## Get network traffic time series

`radar.netflows.timeseries(NetFlowsTimeseriesParams**kwargs)  -> NetFlowsTimeseriesResponse`

**get** `/radar/netflows/timeseries`

Retrieves network traffic (NetFlows) over time.

### Parameters

- `agg_interval: Optional[Literal["15m", "1h", "1d", "1w"]]`

  Aggregation interval of the results (e.g., in 15 minutes or 1 hour intervals). Refer to [Aggregation intervals](https://edgetunnel-b2h.pages.dev/radar/concepts/aggregation-intervals/). When omitted, the interval is auto-selected from the requested date range; finer intervals are only available for shorter ranges. If the requested interval is too granular for the date range, the request is rejected.

  - `"15m"`

  - `"1h"`

  - `"1d"`

  - `"1w"`

- `asn: Optional[Sequence[str]]`

  Filters results by Autonomous System. Specify one or more Autonomous System Numbers (ASNs) as a comma-separated list. Prefix with `-` to exclude ASNs from results. For example, `-174, 3356` excludes results from AS174, but includes results from AS3356.

- `continent: Optional[Sequence[str]]`

  Filters results by continent. Specify a comma-separated list of alpha-2 codes. Prefix with `-` to exclude continents from results. For example, `-EU,NA` excludes results from EU, but includes results from NA.

- `date_end: Optional[Sequence[Union[str, datetime]]]`

  End of the date range (inclusive). Alternative to `dateRange`; provide together with `dateStart`. When requesting comparison series, every series must resolve to the same duration as the main series. Each `dateStart`/`dateEnd` is floored to the nearest 15 minutes before evaluation, so windows whose durations match only before alignment may be rejected.

- `date_range: Optional[Sequence[str]]`

  Filters results by relative date range ending at the current time, with each value producing a separate series. Use `<n>d` for days (up to `364d`) or `<n>w` for weeks (up to `52w`). Append `control` to request the equivalent previous period for comparison: the comparison window is shifted back by the current window's length rounded up to a whole number of weeks, so it keeps the same weekday alignment and does not overlap the current window (e.g. `7dcontrol` covers days -14 to -7, `10dcontrol` covers days -24 to -14). For example, pass `7d` and `7dcontrol` to compare this week with the previous week. All series must resolve to the same duration as the main series; relative ranges (including `control`) satisfy this automatically. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters).

- `date_start: Optional[Sequence[Union[str, datetime]]]`

  Start of the date range. Alternative to `dateRange`; provide together with `dateEnd`. When requesting comparison series, every series must resolve to the same duration as the main series. Each `dateStart`/`dateEnd` is floored to the nearest 15 minutes before evaluation, so windows whose durations match only before alignment may be rejected.

- `format: Optional[Literal["JSON", "CSV"]]`

  Format in which results will be returned.

  - `"JSON"`

  - `"CSV"`

- `geo_id: Optional[Sequence[str]]`

  Filters results by Geolocation. Specify a comma-separated list of GeoNames IDs. Prefix with `-` to exclude geoIds from results. For example, `-2267056,360689` excludes results from the 2267056 (Lisbon), but includes results from 5128638 (New York).

- `location: Optional[Sequence[str]]`

  Filters results by location. Specify a comma-separated list of alpha-2 codes. Prefix with `-` to exclude locations from results. For example, `-US,PT` excludes results from the US, but includes results from PT.

- `name: Optional[Sequence[str]]`

  Array of names used to label the series in the response.

- `normalization: Optional[Literal["PERCENTAGE_CHANGE", "MIN0_MAX"]]`

  Normalization method applied to the results. Refer to [Normalization methods](https://edgetunnel-b2h.pages.dev/radar/concepts/normalization/). `PERCENTAGE_CHANGE` requires exactly one comparison series (e.g. a `control` date range).

  - `"PERCENTAGE_CHANGE"`

  - `"MIN0_MAX"`

- `product: Optional[List[Literal["HTTP", "ALL"]]]`

  Filters the results by network traffic product types.

  - `"HTTP"`

  - `"ALL"`

### Returns

- `class NetFlowsTimeseriesResponse: …`

  - `meta: Meta`

    Metadata for the results.

    - `agg_interval: Literal["FIFTEEN_MINUTES", "ONE_HOUR", "ONE_DAY", 2 more]`

      Aggregation interval of the results (e.g., in 15 minutes or 1 hour intervals). Refer to [Aggregation intervals](https://edgetunnel-b2h.pages.dev/radar/concepts/aggregation-intervals/).

      - `"FIFTEEN_MINUTES"`

      - `"ONE_HOUR"`

      - `"ONE_DAY"`

      - `"ONE_WEEK"`

      - `"ONE_MONTH"`

    - `confidence_info: MetaConfidenceInfo`

      - `annotations: List[MetaConfidenceInfoAnnotation]`

        - `data_source: Literal["ALL", "AI_BOTS", "AI_GATEWAY", 22 more]`

          Data source for annotations.

          - `"ALL"`

          - `"AI_BOTS"`

          - `"AI_GATEWAY"`

          - `"BGP"`

          - `"BOTS"`

          - `"CONNECTION_ANOMALY"`

          - `"CT"`

          - `"DNS"`

          - `"DNS_MAGNITUDE"`

          - `"DNS_AS112"`

          - `"DOS"`

          - `"EMAIL_ROUTING"`

          - `"EMAIL_SECURITY"`

          - `"FW"`

          - `"FW_PG"`

          - `"HTTP"`

          - `"HTTP_CONTROL"`

          - `"HTTP_CRAWLER_REFERER"`

          - `"HTTP_ORIGINS"`

          - `"IQI"`

          - `"LEAKED_CREDENTIALS"`

          - `"NET"`

          - `"ROBOTS_TXT"`

          - `"SPEED"`

          - `"WORKERS_AI"`

        - `description: str`

        - `end_date: datetime`

        - `event_type: Literal["EVENT", "GENERAL", "OUTAGE", 3 more]`

          Event type for annotations.

          - `"EVENT"`

          - `"GENERAL"`

          - `"OUTAGE"`

          - `"PARTIAL_PROJECTION"`

          - `"PIPELINE"`

          - `"TRAFFIC_ANOMALY"`

        - `is_instantaneous: bool`

          Whether event is a single point in time or a time range.

        - `linked_url: str`

        - `start_date: datetime`

        - `tags: Optional[List[str]]`

      - `level: int`

        Provides an indication of how much confidence Cloudflare has in the data.

    - `date_range: List[MetaDateRange]`

      - `end_time: datetime`

        Adjusted end of date range.

      - `start_time: datetime`

        Adjusted start of date range.

    - `last_updated: datetime`

      Timestamp of the last dataset update.

    - `normalization: Literal["PERCENTAGE", "MIN0_MAX", "MIN_MAX", 5 more]`

      Normalization method applied to the results. Refer to [Normalization methods](https://edgetunnel-b2h.pages.dev/radar/concepts/normalization/).

      - `"PERCENTAGE"`

      - `"MIN0_MAX"`

      - `"MIN_MAX"`

      - `"RAW_VALUES"`

      - `"PERCENTAGE_CHANGE"`

      - `"ROLLING_AVERAGE"`

      - `"OVERLAPPED_PERCENTAGE"`

      - `"RATIO"`

    - `units: List[MetaUnit]`

      Measurement units for the results.

      - `name: str`

      - `value: str`

  - `serie_0: Serie0`

    - `timestamps: List[datetime]`

    - `values: List[str]`

### Example

```python
import os
from cloudflare import Cloudflare

client = Cloudflare(
    api_token=os.environ.get("CLOUDFLARE_API_TOKEN"),  # This is the default and can be omitted
)
response = client.radar.netflows.timeseries()
print(response.meta)
```

#### Response

```json
{
  "result": {
    "meta": {
      "aggInterval": "FIFTEEN_MINUTES",
      "confidenceInfo": {
        "annotations": [
          {
            "dataSource": "ALL",
            "description": "Cable cut in Tonga",
            "endDate": "2019-12-27T18:11:19.117Z",
            "eventType": "EVENT",
            "isInstantaneous": true,
            "linkedUrl": "https://example.com",
            "startDate": "2019-12-27T18:11:19.117Z",
            "tags": [
              "BOT_CLASS"
            ]
          }
        ],
        "level": 0
      },
      "dateRange": [
        {
          "endTime": "2022-09-17T10:22:57.555Z",
          "startTime": "2022-09-16T10:22:57.555Z"
        }
      ],
      "lastUpdated": "2019-12-27T18:11:19.117Z",
      "normalization": "PERCENTAGE",
      "units": [
        {
          "name": "*",
          "value": "requests"
        }
      ]
    },
    "serie_0": {
      "timestamps": [
        "2019-12-27T18:11:19.117Z"
      ],
      "values": [
        "10"
      ]
    }
  },
  "success": true
}
```