from artemis import Artemis

client = Artemis()
response = client.insights.list_acceleration_signals()

# The 5 most recent acceleration signals:
for card in response.rows[:5]:
    cadence = card.flag.split("_")[-1]
    multiplier = card.end_value / card.start_value if card.start_value else 0
    print(
        f"{card.entity_id} {card.metric_name}: "
        f"accelerating over {card.duration} {cadence} periods "
        f"({multiplier:.2f}x over {card.date_range})"
    )

{
  "rows": [
    {
      "DOMAIN": "protocol",
      "ENTITY_ID": "base",
      "METRIC_NAME": "STABLECOIN_DAU",
      "FLAG": "accel_weekly",
      "UNIT": "NOMINAL",
      "METRIC_TYPE": "snapshot",
      "DURATION": 4,
      "DATE_RANGE": "2026-04-15 to 2026-05-12",
      "START_VALUE": 215000,
      "END_VALUE": 412000,
      "PERIOD_START_DATE": "2026-04-15",
      "PERIOD_END_DATE": "2026-05-12",
      "FISCAL_YEAR_END": null,
      "FISCAL_PERIOD_END": null,
      "LATEST_REPORT_DATE": null,
      "SPARKLINE": [
        {
          "date": "2026-04-08",
          "value": 198000
        },
        {
          "date": "2026-04-15",
          "value": 215000
        },
        {
          "date": "2026-04-22",
          "value": 268000
        }
      ]
    }
  ]
}