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medconb_client.py
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import logging
from collections import UserList
from dataclasses import dataclass
from typing import Optional, overload
import pandas as pd
from gql import Client as GQLClient
from gql import gql
from gql.transport.aiohttp import AIOHTTPTransport
from pydantic import BaseModel
class Workspace(BaseModel):
collections: Optional[list["Collection"]]
shared: Optional[list["Collection"]]
class Collection(BaseModel):
id: str
name: str
description: Optional[str]
referenceID: Optional[str]
itemType: str
items: list["CodelistInfo | PhenotypeInfo"]
ownerID: str
locked: bool
visibility: str
class CodelistInfo(BaseModel):
id: str
name: str
class PhenotypeInfo(BaseModel):
id: str
name: str
@dataclass
class Codelist:
"""
Codelist is a codelist as defined in MedConB.
Attributes:
id (str): ID of the codelist.
name (str): Name of the codelist.
description (str): Description of the codelist.
codesets (Codesets): List of codesets in the codelist.
"""
id: str
name: str
description: Optional[str]
codesets: "Codesets"
def to_pandas(self):
"""
Convert the codelists codesets to a pandas DataFrame.
Returns:
pd.DataFrame: The codesets as a DataFrame.
"""
return self.codesets.to_pandas()
class Codesets(UserList["Codeset"]):
"""
Codesets is a list of codesets as defined in MedConB.
It's just a thin wrapper, so we can offer `to_pandas`.
"""
def to_pandas(self):
"""
Convert the codesets to a pandas DataFrame.
Returns:
pd.DataFrame: The codesets as a DataFrame.
"""
rows = []
for codeset in self.data:
for code, description in codeset.codes:
rows.append(
{
"ontology": codeset.ontology,
"code": code,
"description": description,
}
)
return pd.DataFrame(rows)
@dataclass
class Codeset:
"""
Codeset is a codeset as defined in MedConB.
Attributes:
ontology (str): Ontology which the codes belong to
codes (list[tuple[str, str]]): List of codes, each represented as a tuple of code and description
"""
ontology: str
codes: list[tuple[str, str]] # code, description
class Client:
def __init__(
self,
endpoint: str,
token: str,
):
"""
Creates a new MedConB client.
Args:
endpoint (str): URL of the MedConB API. E.g. https://api.medconb.example.com/graphql/
token (str): Authorization token.
"""
self.endpoint = endpoint
self.token = token
self.transport = AIOHTTPTransport(
url=self.endpoint, headers={"Authorization": f"Bearer {self.token}"}
)
self.client = GQLClient(
transport=self.transport,
fetch_schema_from_transport=True,
execute_timeout=30,
)
async def get_workspace(self) -> Workspace:
"""
Retrieves a listing of all collections and their codelists/pheontypes
within the workspace.
Returns:
Workspace: Workspace object containing id and name of all codelists and phenotypes.
Example:
For a detailed example, see [Examples](/examples#list-all-collections-in-your-workspace).
```ipython
>>> workspace = await client.get_workspace()
>>> print(workspace)
Workspace(
collections=[
Collection(
id="ff755b3a-8f93-43a2-bb8f-2ee435e28938",
name="ATTR CM Library",
description="...",
referenceID="...",
itemType="Codelist",
items=[
CodelistInfo(id="...", name="..."),
CodelistInfo(id="...", name="..."),
...
],
ownerID="...",
locked=False,
visibility="Private",
),
...
],
shared=[
Collection(...),
],
)
```
"""
query = gql(_GQL_QUERY_WORKSPACE)
async with self.client as session:
result = await session.execute(query)
workspace_data = result["self"]["workspace"]
return Workspace(**workspace_data)
async def get_codelist(
self, codelist_id: str, with_description: bool = False
) -> "Codelist":
"""
Retrieves the codelist by ID from the API and parses
the data into the python data structures.
It mirrors the logic of the export and current understanding
of transient codesets:
Transient codesets are the current version and should be used
if they exist. (At some point the API might change to reflect
that default behaviour better as it might be a bit confusing
atm.)
"""
query = gql(
_GQL_QUERY_CODELST
if with_description
else _GQL_QUERY_CODELST_NO_DESCRIPTION
)
async with self.client as session:
result = await session.execute(
query, variable_values={"codelistID": codelist_id}
)
codelist_data = result["codelist"]
css = codelist_data["codesets"]
tcss = codelist_data["transientCodesets"]
codesets: Codesets = Codesets()
if tcss is None:
tcss = css
for cs in tcss:
codesets.append(
Codeset(
ontology=cs["ontology"]["name"],
codes=[
(
c["code"],
c["description"] if with_description else "",
)
for c in cs["codes"]
],
)
)
return Codelist(
id=codelist_data["id"],
name=codelist_data["name"],
description=codelist_data.get("description"),
codesets=codesets,
)
@overload
def get_codelist_by_name(
self, *, codelist_name: str, codelist_collection_name: str
): ...
@overload
def get_codelist_by_name(
self, *, codelist_name: str, phenotype_collection_name: str, phenotype_name: str
): ...
async def get_codelist_by_name(
self,
*,
codelist_name,
codelist_collection_name=None,
phenotype_collection_name=None,
phenotype_name=None,
):
"""
Retrieves a Codelist by its name.
Use the arguments `codelist_name` with either:
- `codelist_collection_name` or
- `phenotype_collection_name` and `phenotype_name`
Args:
codelist_name (str): Name of the codelist
codelist_collection_name (str, optional): Name of the codelist collection
phenotype_collection_name (str, optional): Name of the phenotype collection
phenotype_name (str, optional): Name of the phenotype
"""
# codelist_collection_name = kwargs.get("codelist_collection_name")
# codelist_name = kwargs.get("codelist_name")
# phenotype_collection_name = kwargs.get("phenotype_collection_name")
# phenotype_name = kwargs.get("phenotype_name")
if codelist_name is None:
raise ValueError("Invalid arguments: codelist_name is required")
mode = None
if codelist_collection_name is not None:
mode = "collection"
elif phenotype_collection_name is not None and phenotype_name is not None:
mode = "phenotype"
else:
raise ValueError(
"Invalid arguments: Specify either codelist_collection_name or"
" phenotype_collection_name and phenotype_name"
)
candidates = await self._search_codelist(codelist_name)
matches = []
if mode == "collection":
matches = self._filter_codelist_in_collection(
candidates, codelist_collection_name
)
else:
matches = self._filter_codelist_in_phenotype(
candidates, phenotype_collection_name, phenotype_name
)
if len(matches) > 1:
raise ValueError(
"The codelist can not be retrieved because the name is ambiguous"
)
if len(matches) == 0:
raise ValueError(
"The codelist can not be retrieved because it was not found"
)
return await self.get_codelist(matches[0])
def _filter_codelist_in_phenotype(
self,
candidates: list[dict],
phenotype_collection_name: str,
phenotype_name: str,
) -> list[str]:
matches = []
for candidate in candidates:
ch = candidate["containerHierarchy"]
if len(ch) != 2:
# codelists are stacked:
# Phenotype Collection -> Phenotype -> Codelist
# so this is probably a codelist Collection
continue
if ch[0]["type"] != "Collection" or ch[1]["type"] != "Phenotype":
logging.warning("API returned an unexpected data structure.")
continue
if (
ch[0]["name"] != phenotype_collection_name
or ch[1]["name"] != phenotype_name
):
logging.debug(
"Disregarding codelist of the requested name because"
" the containing Collection has the wrong name"
f" ({ch[0]['name']} != {phenotype_collection_name}"
f", {ch[1]['name']} != {phenotype_name})"
)
continue
matches.append(candidate["id"])
return matches
def _filter_codelist_in_collection(
self, candidates: list[dict], codelist_collection_name: str
) -> list[str]:
matches = []
for candidate in candidates:
ch = candidate["containerHierarchy"]
if len(ch) != 1:
# codelists are directly in codelist collections
# so this is probably a codelist of a Phenotype
continue
if ch[0]["type"] != "Collection":
logging.warning(
"API returned an unexpected data structure: No Collection as root."
)
continue
if ch[0]["name"] != codelist_collection_name:
logging.debug(
"Disregarding codelist of the requested name because"
" the containing Collection has the wrong name"
f" ({ch[0]['name']} != {codelist_collection_name})"
)
continue
matches.append(candidate["id"])
return matches
async def _search_codelist(self, codelist_name: str) -> list[dict]:
query = gql(_GQL_QUERY_SEARCH_CODELIST)
query_str = f"name:'^{codelist_name}$' visibility:'public,shared,own'"
async with self.client as session:
result = await session.execute(query, variable_values={"query": query_str})
return result["searchEntities"]["items"]
# GQL Queries
_GQL_QUERY_WORKSPACE = """
query {
self {
workspace {
collections {
id
name
description
referenceID
itemType
ownerID
locked
visibility
items {
... on Codelist {
id
name
}
... on Phenotype {
id
name
}
}
}
shared {
id
name
description
referenceID
itemType
ownerID
locked
visibility
items {
... on Codelist {
id
name
}
... on Phenotype {
id
name
}
}
}
}
}
}
"""
_GQL_QUERY_CODELST = """
query codelist($codelistID: ID!) {
codelist(codelistID: $codelistID) {
id
name
codesets {
ontology { name }
codes {
code
id
description
numberOfChildren
}
}
transientCodesets {
ontology { name }
codes {
code
id
description
numberOfChildren
}
}
}
}
"""
_GQL_QUERY_CODELST_NO_DESCRIPTION = """
query codelist($codelistID: ID!) {
codelist(codelistID: $codelistID) {
id
name
codesets {
ontology { name }
codes {
code
id
numberOfChildren
}
}
transientCodesets {
ontology { name }
codes {
code
id
numberOfChildren
}
}
}
}
"""
_GQL_QUERY_SEARCH_CODELIST = """
query codelist($query: String!) {
searchEntities(
entityType: Codelist
query: $query
) {
items {
... on Codelist {
id
name
containerHierarchy {
type
name
}
}
}
}
}
"""