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import logging
import sys
import time
from obsei.workflow.store import WorkflowStore
from obsei.source.twitter_source import TwitterSource, TwitterSourceConfig
from obsei.workflow.workflow import Workflow, WorkflowConfig
logger = logging.getLogger(__name__)
logging.basicConfig(stream=sys.stdout, level=logging.INFO)
# Create workflow store instance, by default it will use SQLite to store state data
store = WorkflowStore()
# Pass store reference to observer, so it can use it to store state data
source = TwitterSource(store=store)
def print_state(id: str):
logger.info(f"Source State: {source.store.get_source_state(id)}")
source_config = TwitterSourceConfig(
keywords=["india"],
lookup_period="2m",
tweet_fields=[
"author_id",
"conversation_id",
"created_at",
"id",
"public_metrics",
"text",
],
user_fields=["id", "name", "public_metrics", "username", "verified"],
expansions=["author_id"],
place_fields=None,
max_tweets=10,
)
# Create instance of workflow, adding observer config to it, it will autgenerate unique workflow id
workflow = Workflow(
config=WorkflowConfig(
source_config=source_config,
),
)
# Insert workflow config to DB store
store.add_workflow(workflow)
for i in range(1, 4):
print_state(workflow.id)
# Now always pass workflow id to lookup function
# Observer will fetch old data from DB suing this id and later store new updated state data against this id to DB
source_response_list = source.lookup(source_config, id=workflow.id)
if source_response_list is None or len(source_response_list) == 0:
break
time.sleep(180)
print_state(workflow.id)
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