toloka.metrics.pool_metrics.BansInPool | Source code
BansInPool( self, pool_id: str, count_name: Optional[str] = None, filter_by_comment: Optional[Dict[str, str]] = None, cursor_time_lag: timedelta = ..., join_events: bool = False, *, toloka_client: Optional[TolokaClient] = None, atoloka_client: Optional[AsyncTolokaClient] = None, timeout: timedelta = ...)Tracking Toloker restrictions in a pool.
Be careful: if you set in quality controls to ban Tolokers 'on project', bans 'on pool' will never happen.
| Parameters | Type | Description |
|---|---|---|
pool_id | str | From which pool track metrics. |
count_name | Optional[str] | Metric name for a count of bans. |
filter_by_comment | Optional[Dict[str, str]] | Allow to split Toloker restriction into several lines based on comment. Dictionary where, key - comment string, and value - name for line in which will be aggregated bans with this comments. |
cursor_time_lag | timedelta | Time lag for cursor. This controls time lag between user restrictions being added and this metric being updated. See BaseCursor.time_lag for details and reasoning behind this. |
join_events | bool | Count all events in one point. Default |
Examples:
How to collect this metrics:
def print_metric(metric_dict): print(metric_dict)collector = MetricCollector([BansInPool(pool_id, toloka_client=toloka_client)], print_metric)asyncio.run(collector.run()){ 'bans_count': [(datetime.datetime(2021, 11, 18, 13, 30, 11, 522000), 1)],}How to split bans onto several metrics.
collector = MetricCollector( [ BansInPool( pool_id, toloka_client=toloka_client, filter_by_comment={'fast answers': 'fast', 'bad quality on honeypots': 'honeypots'} ), ], print_metric)asyncio.run(collector.run()){ 'honeypots': [(datetime.datetime(2021, 11, 18, 13, 32, 52, 475000), 1)], 'fast': [(datetime.datetime(2021, 11, 18, 13, 32, 50, 453000), 1)],}| Method | Description |
|---|---|
| get_line_names | Returns a list of metric names that can be generated by this class instance. |
Last updated: August 28, 2023