[HOTFIX] Deploy old salmon version rerunning! (and others)

api/data_refinery_api/management/commands/update_es_index.py

@@ -0,0 +1,31 @@
+import datetime
+
+from django.core.management.base import BaseCommand
+from django_elasticsearch_dsl.registries import registry
+from django.utils import timezone
+
+
+# We'll update for the past 30 minutes every 20 minutes.
+UPDATE_WINDOW = datetime.timedelta(minutes=30)
+
+
+class Command(BaseCommand):
+    help = 'Manage elasticsearch index.'
+
+    def handle(self, *args, **options):
+        """This command is based off of the 'populate' command of Django ES DSL:
+
+        https://github.com/sabricot/django-elasticsearch-dsl/blob/f6b2e0694e4ed69826c824196ccec5863874c856/django_elasticsearch_dsl/management/commands/search_index.py#L86
+
+        We have updated it so that it will do incremental updates
+        rather than looping over the full queryset every time.
+        """
+        models = set(registry.get_models())
+
+        for doc in registry.get_documents(models):
+            start_time = timezone.now() - UPDATE_WINDOW
+            qs = doc().get_queryset().filter(last_modified__gt=start_time).order_by('id')
+            self.stdout.write("Indexing {} '{}' objects".format(
+                qs.count(), qs.model.__name__)
+            )
+            doc().update(qs)

api/data_refinery_api/serializers.py

@@ -613,7 +613,7 @@ def __init__(self, *args, **kwargs):
 
         if 'context' in kwargs:
             if 'request' in kwargs['context']:
-                # only inclue the fields `experiments` and `organism_samples` when the param `?details=true`
+                # only include the fields `experiments` and `organism_samples` when the param `?details=true`
                 # is provided. This is used on the frontend to render the downloads page
                 # thanks to https://django.cowhite.com/blog/dynamically-includeexclude-fields-to-django-rest-framwork-serializers-based-on-user-requests/
                 if 'details' not in kwargs['context']['request'].query_params:

api/data_refinery_api/views.py

@@ -939,14 +939,27 @@ def update_cache(cls, range_param):
 
         return data
 
-    EMAIL_USERNAME_BLACKLIST = ['arielsvn', 'miserlou', 'kurt.wheeler91', 'd.prasad']
+
+    EMAIL_USERNAME_BLACKLIST = [
+        'arielsvn',
+        'cansav09',
+        'd.prasad',
+        'daniel.himmelstein',
+        'dv.prasad991',
+        'greenescientist',
+        'jaclyn.n.taroni',
+        'kurt.wheeler91',
+        'michael.zietz',
+        'miserlou'
+    ]
 
     @classmethod
     def _get_dataset_stats(cls, range_param):
         """Returns stats for processed datasets"""
         filter_query = Q()
         for username in Stats.EMAIL_USERNAME_BLACKLIST:
             filter_query = filter_query | Q(email_address__startswith=username)
+        filter_query = filter_query | Q(email_address__endswith='@alexslemonade.org')
         processed_datasets = Dataset.objects.filter(is_processed=True, email_address__isnull=False).exclude(filter_query)
         result = processed_datasets.aggregate(
             total=Count('id'),

common/data_refinery_common/job_management.py

@@ -6,12 +6,16 @@
     DownloaderJob,
     DownloaderJobOriginalFileAssociation,
     OriginalFile,
+    ProcessorJob,
+    ProcessorJobOriginalFileAssociation,
 )
 from data_refinery_common.utils import (
     get_env_variable,
     get_env_variable_gracefully,
     get_instance_id,
 )
+from data_refinery_common.job_lookup import determine_processor_pipeline, determine_ram_amount, ProcessorEnum, ProcessorPipeline, Downloaders
+from data_refinery_common.message_queue import send_job
 
 
 logger = get_and_configure_logger(__name__)
@@ -141,3 +145,122 @@ def create_downloader_job(undownloaded_files: List[OriginalFile],
             )
 
     return True
+
+# TODO: extend this list.
+BLACKLISTED_EXTENSIONS = ["xml", "chp", "exp"]
+
+def delete_if_blacklisted(original_file: OriginalFile) -> OriginalFile:
+    extension = original_file.filename.split(".")[-1]
+    if extension.lower() in BLACKLISTED_EXTENSIONS:
+        logger.debug("Original file had a blacklisted extension of %s, skipping",
+                     extension,
+                     original_file=original_file.id)
+
+        original_file.delete_local_file()
+        original_file.is_downloaded = False
+        original_file.save()
+        return None
+
+    return original_file
+
+def create_processor_jobs_for_original_files(original_files: List[OriginalFile],
+                                             downloader_job: DownloaderJob=None):
+    """
+    Creates one processor job for each original file given.
+    """
+    for original_file in original_files:
+        sample_object = original_file.samples.first()
+
+        if not delete_if_blacklisted(original_file):
+            continue
+
+        # Fix for: https://github.com/AlexsLemonade/refinebio/issues/968
+        # Basically, we incorrectly detected technology/manufacturers
+        # for many Affymetrix samples and this is a good place to fix
+        # some of them.
+        if original_file.is_affy_data():
+            # Only Affymetrix Microarrays produce .CEL files
+            sample_object.technology = 'MICROARRAY'
+            sample_object.manufacturer = 'AFFYMETRIX'
+            sample_object.save()
+
+        pipeline_to_apply = determine_processor_pipeline(sample_object, original_file)
+
+        if pipeline_to_apply == ProcessorPipeline.NONE:
+            logger.info("No valid processor pipeline found to apply to sample.",
+                        sample=sample_object.id,
+                        original_file=original_files[0].id)
+            original_file.delete_local_file()
+            original_file.is_downloaded = False
+            original_file.save()
+        else:
+            processor_job = ProcessorJob()
+            processor_job.pipeline_applied = pipeline_to_apply.value
+            processor_job.ram_amount = determine_ram_amount(sample_object, processor_job)
+            processor_job.save()
+
+            assoc = ProcessorJobOriginalFileAssociation()
+            assoc.original_file = original_file
+            assoc.processor_job = processor_job
+            assoc.save()
+
+            if downloader_job:
+                logger.debug("Queuing processor job.",
+                             processor_job=processor_job.id,
+                             original_file=original_file.id,
+                             downloader_job=downloader_job.id)
+            else:
+                logger.debug("Queuing processor job.",
+                             processor_job=processor_job.id,
+                             original_file=original_file.id)
+
+            try:
+                send_job(pipeline_to_apply, processor_job)
+            except:
+                # If we cannot queue the job now the Foreman will do
+                # it later.
+                pass
+
+
+def create_processor_job_for_original_files(original_files: List[OriginalFile],
+                                            downloader_job: DownloaderJob=None):
+    """
+    Create a processor job and queue a processor task for sample related to an experiment.
+    """
+
+    # If there's no original files then we've created all the jobs we need to!
+    if len(original_files) == 0:
+        return
+
+    # For anything that has raw data there should only be one Sample per OriginalFile
+    sample_object = original_files[0].samples.first()
+    pipeline_to_apply = determine_processor_pipeline(sample_object, original_files[0])
+
+    if pipeline_to_apply == ProcessorPipeline.NONE:
+        logger.info("No valid processor pipeline found to apply to sample.",
+                    sample=sample_object.id,
+                    original_file=original_files[0].id)
+        for original_file in original_files:
+            original_file.delete_local_file()
+            original_file.is_downloaded = False
+            original_file.save()
+    else:
+        processor_job = ProcessorJob()
+        processor_job.pipeline_applied = pipeline_to_apply.value
+        processor_job.ram_amount = determine_ram_amount(sample_object, processor_job)
+        processor_job.save()
+        for original_file in original_files:
+            assoc = ProcessorJobOriginalFileAssociation()
+            assoc.original_file = original_file
+            assoc.processor_job = processor_job
+            assoc.save()
+
+        logger.debug("Queuing processor job.",
+                     processor_job=processor_job.id)
+
+        try:
+            send_job(pipeline_to_apply, processor_job)
+        except:
+            # If we cannot queue the job now the Foreman will do
+            # it later.
+            pass

common/data_refinery_common/rna_seq.py

@@ -1,4 +1,5 @@
 from typing import Dict, List
+from django.db.models import OuterRef, Subquery
 
 from data_refinery_common.job_lookup import ProcessorEnum
 from data_refinery_common.logging import get_and_configure_logger
@@ -33,15 +34,24 @@
 
 
 def should_run_tximport(experiment: Experiment,
-                        num_quantified: int,
+                        results,
                         is_tximport_job: bool):
     """ Returns whether or not the experiment is eligible to have tximport
     run on it.
 
-    num_quantified is how many samples have had salmon quant run on them.
+    results is a queryset of ComputationalResults for the samples that had salmon quant run on them.
     """
+    num_quantified = results.count()
     if num_quantified == 0:
         return False
+
+    num_salmon_versions = results.filter(organism_index__salmon_version__isnull=False)\
+                                 .values_list('organism_index__salmon_version')\
+                                 .distinct().count()
+    if num_salmon_versions > 1:
+        # Tximport requires that all samples are processed with the same salmon version
+        # https://github.com/AlexsLemonade/refinebio/issues/1496
+        return False
 
     eligible_samples = experiment.samples.filter(source_database='SRA', technology='RNA-SEQ')
 
@@ -66,16 +76,29 @@ def should_run_tximport(experiment: Experiment,
 
 def get_quant_results_for_experiment(experiment: Experiment):
     """Returns a list of salmon quant results from `experiment`."""
-    results = []
-    for sample in experiment.samples.all():
-        for result in sample.results.order_by('-created_at').all():
-            # TODO: this will break when we want to run for a new version.
-            if result.processor.name == ProcessorEnum.SALMON_QUANT.value['name']:
-                results.append(result)
-                break
-
-    return results
-
+    # Subquery to calculate quant results
+    # https://docs.djangoproject.com/en/2.2/ref/models/expressions/#subquery-expressions
+
+    # Calculate the computational results sorted that are associated with a given sample (
+    # referenced from the top query)
+    newest_computational_results = ComputationalResult.objects.all()\
+        .filter(
+            samples=OuterRef('id'),
+            processor__name=ProcessorEnum.SALMON_QUANT.value['name']
+        )\
+        .order_by('-created_at')
+
+    # Annotate each sample in the experiment with the id of the most recent computational result
+    computational_results_ids = experiment.samples.all().annotate(
+        latest_computational_result_id=Subquery(newest_computational_results.values('id')[:1])
+    )\
+    .filter(latest_computational_result_id__isnull=False)\
+    .values_list('latest_computational_result_id', flat=True)
+
+    # return the computational results that match those ids
+    return ComputationalResult.objects.all().filter(
+        id__in=computational_results_ids
+    )
 
 def get_quant_files_for_results(results: List[ComputationalResult]):
     """Returns a list of salmon quant results from `experiment`."""

workers/data_refinery_workers/downloaders/test_utils.py → common/data_refinery_common/test_job_management.py

@@ -1,18 +1,15 @@
-import os
-import psutil
 
 from django.test import TestCase, tag
 from typing import List
 from unittest.mock import patch, call
 from urllib.error import URLError
 
-from data_refinery_workers.downloaders import utils
+from data_refinery_common.job_management import create_processor_job_for_original_files
 
 
 class UtilsTestCase(TestCase):
-    @tag('downloaders')
     def test_no_jobs_to_create(self):
         """Make sure this function doesn't raise an exception with no files."""
-        utils.create_processor_job_for_original_files([])
+        create_processor_job_for_original_files([])
 
         self.assertTrue(True)