ci: add CodeQL security scanning and Dependabot

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Justin Visser 2026-02-27 00:05:17 +01:00
parent ac002131d6
commit 3866c6d6f0
90 changed files with 40 additions and 1 deletions

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from __future__ import annotations
import logging
logger = logging.getLogger(__name__)

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import logging
import httpx
from tenacity import (
retry,
retry_if_exception_type,
stop_after_attempt,
wait_exponential,
)
from app.services.domains.openalex.types import OpenAlexWork
logger = logging.getLogger(__name__)
OPENALEX_BASE_URL = "https://api.openalex.org"
class OpenAlexClientError(Exception):
pass
class OpenAlexRateLimitError(OpenAlexClientError):
"""Transient rate limit (too many requests per second)."""
pass
class OpenAlexBudgetExhaustedError(OpenAlexClientError):
"""Daily API budget exhausted — retrying is futile until midnight UTC."""
pass
class OpenAlexClient:
def __init__(
self,
api_key: str | None = None,
mailto: str | None = None,
timeout: float = 10.0,
) -> None:
self.api_key = api_key
self.mailto = mailto
self.timeout = timeout
@property
def _base_params(self) -> dict[str, str]:
params = {}
if self.mailto:
params["mailto"] = self.mailto
if self.api_key:
params["api_key"] = self.api_key
return params
@retry(
retry=retry_if_exception_type((httpx.NetworkError, httpx.TimeoutException)),
stop=stop_after_attempt(3),
wait=wait_exponential(multiplier=1, min=2, max=10),
reraise=True,
)
async def get_work_by_doi(self, doi: str) -> OpenAlexWork | None:
"""Fetch a single work by DOI directly."""
clean_doi = doi.replace("https://doi.org/", "")
if not clean_doi:
return None
url = f"{OPENALEX_BASE_URL}/works/{clean_doi}"
headers = {}
if self.mailto:
headers["User-Agent"] = f"scholar-scraper/1.0 (mailto:{self.mailto})"
else:
headers["User-Agent"] = "scholar-scraper/1.0"
async with httpx.AsyncClient(timeout=self.timeout, follow_redirects=True, headers=headers) as client:
response = await client.get(url, params=self._base_params)
if response.status_code == 404:
return None
if response.status_code == 429:
remaining = response.headers.get("X-RateLimit-Remaining-USD", "")
if remaining == "0" or remaining.startswith("-"):
raise OpenAlexBudgetExhaustedError("Daily API budget exhausted; retrying won't help until midnight UTC")
raise OpenAlexRateLimitError("Rate limit exceeded fetching OpenAlex work by DOI")
if response.status_code >= 400:
logger.warning("OpenAlex API error: %s %s", response.status_code, response.text[:500])
raise OpenAlexClientError(f"API Error {response.status_code}")
data = response.json()
return OpenAlexWork.from_api_dict(data)
@retry(
retry=retry_if_exception_type((httpx.NetworkError, httpx.TimeoutException)),
stop=stop_after_attempt(3),
wait=wait_exponential(multiplier=1, min=2, max=10),
reraise=True,
)
async def get_works_by_filter(
self,
filters: dict[str, str],
limit: int = 50,
) -> list[OpenAlexWork]:
"""
Fetch works using the ?filter= query parameter.
Supports fetching multiple records by joining filters with | (OR logic).
"""
if not filters:
return []
# Example: {"doi": "10.foo|10.bar", "title.search": "query"}
filter_str = ",".join(f"{k}:{v}" for k, v in filters.items())
params = self._base_params.copy()
params["filter"] = filter_str
params["per-page"] = str(limit)
url = f"{OPENALEX_BASE_URL}/works"
headers = {}
if self.mailto:
headers["User-Agent"] = f"scholar-scraper/1.0 (mailto:{self.mailto})"
else:
headers["User-Agent"] = "scholar-scraper/1.0"
async with httpx.AsyncClient(timeout=self.timeout, follow_redirects=True, headers=headers) as client:
response = await client.get(url, params=params)
if response.status_code == 429:
remaining = response.headers.get("X-RateLimit-Remaining-USD", "")
if remaining == "0" or remaining.startswith("-"):
raise OpenAlexBudgetExhaustedError("Daily API budget exhausted; retrying won't help until midnight UTC")
raise OpenAlexRateLimitError("Rate limit exceeded fetching OpenAlex works list")
if response.status_code >= 400:
logger.warning("OpenAlex API error (filters=%s): %s %s", filters, response.status_code, response.text[:500])
raise OpenAlexClientError(f"API Error {response.status_code}")
data = response.json()
results = data.get("results") or []
parsed_works = []
for raw_work in results:
try:
parsed_works.append(OpenAlexWork.from_api_dict(raw_work))
except Exception as e:
logger.warning("Failed to parse OpenAlex raw dict: %s", e)
continue
return parsed_works

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import logging
import re
from rapidfuzz import fuzz
from app.services.domains.openalex.types import OpenAlexWork
logger = logging.getLogger(__name__)
# A minimum similarity score out of 100 for a title to be considered a match candidate.
TITLE_MATCH_THRESHOLD = 90.0
# The margin within the top score where a secondary tiebreaker (author/year) is necessary.
TIEBREAKER_MARGIN = 5.0
def _clean_string(s: str | None) -> str:
if not s:
return ""
# Strip non-alphanumeric (keep spaces), lowercase, and collapse whitespace
cleaned = re.sub(r"[^a-z0-9\s]", " ", s.lower())
return " ".join(cleaned.split())
def _author_overlap_score(target_authors: str | None, candidate_authors: list[str]) -> bool:
if not target_authors or not candidate_authors:
return False
target_clean = _clean_string(target_authors)
if not target_clean:
return False
for candidate in candidate_authors:
cand_clean = _clean_string(candidate)
if cand_clean and (cand_clean in target_clean or target_clean in cand_clean):
return True
# Alternatively check rapidfuzz token_set_ratio
if cand_clean and fuzz.token_set_ratio(target_clean, cand_clean) > 80:
return True
return False
def find_best_match(
target_title: str,
target_year: int | None,
target_authors: str | None,
candidates: list[OpenAlexWork],
) -> OpenAlexWork | None:
"""
Finds the best matching OpenAlexWork from a list of candidates, prioritizing title similarity (>90%)
with year and author overlap as tiebreakers for close candidates.
"""
if not target_title or not candidates:
return None
clean_target = _clean_string(target_title)
if not clean_target:
return None
scored_candidates: list[tuple[float, OpenAlexWork]] = []
for cand in candidates:
if not cand.title:
continue
clean_cand = _clean_string(cand.title)
# Primary sort: string similarity ratio
score = fuzz.ratio(clean_target, clean_cand)
if score >= TITLE_MATCH_THRESHOLD:
scored_candidates.append((score, cand))
if not scored_candidates:
return None
# Sort descending by score
scored_candidates.sort(key=lambda x: x[0], reverse=True)
best_score = scored_candidates[0][0]
# Extract all candidates within the tiebreaker margin
top_scored_candidates = [
(score, cand) for score, cand in scored_candidates if best_score - score <= TIEBREAKER_MARGIN
]
if len(top_scored_candidates) == 1:
return top_scored_candidates[0][1]
# We have a tie or near-tie. Use year and author overlap to break the tie.
# Score candidates: +1 for year match (within 1 year), +1 for author overlap
tiebreaker_scores: list[tuple[int, float, OpenAlexWork]] = []
for original_score, cand in top_scored_candidates:
tb_score = 0
if target_year is not None and cand.publication_year is not None and abs(target_year - cand.publication_year) <= 1:
tb_score += 1
candidate_author_names = [a.display_name for a in cand.authors if a.display_name]
if _author_overlap_score(target_authors, candidate_author_names):
tb_score += 1
tiebreaker_scores.append((tb_score, original_score, cand))
tiebreaker_scores.sort(key=lambda x: (x[0], x[1]), reverse=True)
return tiebreaker_scores[0][2]

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from __future__ import annotations
from collections.abc import Mapping
from dataclasses import dataclass, field
from typing import Any
@dataclass(frozen=True)
class OpenAlexAuthor:
openalex_id: str | None
display_name: str | None
@dataclass(frozen=True)
class OpenAlexWork:
openalex_id: str
doi: str | None
pmid: str | None
pmcid: str | None
title: str | None
publication_year: int | None
cited_by_count: int
is_oa: bool
oa_url: str | None
authors: list[OpenAlexAuthor] = field(default_factory=list)
raw_data: Mapping[str, Any] = field(default_factory=dict, repr=False)
@classmethod
def from_api_dict(cls, data: Mapping[str, Any]) -> OpenAlexWork:
ids = data.get("ids") or {}
# Extract DOI without the https://doi.org/ prefix
doi = ids.get("doi")
if doi and doi.startswith("https://doi.org/"):
doi = doi[16:]
# Extract PMID without the url prefix
pmid = ids.get("pmid")
if pmid and pmid.startswith("https://pubmed.ncbi.nlm.nih.gov/"):
pmid = pmid[32:]
# Extract PMCID without the url prefix
pmcid = ids.get("pmcid")
if pmcid and pmcid.startswith("https://www.ncbi.nlm.nih.gov/pmc/articles/"):
pmcid = pmcid[42:]
open_access = data.get("open_access") or {}
authors = []
for authorship in data.get("authorships") or []:
author_data = authorship.get("author") or {}
authors.append(
OpenAlexAuthor(
openalex_id=author_data.get("id"),
display_name=author_data.get("display_name"),
)
)
return cls(
openalex_id=data.get("id", ""),
doi=doi,
pmid=pmid,
pmcid=pmcid,
title=data.get("title"),
publication_year=data.get("publication_year"),
cited_by_count=data.get("cited_by_count", 0),
is_oa=bool(open_access.get("is_oa")),
oa_url=open_access.get("oa_url"),
authors=authors,
raw_data=dict(data),
)