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Get network traffic distribution by dimension

radar.netflows.summary_v2(Literal["ADM1", "AS", "LOCATION", "PRODUCT"]dimension, NetFlowsSummaryV2Params**kwargs) -> NetFlowsSummaryV2Response
GET/radar/netflows/summary/{dimension}

Retrieves the distribution of network traffic (NetFlows) by the specified dimension.

Security
API Token

The preferred authorization scheme for interacting with the Cloudflare API. Create a token.

Example:Authorization: Bearer Sn3lZJTBX6kkg7OdcBUAxOO963GEIyGQqnFTOFYY
API Email + API Key

The previous authorization scheme for interacting with the Cloudflare API, used in conjunction with a Global API key.

Example:X-Auth-Email: user@example.com

The previous authorization scheme for interacting with the Cloudflare API. When possible, use API tokens instead of Global API keys.

Example:X-Auth-Key: 144c9defac04969c7bfad8efaa8ea194
Accepted Permissions (at least one required)
User Details WriteUser Details Read
ParametersExpand Collapse
dimension: Literal["ADM1", "AS", "LOCATION", "PRODUCT"]

Specifies the NetFlows attribute by which to group the results.

One of the following:
"ADM1"
"AS"
"LOCATION"
"PRODUCT"
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.

One of the following:
"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).

limit_per_group: Optional[int]

Limits the number of objects per group to the top items within the specified time range. When item count exceeds the limit, extra items appear grouped under an “other” category. Only supported on high-cardinality dimensions; otherwise the request is rejected. Minimum value is 2.

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.

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

Filters the results by network traffic product types.

One of the following:
"HTTP"
"ALL"
ReturnsExpand Collapse
class NetFlowsSummaryV2Response:
meta: Meta

Metadata for the results.

confidence_info: MetaConfidenceInfo
annotations: List[MetaConfidenceInfoAnnotation]
data_source: Literal["ALL", "AI_BOTS", "AI_GATEWAY", 22 more]

Data source for annotations.

One of the following:
"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
formatdate-time
event_type: Literal["EVENT", "GENERAL", "OUTAGE", 3 more]

Event type for annotations.

One of the following:
"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
formaturi
start_date: datetime
formatdate-time
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.

formatdate-time
start_time: datetime

Adjusted start of date range.

formatdate-time
last_updated: datetime

Timestamp of the last dataset update.

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

Normalization method applied to the results. Refer to Normalization methods.

One of the following:
"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
summary_0: Dict[str, str]

Get network traffic distribution by dimension

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.summary_v2(
    dimension="ADM1",
)
print(response.meta)
{
  "result": {
    "meta": {
      "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"
        }
      ]
    },
    "summary_0": {
      "Germany": "25.084366",
      "United States": "50.168733"
    }
  },
  "success": true
}
Returns Examples
{
  "result": {
    "meta": {
      "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"
        }
      ]
    },
    "summary_0": {
      "Germany": "25.084366",
      "United States": "50.168733"
    }
  },
  "success": true
}