def get(self, cid):
"""Retrieve (and build) notebook for a single contribution [internal].
---
operationId: get_entry
parameters:
- name: cid
in: path
type: string
pattern: '^[a-f0-9]{24}$'
required: true
description: contribution ID (ObjectId)
responses:
200:
description: single notebook
schema:
$ref: '#/definitions/NotebooksSchema'
"""
try:
nb = Notebooks.objects.get(id=cid)
nb.restore()
except DoesNotExist:
cells = [
nbf.new_code_cell(
"# provide apikey to `load_client` in order to connect to api.mpcontribs.org\n"
"# or use bravado (see https://mpcontribs.org/api)\n"
"from mpcontribs.client import load_client\n"
"client = load_client()"
), nbf.new_code_cell(
"from mpcontribs.io.archieml.mpfile import MPFile\n"
f"result = client.contributions.get_entry(cid='{cid}').response().result\n"
"mpfile = MPFile.from_contribution(result)"
)
]
for typ in ['h', 't', 'g', 's']:
cells.append(nbf.new_code_cell(f"mpfile.{typ}data"))
nb = nbf.new_notebook()
nb['cells'] = cells
exprep.preprocess(nb, {})
nb = Notebooks(**nb)
nb.id = cid # to link to the according contribution
nb.save() # calls Notebooks.clean()
del nb.id
return nb
def get(self, cid):
"""Retrieve (and build) notebook for a single contribution [internal].
---
operationId: get_entry
parameters:
- name: cid
in: path
type: string
pattern: '^[a-f0-9]{24}$'
required: true
description: contribution ID (ObjectId)
responses:
200:
description: single notebook
schema:
$ref: '#/definitions/NotebooksSchema'
"""
try:
nb = Notebooks.objects.get(id=cid)
nb.restore()
except DoesNotExist:
cells = [
nbf.new_code_cell(
"# provide apikey to `load_client` in order to connect to api.mpcontribs.org\n"
"# or use bravado (see https://mpcontribs.org/api)\n"
"from mpcontribs.client import load_client\n"
"client = load_client()"),
nbf.new_code_cell(
"from mpcontribs.io.archieml.mpfile import MPFile\n"
f"result = client.contributions.get_entry(cid='{cid}').response().result\n"
"mpfile = MPFile.from_contribution(result)")
]
for typ in ['h', 't', 'g', 's']:
cells.append(nbf.new_code_cell(f"mpfile.{typ}data"))
nb = nbf.new_notebook()
nb['cells'] = cells
exprep.preprocess(nb, {})
nb = Notebooks(**nb)
nb.id = cid # to link to the according contribution
nb.save() # calls Notebooks.clean()
del nb.id
return nb
def get(self, **kwargs):
cid = kwargs["pk"]
try:
super().get(**kwargs) # trigger DoesNotExist if necessary
nb = Notebooks.objects.get(pk=cid)
try:
if not nb.cells[-1]["outputs"]:
kernel = client.start_kernel("python3")
for idx, cell in enumerate(nb.cells):
if cell["cell_type"] == "code":
output = kernel.execute(cell["source"])
if output:
outtype = ("text/html"
if output.startswith("<div") else
"text/plain")
cell["outputs"].append({
"data": {
outtype: output
},
"metadata": {},
"transient": {},
"output_type":
"display_data",
})
sse.publish({"message": idx + 1},
type="notebook",
channel=cid)
nb.cells[1] = nbf.new_code_cell(
"client = load_client('<your-api-key-here>')")
nb.save() # calls Notebooks.clean()
sse.publish({"message": 0}, type="notebook", channel=cid)
client.shutdown_kernel(kernel)
except Exception as ex:
print(ex)
sse.publish({"message": -1}, type="notebook", channel=cid)
return super().get(**kwargs)
except DoesNotExist:
nb = None
try:
nb = Notebooks.objects.only("pk").get(pk=cid)
except DoesNotExist:
# create and save unexecuted notebook, also start entry to avoid rebuild on subsequent requests
contrib = Contributions.objects.get(id=cid)
cells = [
nbf.new_code_cell(
"headers = {'X-Consumer-Groups': 'admin', 'X-Consumer-Username': '******'}\n"
"client = load_client(headers=headers)"),
nbf.new_code_cell(
f"contrib = client.contributions.get_entry(pk='{cid}', _fields=['_all']).result()"
),
nbf.new_markdown_cell("## Info"),
nbf.new_code_cell(
"fields = ['title', 'owner', 'authors', 'description', 'urls']\n"
"prov = client.projects.get_entry(pk=contrib['project'], _fields=fields).result()\n"
"HierarchicalData(prov)"),
nbf.new_markdown_cell("## HData"),
nbf.new_code_cell("HierarchicalData(contrib['data'])"),
]
tables = Tables.objects.only("id",
"name").filter(contribution=cid)
if tables:
cells.append(nbf.new_markdown_cell("## Tables"))
for table in tables:
cells.append(nbf.new_markdown_cell(table.name))
cells.append(
nbf.new_code_cell(
f"table = client.tables.get_entry(pk='{table.id}', _fields=['_all']).result()\n"
"Table.from_dict(table)"))
cells.append(
nbf.new_code_cell("Plot.from_dict(table)"))
structures = Structures.objects.only(
"id", "name").filter(contribution=cid)
if structures:
cells.append(nbf.new_markdown_cell("## Structures"))
for structure in structures:
cells.append(nbf.new_markdown_cell(structure.name))
cells.append(
nbf.new_code_cell(
"structure = client.structures.get_entry(\n"
f"\tpk='{structure.id}', _fields=['lattice', 'sites', 'charge']\n"
").result()\n"
"Structure.from_dict(structure)"))
nb = Notebooks(pk=cid, is_public=contrib.is_public)
doc = deepcopy(seed_nb)
doc["cells"] += cells
self.Schema().update(nb, doc)
nb.save() # calls Notebooks.clean()
return super().get(**kwargs)
if nb is not None:
raise DoesNotExist(
f"Notebook {nb.id} exists but user not in project group")
def get(self, **kwargs):
cid = kwargs["pk"]
qfilter = lambda qs: self.has_read_permission(request, qs.clone())
try:
# trigger DoesNotExist if necessary (due to permissions or non-existence)
nb = self._resource.get_object(cid, qfilter=qfilter)
try:
if not nb.cells[-1]["outputs"]:
ws = connect_kernel()
for idx, cell in enumerate(nb.cells):
if cell["cell_type"] == "code":
cell["outputs"] = execute(ws, cid, cell["source"])
sse.publish({"message": idx + 1},
type="notebook",
channel=cid)
ws.close()
nb.cells[1] = nbf.new_code_cell(
"client = Client('<your-api-key-here>')")
nb.save() # calls Notebooks.clean()
sse.publish({"message": 0}, type="notebook", channel=cid)
except Exception as ex:
print(ex)
sse.publish({"message": -1}, type="notebook", channel=cid)
return self._resource.serialize(nb, params=request.args)
except DoesNotExist:
nb = None
try:
nb = Notebooks.objects.only("pk").get(pk=cid)
except DoesNotExist:
# create and save unexecuted notebook, also start entry to avoid rebuild on subsequent requests
from mpcontribs.api.contributions.views import ContributionsResource
res = ContributionsResource()
res._params = {"_fields": "_all"}
contrib = res.get_object(cid, qfilter=qfilter)
cells = [
nbf.new_code_cell(
'client = Client(headers={"X-Consumer-Groups": "admin"})'
),
nbf.new_markdown_cell("## Project"),
nbf.new_code_cell(
f'client.get_project("{contrib.project.pk}").pretty()'
),
nbf.new_markdown_cell("## Contribution"),
nbf.new_code_cell(
f'client.get_contribution("{cid}").pretty()'),
]
if contrib.tables:
cells.append(nbf.new_markdown_cell("## Tables"))
for _, tables in contrib.tables.items():
for table in tables:
tid = table["id"]
cells.append(
nbf.new_code_cell(
f'client.get_table("{tid}").plot()'))
if contrib.structures:
cells.append(nbf.new_markdown_cell("## Structures"))
for _, structures in contrib.structures.items():
for structure in structures:
sid = structure["id"]
cells.append(
nbf.new_code_cell(
f'client.get_structure("{sid}")'))
nb = Notebooks(pk=cid, is_public=contrib.is_public)
doc = deepcopy(seed_nb)
doc["cells"] += cells
self.Schema().update(nb, doc)
nb.save() # calls Notebooks.clean()
return self._resource.serialize(nb, params=request.args)
if nb is not None:
raise DoesNotExist(
f"Notebook {nb.id} exists but user not in project group")
def get(self, cid):
"""Retrieve (and build) notebook for a single contribution [internal].
---
operationId: get_entry
parameters:
- name: cid
in: path
type: string
pattern: '^[a-f0-9]{24}$'
required: true
description: contribution ID (ObjectId)
responses:
200:
description: single notebook
schema:
$ref: '#/definitions/NotebooksSchema'
"""
try:
nb = Notebooks.objects.get(id=cid)
nb.restore()
except DoesNotExist:
contrib = Contributions.objects.no_dereference().get(id=cid)
cells = [
nbf.new_code_cell(
"client = load_client() # provide apikey as argument to use api.mpcontribs.org\n"
f"contrib = client.contributions.get_entry(cid='{cid}').response().result"
),
nbf.new_markdown_cell("## Provenance Info"),
nbf.new_code_cell(
"mask = ['title', 'authors', 'description', 'urls', 'other', 'project']\n"
"prov = client.projects.get_entry(project=contrib['project'], mask=mask).response().result\n"
"RecursiveDict(prov)"),
nbf.new_markdown_cell(
f"## Hierarchical Data for {contrib['identifier']}"),
nbf.new_code_cell("HierarchicalData(contrib['content'])")
]
tables = contrib.content['tables']
if tables:
cells.append(
nbf.new_markdown_cell(
f"## Tabular Data for {contrib['identifier']}"))
for ref in tables:
cells.append(
nbf.new_code_cell(
f"table = client.tables.get_entry(tid='{ref.id}').response().result # Pandas DataFrame format\n"
"Table.from_dict(table)"))
cells.append(nbf.new_code_cell("Plot.from_dict(table)"))
structures = contrib.content['structures']
if structures:
cells.append(
nbf.new_markdown_cell(
f"## Pymatgen Structures for {contrib['identifier']}"))
for ref in structures:
cells.append(
nbf.new_code_cell(
f"Structure.from_dict(client.structures.get_entry(sid='{ref.id}').response().result)"
))
kernel = client.start_kernel()
for cell in cells:
if cell.cell_type == 'code':
cell.outputs = kernel.execute(cell.source)
client.shutdown_kernel(kernel)
nb = deepcopy(seed_nb)
nb.cells += cells
nb = Notebooks(**nb)
nb.id = cid # to link to the according contribution
nb.save() # calls Notebooks.clean()
del nb.id
return nb