Add Celery job processing, routes, & BatchAggregation lib

.github/workflows/python-versions.yml

@@ -9,6 +9,16 @@ on:
 jobs:
   build:
     runs-on: ubuntu-latest
+    services:
+      redis:
+        image: redis
+        options: >-
+          --health-cmd "redis-cli ping"
+          --health-interval 10s
+          --health-timeout 5s
+          --health-retries 5
+        ports:
+          - 6379:6379
     strategy:
       matrix:
         python-version: [3.8, 3.9, "3.10", "3.11"]
@@ -30,11 +40,14 @@ jobs:
     - name: Run tests
       env:
         TRAVIS: true  # one test is skipped on CI and looks for this env value
+        REDIS_HOST: redis
+        CELERY_BROKER_URL: redis://localhost:6379/0
+        CELERY_RESULT_BACKEND: redis://localhost:6379/0
       run: |
         coverage run
         coverage report
     - name: Coveralls
       if: ${{ matrix.python-version == 3.10 }}
-      env: 
+      env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
       run: coveralls --service=github

.gitignore

@@ -113,3 +113,5 @@ endpoints.yml
 
 .vscode/
 .noseids
+tmp/*
+.DS_Store

Dockerfile

@@ -21,10 +21,12 @@ COPY . .
 RUN pip install -U .[online,test,doc]
 
 # make documentation
-RUN /bin/bash -lc ./make_docs.sh
+RUN /bin/bash -lc ./scripts/make_docs.sh
+
+ADD ./ /usr/src/aggregation
 
 ARG REVISION=''
 ENV REVISION=$REVISION
 
 # load configs and start flask app
-CMD ["bash", "./start-flask.sh"]
+CMD ["bash", "./scripts/start-flask.sh"]

docker-compose.yml

@@ -6,14 +6,59 @@ services:
       args:
         REVISION: fake-git-sha-id
     volumes:
-      - ./panoptes_aggregation:/usr/src/aggregation/panoptes_aggregation
+      - ./:/usr/src/aggregation
       - ~/.aws:/root/.aws
     environment:
       - AWS_REGION=${AWS_REGION}
       - AWS_ACCESS_KEY_ID=${AWS_ACCESS_KEY_ID}
       - AWS_SECRET_ACCESS_KEY=${AWS_SECRET_ACCESS_KEY}
       - AWS_SESSION_TOKEN=${AWS_SESSION_TOKEN}
       - AWS_SECURITY_TOKEN=${AWS_SECURITY_TOKEN}
-      - LISTEN_PORT=5000
+      - CELERY_BROKER_URL=redis://redis:6379/0
+      - CELERY_RESULT_BACKEND=redis://redis:6379/0
+      - FLASK_DEBUG=1
+      - FLASK_ENV=development
+      - LISTEN_PORT=4000
     ports:
-      - "5000:5000"
+      - "4000:4000"
+    links:
+      - redis:redis
+
+  worker:
+    build:
+      context: ./
+      args:
+        REVISION: fake-git-sha-id
+    command: celery --app panoptes_aggregation.tasks.celery worker --loglevel=info
+    volumes:
+      - ./:/usr/src/aggregation
+    environment:
+      - FLASK_DEBUG=1
+      - APP_SETTINGS=project.server.config.DevelopmentConfig
+      - CELERY_BROKER_URL=redis://redis:6379/0
+      - CELERY_RESULT_BACKEND=redis://redis:6379/0
+      - FLASK_ENV=development
+    links:
+      - redis:redis
+    depends_on:
+      - redis
+
+  dashboard:
+    build: .
+    command: celery --app panoptes_aggregation.tasks.celery flower --port=5555 --broker=redis://redis:6379/0
+    ports:
+      - 5556:5555
+    environment:
+      - FLASK_DEBUG=1
+      - APP_SETTINGS=project.server.config.DevelopmentConfig
+      - CELERY_BROKER_URL=redis://redis:6379/0
+      - CELERY_RESULT_BACKEND=redis://redis:6379/0
+    links:
+      - redis:redis
+    depends_on:
+      - redis
+      - worker
+
+  redis:
+    image: redis
+    command: redis-server --appendonly yes

panoptes_aggregation/batch_aggregation.py

@@ -0,0 +1,138 @@
+from celery import Celery
+import json
+import pandas as pd
+import os
+import urllib3
+from shutil import make_archive
+import uuid
+
+from azure.storage.blob import BlobServiceClient
+
+from panoptes_client import Panoptes, Project, Workflow
+from panoptes_aggregation.workflow_config import workflow_extractor_config
+from panoptes_aggregation.scripts import batch_utils
+
+import logging
+panoptes_client_logger = logging.getLogger('panoptes_client').setLevel(logging.ERROR)
+
+celery = Celery(__name__)
+celery.conf.broker_url = os.environ.get("CELERY_BROKER_URL", "redis://localhost:6379")
+celery.conf.result_backend = os.environ.get("CELERY_RESULT_BACKEND", "redis://localhost:6379")
+
+
+@celery.task(name="run_aggregation")
+def run_aggregation(project_id, workflow_id, user_id):
+    ba = BatchAggregator(project_id, workflow_id, user_id)
+    ba.save_exports()
+
+    ba.process_wf_export(ba.wf_csv)
+    cls_df = ba.process_cls_export(ba.cls_csv)
+
+    extractor_config = workflow_extractor_config(ba.tasks)
+    extracted_data = batch_utils.batch_extract(cls_df, extractor_config)
+
+    batch_standard_reducers = {
+        'question_extractor': ['question_reducer', 'question_consensus_reducer'],
+        'survey_extractor': ['survey_reducer']
+    }
+
+    for task_type, extract_df in extracted_data.items():
+        extract_df.to_csv(f'{ba.output_path}/{ba.workflow_id}_{task_type}.csv')
+        reducer_list = batch_standard_reducers[task_type]
+        reduced_data = {}
+
+        for reducer in reducer_list:
+            # This is an override. The workflow_reducer_config method returns a config object
+            # that is incompatible with the batch_utils batch_reduce method
+            reducer_config = {'reducer_config': {reducer: {}}}
+            reduced_data[reducer] = batch_utils.batch_reduce(extract_df, reducer_config)
+            filename = f'{ba.output_path}/{ba.workflow_id}_reductions.csv'
+            reduced_data[reducer].to_csv(filename, mode='a')
+    ba.upload_files()
+
+    # hit up panoptes, let em know you're done
+
+
+class BatchAggregator:
+    """
+    Bunch of stuff to manage a batch aggregation run
+    """
+
+    def __init__(self, project_id, workflow_id, user_id):
+        self.project_id = project_id
+        self.workflow_id = workflow_id
+        self.user_id = user_id
+        self._generate_uuid()
+        self._connect_api_client()
+
+    def save_exports(self):
+        self.output_path = f'tmp/{self.workflow_id}'
+        os.mkdir(self.output_path)
+
+        cls_export = Workflow(self.workflow_id).describe_export('classifications')
+        full_cls_url = cls_export['media'][0]['src']
+        cls_file = f'{self.output_path}/{self.workflow_id}_cls_export.csv'
+        self._download_export(full_cls_url, cls_file)
+
+        wf_export = Project(self.project_id).describe_export('workflows')
+        full_wf_url = wf_export['media'][0]['src']
+        wf_file = f'{self.output_path}/{self.workflow_id}_workflow_export.csv'
+        self._download_export(full_wf_url, wf_file)
+
+        self.cls_csv = cls_file
+        self.wf_csv = wf_file
+        return {'classifications': cls_file, 'workflows': wf_file}
+
+    def process_wf_export(self, wf_csv):
+        self.wf_df = pd.read_csv(wf_csv)
+        self.wf_maj_version = self.wf_df.query(f'workflow_id == {self.workflow_id}')['version'].max()
+        self.wf_min_version = self.wf_df.query(f'workflow_id == {self.workflow_id} & version == {self.wf_maj_version}')['minor_version'].max()
+        self.workflow_version = f'{self.wf_maj_version}.{self.wf_min_version}'
+        self.workflow_row = self.wf_df.query(f'workflow_id == {self.workflow_id} & minor_version == {self.wf_min_version}')
+        self.tasks = json.loads(self.workflow_row.iloc[0]['tasks'])
+        return self.wf_df
+
+    def process_cls_export(self, cls_csv):
+        cls_df = pd.read_csv(cls_csv)
+        self.cls_df = cls_df.query(f'workflow_version == {self.workflow_version}')
+        return self.cls_df
+
+    def connect_blob_storage(self):
+        connect_str = os.getenv('AZURE_STORAGE_CONNECTION_STRING')
+        self.blob_service_client = BlobServiceClient.from_connection_string(connect_str)
+        self.blob_service_client.create_container(name=self.id)
+
+    def upload_file_to_storage(self, container_name, filepath):
+        blob = filepath.split('/')[-1]
+        blob_client = self.blob_service_client.get_blob_client(container=container_name, blob=blob)
+        with open(file=filepath, mode="rb") as data:
+            blob_client.upload_blob(data, overwrite=True)
+
+    def upload_files(self):
+        self.connect_blob_storage()
+        reductions_file = f'{self.output_path}/{self.workflow_id}_reductions.csv'
+        self.upload_file_to_storage(self.id, reductions_file)
+        zipfile = make_archive(f'tmp/{self.id}', 'zip', self.output_path)
+        self.upload_file_to_storage(self.id, zipfile)
+
+    def _generate_uuid(self):
+        self.id = uuid.uuid4().hex
+
+    def _download_export(self, url, filepath):
+        http = urllib3.PoolManager()
+        r = http.request('GET', url, preload_content=False)
+        with open(filepath, 'wb') as out:
+            while True:
+                data = r.read(65536)
+                if not data:
+                    break
+                out.write(data)
+        r.release_conn()
+
+    def _connect_api_client(self):
+        # connect to the API only once for this function request
+        Panoptes.connect(
+            endpoint=os.getenv('PANOPTES_URL', 'https://panoptes.zooniverse.org/'),
+            client_id=os.getenv('PANOPTES_CLIENT_ID'),
+            client_secret=os.getenv('PANOPTES_CLIENT_SECRET')
+        )