diff options
Diffstat (limited to 'uploader/phenotypes')
| -rw-r--r-- | uploader/phenotypes/misc.py | 26 | ||||
| -rw-r--r-- | uploader/phenotypes/models.py | 281 | ||||
| -rw-r--r-- | uploader/phenotypes/views.py | 235 |
3 files changed, 493 insertions, 49 deletions
diff --git a/uploader/phenotypes/misc.py b/uploader/phenotypes/misc.py new file mode 100644 index 0000000..cbe3b7f --- /dev/null +++ b/uploader/phenotypes/misc.py @@ -0,0 +1,26 @@ +"""Miscellaneous functions handling phenotypes and phenotypes data.""" +import logging + +logger = logging.getLogger(__name__) + + +def phenotypes_data_differences( + filedata: tuple[dict, ...], dbdata: tuple[dict, ...] +) -> tuple[dict, ...]: + """Compute differences between file data and db data""" + diff = tuple() + for filerow, dbrow in zip( + sorted(filedata, key=lambda item: (item["phenotype_id"], item["xref_id"])), + sorted(dbdata, key=lambda item: (item["PhenotypeId"], item["xref_id"]))): + for samplename, value in filerow["data"].items(): + if value != dbrow["data"].get(samplename, {}).get("value"): + diff = diff + ({ + "PhenotypeId": filerow["phenotype_id"], + "xref_id": filerow["xref_id"], + "DataId": dbrow["DataId"], + "StrainId": dbrow["data"].get(samplename, {}).get("StrainId"), + "StrainName": samplename, + "value": value + },) + + return diff diff --git a/uploader/phenotypes/models.py b/uploader/phenotypes/models.py index e1ec0c9..e40155f 100644 --- a/uploader/phenotypes/models.py +++ b/uploader/phenotypes/models.py @@ -1,14 +1,31 @@ """Database and utility functions for phenotypes.""" -from typing import Optional +import logging +import tempfile +from pathlib import Path from functools import reduce from datetime import datetime +from typing import Optional, Iterable import MySQLdb as mdb from MySQLdb.cursors import Cursor, DictCursor -from flask import current_app as app from gn_libs.mysqldb import debug_query +from functional_tools import take + +logger = logging.getLogger(__name__) + + +__PHENO_DATA_TABLES__ = { + "PublishData": { + "table": "PublishData", "valueCol": "value", "DataIdCol": "Id"}, + "PublishSE": { + "table": "PublishSE", "valueCol": "error", "DataIdCol": "DataId"}, + "NStrain": { + "table": "NStrain", "valueCol": "count", "DataIdCol": "DataId"} +} + + def datasets_by_population( conn: mdb.Connection, species_id: int, @@ -32,10 +49,10 @@ def dataset_by_id(conn: mdb.Connection, """Fetch dataset details by identifier""" with conn.cursor(cursorclass=DictCursor) as cursor: cursor.execute( - "SELECT s.SpeciesId, pf.* FROM Species AS s " - "INNER JOIN InbredSet AS iset ON s.Id=iset.SpeciesId " - "INNER JOIN PublishFreeze AS pf ON iset.Id=pf.InbredSetId " - "WHERE s.Id=%s AND iset.Id=%s AND pf.Id=%s", + "SELECT Species.SpeciesId, PublishFreeze.* FROM Species " + "INNER JOIN InbredSet ON Species.Id=InbredSet.SpeciesId " + "INNER JOIN PublishFreeze ON InbredSet.Id=PublishFreeze.InbredSetId " + "WHERE Species.Id=%s AND InbredSet.Id=%s AND PublishFreeze.Id=%s", (species_id, population_id, dataset_id)) return dict(cursor.fetchone()) @@ -75,7 +92,8 @@ def dataset_phenotypes(conn: mdb.Connection, limit: Optional[int] = None) -> tuple[dict, ...]: """Fetch the actual phenotypes.""" _query = ( - "SELECT pheno.*, pxr.Id AS xref_id, ist.InbredSetCode FROM Phenotype AS pheno " + "SELECT pheno.*, pxr.Id AS xref_id, pxr.InbredSetId, ist.InbredSetCode " + "FROM Phenotype AS pheno " "INNER JOIN PublishXRef AS pxr ON pheno.Id=pxr.PhenotypeId " "INNER JOIN PublishFreeze AS pf ON pxr.InbredSetId=pf.InbredSetId " "INNER JOIN InbredSet AS ist ON pf.InbredSetId=ist.Id " @@ -83,7 +101,7 @@ def dataset_phenotypes(conn: mdb.Connection, f" LIMIT {limit} OFFSET {offset}" if bool(limit) else "") with conn.cursor(cursorclass=DictCursor) as cursor: cursor.execute(_query, (population_id, dataset_id)) - debug_query(cursor, app.logger) + debug_query(cursor, logger) return tuple(dict(row) for row in cursor.fetchall()) @@ -94,7 +112,7 @@ def __phenotype_se__(cursor: Cursor, xref_id, dataids_and_strainids): cursor.execute("SELECT * FROM PublishSE WHERE (DataId, StrainId) IN " f"({paramstr})", flat) - debug_query(cursor, app.logger) + debug_query(cursor, logger) _se = { (row["DataId"], row["StrainId"]): { "DataId": row["DataId"], @@ -107,7 +125,7 @@ def __phenotype_se__(cursor: Cursor, xref_id, dataids_and_strainids): cursor.execute("SELECT * FROM NStrain WHERE (DataId, StrainId) IN " f"({paramstr})", flat) - debug_query(cursor, app.logger) + debug_query(cursor, logger) _n = { (row["DataId"], row["StrainId"]): { "DataId": row["DataId"], @@ -137,6 +155,7 @@ def __organise_by_phenotype__(pheno, row): "Pre_publication_abbreviation": row["Pre_publication_abbreviation"], "Post_publication_abbreviation": row["Post_publication_abbreviation"], "xref_id": row["pxr.Id"], + "DataId": row["DataId"], "data": { **(_pheno["data"] if bool(_pheno) else {}), (row["DataId"], row["StrainId"]): { @@ -200,7 +219,7 @@ def phenotype_by_id( ).values()) } if bool(_pheno) and len(_pheno.keys()) > 1: - raise Exception( + raise Exception(# pylint: disable=[broad-exception-raised] "We found more than one phenotype with the same identifier!") return None @@ -225,7 +244,7 @@ def phenotypes_data(conn: mdb.Connection, f" LIMIT {limit} OFFSET {offset}" if bool(limit) else "") with conn.cursor(cursorclass=DictCursor) as cursor: cursor.execute(_query, (population_id, dataset_id)) - debug_query(cursor, app.logger) + debug_query(cursor, logger) return tuple(dict(row) for row in cursor.fetchall()) @@ -252,5 +271,241 @@ def save_new_dataset(cursor: Cursor, "%(created)s, %(public)s, %(population_id)s, %(confidentiality)s, " "%(users)s)", params) - debug_query(cursor, app.logger) + debug_query(cursor, logger) return {**params, "Id": cursor.lastrowid} + + +def phenotypes_data_by_ids( + conn: mdb.Connection, + inbred_pheno_xref: dict[str, int] +) -> tuple[dict, ...]: + """Fetch all phenotype data, filtered by the `inbred_pheno_xref` mapping.""" + _paramstr = ",".join(["(%s, %s, %s)"] * len(inbred_pheno_xref)) + _query = ("SELECT " + "pub.PubMed_ID, pheno.*, pxr.*, pd.*, str.*, iset.InbredSetCode " + "FROM Publication AS pub " + "RIGHT JOIN PublishXRef AS pxr0 ON pub.Id=pxr0.PublicationId " + "INNER JOIN Phenotype AS pheno ON pxr0.PhenotypeId=pheno.id " + "INNER JOIN PublishXRef AS pxr ON pheno.Id=pxr.PhenotypeId " + "INNER JOIN PublishData AS pd ON pxr.DataId=pd.Id " + "INNER JOIN Strain AS str ON pd.StrainId=str.Id " + "INNER JOIN StrainXRef AS sxr ON str.Id=sxr.StrainId " + "INNER JOIN PublishFreeze AS pf ON sxr.InbredSetId=pf.InbredSetId " + "INNER JOIN InbredSet AS iset ON pf.InbredSetId=iset.InbredSetId " + f"WHERE (pxr.InbredSetId, pheno.Id, pxr.Id) IN ({_paramstr}) " + "ORDER BY pheno.Id") + with conn.cursor(cursorclass=DictCursor) as cursor: + cursor.execute(_query, tuple(item for row in inbred_pheno_xref + for item in (row["population_id"], + row["phenoid"], + row["xref_id"]))) + debug_query(cursor, logger) + return tuple( + reduce(__organise_by_phenotype__, cursor.fetchall(), {}).values()) + + +def __pre_process_phenotype_data__(row): + _desc = row.get("description", "") + _pre_pub_desc = row.get("pre_publication_description", _desc) + _orig_desc = row.get("original_description", _desc) + _post_pub_desc = row.get("post_publication_description", _orig_desc) + _pre_pub_abbr = row.get("pre_publication_abbreviation", row["id"]) + _post_pub_abbr = row.get("post_publication_abbreviation", _pre_pub_abbr) + return { + "pre_publication_description": _pre_pub_desc, + "post_publication_description": _post_pub_desc, + "original_description": _orig_desc, + "units": row["units"], + "pre_publication_abbreviation": _pre_pub_abbr, + "post_publication_abbreviation": _post_pub_abbr + } + + +def create_new_phenotypes(# pylint: disable=[too-many-locals] + conn: mdb.Connection, + population_id: int, + publication_id: int, + phenotypes: Iterable[dict] +) -> tuple[dict, ...]: + """Add entirely new phenotypes to the database. WARNING: Not thread-safe.""" + _phenos = tuple() + with conn.cursor(cursorclass=DictCursor) as cursor: + def make_next_id(idcol, table): + cursor.execute(f"SELECT MAX({idcol}) AS last_id FROM {table}") + _last_id = int(cursor.fetchone()["last_id"]) + def __next_id__(): + _next_id = _last_id + 1 + while True: + yield _next_id + _next_id = _next_id + 1 + + return __next_id__ + + ### Bottleneck: Everything below makes this function not ### + ### thread-safe because we have to retrieve the last IDs from ### + ### the database and increment those to compute the next IDs. ### + ### This is an unfortunate result from the current schema that ### + ### has a cross-reference table that requires that a phenotype ### + ### be linked to an existing publication, and have data IDs to ### + ### link to that phenotype's data. ### + ### The fact that the IDs are sequential also compounds the ### + ### bottleneck. ### + ### + ### For extra safety, ensure the following tables are locked ### + ### for `WRITE`: ### + ### - PublishXRef ### + ### - Phenotype ### + ### - PublishXRef ### + __next_xref_id = make_next_id("Id", "PublishXRef")() + __next_pheno_id__ = make_next_id("Id", "Phenotype")() + __next_data_id__ = make_next_id("DataId", "PublishXRef")() + + def __build_params_and_prepubabbrevs__(acc, row): + processed = __pre_process_phenotype_data__(row) + return ( + acc[0] + ({ + **processed, + "population_id": population_id, + "publication_id": publication_id, + "phenotype_id": next(__next_pheno_id__), + "xref_id": next(__next_xref_id), + "data_id": next(__next_data_id__) + },), + acc[1] + (processed["pre_publication_abbreviation"],)) + while True: + batch = take(phenotypes, 1000) + if len(batch) == 0: + break + + params, abbrevs = reduce(__build_params_and_prepubabbrevs__, + batch, + (tuple(), tuple())) + # Check for uniqueness for all "Pre_publication_description" values + abbrevs_paramsstr = ", ".join(["%s"] * len(abbrevs)) + _query = ("SELECT PublishXRef.PhenotypeId, Phenotype.* " + "FROM PublishXRef " + "INNER JOIN Phenotype " + "ON PublishXRef.PhenotypeId=Phenotype.Id " + "WHERE PublishXRef.InbredSetId=%s " + "AND Phenotype.Pre_publication_abbreviation IN " + f"({abbrevs_paramsstr})") + cursor.execute(_query, + ((population_id,) + abbrevs)) + existing = tuple(row["Pre_publication_abbreviation"] + for row in cursor.fetchall()) + if len(existing) > 0: + # Narrow this exception, perhaps? + raise Exception(# pylint: disable=[broad-exception-raised] + "Found already existing phenotypes with the following " + "'Pre-publication abbreviations':\n\t" + "\n\t".join(f"* {item}" for item in existing)) + + cursor.executemany( + ( + "INSERT INTO " + "Phenotype(" + "Id, " + "Pre_publication_description, " + "Post_publication_description, " + "Original_description, " + "Units, " + "Pre_publication_abbreviation, " + "Post_publication_abbreviation, " + "Authorized_Users" + ")" + "VALUES (" + "%(phenotype_id)s, " + "%(pre_publication_description)s, " + "%(post_publication_description)s, " + "%(original_description)s, " + "%(units)s, " + "%(pre_publication_abbreviation)s, " + "%(post_publication_abbreviation)s, " + "'robwilliams'" + ")"), + params) + _comments = f"Created at {datetime.now().isoformat()}" + cursor.executemany( + ("INSERT INTO PublishXRef(" + "Id, " + "InbredSetId, " + "PhenotypeId, " + "PublicationId, " + "DataId, " + "comments" + ")" + "VALUES(" + "%(xref_id)s, " + "%(population_id)s, " + "%(phenotype_id)s, " + "%(publication_id)s, " + "%(data_id)s, " + f"'{_comments}'" + ")"), + params) + _phenos = _phenos + params + + return _phenos + + +def save_phenotypes_data( + conn: mdb.Connection, + table: str, + data: Iterable[dict] +) -> int: + """Save new phenotypes data into the database.""" + _table_details = __PHENO_DATA_TABLES__[table] + with conn.cursor(cursorclass=DictCursor) as cursor: + _count = 0 + while True: + batch = take(data, 100000) + if len(batch) == 0: + logger.warning("Got an empty batch. This needs investigation.") + break + + logger.debug("Saving batch of %s items.", len(batch)) + cursor.executemany( + (f"INSERT INTO {_table_details['table']}" + f"({_table_details['DataIdCol']}, StrainId, {_table_details['valueCol']}) " + "VALUES " + f"(%(data_id)s, %(sample_id)s, %(value)s) "), + tuple(batch)) + debug_query(cursor, logger) + _count = _count + len(batch) + + + logger.debug("Saved a total of %s data rows", _count) + return _count + + +def quick_save_phenotypes_data( + conn: mdb.Connection, + table: str, + dataitems: Iterable[dict], + tmpdir: Path +) -> int: + """Save data items to the database, but using """ + _table_details = __PHENO_DATA_TABLES__[table] + with (tempfile.NamedTemporaryFile( + prefix=f"{table}_data", mode="wt", dir=tmpdir) as tmpfile, + conn.cursor(cursorclass=DictCursor) as cursor): + _count = 0 + logger.debug("Write data rows to text file.") + for row in dataitems: + tmpfile.write( + f'{row["data_id"]}\t{row["sample_id"]}\t{row["value"]}\n') + _count = _count + 1 + tmpfile.flush() + + logger.debug("Load text file into database (table: %s)", + _table_details["table"]) + cursor.execute( + f"LOAD DATA LOCAL INFILE '{tmpfile.name}' " + f"INTO TABLE {_table_details['table']} " + "(" + f"{_table_details['DataIdCol']}, " + "StrainId, " + f"{_table_details['valueCol']}" + ")") + debug_query(cursor, logger) + return _count diff --git a/uploader/phenotypes/views.py b/uploader/phenotypes/views.py index dc2df8f..556b5ff 100644 --- a/uploader/phenotypes/views.py +++ b/uploader/phenotypes/views.py @@ -1,19 +1,26 @@ -"""Views handling ('classical') phenotypes.""" +"""Views handling ('classical') phenotypes."""# pylint: disable=[too-many-lines] import sys import uuid import json -import datetime +import logging from typing import Any from pathlib import Path from zipfile import ZipFile from functools import wraps, reduce -from logging import INFO, ERROR, DEBUG, FATAL, CRITICAL, WARNING +from urllib.parse import urljoin, urlparse, ParseResult, urlunparse, urlencode + +import datetime from redis import Redis from pymonad.either import Left from requests.models import Response from MySQLdb.cursors import DictCursor + +from gn_libs import sqlite3 +from gn_libs import jobs as gnlibs_jobs +from gn_libs.jobs.jobs import JobNotFound from gn_libs.mysqldb import database_connection + from flask import (flash, request, url_for, @@ -22,19 +29,23 @@ from flask import (flash, Blueprint, current_app as app) -# from r_qtl import r_qtl2 as rqtl2 from r_qtl import r_qtl2_qc as rqc from r_qtl import exceptions as rqe + from uploader import jobs +from uploader import session from uploader.files import save_file#, fullpath from uploader.ui import make_template_renderer from uploader.oauth2.client import oauth2_post +from uploader.oauth2.tokens import request_token from uploader.authorisation import require_login +from uploader.oauth2 import client as oauth2client from uploader.route_utils import generic_select_population from uploader.datautils import safe_int, enumerate_sequence from uploader.species.models import all_species, species_by_id from uploader.monadic_requests import make_either_error_handler +from uploader.publications.models import fetch_publication_by_id from uploader.request_checks import with_species, with_population from uploader.input_validation import (encode_errors, decode_errors, @@ -241,12 +252,7 @@ def view_phenotype(# pylint: disable=[unused-argument] if (key in ("PubMed_ID", "Authors", "Title", "Journal") and __non_empty__(val)) }, - privileges=(privileges - ### For demo! Do not commit this part - + ("group:resource:edit-resource", - "group:resource:delete-resource",) - ### END: For demo! Do not commit this part - ), + privileges=privileges, activelink="view-phenotype") def __fail__(error): @@ -353,10 +359,17 @@ def process_phenotypes_individual_files(error_uri): bundlepath = Path(app.config["UPLOAD_FOLDER"], f"{str(uuid.uuid4()).replace('-', '')}.zip") with ZipFile(bundlepath,mode="w") as zfile: - for rqtlkey, formkey in (("phenocovar", "phenotype-descriptions"), - ("pheno", "phenotype-data"), - ("phenose", "phenotype-se"), - ("phenonum", "phenotype-n")): + for rqtlkey, formkey, _type in ( + ("phenocovar", "phenotype-descriptions", "mandatory"), + ("pheno", "phenotype-data", "mandatory"), + ("phenose", "phenotype-se", "optional"), + ("phenonum", "phenotype-n", "optional")): + if _type == "optional" and not bool(form.get(formkey)): + continue # skip if an optional key does not exist. + + cdata[f"{rqtlkey}_transposed"] = ( + (form.get(f"{formkey}-transposed") or "off") == "on") + if form.get("resumable-upload", False): # Chunked upload of large files was used filedata = json.loads(form[formkey]) @@ -365,7 +378,7 @@ def process_phenotypes_individual_files(error_uri): arcname=filedata["original-name"]) cdata[rqtlkey] = cdata.get(rqtlkey, []) + [filedata["original-name"]] else: - # TODO: Check this path: fix any bugs. + # T0DO: Check this path: fix any bugs. _sentfile = request.files[formkey] if not bool(_sentfile): flash(f"Expected file ('{formkey}') was not provided.", @@ -379,6 +392,7 @@ def process_phenotypes_individual_files(error_uri): arcname=filepath.name) cdata[rqtlkey] = cdata.get(rqtlkey, []) + [filepath.name] + zfile.writestr("control_data.json", data=json.dumps(cdata, indent=2)) return bundlepath @@ -403,10 +417,7 @@ def add_phenotypes(species: dict, population: dict, dataset: dict, **kwargs):# p dataset_id=dataset["Id"])) _redisuri = app.config["REDIS_URL"] _sqluri = app.config["SQL_URI"] - with (Redis.from_url(_redisuri, decode_responses=True) as rconn, - # database_connection(_sqluri) as conn, - # conn.cursor(cursorclass=DictCursor) as cursor - ): + with Redis.from_url(_redisuri, decode_responses=True) as rconn: if request.method == "GET": today = datetime.date.today() return render_template( @@ -441,24 +452,20 @@ def add_phenotypes(species: dict, population: dict, dataset: dict, **kwargs):# p [sys.executable, "-m", "scripts.rqtl2.phenotypes_qc", _sqluri, _redisuri, _namespace, str(_jobid), str(species["SpeciesId"]), str(population["Id"]), - # str(dataset["Id"]), str(phenobundle), "--loglevel", - { - INFO: "INFO", - ERROR: "ERROR", - DEBUG: "DEBUG", - FATAL: "FATAL", - CRITICAL: "CRITICAL", - WARNING: "WARNING" - }[app.logger.getEffectiveLevel()], + logging.getLevelName( + app.logger.getEffectiveLevel() + ).lower(), "--redisexpiry", str(_ttl_seconds)], "phenotype_qc", _ttl_seconds, {"job-metadata": json.dumps({ "speciesid": species["SpeciesId"], "populationid": population["Id"], "datasetid": dataset["Id"], - "bundle": str(phenobundle.absolute())})}), + "bundle": str(phenobundle.absolute()), + **({"publicationid": request.form["publication-id"]} + if request.form.get("publication-id") else {})})}), _redisuri, f"{app.config['UPLOAD_FOLDER']}/job_errors") @@ -531,7 +538,8 @@ def review_job_data( **kwargs ):# pylint: disable=[unused-argument] """Review data one more time before entering it into the database.""" - with Redis.from_url(app.config["REDIS_URL"], decode_responses=True) as rconn: + with (Redis.from_url(app.config["REDIS_URL"], decode_responses=True) as rconn, + database_connection(app.config["SQL_URI"]) as conn): try: job = jobs.job(rconn, jobs.jobsnamespace(), str(job_id)) except jobs.JobNotFound as _jnf: @@ -579,6 +587,7 @@ def review_job_data( filetype: __summarise__(filetype, meta) for filetype,meta in metadata.items() } + _job_metadata = json.loads(job["job-metadata"]) return render_template("phenotypes/review-job-data.html", species=species, population=population, @@ -586,9 +595,103 @@ def review_job_data( job_id=job_id, job=job, summary=summary, + publication=( + fetch_publication_by_id( + conn, int(_job_metadata["publicationid"])) + if _job_metadata.get("publicationid") + else None), activelink="add-phenotypes") +def load_phenotypes_success_handler(job): + """Handle loading new phenotypes into the database successfully.""" + return redirect(url_for( + "species.populations.phenotypes.load_data_success", + species_id=job["metadata"]["species_id"], + population_id=job["metadata"]["population_id"], + dataset_id=job["metadata"]["dataset_id"], + job_id=job["job_id"])) + + +@phenotypesbp.route( + "<int:species_id>/populations/<int:population_id>/phenotypes/datasets" + "/<int:dataset_id>/load-data-to-database", + methods=["POST"]) +@require_login +@with_dataset( + species_redirect_uri="species.populations.phenotypes.index", + population_redirect_uri="species.populations.phenotypes.select_population", + redirect_uri="species.populations.phenotypes.list_datasets") +def load_data_to_database( + species: dict, + population: dict, + dataset: dict, + **kwargs +):# pylint: disable=[unused-argument] + """Load the data from the given QC job into the database.""" + _jobs_db = app.config["ASYNCHRONOUS_JOBS_SQLITE_DB"] + with (Redis.from_url(app.config["REDIS_URL"], decode_responses=True) as rconn, + sqlite3.connection(_jobs_db) as conn): + # T0DO: Maybe break the connection between the jobs here, pass: + # - the bundle name (rebuild the full path here.) + # - publication details, where separate + # - details about the files: e.g. total lines, etc + qc_job = jobs.job(rconn, jobs.jobsnamespace(), request.form["data-qc-job-id"]) + _meta = json.loads(qc_job["job-metadata"]) + _load_job_id = uuid.uuid4() + _loglevel = logging.getLevelName(app.logger.getEffectiveLevel()).lower() + command = [ + sys.executable, + "-u", + "-m", + "scripts.load_phenotypes_to_db", + app.config["SQL_URI"], + _jobs_db, + str(_load_job_id), + "--log-level", + _loglevel + ] + + def __handle_error__(resp): + return render_template("http-error.html", *resp.json()) + + def __handle_success__(load_job): + app.logger.debug("The phenotypes loading job: %s", load_job) + return redirect(url_for( + "background-jobs.job_status", job_id=load_job["job_id"])) + + + return request_token( + token_uri=urljoin(oauth2client.authserver_uri(), "auth/token"), + user_id=session.user_details()["user_id"] + ).then( + lambda token: gnlibs_jobs.initialise_job( + conn, + _load_job_id, + command, + "load-new-phenotypes-data", + extra_meta={ + "species_id": species["SpeciesId"], + "population_id": population["Id"], + "dataset_id": dataset["Id"], + "bundle_file": _meta["bundle"], + "publication_id": _meta["publicationid"], + "authserver": oauth2client.authserver_uri(), + "token": token["access_token"], + "success_handler": ( + "uploader.phenotypes.views" + ".load_phenotypes_success_handler") + }) + ).then( + lambda job: gnlibs_jobs.launch_job( + job, + _jobs_db, + Path(f"{app.config['UPLOAD_FOLDER']}/job_errors"), + worker_manager="gn_libs.jobs.launcher", + loglevel=_loglevel) + ).either(__handle_error__, __handle_success__) + + def update_phenotype_metadata(conn, metadata: dict): """Update a phenotype's basic metadata values.""" with conn.cursor(cursorclass=DictCursor) as cursor: @@ -741,12 +844,7 @@ def edit_phenotype_data(# pylint: disable=[unused-argument] def __render__(**kwargs): processed_kwargs = { **kwargs, - "privileges": (kwargs.get("privileges", tuple()) - ### For demo! Do not commit this part - + ("group:resource:edit-resource", - "group:resource:delete-resource",) - ### END: For demo! Do not commit this part - ) + "privileges": kwargs.get("privileges", tuple()) } return render_template( "phenotypes/edit-phenotype.html", @@ -844,3 +942,68 @@ def edit_phenotype_data(# pylint: disable=[unused-argument] population_id=population["Id"], dataset_id=dataset["Id"], xref_id=xref_id)) + + +@phenotypesbp.route( + "<int:species_id>/populations/<int:population_id>/phenotypes/datasets" + "/<int:dataset_id>/load-data-success/<uuid:job_id>", + methods=["GET"]) +@require_login +@with_dataset( + species_redirect_uri="species.populations.phenotypes.index", + population_redirect_uri="species.populations.phenotypes.select_population", + redirect_uri="species.populations.phenotypes.list_datasets") +def load_data_success( + species: dict, + population: dict, + dataset: dict, + job_id: uuid.UUID, + **kwargs +):# pylint: disable=[unused-argument] + """Display success page if loading data to database was successful.""" + with (database_connection(app.config["SQL_URI"]) as conn, + sqlite3.connection(app.config["ASYNCHRONOUS_JOBS_SQLITE_DB"]) + as jobsconn): + try: + gn2_uri = urlparse(app.config["GN2_SERVER_URL"]) + job = gnlibs_jobs.job(jobsconn, job_id, fulldetails=True) + app.logger.debug("THE JOB: %s", job) + _xref_ids = tuple( + str(item) for item + in json.loads(job["metadata"].get("xref_ids", "[]"))) + _publication = fetch_publication_by_id( + conn, int(job["metadata"].get("publication_id", "0"))) + _search_terms = (item for item in + (str(_publication["PubMed_ID"] or ""), + _publication["Authors"], + (_publication["Title"] or "")) + if item != "") + return render_template("phenotypes/load-phenotypes-success.html", + species=species, + population=population, + dataset=dataset, + job=job, + search_page_uri=urlunparse(ParseResult( + scheme=gn2_uri.scheme, + netloc=gn2_uri.netloc, + path="/search", + params="", + query=urlencode({ + "species": species["Name"], + "group": population["Name"], + "type": "Phenotypes", + "dataset": dataset["Name"], + "search_terms_or": ( + # Very long URLs will cause + # errors. + " ".join(_xref_ids) + if len(_xref_ids) <= 100 + else ""), + "search_terms_and": " ".join( + _search_terms).strip(), + "accession_id": "None", + "FormID": "searchResult" + }), + fragment=""))) + except JobNotFound as _jnf: + return render_template("jobs/job-not-found.html", job_id=job_id) |