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70 lines
2.5 KiB
Python
70 lines
2.5 KiB
Python
import datetime
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from typing import Union
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from django.conf import settings
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import structlog
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from celery import chain
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from prometheus_client import Histogram
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from posthog.models.dashboard_tile import get_tiles_ordered_by_position
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from posthog.models.exported_asset import ExportedAsset
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from posthog.models.insight import Insight
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from posthog.models.sharing_configuration import SharingConfiguration
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from posthog.models.subscription import Subscription
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from posthog.tasks import exporter
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from posthog.utils import wait_for_parallel_celery_group
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logger = structlog.get_logger(__name__)
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UTM_TAGS_BASE = "utm_source=posthog&utm_campaign=subscription_report"
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DEFAULT_MAX_ASSET_COUNT = 6
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SUBSCRIPTION_ASSET_GENERATION_TIMER = Histogram(
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"subscription_asset_generation_duration_seconds",
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"Time spent generating assets for a subscription",
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buckets=(1, 5, 10, 30, 60, 120, 240, 300, 360, 420, 480, 540, 600, float("inf")),
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)
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def generate_assets(
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resource: Union[Subscription, SharingConfiguration],
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max_asset_count: int = DEFAULT_MAX_ASSET_COUNT,
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) -> tuple[list[Insight], list[ExportedAsset]]:
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with SUBSCRIPTION_ASSET_GENERATION_TIMER.time():
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if resource.dashboard:
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tiles = get_tiles_ordered_by_position(resource.dashboard)
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insights = [tile.insight for tile in tiles if tile.insight]
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elif resource.insight:
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insights = [resource.insight]
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else:
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raise Exception("There are no insights to be sent for this Subscription")
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# Create all the assets we need
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assets = [
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ExportedAsset(
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team=resource.team,
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export_format="image/png",
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insight=insight,
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dashboard=resource.dashboard,
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)
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for insight in insights[:max_asset_count]
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]
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ExportedAsset.objects.bulk_create(assets)
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if not assets:
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return insights, assets
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# Wait for all assets to be exported
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tasks = [exporter.export_asset.si(asset.id) for asset in assets]
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# run them one after the other, so we don't exhaust celery workers
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exports_expire = datetime.datetime.now(tz=datetime.UTC) + datetime.timedelta(
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minutes=settings.PARALLEL_ASSET_GENERATION_MAX_TIMEOUT_MINUTES
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)
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parallel_job = chain(*tasks).apply_async(expires=exports_expire, retry=False)
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wait_for_parallel_celery_group(
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parallel_job,
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expires=exports_expire,
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)
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return insights, assets
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