||||
# Export #
|
||||
##########
|
||||
class PackageExportInSchema(Schema):
|
||||
package_uuid: str
|
||||
additional_information_types: List[str] | None = None
|
||||
|
||||
|
||||
@router.get("/export", response={200: Any, 403: Error})
|
||||
def export(request, q: Query[PackageExportInSchema]):
|
||||
try:
|
||||
p = get_package_for_read(request.user, q.package_uuid)
|
||||
|
||||
from envipy_additional_information import registry
|
||||
from utilities.misc import PathwayExporter
|
||||
|
||||
ai_types = []
|
||||
if q.additional_information_types is not None:
|
||||
for ai_type in q.additional_information_types:
|
||||
if registry.get_model(ai_type) is None:
|
||||
return 400, {
|
||||
"message": f"Exporting Package with id {q.package_uuid} failed as {ai_type} is not a valid additional information type!"
|
||||
}
|
||||
ai_types.append(ai_type)
|
||||
|
||||
exporter = PathwayExporter(p, add_infs_to_export=ai_types)
|
||||
res = exporter.do_export()
|
||||
|
||||
filename = f"{p.get_name().replace(' ', '_')}_{p.uuid}.tsv"
|
||||
response = HttpResponse(res, content_type="text/csv")
|
||||
response["Content-Disposition"] = f'attachment; filename="{filename}"'
|
||||
|
||||
return response
|
||||
except ValueError:
|
||||
return 403, {
|
||||
"message": f"Exporting Package with id {q.package_uuid} failed due to insufficient rights!"
|
||||
}
|
||||
|
||||
@ -44,20 +44,25 @@ class Command(BaseCommand):
|
||||
"EPModel",
|
||||
"ApplicabilityDomain",
|
||||
"EnzymeLink",
|
||||
"AdditionalInformation",
|
||||
]
|
||||
for model in MODELS:
|
||||
obj_cls = apps.get_model("epdb", model)
|
||||
obj_cls.objects.update(
|
||||
url=Replace(F("url"), Value(options["old"]), Value(options["new"]))
|
||||
)
|
||||
if issubclass(obj_cls, EnviPathModel):
|
||||
obj_cls.objects.update(
|
||||
kv=Cast(
|
||||
Replace(
|
||||
Cast(F("kv"), output_field=TextField()),
|
||||
Value(options["old"]),
|
||||
Value(options["new"]),
|
||||
),
|
||||
output_field=JSONField(),
|
||||
)
|
||||
|
||||
update_fields = {"url": Replace(F("url"), Value(options["old"]), Value(options["new"]))}
|
||||
if hasattr(obj_cls, "description"):
|
||||
update_fields["description"] = Replace(
|
||||
F("description"), Value(options["old"]), Value(options["new"])
|
||||
)
|
||||
|
||||
if issubclass(obj_cls, EnviPathModel):
|
||||
update_fields["kv"] = Cast(
|
||||
Replace(
|
||||
Cast(F("kv"), output_field=TextField()),
|
||||
Value(options["old"]),
|
||||
Value(options["new"]),
|
||||
),
|
||||
output_field=JSONField(),
|
||||
)
|
||||
|
||||
obj_cls.objects.update(**update_fields)
|
||||
|
||||
97
epdb/management/commands/reaction_rule_mapping.py
Normal file
97
epdb/management/commands/reaction_rule_mapping.py
Normal file
@ -0,0 +1,97 @@
|
||||
import logging
|
||||
|
||||
from django.core.management.base import BaseCommand
|
||||
from django.db import transaction
|
||||
from uuid import uuid4
|
||||
from epdb.models import Package, ReactionExplanation
|
||||
from utilities.chem import FormatConverter
|
||||
from django.utils import timezone
|
||||
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class Command(BaseCommand):
|
||||
def add_arguments(self, parser):
|
||||
parser.add_argument(
|
||||
"--rule-package",
|
||||
action="append",
|
||||
default=["32de3cf4-e3e6-4168-956e-32fa5ddb0ce1"],
|
||||
type=str,
|
||||
help="UUID to process. Can be specified multiple times.",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--reaction-package",
|
||||
action="append",
|
||||
default=[
|
||||
"32de3cf4-e3e6-4168-956e-32fa5ddb0ce1", # BBD
|
||||
"f05e38d8-e9b4-4c3e-b0d8-9ab29966eccf", # Sediment
|
||||
"521c547a-fd2a-491c-ad5b-7eaa1577fb65", # Sludge
|
||||
"5882df9c-dae1-4d80-a40e-db4724271456", # Soil
|
||||
"87a49584-d937-482c-9c33-25928dcb02a8", # PFAS
|
||||
],
|
||||
type=str,
|
||||
help="UUID to process. Can be specified multiple times.",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--dry-run",
|
||||
default=False,
|
||||
action="store_true",
|
||||
help="Perform dry run",
|
||||
)
|
||||
|
||||
@transaction.atomic
|
||||
def handle(self, *args, **options):
|
||||
RUN_UUID = uuid4()
|
||||
RUN_START = timezone.now()
|
||||
|
||||
rule_packages = Package.objects.filter(uuid__in=options["rule_package"])
|
||||
reaction_packages = Package.objects.filter(uuid__in=options["reaction_package"])
|
||||
|
||||
rules = []
|
||||
for rule_package in rule_packages:
|
||||
rules.extend(rule_package.get_applicable_rules())
|
||||
|
||||
reactions = []
|
||||
for reaction_package in reaction_packages:
|
||||
reactions.extend(reaction_package.reactions)
|
||||
|
||||
logger.debug(f"Collected {len(rules)} rules and {len(reactions)} reactions.")
|
||||
|
||||
for i, reaction in enumerate(reactions):
|
||||
logger.debug(f"Reaction {i} / {len(reactions)}")
|
||||
for j, rule in enumerate(rules):
|
||||
reactants, products = reaction.smirks().split(">>")
|
||||
|
||||
if len(reactants.split(".")) > 1:
|
||||
logger.debug(f"Skipping reaction {reaction.uuid} as it has multiple reactants.")
|
||||
break
|
||||
|
||||
products = products.split(".")
|
||||
|
||||
# Run reaction with rule
|
||||
rule_products = rule.apply(reactants)
|
||||
|
||||
# Check if products match (in both directions if extras are not allowed)
|
||||
for product_set in rule_products:
|
||||
covered, exact = FormatConverter.smiles_covered_by(
|
||||
products,
|
||||
product_set.product_set,
|
||||
standardize=True,
|
||||
canonicalize_tautomers=True,
|
||||
return_exact_match=True,
|
||||
)
|
||||
|
||||
if covered and not options["dry-run"]:
|
||||
logger.debug(f"Reaction {reaction.uuid} explained by rule {rule.uuid}")
|
||||
re = ReactionExplanation()
|
||||
re.run_uuid = RUN_UUID
|
||||
re.run_start = RUN_START
|
||||
re.reaction = reaction
|
||||
re.rule = rule
|
||||
re.exact = exact
|
||||
re.save()
|
||||
# Its explained, if there are more sets skip them
|
||||
break
|
||||
113
epdb/migrations/0028_auto_20260812_0902.py
Normal file
113
epdb/migrations/0028_auto_20260812_0902.py
Normal file
@ -0,0 +1,113 @@
|
||||
# Generated by Django 6.0.3 on 2026-08-12 09:02
|
||||
|
||||
from django.conf import settings as s
|
||||
from django.db import migrations
|
||||
from envipy_additional_information import Likelihood, RuleLikelihood
|
||||
|
||||
NEW_RULE = {
|
||||
"parent": "bt0005",
|
||||
"name": "bt0005-3667",
|
||||
"description": "vic-unsubstituted Aromatic > vic-Dihydroxyaromatic",
|
||||
"smirks": "[#8:7]([H])-[#6:1]([H])-1-[#6:2]=[#6:3]-[#6:4]=[#6:5]-[#6:6]([H])-1-[#8:8]([H])>>[#8:7]([H])-[#6:1]=1-[#6:2]=[#6:3]-[#6:4]=[#6:5]-[#6:6]=1-[#8:8]([H])",
|
||||
"scenario_name": "bt0005-3667 aerobic likelihood",
|
||||
"scenario_aerobic_likelihood": RuleLikelihood(likelihood=Likelihood.LIKELY),
|
||||
}
|
||||
|
||||
RULE_FIXES = {
|
||||
"bt0005-4282": "[c:1]([H])1:[c:2]([H]):[#6,#7;a:3]:[c:4]:[c:5]:[c:6]1>>[c:1]([#8])1:[c:2]([#8]):[#6,#7;a:3]:[c:4]:[c:5]:[c:6]1",
|
||||
"bt0014-4215": "[c:1]([H])1[c:8][#6,#7;a:7][c:6][c:5][c:4]1[#8;!$([OH]c:[#6,#7;a:7]([OH])):9]([H])>>[#8:9]([H])[c:4]1:[c:5]:[c:6]:[#6,#7;a:7]:[c:8]:[c:1]1[#8]([H])",
|
||||
# "bt0063-3938": "[#1,#6:6][#7;X3;!$(NC1CC1)!$([N][C]=O)!$([!#8]CNC=O):1]([#1,#6:7])[#6;A;X4:2][H:3]>>[#1,#6:6][#7;X3:1]([H:3])(=[#1,#6:7]).[#6;A:2]=O",
|
||||
# CN1C=NC2=C1C(=O)N(C)C(=O)N2 not working anymore with bt0063-3938 if change above is applied
|
||||
"bt0063-3938": "[#1,#6:6][#7;X3;!$(NC1CC1)!$([N][C]=O)!$([!#8]CNC=O):1]([#1,#6:7])[#6;A;X4:2][H:3]>>[#1,#6:6][#7;X3:1]([#1,#6:7])[H:3].[#6;A:2]=O",
|
||||
"bt0068-3564": "[#7:4]!@-[#6:2](!@-[#7:1])=[O:5]>>[#7:4]-[#6:2](-[O+0H1])=[O:5].[#7H1:1]",
|
||||
"bt0180-2844": "[H][C:2]([#6:5]([H])([H])([H]))([#1,#6:4])!@-[#6:1]([H])([H])-[#6:3](-[#8-:8])=[O:6]>>[#6:5]([H])([H])([H])\\[#6:2](-[#1,#6:4])=[#6H:1]\\[#6:3](-[#8-:8])=[O:6]",
|
||||
"bt0181-1278": "[#8-:1]-[#6:2](=[O:11])-[#6:7]=[#6:8]-[#6:3](-[H])=[#6:5](-Cl)-[#6:6](-[#8-:10])=[O:9]>>[O+0H1:10]-[#6:6](=[O:9])-[#6:5]=[#6:3]-1-[O+0:1]-[#6:2](=[O:11])-[#6:7]=[#6:8]-1",
|
||||
"bt0298-3335": "[#6:1][N+:2]#[C:3]>>[#6:1]-[#7H2:2]-[#6:3]=O",
|
||||
"bt0322-3393": "[H:10]\\[#6:6](=[#6:9](/[#6:1]([H])([H])([H]))-[#6:11]-[#6:12]-[#6:13]=[#6:14])-[#6:5](-[#16:7])=[O:8]>>[H:10]\\[#6:6](-[#6:5](-[#16:7])=[O:8])=[#6:9](\\[#6:11]-[#6:12]-[#6:13]=[#6:14])-[#6:1]-[#6](-[#8-])=O",
|
||||
"bt0343-2675": "[#8-]-[#6](=O)-[c:1]1[c:6][cH:7][c:8](-[#7H2,#8H1:9])[cH:10][c:11]1>>[#8H][c:1]1[c:6][c:7][c:8]([*:9])[c:10][c:11]1",
|
||||
"bt0350-3319": "[#6:6][#7:3][#6;!R:2]=[#7;!R:1][#6:5]>>[#6:5][#7:1][#6:2]=O.[#6:6][#7:3]", # Trig before 5 -> all of them shouldn't
|
||||
"bt0374-4081": "[cH:4]1[c:16][c:15][c:14][c:13][c:3]1[#7,#8:2][c:1]1[c:8][c:9][c:10][c:11][c:12]1>>[#7,#8:2]-[c:1]1[c:12][c:11][c:10][c:9][c:8]1[c:13]1[c:14][c:15][c:16][c:4](-[#8])[c:3]1-[#8]",
|
||||
"bt0378-3188": "[#8-:7][c:1]1[c:6]([#7+]([#8-])=O)[c:5][c:4]([#7+:9]([#8-])=O)[c:3][c:2]1([#7+:8]([#8-])=O)>>[#8+0:7]=[#6:1]1-[#6:6]-[#6:5]-[#6:4]([#7+:9]([#8-])=O)-[#6:3]-[#6:2]1([#7+:8]([#8-])=O)",
|
||||
"bt0379-3190": "[#9,#17,#35,#53]-[#6:1](-[H])-1-[#6:5]-,=[#6:6]-[#6:7]-,=[#6:8]-[#6:2](-[H])-1-[#9,#17,#35,#53]>>[#6:6]~1-[#6:7]~[#6:8]-[#6:2]=[#6:1]-[#6:5]~1",
|
||||
"bt0393-3367": "[#6:5]-[#6:1](-[#7:2](-[H])(-[H]))=[S+:3]-[#8-:6]>>[#6:5]-[#6:1](=[#7H1:2])-[S+0:3](=[O])-[#8+0H1:6]",
|
||||
}
|
||||
|
||||
|
||||
def forward_func(apps, schema_editor):
|
||||
ContentType = apps.get_model("contenttypes", "ContentType")
|
||||
|
||||
pkg_class = s.EPDB_PACKAGE_MODEL
|
||||
|
||||
if len(pkg_class.split(".")) != 2:
|
||||
raise ValueError(
|
||||
f"EPDB_PACKAGE_MODEL must be of the form 'app_label.model_name', got {pkg_class}"
|
||||
)
|
||||
|
||||
app_label, model_name = pkg_class.split(".")
|
||||
Package = apps.get_model(app_label, model_name)
|
||||
SimpleAmbitRule = apps.get_model("epdb", "SimpleAmbitRule")
|
||||
ParallelRule = apps.get_model("epdb", "ParallelRule")
|
||||
Scenario = apps.get_model("epdb", "Scenario")
|
||||
AdditionalInformation = apps.get_model("epdb", "AdditionalInformation")
|
||||
simple_ambit_rule_ct = ContentType.objects.get_for_model(SimpleAmbitRule)
|
||||
|
||||
if Package.objects.filter(name="EAWAG-BBD").exists():
|
||||
p = Package.objects.get(name="EAWAG-BBD")
|
||||
|
||||
if not SimpleAmbitRule.objects.filter(package=p, name=NEW_RULE["name"]).exists():
|
||||
# Create Missing Rule
|
||||
new_sr = SimpleAmbitRule()
|
||||
new_sr.polymorphic_ctype = simple_ambit_rule_ct
|
||||
new_sr.package = p
|
||||
new_sr.name = NEW_RULE["name"]
|
||||
new_sr.description = NEW_RULE["description"]
|
||||
new_sr.smirks = NEW_RULE["smirks"]
|
||||
new_sr.save()
|
||||
|
||||
new_sr.url = "{}/simple-ambit-rule/{}".format(new_sr.package.url, new_sr.uuid)
|
||||
new_sr.save()
|
||||
|
||||
# Add likelihood
|
||||
new_scen = Scenario()
|
||||
new_scen.package = p
|
||||
new_scen.name = NEW_RULE["scenario_name"]
|
||||
new_scen.save()
|
||||
|
||||
new_scen.url = "{}/scenario/{}".format(new_scen.package.url, new_scen.uuid)
|
||||
new_scen.save()
|
||||
|
||||
ai = NEW_RULE["scenario_aerobic_likelihood"]
|
||||
new_add_inf = AdditionalInformation()
|
||||
new_add_inf.package = p
|
||||
new_add_inf.type = ai.__class__.__name__
|
||||
new_add_inf.data = ai.model_dump(mode="json")
|
||||
new_add_inf.scenario = new_scen
|
||||
new_add_inf.save()
|
||||
|
||||
new_add_inf.url = "{}/additional-information/{}".format(
|
||||
new_add_inf.scenario.url, new_add_inf.uuid
|
||||
)
|
||||
new_add_inf.save()
|
||||
|
||||
# Link Scenario
|
||||
new_sr.scenarios.add(new_scen)
|
||||
|
||||
# Link to bt0005
|
||||
pr = ParallelRule.objects.get(package=p, name="bt0005")
|
||||
pr.simple_rules.add(new_sr)
|
||||
|
||||
# Update others
|
||||
for rule_name, smirks in RULE_FIXES.items():
|
||||
sr = SimpleAmbitRule.objects.get(package=p, name=rule_name)
|
||||
sr.smirks = smirks
|
||||
sr.save()
|
||||
|
||||
|
||||
class Migration(migrations.Migration):
|
||||
dependencies = [
|
||||
("epdb", "0027_alter_compound_aliases_and_more"),
|
||||
]
|
||||
|
||||
operations = [
|
||||
migrations.RunPython(forward_func, reverse_code=migrations.RunPython.noop),
|
||||
]
|
||||
@ -0,0 +1,63 @@
|
||||
# Generated by Django 6.0.3 on 2026-08-13 09:58
|
||||
|
||||
import django.db.models.deletion
|
||||
import django.utils.timezone
|
||||
import model_utils.fields
|
||||
from django.db import migrations, models
|
||||
|
||||
|
||||
class Migration(migrations.Migration):
|
||||
dependencies = [
|
||||
("epdb", "0028_auto_20260812_0902"),
|
||||
]
|
||||
|
||||
operations = [
|
||||
migrations.CreateModel(
|
||||
name="ReactionExplanation",
|
||||
fields=[
|
||||
(
|
||||
"id",
|
||||
models.BigAutoField(
|
||||
auto_created=True, primary_key=True, serialize=False, verbose_name="ID"
|
||||
),
|
||||
),
|
||||
(
|
||||
"created",
|
||||
model_utils.fields.AutoCreatedField(
|
||||
default=django.utils.timezone.now, editable=False, verbose_name="created"
|
||||
),
|
||||
),
|
||||
(
|
||||
"modified",
|
||||
model_utils.fields.AutoLastModifiedField(
|
||||
default=django.utils.timezone.now, editable=False, verbose_name="modified"
|
||||
),
|
||||
),
|
||||
("run_uuid", models.UUIDField()),
|
||||
("run_start", models.DateTimeField()),
|
||||
("exact", models.BooleanField(default=False)),
|
||||
(
|
||||
"reaction",
|
||||
models.ForeignKey(
|
||||
on_delete=django.db.models.deletion.CASCADE, to="epdb.reaction"
|
||||
),
|
||||
),
|
||||
(
|
||||
"rule",
|
||||
models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to="epdb.rule"),
|
||||
),
|
||||
],
|
||||
options={
|
||||
"abstract": False,
|
||||
},
|
||||
),
|
||||
migrations.AddField(
|
||||
model_name="reaction",
|
||||
name="explained_by",
|
||||
field=models.ManyToManyField(
|
||||
related_name="explained_reactions",
|
||||
through="epdb.ReactionExplanation",
|
||||
to="epdb.rule",
|
||||
),
|
||||
),
|
||||
]
|
||||
37
epdb/migrations/0030_auto_20260814_0741.py
Normal file
37
epdb/migrations/0030_auto_20260814_0741.py
Normal file
@ -0,0 +1,37 @@
|
||||
# Generated by Django 6.0.3 on 2026-08-14 07:41
|
||||
|
||||
from django.db import migrations
|
||||
|
||||
|
||||
def forward_func(apps, schema_editor):
|
||||
ContentType = apps.get_model("contenttypes", "ContentType")
|
||||
AdditionalInformation = apps.get_model("epdb", "AdditionalInformation")
|
||||
|
||||
models = {}
|
||||
|
||||
for c in ContentType.objects.all():
|
||||
try:
|
||||
models[(c.app_label, c.model)] = apps.get_model(c.app_label, c.model)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
for ai in AdditionalInformation.objects.all():
|
||||
if ai.url is None:
|
||||
if ai.content_type is None:
|
||||
ai.url = "{}/additional-information/{}".format(ai.scenario.url, ai.uuid)
|
||||
else:
|
||||
model = models[(ai.content_type.app_label, ai.content_type.model)]
|
||||
obj = model.objects.get(pk=ai.object_id)
|
||||
ai.url = "{}/additional-information/{}".format(obj.url, ai.uuid)
|
||||
|
||||
ai.save()
|
||||
|
||||
|
||||
class Migration(migrations.Migration):
|
||||
dependencies = [
|
||||
("epdb", "0029_reactionexplanation_reaction_explained_by"),
|
||||
]
|
||||
|
||||
operations = [
|
||||
migrations.RunPython(forward_func, reverse_code=migrations.RunPython.noop),
|
||||
]
|
||||
123
epdb/models.py
123
epdb/models.py
@ -859,9 +859,15 @@ class Compound(
|
||||
@property
|
||||
def related_reactions(self):
|
||||
return (
|
||||
Reaction.objects.filter(package=self.package, educts__in=[self.default_structure])
|
||||
| Reaction.objects.filter(package=self.package, products__in=[self.default_structure])
|
||||
).order_by("name")
|
||||
(
|
||||
Reaction.objects.filter(package=self.package, educts__in=[self.default_structure])
|
||||
| Reaction.objects.filter(
|
||||
package=self.package, products__in=[self.default_structure]
|
||||
)
|
||||
)
|
||||
.distinct()
|
||||
.order_by("name")
|
||||
)
|
||||
|
||||
@property
|
||||
def related_nodes(self):
|
||||
@ -1735,6 +1741,14 @@ class SequentialRuleOrdering(models.Model):
|
||||
order_index = models.IntegerField(null=False, blank=False)
|
||||
|
||||
|
||||
class ReactionExplanation(TimeStampedModel):
|
||||
run_uuid = models.UUIDField(null=False, blank=False)
|
||||
run_start = models.DateTimeField(null=False, blank=False)
|
||||
reaction = models.ForeignKey("epdb.Reaction", on_delete=models.CASCADE)
|
||||
rule = models.ForeignKey("epdb.Rule", on_delete=models.CASCADE)
|
||||
exact = models.BooleanField(default=False)
|
||||
|
||||
|
||||
class Reaction(
|
||||
EnviPathModel, AliasMixin, ScenarioMixin, ReactionIdentifierMixin, AdditionalInformationMixin
|
||||
):
|
||||
@ -1760,6 +1774,12 @@ class Reaction(
|
||||
|
||||
external_identifiers = GenericRelation("ExternalIdentifier")
|
||||
|
||||
explained_by = models.ManyToManyField(
|
||||
"epdb.Rule",
|
||||
through="ReactionExplanation",
|
||||
related_name="explained_reactions",
|
||||
)
|
||||
|
||||
def _url(self):
|
||||
return "{}/reaction/{}".format(self.package.url, self.uuid)
|
||||
|
||||
@ -2173,7 +2193,7 @@ class Pathway(EnviPathModel, AliasMixin, ScenarioMixin, AdditionalInformationMix
|
||||
|
||||
row += [cs.smiles, cs.get_name(), n.depth]
|
||||
|
||||
edges = self.edges.filter(end_nodes__in=[n])
|
||||
edges = self.edges.filter(end_nodes=n)
|
||||
if len(edges):
|
||||
for e in edges:
|
||||
_row = row.copy()
|
||||
@ -2585,7 +2605,7 @@ class Node(EnviPathModel, AliasMixin, ScenarioMixin, AdditionalInformationMixin)
|
||||
collected[str(ai.scenario.uuid)]["proposed"] = True
|
||||
|
||||
if ai.type == "Confidence":
|
||||
collected[str(ai.scenario.uuid)]["Confidence"] = ai.get().level
|
||||
collected[str(ai.scenario.uuid)]["Confidence"] = ai.get().level.value
|
||||
|
||||
if ai.type == "TransformationProductImportance":
|
||||
collected[str(ai.scenario.uuid)]["Transformation product importance"] = (
|
||||
@ -2815,6 +2835,49 @@ class PackageBasedModel(EPModel):
|
||||
)
|
||||
multigen_eval = models.BooleanField(null=False, blank=False, default=False)
|
||||
|
||||
@property
|
||||
def pr_curve(self):
|
||||
if self.model_status != self.FINISHED:
|
||||
raise ValueError(f"Expected {self.FINISHED} but model is in status {self.model_status}")
|
||||
|
||||
res = []
|
||||
|
||||
thresholds = self.eval_results["average_precision_per_threshold"].keys()
|
||||
|
||||
for t in thresholds:
|
||||
res.append(
|
||||
{
|
||||
"precision": self.eval_results["average_precision_per_threshold"][t],
|
||||
"recall": self.eval_results["average_recall_per_threshold"][t],
|
||||
"threshold": float(t),
|
||||
}
|
||||
)
|
||||
|
||||
return res
|
||||
|
||||
@property
|
||||
def mg_pr_curve(self):
|
||||
if self.model_status != self.FINISHED:
|
||||
raise ValueError(f"Expected {self.FINISHED} but model is in status {self.model_status}")
|
||||
|
||||
if not self.multigen_eval:
|
||||
raise ValueError("MG PR Curve is only available for multigen models")
|
||||
|
||||
res = []
|
||||
|
||||
thresholds = self.eval_results["multigen_average_precision_per_threshold"].keys()
|
||||
|
||||
for t in thresholds:
|
||||
res.append(
|
||||
{
|
||||
"precision": self.eval_results["multigen_average_precision_per_threshold"][t],
|
||||
"recall": self.eval_results["multigen_average_recall_per_threshold"][t],
|
||||
"threshold": float(t),
|
||||
}
|
||||
)
|
||||
|
||||
return res
|
||||
|
||||
def parameters(self):
|
||||
params = {
|
||||
"Model Evaluation Threshold": f"{self.threshold:.2f}",
|
||||
@ -2867,49 +2930,6 @@ class PackageBasedModel(EPModel):
|
||||
],
|
||||
}
|
||||
|
||||
@property
|
||||
def pr_curve(self):
|
||||
if self.model_status != self.FINISHED:
|
||||
raise ValueError(f"Expected {self.FINISHED} but model is in status {self.model_status}")
|
||||
|
||||
res = []
|
||||
|
||||
thresholds = self.eval_results["average_precision_per_threshold"].keys()
|
||||
|
||||
for t in thresholds:
|
||||
res.append(
|
||||
{
|
||||
"precision": self.eval_results["average_precision_per_threshold"][t],
|
||||
"recall": self.eval_results["average_recall_per_threshold"][t],
|
||||
"threshold": float(t),
|
||||
}
|
||||
)
|
||||
|
||||
return res
|
||||
|
||||
@property
|
||||
def mg_pr_curve(self):
|
||||
if self.model_status != self.FINISHED:
|
||||
raise ValueError(f"Expected {self.FINISHED} but model is in status {self.model_status}")
|
||||
|
||||
if not self.multigen_eval:
|
||||
raise ValueError("MG PR Curve is only available for multigen models")
|
||||
|
||||
res = []
|
||||
|
||||
thresholds = self.eval_results["multigen_average_precision_per_threshold"].keys()
|
||||
|
||||
for t in thresholds:
|
||||
res.append(
|
||||
{
|
||||
"precision": self.eval_results["multigen_average_precision_per_threshold"][t],
|
||||
"recall": self.eval_results["multigen_average_recall_per_threshold"][t],
|
||||
"threshold": float(t),
|
||||
}
|
||||
)
|
||||
|
||||
return res
|
||||
|
||||
@cached_property
|
||||
def applicable_rules(self) -> List["Rule"]:
|
||||
"""
|
||||
@ -3148,7 +3168,6 @@ class PackageBasedModel(EPModel):
|
||||
avg_mg_acc = mg_acc / len(root_compounds)
|
||||
precision = {k: sum(v) / len(v) if len(v) > 0 else 0 for k, v in precision.items()}
|
||||
recall = {k: sum(v) / len(v) if len(v) > 0 else 0 for k, v in recall.items()}
|
||||
logger.info("Average Multigen Accuracy: {:.2f}".format(avg_mg_acc))
|
||||
return avg_mg_acc, precision, recall
|
||||
|
||||
# If there are eval packages perform single generation evaluation on them instead of random splits
|
||||
@ -4281,6 +4300,9 @@ class ClassifierPluginModel(PackageBasedModel):
|
||||
instance = impl(conf)
|
||||
return instance
|
||||
|
||||
def parameters(self):
|
||||
return self.instance().parameters()
|
||||
|
||||
def build_dataset(self):
|
||||
"""
|
||||
Required by general model contract but actual implementation resides in plugin.
|
||||
@ -4501,6 +4523,9 @@ class PropertyPluginModel(PackageBasedModel):
|
||||
instance = impl()
|
||||
return instance
|
||||
|
||||
def parameters(self):
|
||||
return self.instance().parameters()
|
||||
|
||||
def build_dataset(self):
|
||||
"""
|
||||
Required by general model contract but actual implementation resides in plugin.
|
||||
|
||||
@ -1145,19 +1145,23 @@ def package_model(request, package_uuid, model_uuid):
|
||||
for pr in pred_res:
|
||||
if len(pr) > 0:
|
||||
products = []
|
||||
|
||||
for prod_set in pr.product_sets:
|
||||
logger.debug(f"Checking {prod_set}")
|
||||
products.append(tuple([x for x in prod_set]))
|
||||
|
||||
res["pred"].append(
|
||||
{
|
||||
"products": list(set(products)),
|
||||
"probability": pr.probability,
|
||||
"btrule": {k: getattr(pr.rule, k) for k in ["url", "name"]}
|
||||
if pr.rule is not None
|
||||
else None,
|
||||
}
|
||||
)
|
||||
products = list(set(products))
|
||||
|
||||
for prod in products:
|
||||
res["pred"].append(
|
||||
{
|
||||
"products": list(prod),
|
||||
"probability": pr.probability,
|
||||
"btrule": {k: getattr(pr.rule, k) for k in ["url", "name"]}
|
||||
if pr.rule is not None
|
||||
else None,
|
||||
}
|
||||
)
|
||||
|
||||
# Sort data by prob desc
|
||||
res["pred"] = sorted(
|
||||
|
||||
@ -118,37 +118,38 @@
|
||||
</div>
|
||||
{% endif %}
|
||||
|
||||
<!-- Model Parameters Panel -->
|
||||
<div class="collapse-arrow bg-base-200 collapse">
|
||||
<input type="checkbox" checked />
|
||||
<div class="collapse-title text-xl font-medium">Model Parameters</div>
|
||||
<div class="collapse-content">
|
||||
<div class="flex justify-center">
|
||||
<div
|
||||
id="model-stats"
|
||||
class="overflow-x-auto rounded-box shadow-md bg-base-100"
|
||||
>
|
||||
<table class="table table-fixed w-full">
|
||||
<thead class="text-base">
|
||||
<tr>
|
||||
<th class="w-3/5">Parameter</th>
|
||||
<th>Value</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
{% for param, value in model.parameters.items %}
|
||||
{% if model.parameters %}
|
||||
<!-- Model Parameters Panel -->
|
||||
<div class="collapse-arrow bg-base-200 collapse">
|
||||
<input type="checkbox" checked />
|
||||
<div class="collapse-title text-xl font-medium">Model Parameters</div>
|
||||
<div class="collapse-content">
|
||||
<div class="flex justify-center">
|
||||
<div
|
||||
id="model-stats"
|
||||
class="overflow-x-auto rounded-box shadow-md bg-base-100"
|
||||
>
|
||||
<table class="table table-fixed w-full">
|
||||
<thead class="text-base">
|
||||
<tr>
|
||||
<td>{{ param }}</td>
|
||||
<td>{{ value }}</td>
|
||||
<th class="w-3/5">Parameter</th>
|
||||
<th>Value</th>
|
||||
</tr>
|
||||
{% endfor %}
|
||||
</tbody>
|
||||
</table>
|
||||
</thead>
|
||||
<tbody>
|
||||
{% for param, value in model.parameters.items %}
|
||||
<tr>
|
||||
<td>{{ param }}</td>
|
||||
<td>{{ value }}</td>
|
||||
</tr>
|
||||
{% endfor %}
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{% endif %}
|
||||
{% endblock %}
|
||||
|
||||
{% block usemodel %}
|
||||
|
||||
@ -109,12 +109,12 @@
|
||||
res += "<th scope='row'>" + cnt + "</th>";
|
||||
res +=
|
||||
"<th scope='row'>" +
|
||||
data[transformation]["products"][0].join(", ") +
|
||||
data[transformation]["products"].join(", ") +
|
||||
"</th>";
|
||||
res +=
|
||||
"<th scope='row'>" +
|
||||
"<img width='400' src='{% url 'depict' %}?smiles=" +
|
||||
encodeURIComponent(data[transformation]["products"][0].join(".")) +
|
||||
encodeURIComponent(data[transformation]["products"].join(".")) +
|
||||
"'></th>";
|
||||
res +=
|
||||
"<th scope='row'>" +
|
||||
|
||||
@ -139,7 +139,7 @@
|
||||
</tr>
|
||||
<tr>
|
||||
<td>Model</td>
|
||||
<td>{{ half_lifes.0.model }}</td>
|
||||
<td>{{ half_lifes.0.model.value }}</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
|
||||
@ -96,22 +96,22 @@
|
||||
|
||||
<!-- Other Prediction Settings -->
|
||||
{% if meta.available_settings|length > 1 %}
|
||||
<div class="collapse-arrow bg-base-200 collapse">
|
||||
<input type="checkbox" />
|
||||
<div class="collapse-title text-xl font-medium">
|
||||
Other Prediction Settings
|
||||
<div class="collapse-arrow bg-base-200 collapse">
|
||||
<input type="checkbox" />
|
||||
<div class="collapse-title text-xl font-medium">
|
||||
Other Prediction Settings
|
||||
</div>
|
||||
<div class="collapse-content space-y-3">
|
||||
{% for setting in meta.available_settings %}
|
||||
{% if setting != user.default_setting %}
|
||||
{% with setting_to_render=setting can_be_default=True %}
|
||||
{% include "objects/setting_template.html" %}
|
||||
{% endwith %}
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
<div class="collapse-content space-y-3">
|
||||
{% for setting in meta.available_settings %}
|
||||
{% if setting != user.default_setting %}
|
||||
{% with setting_to_render=setting can_be_default=True %}
|
||||
{% include "objects/setting_template.html" %}
|
||||
{% endwith %}
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
</div>
|
||||
</div>
|
||||
{% endif %}
|
||||
{% endif %}
|
||||
</div>
|
||||
|
||||
<script>
|
||||
|
||||
@ -58,7 +58,7 @@ class MultiGenTest(TestCase):
|
||||
|
||||
self.assertEqual(
|
||||
pw.setting_with_overrides.max_depth,
|
||||
f"{num_tps} (this is an override for this particular pathway)",
|
||||
5,
|
||||
)
|
||||
self.assertEqual(
|
||||
pw.setting_with_overrides.max_nodes,
|
||||
|
||||
@ -47,7 +47,7 @@ class ModelViewTest(TestCase):
|
||||
|
||||
expected = [
|
||||
{
|
||||
"products": [["CCN(CC)C(=O)C1=CC(C=O)=CC=C1"]],
|
||||
"products": ["CCN(CC)C(=O)C1=CC(C=O)=CC=C1"],
|
||||
"probability": 0.75,
|
||||
"btrule": {
|
||||
"url": "http://localhost:8000/package/1869d3f0-60bb-41fd-b6f8-afa75ffb09d3/simple-ambit-rule/2f2e0c39-e109-4836-959f-2bda2524f022",
|
||||
@ -55,7 +55,7 @@ class ModelViewTest(TestCase):
|
||||
},
|
||||
},
|
||||
{
|
||||
"products": [["O=C(O)C1=CC(CO)=CC=C1", "CCNCC"]],
|
||||
"products": ["O=C(O)C1=CC(CO)=CC=C1", "CCNCC"],
|
||||
"probability": 0.25,
|
||||
"btrule": {
|
||||
"url": "http://localhost:8000/package/1869d3f0-60bb-41fd-b6f8-afa75ffb09d3/simple-ambit-rule/0e6e9290-b658-4450-b291-3ec19fa19206",
|
||||
@ -63,7 +63,7 @@ class ModelViewTest(TestCase):
|
||||
},
|
||||
},
|
||||
{
|
||||
"products": [["CCNC(=O)C1=CC(CO)=CC=C1", "CC=O"]],
|
||||
"products": ["CCNC(=O)C1=CC(CO)=CC=C1", "CC=O"],
|
||||
"probability": 0.0,
|
||||
"btrule": {
|
||||
"url": "http://localhost:8000/package/1869d3f0-60bb-41fd-b6f8-afa75ffb09d3/simple-ambit-rule/27a3a353-0b66-4228-bd16-e407949e90df",
|
||||
|
||||
@ -68,6 +68,8 @@ class PredictionResult(object):
|
||||
|
||||
|
||||
class FormatConverter(object):
|
||||
tautomer_enumerator = rdMolStandardize.TautomerEnumerator()
|
||||
|
||||
@staticmethod
|
||||
def mass(smiles):
|
||||
return Descriptors.MolWt(FormatConverter.from_smiles(smiles))
|
||||
@ -240,8 +242,9 @@ class FormatConverter(object):
|
||||
Chem.RemoveStereochemistry(res_mol)
|
||||
|
||||
if canonicalize_tautomers:
|
||||
te = rdMolStandardize.TautomerEnumerator() # idem
|
||||
res_mol = te.Canonicalize(res_mol)
|
||||
tautomers = FormatConverter.tautomer_enumerator.Enumerate(res_mol)
|
||||
if len(tautomers) >= 1:
|
||||
res_mol = FormatConverter.tautomer_enumerator.PickCanonical(tautomers)
|
||||
|
||||
return Chem.MolToSmiles(res_mol, kekuleSmiles=True)
|
||||
|
||||
@ -389,7 +392,7 @@ class FormatConverter(object):
|
||||
prods.append(p)
|
||||
|
||||
except ValueError as e:
|
||||
logger.error(f"Sanitizing and converting failed:\n{e}")
|
||||
logger.debug(f"Sanitizing and converting failed:\n{e}")
|
||||
continue
|
||||
|
||||
if len(prods):
|
||||
@ -397,7 +400,8 @@ class FormatConverter(object):
|
||||
pss.add(ps)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Applying {smirks} on {smiles} failed:\n{e}")
|
||||
logger.debug(f"Applying {smirks} on {smiles} failed:\n{e}")
|
||||
pass
|
||||
|
||||
return list(pss)
|
||||
|
||||
@ -444,6 +448,7 @@ class FormatConverter(object):
|
||||
r_smiles: List[str],
|
||||
standardize: bool = True,
|
||||
canonicalize_tautomers: bool = True,
|
||||
return_exact_match: bool = False,
|
||||
) -> bool:
|
||||
"""
|
||||
Check if all SMILES in the left list are covered by (contained in) the right list.
|
||||
@ -482,8 +487,10 @@ class FormatConverter(object):
|
||||
if standardize:
|
||||
for smi in l_smiles:
|
||||
try:
|
||||
smi = FormatConverter.standardize(
|
||||
smi, remove_stereo=True, canonicalize_tautomers=canonicalize_tautomers
|
||||
smi = FormatConverter.canonicalize(
|
||||
FormatConverter.standardize(
|
||||
smi, remove_stereo=True, canonicalize_tautomers=canonicalize_tautomers
|
||||
)
|
||||
)
|
||||
except Exception:
|
||||
# :shrug:
|
||||
@ -497,8 +504,12 @@ class FormatConverter(object):
|
||||
if standardize:
|
||||
for smi in r_smiles:
|
||||
try:
|
||||
smi = FormatConverter.standardize(
|
||||
smi, remove_stereo=True, canonicalize_tautomers=canonicalize_tautomers
|
||||
smi = FormatConverter.canonicalize(
|
||||
FormatConverter.standardize(
|
||||
smi,
|
||||
remove_stereo=True,
|
||||
canonicalize_tautomers=canonicalize_tautomers,
|
||||
)
|
||||
)
|
||||
except Exception:
|
||||
# :shrug:
|
||||
@ -507,8 +518,11 @@ class FormatConverter(object):
|
||||
standardized_r_smiles.append(smi)
|
||||
else:
|
||||
standardized_r_smiles = r_smiles
|
||||
|
||||
return len(set(standardized_l_smiles).difference(set(standardized_r_smiles))) == 0
|
||||
if not return_exact_match:
|
||||
return len(set(standardized_l_smiles).difference(set(standardized_r_smiles))) == 0
|
||||
return len(set(standardized_l_smiles).difference(set(standardized_r_smiles))) == 0, set(
|
||||
standardized_l_smiles
|
||||
) == set(standardized_r_smiles)
|
||||
|
||||
|
||||
class Standardizer(ABC):
|
||||
|
||||
@ -4,11 +4,13 @@ import hmac
|
||||
import json
|
||||
import logging
|
||||
import uuid
|
||||
from abc import ABC, abstractmethod
|
||||
from collections import defaultdict
|
||||
from datetime import datetime
|
||||
from typing import Any, Dict, List, Optional, TYPE_CHECKING
|
||||
from typing import Any, Dict, List, Optional, TYPE_CHECKING, Type
|
||||
|
||||
from django.conf import settings as s
|
||||
from envipy_additional_information import EnviPyModel, UIConfig
|
||||
from ninja import Schema
|
||||
from pydantic import HttpUrl, ValidationError
|
||||
|
||||
@ -156,7 +158,7 @@ class EnzymeExportSchema(RefEnzymeExportSchema):
|
||||
|
||||
|
||||
class EnzymeRuleExportSchema(RefRuleExportSchema):
|
||||
enzymes: List[EnzymeExportSchema] | None = None
|
||||
enzymes: List[EnzymeExportSchema] = []
|
||||
|
||||
@staticmethod
|
||||
def resolve_enzymes(obj):
|
||||
@ -319,15 +321,20 @@ class PackageExportSchema(Schema):
|
||||
return AdditionalInformation.objects.filter(package=obj)
|
||||
|
||||
|
||||
class PackageExporter:
|
||||
class Exporter(ABC):
|
||||
def __init__(self, package: Package):
|
||||
self._raw_package = package
|
||||
|
||||
def do_export(self):
|
||||
return PackageExporter._export_package_as_json(self._raw_package)
|
||||
return self._export()
|
||||
|
||||
@staticmethod
|
||||
def _export_package_as_json(package: Package) -> Dict[str, Any]:
|
||||
@abstractmethod
|
||||
def _export(self):
|
||||
pass
|
||||
|
||||
|
||||
class PackageExporter(Exporter):
|
||||
def _export(self) -> Dict[str, Any]:
|
||||
"""
|
||||
Dumps a Package and all its related objects as JSON.
|
||||
|
||||
@ -338,11 +345,126 @@ class PackageExporter:
|
||||
Dict containing the complete package data as JSON-serializable structure
|
||||
"""
|
||||
|
||||
data = PackageExportSchema.from_orm(package)
|
||||
data = PackageExportSchema.from_orm(self._raw_package)
|
||||
|
||||
return data.model_dump(mode="json")
|
||||
|
||||
|
||||
class PathwayExporter(Exporter):
|
||||
def __init__(self, package: Package, add_infs_to_export: List[str] = []):
|
||||
super().__init__(package)
|
||||
self._add_infs_to_export = add_infs_to_export
|
||||
|
||||
def _flatten_additional_information(self, ai: AdditionalInformation) -> dict[str, Any]:
|
||||
model_cls: Type[EnviPyModel] = type(ai.get())
|
||||
|
||||
def _flatten(d: dict, parent_key: str = "") -> dict[str, Any]:
|
||||
items: dict[str, Any] = {}
|
||||
for key, value in d.items():
|
||||
new_key = f"{parent_key}__{key.lower()}" if parent_key else key.lower()
|
||||
if isinstance(value, dict):
|
||||
items.update(_flatten(value, new_key))
|
||||
else:
|
||||
items[new_key] = value
|
||||
return items
|
||||
|
||||
flat = _flatten(ai.data, ai.type)
|
||||
|
||||
ui_class = getattr(model_cls, "UI", None)
|
||||
if ui_class is None:
|
||||
return flat
|
||||
|
||||
for f in model_cls.model_fields:
|
||||
ui_info = getattr(ui_class, f, None)
|
||||
|
||||
if not isinstance(ui_info, UIConfig) or ui_info.unit is None:
|
||||
continue
|
||||
|
||||
flat[f"{model_cls.__name__}__{f}__unit"] = ui_info.unit
|
||||
|
||||
return flat
|
||||
|
||||
def _export(self):
|
||||
from io import StringIO
|
||||
from csv import DictWriter
|
||||
|
||||
rows = []
|
||||
|
||||
for pw in self._raw_package.pathways.all():
|
||||
for n in pw.nodes:
|
||||
for scen in pw.scenarios.all():
|
||||
row = {
|
||||
"pathway_name": pw.name,
|
||||
"pathway_id": str(pw.url),
|
||||
"node_depth": n.depth,
|
||||
"compound_id": str(n.default_node_label.compound.url),
|
||||
"pubchem_ID": n.default_node_label.pubchem_compound_id,
|
||||
"compound_name": n.default_node_label.compound.name,
|
||||
"compound_smiles": n.default_node_label.smiles,
|
||||
"scenario_id": str(scen.url),
|
||||
"scenario_name": scen.name,
|
||||
"scenario_type": scen.scenario_type,
|
||||
"scenario_description": scen.description,
|
||||
}
|
||||
|
||||
if self._add_infs_to_export:
|
||||
ai_qs = AdditionalInformation.objects.filter(
|
||||
scenario=scen, type__in=self._add_infs_to_export
|
||||
)
|
||||
else:
|
||||
ai_qs = AdditionalInformation.objects.filter(scenario=scen)
|
||||
|
||||
for ai in ai_qs:
|
||||
if ai.type == "ProposedIntermediate" and ai.content_object == n:
|
||||
row.update({"proposed_intermediate": True})
|
||||
elif ai.type == "SpikeCompound":
|
||||
spike = {"SpikeCompound__url": ai.get().url}
|
||||
|
||||
try:
|
||||
struc = CompoundStructure.objects.get(
|
||||
compound__package=self._raw_package, url=ai.get().url
|
||||
)
|
||||
spike["SpikeCompound__smiles"] = struc.smiles
|
||||
except Exception:
|
||||
spike["SpikeCompound__smiles"] = None
|
||||
|
||||
row.update(**spike)
|
||||
else:
|
||||
row.update(self._flatten_additional_information(ai))
|
||||
rows.append(row)
|
||||
|
||||
# Get all header fields
|
||||
all_header_fields = set()
|
||||
for row in rows:
|
||||
all_header_fields.update(row.keys())
|
||||
|
||||
# Per request the CSV should start with these fields
|
||||
header = [
|
||||
"pathway_name",
|
||||
"pathway_id",
|
||||
"node_depth",
|
||||
"compound_id",
|
||||
"pubchem_ID",
|
||||
"compound_name",
|
||||
"compound_smiles",
|
||||
"scenario_id",
|
||||
"scenario_name",
|
||||
"scenario_type",
|
||||
"scenario_description",
|
||||
]
|
||||
|
||||
# User remaining fields and place them after the predefined values in a sorted manner
|
||||
remainder = sorted(list(all_header_fields.difference(set(header))))
|
||||
header.extend(remainder)
|
||||
|
||||
buffer = StringIO()
|
||||
writer = DictWriter(buffer, fieldnames=header, delimiter="\t")
|
||||
writer.writeheader()
|
||||
writer.writerows(rows)
|
||||
buffer.seek(0)
|
||||
return buffer.getvalue()
|
||||
|
||||
|
||||
class PackageImporter:
|
||||
def __init__(self, package: Dict[str, Any], preserve_uuids: bool = False):
|
||||
self.preserve_uuids = preserve_uuids
|
||||
|
||||
@ -238,9 +238,11 @@ class RuleBasedDataset(Dataset):
|
||||
):
|
||||
if feat_funcs is None:
|
||||
feat_funcs = [FormatConverter.maccs]
|
||||
_structures = set() # Get all the structures
|
||||
|
||||
_structures = set()
|
||||
for r in reactions:
|
||||
_structures.update(r.educts.all())
|
||||
|
||||
if not educts_only:
|
||||
_structures.update(r.products.all())
|
||||
|
||||
@ -282,17 +284,14 @@ class RuleBasedDataset(Dataset):
|
||||
if key not in triggered:
|
||||
continue
|
||||
|
||||
# standardize products from reactions for comparison
|
||||
standardized_products = []
|
||||
for cs in r.products.all():
|
||||
smi = cs.smiles
|
||||
try:
|
||||
smi = FormatConverter.standardize(smi, remove_stereo=True)
|
||||
except Exception:
|
||||
logger.debug(f"Standardizing SMILES failed for {smi}")
|
||||
standardized_products.append(smi)
|
||||
if len(set(standardized_products).difference(triggered[key])) == 0:
|
||||
if FormatConverter.smiles_covered_by(
|
||||
[prod.smiles for prod in r.products.all()],
|
||||
list(triggered[key]),
|
||||
standardize=True,
|
||||
canonicalize_tautomers=True,
|
||||
):
|
||||
observed.add(key)
|
||||
|
||||
feat_columns = []
|
||||
for feat_func in feat_funcs:
|
||||
if isinstance(feat_func, Descriptor):
|
||||
@ -301,6 +300,7 @@ class RuleBasedDataset(Dataset):
|
||||
feats = feat_func(compounds[0].smiles)
|
||||
start_i = len(feat_columns)
|
||||
feat_columns.extend([f"feature_{start_i + i}" for i, _ in enumerate(feats)])
|
||||
|
||||
ds_columns = (
|
||||
["structure_id"]
|
||||
+ feat_columns
|
||||
@ -334,7 +334,9 @@ class RuleBasedDataset(Dataset):
|
||||
obs.append(None)
|
||||
else:
|
||||
obs.append(0)
|
||||
|
||||
rows.append([str(comp.uuid)] + feats + trig + obs)
|
||||
|
||||
ds = RuleBasedDataset(len(applicable_rules), ds_columns, data=rows)
|
||||
return ds
|
||||
|
||||
@ -680,9 +682,13 @@ class RelativeReasoning:
|
||||
|
||||
def predict(self, X):
|
||||
res = np.zeros((len(X), (self.end_index + 1 - self.start_index)))
|
||||
immutable_res = np.zeros((len(X), (self.end_index + 1 - self.start_index)))
|
||||
|
||||
# Loop through all instances
|
||||
for inst_idx, inst in enumerate(X):
|
||||
for i, t in enumerate(inst[self.start_index : self.end_index + 1]):
|
||||
immutable_res[inst_idx][i] = t
|
||||
|
||||
# Loop through all "triggered" features
|
||||
for i, t in enumerate(inst[self.start_index : self.end_index + 1]):
|
||||
# Set label
|
||||
@ -696,7 +702,7 @@ class RelativeReasoning:
|
||||
if i2 in self.winmap.get(i, []):
|
||||
# if thatat rule also triggered, it dominated the current
|
||||
# set label to 0
|
||||
if X[inst_idx][i2]:
|
||||
if immutable_res[inst_idx][i2]:
|
||||
res[inst_idx][i] = 0
|
||||
|
||||
return res
|
||||
|
||||
Reference in New Issue
Block a user