Choose a source
Upload an IP file or select a period of external advertising reports.
These are alternative input paths. CSV/ZIP/GZIP uploads feed file processing; Celery download/ETL chains supply the report branch.
A traffic-analysis pipeline that combines advertising reports, IP context and completeness-aware filtering.
A traffic-analysis application for advertising operations. Users either upload a file of IP addresses or select a date range from imported advertising reports, then filter by geography, IP range, click or impression counts, or deposit counts. The result is a downloadable segment; one workflow can also upload a list to the configured advertising service.
Large advertising reports are hard to inspect manually. Operations need reproducible criteria for identifying IP addresses and ranges, and a way to turn those decisions into usable exports.
Traffic analysts and advertising operations teams who review large reports and prepare repeatable IP or audience segments.
CSV, ZIP or GZIP input
Prepare IP values and ranges
GeoIP and set/range operations
CSV result for the operator
Imported advertising data
Daily import into analytical storage
Missing days stop an incomplete lookup
IP, user-agent, click/impression counts or deposits
CSV, with optional configured upload
Ask for a complete reporting interval
Upload an IP file or select a period of external advertising reports.
These are alternative input paths. CSV/ZIP/GZIP uploads feed file processing; Celery download/ETL chains supply the report branch.
Each source is prepared for its own filtering method.
The file path normalizes IPv4 and mapped IPv6 addresses. The report path loads rows into ClickHouse staging tables and updates the relevant date partitions.
Task state tracks the input; report-based filters also check date coverage.
PostgreSQL stores task/file metadata. Missing-date detection applies to analytical report lookups, not as a mandatory step for every file upload.
The selected workflow produces a segment using geography, event counts or address ranges.
For an uploaded file, GeoIP2 adds location data and the service applies IP/range filters. For advertising reports, ClickHouse filters by IP, user-agent, clicks, impressions, deposits or CIDR.
The interface shows execution progress, output state and errors.
PostgreSQL stores each task state and file metadata; the interface uses them to show progress and the result of a filter.
The result becomes a downloadable list or an optional platform blacklist update.
The service creates a CSV file; a configured workflow can also send the selected list to the advertising platform.
PostgreSQL stores application state while ClickHouse serves report-scale analytical access.
Data availability becomes a condition for running a meaningful filter.
A filter produces an export that operators can apply in their advertising workflow.
Tell me what the application should do, how the team works today and which requirements or deadlines matter.