mirror of
https://github.com/migatu/conjurer.git
synced 2026-07-14 13:34:40 +00:00
fd6427a282
(Re-applied cleanly on top of main: PR #18 was rebase-merged, so the branch that became #19 conflicted on the already-landed commits. This carries ONLY the librarian state fix - the sole content difference between that branch and main - so nothing else is touched or lost.) The worker threads open cr_results/rr_results/not_in_db/s_results.json in place ('r+'), crashing with FileNotFoundError in a fresh container. New conjurer_librarian/lib_paths.py resolves all four under a persistent dir (CONJURER_LIBRARIAN_STATE_DIR, default /lib_temp_files) and seeds missing ones with '{}' on import; shared by conjurer_librarian.py and scrape_bot.py (no circular import). ndb_database/database initialised to {} before load so a corrupt persisted file degrades to empty instead of NameError. search_bot /search_bot2 open the DOI DB 'r' not 'r+' so /doi can stay read-only. Docker: STATE_DIR env + VOLUME, compose mounts /srv/librarian/state:/lib_temp_files. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
561 lines
18 KiB
Python
561 lines
18 KiB
Python
"""
|
|
This module contains the implementation of the Librarian class and
|
|
related functions for searching and refining queries.
|
|
|
|
Classes:
|
|
- Librarian: Represents a librarian object that performs search and
|
|
refinement operations on queries
|
|
|
|
Functions:
|
|
- flask_debug: Starts a Flask application in debug mode without using the reloader.
|
|
- waitress_run: Serves the Flask application using the Waitress WSGI server.
|
|
- BackgroundTaskSearch: Represents a background task for running the
|
|
Librarian object asynchronously
|
|
"""
|
|
|
|
import asyncio
|
|
import json
|
|
import logging
|
|
import os
|
|
import threading
|
|
from json.decoder import JSONDecodeError
|
|
from logging import handlers
|
|
from pathlib import Path
|
|
from queue import Queue
|
|
from typing import Dict, Optional
|
|
|
|
import requests
|
|
import lib_paths
|
|
import scrape_bot
|
|
import search_bot
|
|
# import search_bot2 as search_bot
|
|
from flask import Flask, jsonify, request, abort
|
|
from habanero import Crossref
|
|
from waitress import serve
|
|
|
|
try:
|
|
import netrc
|
|
except ImportError: # pragma: no cover
|
|
netrc = None
|
|
|
|
# Constants
|
|
|
|
|
|
def _env(name: str, default: str) -> str:
|
|
return os.getenv(name, default)
|
|
|
|
|
|
def _env_path(name: str, default: str) -> Path:
|
|
return Path(os.getenv(name, default)).expanduser().resolve()
|
|
|
|
|
|
BASE_DIR = Path(
|
|
os.getenv("CONJURER_LIBRARIAN_BASE", str(Path(__file__).resolve().parent))
|
|
)
|
|
NETRC_FILE = _env_path("CONJURER_NETRC_FILE", str(Path.home() / ".netrc"))
|
|
HOST_ADDRESS = _env("CONJURER_LIBRARIAN_HOST", "0.0.0.0")
|
|
PORT_ADDRESS = int(_env("CONJURER_LIBRARIAN_PORT", "5001"))
|
|
MAIN_BOT_ADDRESS = _env("CONJURER_MAIN_BOT", "http://127.0.0.1:5000")
|
|
SEND_RESULTS = _env("CONJURER_LIBRARIAN_RESULTS_ENDPOINT", "/conjurer")
|
|
MAX_CR_RESULTS = int(_env("CONJURER_LIBRARIAN_MAX_RESULTS", "500"))
|
|
ENCODING = _env("CONJURER_ENCODING", "utf-8")
|
|
API_KEY = os.getenv("CONJURER_API_KEY")
|
|
LOGFILE_PATH = _env_path(
|
|
"CONJURER_LIBRARIAN_LOG", str(BASE_DIR / "librarian.log")
|
|
)
|
|
|
|
app = Flask(__name__)
|
|
|
|
librarian_queue = Queue()
|
|
librarian_list = []
|
|
|
|
|
|
def _service_headers() -> Dict[str, str]:
|
|
if API_KEY:
|
|
return {"X-Conjurer-Api-Key": API_KEY}
|
|
return {}
|
|
|
|
|
|
def _authorize_request() -> None:
|
|
if API_KEY and request.headers.get("X-Conjurer-Api-Key") != API_KEY:
|
|
abort(401)
|
|
|
|
|
|
# trunk-ignore(pylint/R0902)
|
|
class Librarian(object):
|
|
"""
|
|
Represents a librarian object that performs search and refinement operations on queries.
|
|
"""
|
|
|
|
def __init__(self, _app, query, uuid, _deep_search) -> None:
|
|
"""
|
|
Initializes a Librarian object.
|
|
|
|
Args:
|
|
- _app: The Flask application object.
|
|
- query: The query to be searched.
|
|
- uuid: The unique identifier for the search.
|
|
|
|
Attributes:
|
|
- cr: The Crossref object for performing the search.
|
|
- query: The query to be searched.
|
|
- uuid: The unique identifier for the search.
|
|
- limit: The maximum number of search results to fetch.
|
|
- fetched: The number of search results fetched so far.
|
|
- hit: The number of search results that match the refinement criteria.
|
|
- total: The total number of search results.
|
|
- app: The Flask application object.
|
|
- live_results: A list to store live search results.
|
|
- final_result: A list to store the final refined search results.
|
|
- not_in_db: A list to store search results that are not in the local database.
|
|
- search_result_from_cr: A dictionary to store the search results from Crossref.
|
|
- done: A flag indicating if the search is done.
|
|
"""
|
|
mailto_contact: Optional[str] = os.getenv("CONJURER_CROSSREF_MAILTO")
|
|
if netrc:
|
|
try:
|
|
netrc_mod = netrc.netrc(str(NETRC_FILE))
|
|
auth_tokens = netrc_mod.authenticators("crossref")
|
|
if auth_tokens:
|
|
mailto_contact = auth_tokens[0]
|
|
except (FileNotFoundError, netrc.NetrcParseError):
|
|
logging.getLogger("conjurer_librarian").warning(
|
|
"Crossref credentials missing in netrc %s", NETRC_FILE
|
|
)
|
|
if not mailto_contact:
|
|
raise RuntimeError(
|
|
"Crossref credentials not configured. Set CONJURER_CROSSREF_MAILTO or add to netrc."
|
|
)
|
|
self.cr = Crossref(
|
|
mailto=mailto_contact,
|
|
ua_string=f"Conjurer project. mailto:{mailto_contact}"
|
|
)
|
|
self.query = query
|
|
self.uuid = str(uuid)
|
|
self.limit = MAX_CR_RESULTS
|
|
self.fetched = 0
|
|
self.hit = 0
|
|
self.total = 0
|
|
self.app = _app
|
|
self.live_results = []
|
|
self.final_result = {}
|
|
self.not_in_db = {}
|
|
self.search_result_from_cr = {}
|
|
self.done = False
|
|
self.deep_search = _deep_search
|
|
|
|
async def search_crossref(self, query, deep_search=False):
|
|
"""
|
|
Performs a search on Crossref for the given query.
|
|
|
|
Args:
|
|
- query: The query to be searched.
|
|
|
|
Returns:
|
|
- result: The search result from Crossref.
|
|
|
|
Raises:
|
|
- None.
|
|
"""
|
|
|
|
self.app.logger.info("STARTED SEARCH")
|
|
|
|
if not deep_search:
|
|
query_limit = MAX_CR_RESULTS if MAX_CR_RESULTS < 1000 else 1000
|
|
cr_result = self.cr.works(query=query, limit=query_limit)
|
|
self.search_result_from_cr.update(cr_result)
|
|
self.total = cr_result["message"]["total-results"]
|
|
self.fetched += len(cr_result["message"]["items"])
|
|
self.app.logger.info(self.total)
|
|
self.app.logger.info(self.fetched)
|
|
while self.total > self.fetched and self.limit > self.fetched:
|
|
tmp_result = self.cr.works(query=query, limit=query_limit, offset=self.fetched)
|
|
cr_result["message"]["items"].extend(tmp_result["message"]["items"])
|
|
self.total = tmp_result["message"]["total-results"]
|
|
self.fetched = len(cr_result["message"]["items"])
|
|
self.app.logger.info(self.total)
|
|
self.app.logger.info(self.fetched)
|
|
await asyncio.sleep(0.1)
|
|
|
|
else:
|
|
cr_result = self.cr.works(query=query, cursor_max=15000, cursor='*', progress_bar = True)
|
|
result = cr_result[0]
|
|
for item in cr_result[1:]:
|
|
result["message"]["items"].extend(item["message"]["items"])
|
|
self.total = item["message"]["total-results"]
|
|
self.fetched = len(result["message"]["items"])
|
|
self.app.logger.info(self.total)
|
|
self.app.logger.info(self.fetched)
|
|
cr_result = result
|
|
self.app.logger.info("Total, fetched:")
|
|
self.app.logger.info(self.total)
|
|
self.app.logger.info(self.fetched)
|
|
self.search_result_from_cr.update(cr_result)
|
|
self.total = cr_result["message"]["total-results"]
|
|
self.app.logger.info("CROSSREF DONE")
|
|
|
|
self.app.logger.info("CROSSREF DONE")
|
|
with open(lib_paths.CR_RESULTS, "r+", encoding="utf-8") as data_file:
|
|
# First we load existing data into a dict.
|
|
try:
|
|
file_data = json.load(data_file)
|
|
except JSONDecodeError:
|
|
file_data = {}
|
|
data_file.truncate(0)
|
|
data_file.seek(0)
|
|
tmp = {self.uuid : self.search_result_from_cr}
|
|
if file_data:
|
|
file_data.update(tmp)
|
|
else:
|
|
file_data = tmp
|
|
json.dump(file_data, data_file, indent=4)
|
|
return cr_result
|
|
|
|
|
|
async def refine_search(self, unrefined_result):
|
|
"""
|
|
Refines the search query based on the unrefined search result.
|
|
|
|
Args:
|
|
- unrefined_result: The unrefined search result.
|
|
|
|
Returns:
|
|
- refined_result: The refined search result.
|
|
|
|
Raises:
|
|
- None.
|
|
"""
|
|
summarized_results = []
|
|
self.app.logger.info("REFINE: Removing all derived works from the list")
|
|
for item in unrefined_result["message"]["items"]:
|
|
summarized_results.append(
|
|
{
|
|
"DOI": item["DOI"],
|
|
"title": item["title"] if "title" in item else None,
|
|
"type": item["type"] if "type" in item else None,
|
|
}
|
|
)
|
|
|
|
partial_result = {
|
|
self.uuid: {
|
|
"total_results": self.search_result_from_cr["message"][
|
|
"total-results"
|
|
],
|
|
"on_page": 1,
|
|
"summary": summarized_results,
|
|
"results": self.search_result_from_cr["message"]["items"],
|
|
}
|
|
}
|
|
self.app.logger.info("REFINE: Dumping to file")
|
|
temp = []
|
|
refined_result = {}
|
|
for key in partial_result:
|
|
self.app.logger.info("KEY:")
|
|
self.app.logger.info(key)
|
|
|
|
for item in partial_result[self.uuid]["summary"]:
|
|
if item["title"]:
|
|
temp.append(item)
|
|
|
|
for item in temp:
|
|
refined_result[item["DOI"]]= item
|
|
with open(lib_paths.RR_RESULTS, "r+", encoding="utf-8") as data_file:
|
|
# First we load existing data into a dict.
|
|
try:
|
|
file_data = json.load(data_file)
|
|
except JSONDecodeError:
|
|
file_data = {}
|
|
data_file.truncate(0)
|
|
data_file.seek(0)
|
|
tmp = {self.uuid: refined_result}
|
|
if file_data:
|
|
file_data.update(tmp)
|
|
else:
|
|
file_data = tmp
|
|
json.dump(file_data, data_file, indent=4)
|
|
return refined_result
|
|
|
|
async def check_if_exists(self, refined_result):
|
|
"""
|
|
Checks if the given DOI exists.
|
|
|
|
Args:
|
|
- doi: The DOI to be checked.
|
|
- brute_force: A flag indicating if brute force method should be used.
|
|
|
|
Returns:
|
|
- result: The search result.
|
|
|
|
Raises:
|
|
- None.
|
|
"""
|
|
result = {}
|
|
self.app.logger.info("REFINE: Running search in the backend app")
|
|
dois = []
|
|
for item, value in refined_result.items():
|
|
dois.append([item, value])
|
|
coro = asyncio.to_thread(
|
|
search_bot.search_for_doi, dois, self.live_results, self.app.logger
|
|
)
|
|
result = await coro
|
|
result_list = []
|
|
result_no_db = []
|
|
for item in result:
|
|
if item["exists"]:
|
|
result_list.append(item)
|
|
else:
|
|
result_no_db.append(item)
|
|
self.hit = len(result)
|
|
return result_list, result_no_db
|
|
|
|
|
|
async def answer_query(self, deep_search=False):
|
|
"""
|
|
Answers the search query.
|
|
|
|
Args:
|
|
- None.
|
|
|
|
Returns:
|
|
- result: The search result.
|
|
|
|
Raises:
|
|
- None.
|
|
"""
|
|
self.app.logger.info(f"Search started {self.uuid}")
|
|
cr_result = await self.search_crossref(query=self.query, deep_search=deep_search)
|
|
refined_result = await self.refine_search(cr_result)
|
|
answer, negative_answer = await self.check_if_exists(refined_result)
|
|
|
|
self.app.logger.info("Returning result")
|
|
self.app.logger.info(answer)
|
|
self.app.logger.info(negative_answer)
|
|
|
|
for item in answer:
|
|
self.final_result[item["DOI"]] = {"Title": item["data"]["title"], "type": item["data"]["type"]}
|
|
for item in negative_answer:
|
|
self.not_in_db[item["DOI"]] = {"Title": item["data"]["title"], "type": item["data"]["type"]}
|
|
self.app.logger.info("Returning result case2")
|
|
self.app.logger.info(self.final_result)
|
|
return self.final_result
|
|
|
|
# ============================= FLASK INTERNALS===============================
|
|
|
|
|
|
def flask_debug():
|
|
"""
|
|
Starts a Flask application in debug mode without using the reloader.
|
|
|
|
Args:
|
|
- None.
|
|
|
|
Returns:
|
|
- None.
|
|
|
|
Raises:
|
|
- None.
|
|
"""
|
|
# trunk-ignore(bandit/B201)
|
|
app.run(debug=True, use_reloader=False, host=HOST_ADDRESS, port=PORT_ADDRESS)
|
|
|
|
|
|
def waitress_run():
|
|
"""
|
|
Serves the Flask application using the Waitress WSGI server.
|
|
|
|
Args:
|
|
- None.
|
|
|
|
Returns:
|
|
- None.
|
|
|
|
Raises:
|
|
- None.
|
|
"""
|
|
serve(app, host=HOST_ADDRESS, port=PORT_ADDRESS)
|
|
|
|
|
|
class BackgroundTaskSearch(threading.Thread):
|
|
"""
|
|
A background task for searching and saving results to files.
|
|
|
|
This class extends the `threading.Thread` class and is responsible for running
|
|
the search task in the background. It retrieves queries from a queue, performs
|
|
the search, and saves the results to files.
|
|
|
|
Attributes:
|
|
app (App): The application instance.
|
|
"""
|
|
|
|
def run(self):
|
|
"""
|
|
Run the background task.
|
|
|
|
This method is called when the thread is started. It creates a new event loop,
|
|
runs the `_run` method, and closes the event loop.
|
|
"""
|
|
loop = asyncio.new_event_loop()
|
|
loop.run_until_complete(self._run())
|
|
loop.close()
|
|
|
|
async def _run(self):
|
|
"""
|
|
Perform the search task.
|
|
|
|
This method is an asynchronous coroutine that runs in a loop. It retrieves a
|
|
librarian from the queue, answers the query, and saves the results to files.
|
|
It also sends the results to a remote server.
|
|
|
|
The search task continues running indefinitely until the thread is stopped.
|
|
"""
|
|
while True:
|
|
database = None
|
|
ndb_database = None
|
|
librarian = librarian_queue.get()
|
|
self.app.logger.info("STARTED")
|
|
result = await librarian.answer_query(librarian.deep_search)
|
|
result = {librarian.uuid: result}
|
|
self.app.logger.info("Saving to file")
|
|
|
|
# Save results to "not_in_db.json" file
|
|
with open(lib_paths.NOT_IN_DB, "r+", encoding="utf-8") as ndb_file:
|
|
ndb_database = {}
|
|
try:
|
|
ndb_database = json.load(ndb_file)
|
|
except JSONDecodeError:
|
|
pass
|
|
if ndb_database:
|
|
ndb_database.update(librarian.not_in_db)
|
|
else:
|
|
ndb_database = librarian.not_in_db
|
|
ndb_file.truncate(0)
|
|
ndb_file.seek(0)
|
|
json.dump(ndb_database, ndb_file)
|
|
|
|
# Save results to "s_results.json" file
|
|
with open(lib_paths.S_RESULTS, "r+", encoding="utf-8") as s_file:
|
|
database = {}
|
|
try:
|
|
database = json.load(s_file)
|
|
except JSONDecodeError:
|
|
pass
|
|
if database:
|
|
self.app.logger.info(database)
|
|
self.app.logger.info(result)
|
|
database.update(result)
|
|
else:
|
|
database = result
|
|
self.app.logger.info("DUMPING DATA")
|
|
s_file.truncate(0)
|
|
s_file.seek(0)
|
|
json.dump(database, s_file)
|
|
self.app.logger.info("FINISHED")
|
|
|
|
self.app.logger.info(result)
|
|
coroutine = asyncio.to_thread(
|
|
requests.post,
|
|
f"{MAIN_BOT_ADDRESS}{SEND_RESULTS}",
|
|
json=result,
|
|
headers=_service_headers(),
|
|
timeout=360,
|
|
)
|
|
self.app.logger.info("SENT")
|
|
result = await coroutine
|
|
self.app.logger.info(result.status_code)
|
|
self.app.logger.info("SEND CONFIRMED")
|
|
await asyncio.sleep(1)
|
|
|
|
|
|
# ==================================SERVER ROUTES==========================================
|
|
@app.route("/query", methods=["POST"])
|
|
async def query_database():
|
|
_authorize_request()
|
|
"""
|
|
Endpoint for querying the database.
|
|
|
|
This function receives a POST request containing a JSON payload with a query and a UUID.
|
|
It creates a Librarian object with the query and UUID,
|
|
and adds it to the librarian_queue and librarian_list.
|
|
Finally, it returns a JSON response indicating the success
|
|
of the operation, along with the query, UUID,
|
|
and the current size of the librarian_queue.
|
|
|
|
Returns:
|
|
tuple: A tuple containing a JSON response and a status code.
|
|
"""
|
|
record = json.loads(request.data)
|
|
app.logger.info(record)
|
|
app.logger.info(record["query"])
|
|
app.logger.info(record["UUID"])
|
|
uuid = record["UUID"]
|
|
deep_search = record["deep_search"]
|
|
cl = Librarian(app, record["query"], uuid, deep_search)
|
|
librarian_queue.put(cl)
|
|
librarian_list.append(cl)
|
|
answer_data = (record["query"], record["UUID"], librarian_queue.qsize())
|
|
return_data = (
|
|
jsonify(isError=False, message="Success", statusCode=200, data=answer_data),
|
|
200,
|
|
)
|
|
return return_data
|
|
|
|
|
|
@app.route("/get_partial_result", methods=["POST"])
|
|
async def get_partial():
|
|
_authorize_request()
|
|
"""
|
|
Retrieves the partial result for a given UUID.
|
|
|
|
Returns:
|
|
A JSON response containing the partial result.
|
|
"""
|
|
record = json.loads(request.data)
|
|
app.logger.info(record)
|
|
app.logger.info(record["UUID"])
|
|
for lib in librarian_list:
|
|
if lib.uuid == record["UUID"]:
|
|
answer_data = lib.live_results
|
|
break
|
|
return_data = (
|
|
jsonify(isError=False, message="Success", statusCode=200, data=answer_data),
|
|
200,
|
|
)
|
|
return return_data
|
|
|
|
|
|
# =======================================MAIN===================================================
|
|
if __name__ == "__main__":
|
|
app.logger.setLevel(logging.DEBUG)
|
|
LOGFILE_PATH.parent.mkdir(parents=True, exist_ok=True)
|
|
h1 = handlers.RotatingFileHandler(
|
|
filename=str(LOGFILE_PATH),
|
|
encoding=ENCODING,
|
|
mode="a",
|
|
maxBytes=6 * 1024 * 1024,
|
|
backupCount=6,
|
|
)
|
|
|
|
app.logger.addHandler(h1)
|
|
threads = []
|
|
threads.append(threading.Thread(target=waitress_run, daemon=True))
|
|
# threads.append(threading.Thread(target=flask_debug))
|
|
bgtask = BackgroundTaskSearch()
|
|
bgtask.app = app
|
|
bgtask.daemon = True
|
|
threads.append(bgtask)
|
|
threads.append(
|
|
threading.Thread(
|
|
target=scrape_bot.scraper, args=(app.logger,), daemon=True
|
|
)
|
|
)
|
|
i = 0
|
|
try:
|
|
for worker in threads:
|
|
app.logger.info("App number: %s", i)
|
|
i += 1
|
|
worker.start()
|
|
for worker in threads:
|
|
worker.join()
|
|
except KeyboardInterrupt:
|
|
app.logger.info("Shutdown requested - exiting librarian service")
|