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3 Commits

Author SHA1 Message Date
a1d9a19d04 Updated view queries 2025-11-12 12:47:31 +00:00
Jonas Linter
c5fa92c4ec Fixed stuff 2025-11-10 13:07:08 +01:00
Jonas Linter
a92c5b699f But no account_currency 2025-11-10 11:49:00 +01:00
12 changed files with 286 additions and 58 deletions

View File

@@ -1,2 +1,4 @@
Uv managed python project that grabs data from the meta api and saves it in a timescaledb database.
Always use uv run to execute python related stuff

View File

@@ -310,7 +310,6 @@ class TimescaleDBClient:
account_id: str,
data: Dict[str, Any],
date_preset: str = "today",
cache_metadata: bool = True,
):
"""
Insert campaign-level insights data.
@@ -321,10 +320,9 @@ class TimescaleDBClient:
account_id: Ad account ID
data: Insights data dictionary from Meta API
date_preset: Date preset used
cache_metadata: If True, automatically cache campaign metadata from insights data
"""
# Cache campaign metadata if requested and available in the insights data
if cache_metadata and data.get("campaign_name"):
# Auto-cache campaign metadata if available in the insights data
if data.get("campaign_name"):
await self.upsert_campaign(
campaign_id=campaign_id,
account_id=account_id,
@@ -389,7 +387,6 @@ class TimescaleDBClient:
account_id: str,
data: Dict[str, Any],
date_preset: str = "today",
cache_metadata: bool = True,
):
"""
Insert ad set level insights data.
@@ -401,21 +398,18 @@ class TimescaleDBClient:
account_id: Ad account ID
data: Insights data dictionary from Meta API
date_preset: Date preset used
cache_metadata: If True, automatically cache adset/campaign metadata from insights data
"""
# Cache metadata if requested and available in the insights data
if cache_metadata:
# Cache adset metadata if available
# Note: Campaign should already exist from cache_campaigns_metadata or grab_campaign_insights
# If it doesn't exist, the foreign key constraint will fail with a clear error
# This is intentional - we should never silently create campaigns with 'Unknown' names
if data.get("adset_name"):
await self.upsert_adset(
adset_id=adset_id,
campaign_id=campaign_id,
adset_name=data["adset_name"],
status=None, # Not available in insights response
)
# Auto-cache adset metadata if available in the insights data
# Note: Campaign should already exist from cache_campaigns_metadata or grab_campaign_insights
# If it doesn't exist, the foreign key constraint will fail with a clear error
# This is intentional - we should never silently create campaigns with 'Unknown' names
if data.get("adset_name"):
await self.upsert_adset(
adset_id=adset_id,
campaign_id=campaign_id,
adset_name=data["adset_name"],
status=None, # Not available in insights response
)
query = """
INSERT INTO adset_insights (

View File

@@ -20,7 +20,6 @@ ALTER TABLE IF EXISTS campaign_insights ADD COLUMN IF NOT EXISTS cost_per_action
ALTER TABLE IF EXISTS adset_insights ADD COLUMN IF NOT EXISTS date_start DATE;
ALTER TABLE IF EXISTS adset_insights ADD COLUMN IF NOT EXISTS date_stop DATE;
ALTER TABLE IF EXISTS adset_insights ADD COLUMN IF NOT EXISTS account_currency VARCHAR(3);
ALTER TABLE IF EXISTS campaign_insights_by_country ADD COLUMN IF NOT EXISTS frequency NUMERIC(10, 4);
ALTER TABLE IF EXISTS campaign_insights_by_country ADD COLUMN IF NOT EXISTS cpp NUMERIC(10, 4);

View File

@@ -438,7 +438,6 @@ class ScheduledInsightsGrabber:
end_date: Optional[date] = None,
breakdowns: Optional[list] = None,
limit: Optional[int] = None,
cache_metadata: bool = False,
required_fields: Optional[dict] = None,
extra_data_processor=None,
) -> tuple[int, Optional[date]]:
@@ -455,7 +454,6 @@ class ScheduledInsightsGrabber:
end_date: End date for custom date range (optional)
breakdowns: List of breakdown fields (optional)
limit: Maximum number of results (optional)
cache_metadata: Whether to cache metadata (for campaign/adset levels)
required_fields: Dict of field_name -> label for validation before insert
extra_data_processor: Optional callable to process/add extra data to insight_dict
@@ -529,14 +527,27 @@ class ScheduledInsightsGrabber:
# Compute appropriate timestamp based on date_start and account timezone
timestamp = self._compute_timestamp(date_start_str, account_timezone)
# Call the appropriate database insert function
await db_insert_func(
time=timestamp,
account_id=account_id,
data=insight_dict,
date_preset=date_preset_for_db,
cache_metadata=cache_metadata,
)
# Build kwargs for insert function based on level
kwargs = {
"time": timestamp,
"account_id": account_id,
"data": insight_dict,
"date_preset": date_preset_for_db,
}
# Add level-specific parameters
if level == "campaign":
kwargs["campaign_id"] = insight_dict.get("campaign_id")
elif level == "adset":
kwargs["adset_id"] = insight_dict.get("adset_id")
kwargs["campaign_id"] = insight_dict.get("campaign_id")
# Add country for breakdown queries
if "country" in insight_dict:
kwargs["country"] = insight_dict.get("country")
# Call the appropriate database insert function with level-specific parameters
await db_insert_func(**kwargs)
count += 1
return count, date_start_value
@@ -602,7 +613,6 @@ class ScheduledInsightsGrabber:
db_insert_func=self.db.insert_campaign_insights,
date_preset=date_preset,
limit=limit,
cache_metadata=True,
required_fields={"campaign_id": "campaign_id"},
)
@@ -640,7 +650,6 @@ class ScheduledInsightsGrabber:
db_insert_func=self.db.insert_adset_insights,
date_preset=date_preset,
limit=limit,
cache_metadata=True,
required_fields={"adset_id": "adset_id", "campaign_id": "campaign_id"},
)
@@ -759,7 +768,6 @@ class ScheduledInsightsGrabber:
start_date=start_date,
end_date=end_date,
limit=limit,
cache_metadata=True,
required_fields={"campaign_id": "campaign_id"},
)
@@ -808,7 +816,6 @@ class ScheduledInsightsGrabber:
start_date=start_date,
end_date=end_date,
limit=limit,
cache_metadata=True,
required_fields={"adset_id": "adset_id", "campaign_id": "campaign_id"},
)

View File

@@ -93,6 +93,8 @@ class ViewManager:
"account_insights_flattened",
"campaign_insights_flattened",
"campaign_insights_by_country_flattened",
#"campaign_insights_by_device_flattened",
#"campaign_insights_by_gender_flattened",
]
async with self.pool.acquire() as conn:

View File

@@ -0,0 +1,20 @@
--- account insights by gender
DROP VIEW IF EXISTS account_insights_by_device CASCADE;
CREATE VIEW account_insights_by_device AS
SELECT
time,
account_id,
device_platform,
SUM(impressions) AS impressions,
SUM(clicks) AS clicks,
SUM(spend) AS spend,
SUM(link_click) AS link_click,
SUM(landing_page_view) AS landing_page_view,
SUM(lead) AS lead
FROM campaign_insights_by_device_flattened
GROUP BY time, account_id, device_platform;

View File

@@ -0,0 +1,53 @@
DROP VIEW IF EXISTS account_insights_by_gender CASCADE;
CREATE VIEW account_insights_by_gender AS
SELECT
time,
account_id,
gender,
SUM(impressions) AS impressions,
SUM(clicks) AS clicks,
SUM(spend) AS spend,
SUM(link_click) AS link_click,
SUM(landing_page_view) AS landing_page_view,
SUM(lead) AS lead
FROM campaign_insights_by_gender
GROUP BY time, account_id, gender;
DROP VIEW IF EXISTS account_insights_by_age CASCADE;
CREATE VIEW account_insights_by_age AS
SELECT
time,
account_id,
age,
SUM(impressions) AS impressions,
SUM(clicks) AS clicks,
SUM(spend) AS spend,
SUM(link_click) AS link_click,
SUM(landing_page_view) AS landing_page_view,
SUM(lead) AS lead
FROM campaign_insights_by_age
GROUP BY time, account_id, age;
DROP VIEW IF EXISTS account_insights_by_gender_and_age CASCADE;
CREATE VIEW account_insights_by_gender_and_age AS
SELECT
time,
account_id,
gender,
age,
SUM(impressions) AS impressions,
SUM(clicks) AS clicks,
SUM(spend) AS spend,
SUM(link_click) AS link_click,
SUM(landing_page_view) AS landing_page_view,
SUM(lead) AS lead
FROM campaign_insights_by_gender_and_age
GROUP BY time, account_id, age, gender;

View File

@@ -0,0 +1,55 @@
DROP VIEW IF EXISTS g_account_insights CASCADE;
CREATE VIEW g_account_insights AS
SELECT
time,
account_id,
clicks,
impressions,
interactions,
cost_micros,
cost_micros / 1000000.0 as cost,
leads,
engagements,
customer_currency_code,
account_name,
-- CTR (Click-Through Rate)
(clicks::numeric / impressions_nz) * 100 as ctr,
-- CPM (Cost Per Mille) in micros and standard units
(cost_micros::numeric / impressions_nz) * 1000 as cpm_micros,
(cost_micros::numeric / impressions_nz) * 1000 / 1000000.0 as cpm,
-- CPC (Cost Per Click) in micros and standard units
cost_micros::numeric / clicks_nz as cpc_micros,
cost_micros::numeric / clicks_nz / 1000000.0 as cpc,
-- CPL (Cost Per Lead) in micros and standard units
cost_micros::numeric / leads_nz as cpl_micros,
cost_micros::numeric / leads_nz / 1000000.0 as cpl,
-- Conversion Rate
(leads::numeric / clicks_nz) * 100 as conversion_rate,
-- Engagement Rate
(engagements::numeric / impressions_nz) * 100 as engagement_rate
FROM (
SELECT
segments_date as time,
customer_id as account_id,
sum(metrics_clicks) as clicks,
sum(metrics_impressions) as impressions,
sum(metrics_interactions) as interactions,
sum(metrics_cost_micros) as cost_micros,
sum(metrics_conversions) as leads,
sum(metrics_engagements) as engagements,
customer_currency_code,
customer_descriptive_name as account_name,
-- Null-safe denominators
NULLIF(sum(metrics_clicks), 0) as clicks_nz,
NULLIF(sum(metrics_impressions), 0) as impressions_nz,
NULLIF(sum(metrics_conversions), 0) as leads_nz
FROM google.account_performance_report
GROUP BY account_id, time, customer_currency_code, account_name
) base;

View File

@@ -3,10 +3,9 @@
DROP MATERIALIZED VIEW IF EXISTS campaign_insights_flattened CASCADE;
CREATE MATERIALIZED VIEW campaign_insights_flattened AS
SELECT
time,
account_id,
campaign_id,
SELECT date_start AS "time",
concat('act_', account_id) AS account_id,
campaign_id,
impressions,
clicks,
spend,
@@ -14,22 +13,18 @@ SELECT
ctr,
cpc,
cpm,
date_preset,
date_start,
date_stop,
fetched_at,
(SELECT (value->>'value')::numeric
FROM jsonb_array_elements(actions)
WHERE value->>'action_type' = 'link_click') AS link_click,
(SELECT (value->>'value')::numeric
FROM jsonb_array_elements(actions)
WHERE value->>'action_type' = 'landing_page_view') AS landing_page_view,
(SELECT (value->>'value')::numeric
FROM jsonb_array_elements(actions)
WHERE value->>'action_type' = 'lead') AS lead
FROM campaign_insights;
( SELECT (jsonb_array_elements.value ->> 'value'::text)::numeric AS "numeric"
FROM jsonb_array_elements(customcampaign_insights.actions) jsonb_array_elements(value)
WHERE (jsonb_array_elements.value ->> 'action_type'::text) = 'link_click'::text) AS link_click,
( SELECT (jsonb_array_elements.value ->> 'value'::text)::numeric AS "numeric"
FROM jsonb_array_elements(customcampaign_insights.actions) jsonb_array_elements(value)
WHERE (jsonb_array_elements.value ->> 'action_type'::text) = 'landing_page_view'::text) AS landing_page_view,
( SELECT (jsonb_array_elements.value ->> 'value'::text)::numeric AS "numeric"
FROM jsonb_array_elements(customcampaign_insights.actions) jsonb_array_elements(value)
WHERE (jsonb_array_elements.value ->> 'action_type'::text) = 'lead'::text) AS lead
FROM meta.customcampaign_insights;
CREATE INDEX idx_campaign_insights_flat_date ON campaign_insights_flattened(date_start, date_stop);

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@@ -3,22 +3,20 @@
DROP MATERIALIZED VIEW IF EXISTS campaign_insights_by_country_flattened CASCADE;
CREATE MATERIALIZED VIEW campaign_insights_by_country_flattened AS
SELECT
time,
account_id,
SELECT date_start AS "time",
concat('act_', account_id) AS account_id,
campaign_id,
country,
impressions,
clicks,
spend,
reach,
frequency,
ctr,
cpc,
cpm,
date_preset,
date_start,
date_stop,
fetched_at,
(SELECT (value->>'value')::numeric
FROM jsonb_array_elements(actions)
WHERE value->>'action_type' = 'link_click') AS link_click,
@@ -29,7 +27,7 @@ SELECT
FROM jsonb_array_elements(actions)
WHERE value->>'action_type' = 'lead') AS lead
FROM campaign_insights_by_country;
FROM meta.custom_campaign_country;
CREATE INDEX idx_campaign_insights_by_country_flat_date ON campaign_insights_by_country_flattened(date_start, date_stop);

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@@ -0,0 +1,32 @@
--- campaign insights by device
DROP MATERIALIZED VIEW IF EXISTS campaign_insights_by_device_flattened CASCADE;
CREATE MATERIALIZED VIEW campaign_insights_by_device_flattened AS
SELECT date_start AS "time",
concat('act_', account_id) AS account_id,
campaign_id,
device_platform,
impressions,
clicks,
spend,
reach,
frequency,
date_start,
date_stop,
(SELECT (value->>'value')::numeric
FROM jsonb_array_elements(actions)
WHERE value->>'action_type' = 'link_click') AS link_click,
(SELECT (value->>'value')::numeric
FROM jsonb_array_elements(actions)
WHERE value->>'action_type' = 'landing_page_view') AS landing_page_view,
(SELECT (value->>'value')::numeric
FROM jsonb_array_elements(actions)
WHERE value->>'action_type' = 'lead') AS lead
FROM meta.custom_campaign_device;
CREATE INDEX idx_campaign_insights_by_device_flat_date ON campaign_insights_by_device_flattened(date_start, date_stop);
CREATE UNIQUE INDEX idx_campaign_insights_by_device_flat_unique ON campaign_insights_by_device_flattened(time, campaign_id, device_platform);
REFRESH MATERIALIZED VIEW CONCURRENTLY campaign_insights_by_device_flattened;

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@@ -0,0 +1,71 @@
--- campaign insights by country
DROP MATERIALIZED VIEW IF EXISTS campaign_insights_by_gender_and_age CASCADE;
CREATE MATERIALIZED VIEW campaign_insights_by_gender_and_age AS
SELECT date_start AS "time",
concat('act_', account_id) AS account_id,
campaign_id,
gender,
age,
impressions,
clicks,
spend,
reach,
frequency,
ctr,
cpc,
cpm,
date_start,
date_stop,
(SELECT (value->>'value')::numeric
FROM jsonb_array_elements(actions)
WHERE value->>'action_type' = 'link_click') AS link_click,
(SELECT (value->>'value')::numeric
FROM jsonb_array_elements(actions)
WHERE value->>'action_type' = 'landing_page_view') AS landing_page_view,
(SELECT (value->>'value')::numeric
FROM jsonb_array_elements(actions)
WHERE value->>'action_type' = 'lead') AS lead
FROM meta.custom_campaign_gender;
CREATE INDEX idx_campaign_insights_by_gender_and_age_date ON campaign_insights_by_gender_and_age(date_start, date_stop);
CREATE UNIQUE INDEX idx_campaign_insights_by_gender_and_age_unique ON campaign_insights_by_gender_and_age(time, campaign_id, gender, age);
REFRESH MATERIALIZED VIEW CONCURRENTLY campaign_insights_by_gender_and_age;
DROP VIEW IF EXISTS campaign_insights_by_gender CASCADE;
create view campaign_insights_by_gender as
Select time,
sum(clicks) as clicks,
sum(link_click) as link_click,
sum(lead) as lead,
sum(landing_page_view) as landing_page_view,
sum(spend) as spend,
sum(reach) as reach,
sum(impressions) as impressions,
gender,
campaign_id,
account_id
from campaign_insights_by_gender_and_age
group by time, gender, account_id, campaign_id, date_start, date_stop;
DROP VIEW IF EXISTS campaign_insights_by_age CASCADE;
create view campaign_insights_by_age as
Select time,
sum(clicks) as clicks,
sum(link_click) as link_click,
sum(lead) as lead,
sum(landing_page_view) as landing_page_view,
sum(spend) as spend,
sum(reach) as reach,
sum(impressions) as impressions,
age,
campaign_id,
account_id
from campaign_insights_by_gender_and_age
group by time, age, account_id, campaign_id, date_start, date_stop;