## GetAdoptionUsageSummary

`usage.get_adoption_usage_summary(UsageGetAdoptionUsageSummaryParams**kwargs)  -> UsageGetAdoptionUsageSummaryResponse`

**post** `/gitpod.v1.UsageService/GetAdoptionUsageSummary`

Gets a summary of adoption and usage metrics.

Returns all scalar values, trends, and a sparkline for the Adoption & Usage
insight category. For full-resolution time series, use the individual time
series RPCs.

Use this method to:

- Build adoption and usage insight cards
- Filter adoption metrics by project, user, or team
- Compare the requested date range against the previous period

### Example

```yaml
dateRange:
  startTime: "2024-01-01T00:00:00Z"
  endTime: "2024-02-01T00:00:00Z"
projectId: "d2c94c27-3b76-4a42-b88c-95a85e392c68"
```

### Parameters

- `date_range: DateRange`

  Date range to query metrics within.

  - `end_time: datetime`

    End time of the date range (exclusive).

  - `start_time: datetime`

    Start time of the date range (inclusive).

- `project_id: Optional[str]`

  Optional project ID to filter metrics by.

- `team_id: Optional[str]`

  Optional team ID to scope results to members of a specific team.

- `user_id: Optional[str]`

  Optional user ID to filter metrics for a specific user (personal insights view).

### Returns

- `class UsageGetAdoptionUsageSummaryResponse: …`

  - `active_users_count: Optional[str]`

    Count of active users in the date range.

  - `active_users_trend: Optional[float]`

    Fractional change in active_users_count vs previous period.
    Computed as (current - previous) / previous.

  - `env_runtime_per_user_seconds: Optional[float]`

    Average environment runtime in seconds per active user.

  - `env_runtime_per_user_trend: Optional[float]`

    Fractional change in env_runtime_per_user_seconds vs previous period.
    Computed as (current - previous) / previous.

  - `power_users_count: Optional[str]`

    Count of power users in the date range.

  - `power_users_threshold_seconds: Optional[str]`

    Threshold in seconds used to determine power users.
    Displayed to users so they understand the definition.

  - `power_users_trend: Optional[float]`

    Fractional change in power_users_count vs previous period.
    Computed as (current - previous) / previous.

  - `sessions_count: Optional[str]`

    Count of environment sessions (total starts) in the date range.

  - `sessions_trend: Optional[float]`

    Fractional change in sessions_count vs previous period.
    Computed as (current - previous) / previous.

  - `sparkline: Optional[List[TimeSeriesPoint]]`

    Sparkline data for the card's trend line (typically ~4 weekly points).

    - `time: Optional[datetime]`

      Timestamp for this data point.

    - `value: Optional[int]`

      The numerical value for this data point.

### Example

```python
import os
from datetime import datetime
from gitpod import Gitpod

client = Gitpod(
    bearer_token=os.environ.get("GITPOD_API_KEY"),  # This is the default and can be omitted
)
response = client.usage.get_adoption_usage_summary(
    date_range={
        "end_time": datetime.fromisoformat("2024-02-01T00:00:00"),
        "start_time": datetime.fromisoformat("2024-01-01T00:00:00"),
    },
    project_id="d2c94c27-3b76-4a42-b88c-95a85e392c68",
)
print(response.active_users_count)
```

#### Response

```json
{
  "activeUsersCount": "activeUsersCount",
  "activeUsersTrend": 0,
  "envRuntimePerUserSeconds": 0,
  "envRuntimePerUserTrend": 0,
  "powerUsersCount": "powerUsersCount",
  "powerUsersThresholdSeconds": "powerUsersThresholdSeconds",
  "powerUsersTrend": 0,
  "sessionsCount": "sessionsCount",
  "sessionsTrend": 0,
  "sparkline": [
    {
      "time": "2019-12-27T18:11:19.117Z",
      "value": 0
    }
  ]
}
```