# AI # To Markdown ## Convert Files into Markdown `radar.ai.to_markdown.create(ToMarkdownCreateParams**kwargs) -> SyncSinglePage[ToMarkdownCreateResponse]` **post** `/accounts/{account_id}/ai/tomarkdown` Converts uploaded files into Markdown format using Workers AI. ### Parameters - `account_id: str` - `files: SequenceNotStr[FileTypes]` ### Returns - `class ToMarkdownCreateResponse: …` - `data: str` - `format: str` - `mime_type: str` - `name: str` - `tokens: 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 ) page = client.radar.ai.to_markdown.create( account_id="023e105f4ecef8ad9ca31a8372d0c353", files=[b"Example data"], ) page = page.result[0] print(page.data) ``` #### Response ```json { "result": [ { "data": "data", "format": "format", "mimeType": "mimeType", "name": "name", "tokens": "tokens" } ], "success": true } ``` ## Domain Types ### To Markdown Create Response - `class ToMarkdownCreateResponse: …` - `data: str` - `format: str` - `mime_type: str` - `name: str` - `tokens: str` # Inference ## Get Workers AI inference distribution by dimension `radar.ai.inference.summary_v2(Literal["MODEL", "TASK"]dimension, InferenceSummaryV2Params**kwargs) -> InferenceSummaryV2Response` **get** `/radar/ai/inference/summary/{dimension}` Retrieves an aggregated summary of unique accounts using Workers AI inference grouped by the specified dimension. ### Parameters - `dimension: Literal["MODEL", "TASK"]` Specifies the attribute by which to group the results. - `"MODEL"` - `"TASK"` - `asn: Optional[SequenceNotStr[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[SequenceNotStr[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[SequenceNotStr[Union[str, datetime]]]` End of the date range (inclusive). - `date_range: Optional[SequenceNotStr[str]]` Filters results by date range. For example, use `7d` and `7dcontrol` to compare this week with the previous week. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters). - `date_start: Optional[SequenceNotStr[Union[str, datetime]]]` Start of the date range. - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` - `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. - `location: Optional[SequenceNotStr[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[SequenceNotStr[str]]` Array of names used to label the series in the response. ### Returns - `class InferenceSummaryV2Response: …` - `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. - `"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` - `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://developers.cloudflare.com/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` - `summary_0: Dict[str, 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.ai.inference.summary_v2( dimension="MODEL", ) print(response.meta) ``` #### Response ```json { "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" } ], "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": { "@cf/meta/llama-3-8b-instruct": "8.381743", "@cf/meta/m2m100-1.2b": "22.904", "@cf/stabilityai/stable-diffusion-xl-base-1.0": "10.274394" } }, "success": true } ``` ## Get time series distribution of Workers AI inference by dimension. `radar.ai.inference.timeseries_groups_v2(Literal["MODEL", "TASK"]dimension, InferenceTimeseriesGroupsV2Params**kwargs) -> InferenceTimeseriesGroupsV2Response` **get** `/radar/ai/inference/timeseries_groups/{dimension}` Retrieves the distribution of unique accounts using Workers AI inference, grouped by the specified dimension over time. ### Parameters - `dimension: Literal["MODEL", "TASK"]` Specifies the attribute by which to group the results. - `"MODEL"` - `"TASK"` - `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://developers.cloudflare.com/radar/concepts/aggregation-intervals/). - `"15m"` - `"1h"` - `"1d"` - `"1w"` - `asn: Optional[SequenceNotStr[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[SequenceNotStr[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[SequenceNotStr[Union[str, datetime]]]` End of the date range (inclusive). - `date_range: Optional[SequenceNotStr[str]]` Filters results by date range. For example, use `7d` and `7dcontrol` to compare this week with the previous week. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters). - `date_start: Optional[SequenceNotStr[Union[str, datetime]]]` Start of the date range. - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` - `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. - `location: Optional[SequenceNotStr[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[SequenceNotStr[str]]` Array of names used to label the series in the response. - `normalization: Optional[Literal["PERCENTAGE", "MIN0_MAX"]]` Normalization method applied to the results. Refer to [Normalization methods](https://developers.cloudflare.com/radar/concepts/normalization/). - `"PERCENTAGE"` - `"MIN0_MAX"` ### Returns - `class InferenceTimeseriesGroupsV2Response: …` - `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://developers.cloudflare.com/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` - `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://developers.cloudflare.com/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]` ### 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.ai.inference.timeseries_groups_v2( dimension="MODEL", ) 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" } ], "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": [ "2023-08-08T10:15:00Z" ] } }, "success": true } ``` ## Domain Types ### Inference Summary V2 Response - `class InferenceSummaryV2Response: …` - `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. - `"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` - `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://developers.cloudflare.com/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` - `summary_0: Dict[str, str]` ### Inference Timeseries Groups V2 Response - `class InferenceTimeseriesGroupsV2Response: …` - `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://developers.cloudflare.com/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` - `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://developers.cloudflare.com/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]` # Summary ## Get Workers AI models summary `radar.ai.inference.summary.model(SummaryModelParams**kwargs) -> SummaryModelResponse` **get** `/radar/ai/inference/summary/model` Retrieves the distribution of unique accounts by model. ### Parameters - `date_end: Optional[SequenceNotStr[Union[str, datetime]]]` End of the date range (inclusive). - `date_range: Optional[SequenceNotStr[str]]` Filters results by date range. For example, use `7d` and `7dcontrol` to compare this week with the previous week. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters). - `date_start: Optional[SequenceNotStr[Union[str, datetime]]]` Start of the date range. - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` - `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. - `name: Optional[SequenceNotStr[str]]` Array of names used to label the series in the response. ### Returns - `class SummaryModelResponse: …` - `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. - `"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` - `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://developers.cloudflare.com/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` - `summary_0: Dict[str, 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.ai.inference.summary.model() print(response.meta) ``` #### Response ```json { "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" } ], "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": { "@cf/meta/llama-3-8b-instruct": "8.381743", "@cf/meta/m2m100-1.2b": "22.904", "@cf/stabilityai/stable-diffusion-xl-base-1.0": "10.274394" } }, "success": true } ``` ## Get Workers AI tasks summary `radar.ai.inference.summary.task(SummaryTaskParams**kwargs) -> SummaryTaskResponse` **get** `/radar/ai/inference/summary/task` Retrieves the distribution of unique accounts by task. ### Parameters - `date_end: Optional[SequenceNotStr[Union[str, datetime]]]` End of the date range (inclusive). - `date_range: Optional[SequenceNotStr[str]]` Filters results by date range. For example, use `7d` and `7dcontrol` to compare this week with the previous week. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters). - `date_start: Optional[SequenceNotStr[Union[str, datetime]]]` Start of the date range. - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` - `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. - `name: Optional[SequenceNotStr[str]]` Array of names used to label the series in the response. ### Returns - `class SummaryTaskResponse: …` - `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. - `"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` - `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://developers.cloudflare.com/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` - `summary_0: Dict[str, 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.ai.inference.summary.task() print(response.meta) ``` #### Response ```json { "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" } ], "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": { "text generation": "10.274394", "text-to-image": "22.904" } }, "success": true } ``` ## Domain Types ### Summary Model Response - `class SummaryModelResponse: …` - `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. - `"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` - `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://developers.cloudflare.com/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` - `summary_0: Dict[str, str]` ### Summary Task Response - `class SummaryTaskResponse: …` - `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. - `"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` - `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://developers.cloudflare.com/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` - `summary_0: Dict[str, str]` # Timeseries Groups # Summary ## Get Workers AI models time series `radar.ai.inference.timeseries_groups.summary.model(SummaryModelParams**kwargs) -> SummaryModelResponse` **get** `/radar/ai/inference/timeseries_groups/model` Retrieves the distribution of unique accounts by model 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://developers.cloudflare.com/radar/concepts/aggregation-intervals/). - `"15m"` - `"1h"` - `"1d"` - `"1w"` - `date_end: Optional[SequenceNotStr[Union[str, datetime]]]` End of the date range (inclusive). - `date_range: Optional[SequenceNotStr[str]]` Filters results by date range. For example, use `7d` and `7dcontrol` to compare this week with the previous week. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters). - `date_start: Optional[SequenceNotStr[Union[str, datetime]]]` Start of the date range. - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` - `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. - `name: Optional[SequenceNotStr[str]]` Array of names used to label the series in the response. ### Returns - `class SummaryModelResponse: …` - `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://developers.cloudflare.com/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` - `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://developers.cloudflare.com/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]` ### 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.ai.inference.timeseries_groups.summary.model() 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" } ], "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": [ "2023-08-08T10:15:00Z" ] } }, "success": true } ``` ## Get Workers AI tasks time series `radar.ai.inference.timeseries_groups.summary.task(SummaryTaskParams**kwargs) -> SummaryTaskResponse` **get** `/radar/ai/inference/timeseries_groups/task` Retrieves the distribution of unique accounts by task 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://developers.cloudflare.com/radar/concepts/aggregation-intervals/). - `"15m"` - `"1h"` - `"1d"` - `"1w"` - `date_end: Optional[SequenceNotStr[Union[str, datetime]]]` End of the date range (inclusive). - `date_range: Optional[SequenceNotStr[str]]` Filters results by date range. For example, use `7d` and `7dcontrol` to compare this week with the previous week. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters). - `date_start: Optional[SequenceNotStr[Union[str, datetime]]]` Start of the date range. - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` - `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. - `name: Optional[SequenceNotStr[str]]` Array of names used to label the series in the response. ### Returns - `class SummaryTaskResponse: …` - `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://developers.cloudflare.com/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` - `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://developers.cloudflare.com/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]` ### 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.ai.inference.timeseries_groups.summary.task() 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" } ], "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": [ "2023-08-08T10:15:00Z" ] } }, "success": true } ``` ## Domain Types ### Summary Model Response - `class SummaryModelResponse: …` - `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://developers.cloudflare.com/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` - `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://developers.cloudflare.com/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]` ### Summary Task Response - `class SummaryTaskResponse: …` - `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://developers.cloudflare.com/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` - `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://developers.cloudflare.com/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]` # Bots ## Get AI bots HTTP requests distribution by dimension `radar.ai.bots.summary_v2(Literal["USER_AGENT", "CRAWL_PURPOSE", "INDUSTRY", 2 more]dimension, BotSummaryV2Params**kwargs) -> BotSummaryV2Response` **get** `/radar/ai/bots/summary/{dimension}` Retrieves an aggregated summary of AI bots HTTP requests grouped by the specified dimension. ### Parameters - `dimension: Literal["USER_AGENT", "CRAWL_PURPOSE", "INDUSTRY", 2 more]` Specifies the attribute by which to group the results. - `"USER_AGENT"` - `"CRAWL_PURPOSE"` - `"INDUSTRY"` - `"VERTICAL"` - `"CONTENT_TYPE"` - `asn: Optional[SequenceNotStr[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. - `content_type: Optional[List[Literal["HTML", "IMAGES", "JSON", 13 more]]]` Filters results by content type category. - `"HTML"` - `"IMAGES"` - `"JSON"` - `"JAVASCRIPT"` - `"CSS"` - `"PLAIN_TEXT"` - `"FONTS"` - `"XML"` - `"YAML"` - `"VIDEO"` - `"AUDIO"` - `"MARKDOWN"` - `"DOCUMENTS"` - `"BINARY"` - `"SERIALIZATION"` - `"OTHER"` - `continent: Optional[SequenceNotStr[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. - `crawl_purpose: Optional[SequenceNotStr[str]]` Filters results by bot crawl purpose. - `date_end: Optional[SequenceNotStr[Union[str, datetime]]]` End of the date range (inclusive). - `date_range: Optional[SequenceNotStr[str]]` Filters results by date range. For example, use `7d` and `7dcontrol` to compare this week with the previous week. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters). - `date_start: Optional[SequenceNotStr[Union[str, datetime]]]` Start of the date range. - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` - `industry: Optional[SequenceNotStr[str]]` Filters results by industry. - `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. - `location: Optional[SequenceNotStr[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[SequenceNotStr[str]]` Array of names used to label the series in the response. - `user_agent: Optional[SequenceNotStr[str]]` Filters results by user agent. - `vertical: Optional[SequenceNotStr[str]]` Filters results by vertical. ### Returns - `class BotSummaryV2Response: …` - `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. - `"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` - `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://developers.cloudflare.com/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` - `summary_0: Dict[str, 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.ai.bots.summary_v2( dimension="USER_AGENT", ) print(response.meta) ``` #### Response ```json { "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" } ], "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": { "Amazonbot": "10.274394", "Bytespider": "8.381743", "facebookexternalhit": "63.40249" } }, "success": true } ``` ## Get AI bots HTTP requests time series `radar.ai.bots.timeseries(BotTimeseriesParams**kwargs) -> BotTimeseriesResponse` **get** `/radar/ai/bots/timeseries` Retrieves AI bots HTTP request volume 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://developers.cloudflare.com/radar/concepts/aggregation-intervals/). - `"15m"` - `"1h"` - `"1d"` - `"1w"` - `asn: Optional[SequenceNotStr[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. - `content_type: Optional[List[Literal["HTML", "IMAGES", "JSON", 13 more]]]` Filters results by content type category. - `"HTML"` - `"IMAGES"` - `"JSON"` - `"JAVASCRIPT"` - `"CSS"` - `"PLAIN_TEXT"` - `"FONTS"` - `"XML"` - `"YAML"` - `"VIDEO"` - `"AUDIO"` - `"MARKDOWN"` - `"DOCUMENTS"` - `"BINARY"` - `"SERIALIZATION"` - `"OTHER"` - `continent: Optional[SequenceNotStr[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. - `crawl_purpose: Optional[SequenceNotStr[str]]` Filters results by bot crawl purpose. - `date_end: Optional[SequenceNotStr[Union[str, datetime]]]` End of the date range (inclusive). - `date_range: Optional[SequenceNotStr[str]]` Filters results by date range. For example, use `7d` and `7dcontrol` to compare this week with the previous week. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters). - `date_start: Optional[SequenceNotStr[Union[str, datetime]]]` Start of the date range. - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` - `industry: Optional[SequenceNotStr[str]]` Filters results by industry. - `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. - `location: Optional[SequenceNotStr[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[SequenceNotStr[str]]` Array of names used to label the series in the response. - `user_agent: Optional[SequenceNotStr[str]]` Filters results by user agent. - `vertical: Optional[SequenceNotStr[str]]` Filters results by vertical. ### Returns - `class BotTimeseriesResponse: …` - `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://developers.cloudflare.com/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` - `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://developers.cloudflare.com/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` ### 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.ai.bots.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" } ], "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" } ] } }, "success": true } ``` ## Get time series distribution of AI bots HTTP requests by dimension. `radar.ai.bots.timeseries_groups(Literal["USER_AGENT", "CRAWL_PURPOSE", "INDUSTRY", 2 more]dimension, BotTimeseriesGroupsParams**kwargs) -> BotTimeseriesGroupsResponse` **get** `/radar/ai/bots/timeseries_groups/{dimension}` Retrieves the distribution of HTTP requests from AI bots, grouped by the specified dimension over time. ### Parameters - `dimension: Literal["USER_AGENT", "CRAWL_PURPOSE", "INDUSTRY", 2 more]` Specifies the attribute by which to group the results. - `"USER_AGENT"` - `"CRAWL_PURPOSE"` - `"INDUSTRY"` - `"VERTICAL"` - `"CONTENT_TYPE"` - `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://developers.cloudflare.com/radar/concepts/aggregation-intervals/). - `"15m"` - `"1h"` - `"1d"` - `"1w"` - `asn: Optional[SequenceNotStr[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. - `content_type: Optional[List[Literal["HTML", "IMAGES", "JSON", 13 more]]]` Filters results by content type category. - `"HTML"` - `"IMAGES"` - `"JSON"` - `"JAVASCRIPT"` - `"CSS"` - `"PLAIN_TEXT"` - `"FONTS"` - `"XML"` - `"YAML"` - `"VIDEO"` - `"AUDIO"` - `"MARKDOWN"` - `"DOCUMENTS"` - `"BINARY"` - `"SERIALIZATION"` - `"OTHER"` - `continent: Optional[SequenceNotStr[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. - `crawl_purpose: Optional[SequenceNotStr[str]]` Filters results by bot crawl purpose. - `date_end: Optional[SequenceNotStr[Union[str, datetime]]]` End of the date range (inclusive). - `date_range: Optional[SequenceNotStr[str]]` Filters results by date range. For example, use `7d` and `7dcontrol` to compare this week with the previous week. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters). - `date_start: Optional[SequenceNotStr[Union[str, datetime]]]` Start of the date range. - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` - `industry: Optional[SequenceNotStr[str]]` Filters results by industry. - `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. - `location: Optional[SequenceNotStr[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[SequenceNotStr[str]]` Array of names used to label the series in the response. - `normalization: Optional[Literal["PERCENTAGE", "MIN0_MAX"]]` Normalization method applied to the results. Refer to [Normalization methods](https://developers.cloudflare.com/radar/concepts/normalization/). - `"PERCENTAGE"` - `"MIN0_MAX"` - `user_agent: Optional[SequenceNotStr[str]]` Filters results by user agent. - `vertical: Optional[SequenceNotStr[str]]` Filters results by vertical. ### Returns - `class BotTimeseriesGroupsResponse: …` - `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://developers.cloudflare.com/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` - `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://developers.cloudflare.com/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]` ### 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.ai.bots.timeseries_groups( dimension="USER_AGENT", ) 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" } ], "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": [ "2023-08-08T10:15:00Z" ] } }, "success": true } ``` ## Domain Types ### Bot Summary V2 Response - `class BotSummaryV2Response: …` - `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. - `"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` - `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://developers.cloudflare.com/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` - `summary_0: Dict[str, str]` ### Bot Timeseries Response - `class BotTimeseriesResponse: …` - `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://developers.cloudflare.com/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` - `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://developers.cloudflare.com/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` ### Bot Timeseries Groups Response - `class BotTimeseriesGroupsResponse: …` - `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://developers.cloudflare.com/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` - `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://developers.cloudflare.com/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]` # Summary ## Get AI user agents summary `radar.ai.bots.summary.user_agent(SummaryUserAgentParams**kwargs) -> SummaryUserAgentResponse` **get** `/radar/ai/bots/summary/user_agent` Retrieves the distribution of traffic by AI user agent. ### Parameters - `asn: Optional[SequenceNotStr[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[SequenceNotStr[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[SequenceNotStr[Union[str, datetime]]]` End of the date range (inclusive). - `date_range: Optional[SequenceNotStr[str]]` Filters results by date range. For example, use `7d` and `7dcontrol` to compare this week with the previous week. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters). - `date_start: Optional[SequenceNotStr[Union[str, datetime]]]` Start of the date range. - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` - `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. - `location: Optional[SequenceNotStr[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[SequenceNotStr[str]]` Array of names used to label the series in the response. ### Returns - `class SummaryUserAgentResponse: …` - `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. - `"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` - `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://developers.cloudflare.com/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` - `summary_0: Dict[str, 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.ai.bots.summary.user_agent() print(response.meta) ``` #### Response ```json { "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" } ], "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": { "Amazonbot": "10.274394", "Bytespider": "8.381743", "facebookexternalhit": "63.40249" } }, "success": true } ``` ## Domain Types ### Summary User Agent Response - `class SummaryUserAgentResponse: …` - `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. - `"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` - `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://developers.cloudflare.com/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` - `summary_0: Dict[str, str]` # Timeseries Groups ## Get AI user agents time series `radar.ai.timeseries_groups.user_agent(TimeseriesGroupUserAgentParams**kwargs) -> TimeseriesGroupUserAgentResponse` **get** `/radar/ai/bots/timeseries_groups/user_agent` Retrieves the distribution of traffic by AI user agent 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://developers.cloudflare.com/radar/concepts/aggregation-intervals/). - `"15m"` - `"1h"` - `"1d"` - `"1w"` - `asn: Optional[SequenceNotStr[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[SequenceNotStr[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[SequenceNotStr[Union[str, datetime]]]` End of the date range (inclusive). - `date_range: Optional[SequenceNotStr[str]]` Filters results by date range. For example, use `7d` and `7dcontrol` to compare this week with the previous week. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters). - `date_start: Optional[SequenceNotStr[Union[str, datetime]]]` Start of the date range. - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` - `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. - `location: Optional[SequenceNotStr[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[SequenceNotStr[str]]` Array of names used to label the series in the response. ### Returns - `class TimeseriesGroupUserAgentResponse: …` - `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://developers.cloudflare.com/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` - `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://developers.cloudflare.com/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]` ### 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.ai.timeseries_groups.user_agent() 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" } ], "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": [ "2023-08-08T10:15:00Z" ] } }, "success": true } ``` ## Get AI bots HTTP requests distribution by dimension `radar.ai.timeseries_groups.summary(Literal["USER_AGENT", "CRAWL_PURPOSE", "INDUSTRY", 2 more]dimension, TimeseriesGroupSummaryParams**kwargs) -> TimeseriesGroupSummaryResponse` **get** `/radar/ai/bots/summary/{dimension}` Retrieves an aggregated summary of AI bots HTTP requests grouped by the specified dimension. ### Parameters - `dimension: Literal["USER_AGENT", "CRAWL_PURPOSE", "INDUSTRY", 2 more]` Specifies the attribute by which to group the results. - `"USER_AGENT"` - `"CRAWL_PURPOSE"` - `"INDUSTRY"` - `"VERTICAL"` - `"CONTENT_TYPE"` - `asn: Optional[SequenceNotStr[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. - `content_type: Optional[List[Literal["HTML", "IMAGES", "JSON", 13 more]]]` Filters results by content type category. - `"HTML"` - `"IMAGES"` - `"JSON"` - `"JAVASCRIPT"` - `"CSS"` - `"PLAIN_TEXT"` - `"FONTS"` - `"XML"` - `"YAML"` - `"VIDEO"` - `"AUDIO"` - `"MARKDOWN"` - `"DOCUMENTS"` - `"BINARY"` - `"SERIALIZATION"` - `"OTHER"` - `continent: Optional[SequenceNotStr[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. - `crawl_purpose: Optional[SequenceNotStr[str]]` Filters results by bot crawl purpose. - `date_end: Optional[SequenceNotStr[Union[str, datetime]]]` End of the date range (inclusive). - `date_range: Optional[SequenceNotStr[str]]` Filters results by date range. For example, use `7d` and `7dcontrol` to compare this week with the previous week. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters). - `date_start: Optional[SequenceNotStr[Union[str, datetime]]]` Start of the date range. - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` - `industry: Optional[SequenceNotStr[str]]` Filters results by industry. - `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. - `location: Optional[SequenceNotStr[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[SequenceNotStr[str]]` Array of names used to label the series in the response. - `user_agent: Optional[SequenceNotStr[str]]` Filters results by user agent. - `vertical: Optional[SequenceNotStr[str]]` Filters results by vertical. ### Returns - `class TimeseriesGroupSummaryResponse: …` - `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. - `"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` - `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://developers.cloudflare.com/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` - `summary_0: Dict[str, 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.ai.timeseries_groups.summary( dimension="USER_AGENT", ) print(response.meta) ``` #### Response ```json { "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" } ], "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": { "Amazonbot": "10.274394", "Bytespider": "8.381743", "facebookexternalhit": "63.40249" } }, "success": true } ``` ## Get AI bots HTTP requests time series `radar.ai.timeseries_groups.timeseries(TimeseriesGroupTimeseriesParams**kwargs) -> TimeseriesGroupTimeseriesResponse` **get** `/radar/ai/bots/timeseries` Retrieves AI bots HTTP request volume 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://developers.cloudflare.com/radar/concepts/aggregation-intervals/). - `"15m"` - `"1h"` - `"1d"` - `"1w"` - `asn: Optional[SequenceNotStr[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. - `content_type: Optional[List[Literal["HTML", "IMAGES", "JSON", 13 more]]]` Filters results by content type category. - `"HTML"` - `"IMAGES"` - `"JSON"` - `"JAVASCRIPT"` - `"CSS"` - `"PLAIN_TEXT"` - `"FONTS"` - `"XML"` - `"YAML"` - `"VIDEO"` - `"AUDIO"` - `"MARKDOWN"` - `"DOCUMENTS"` - `"BINARY"` - `"SERIALIZATION"` - `"OTHER"` - `continent: Optional[SequenceNotStr[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. - `crawl_purpose: Optional[SequenceNotStr[str]]` Filters results by bot crawl purpose. - `date_end: Optional[SequenceNotStr[Union[str, datetime]]]` End of the date range (inclusive). - `date_range: Optional[SequenceNotStr[str]]` Filters results by date range. For example, use `7d` and `7dcontrol` to compare this week with the previous week. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters). - `date_start: Optional[SequenceNotStr[Union[str, datetime]]]` Start of the date range. - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` - `industry: Optional[SequenceNotStr[str]]` Filters results by industry. - `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. - `location: Optional[SequenceNotStr[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[SequenceNotStr[str]]` Array of names used to label the series in the response. - `user_agent: Optional[SequenceNotStr[str]]` Filters results by user agent. - `vertical: Optional[SequenceNotStr[str]]` Filters results by vertical. ### Returns - `class TimeseriesGroupTimeseriesResponse: …` - `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://developers.cloudflare.com/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` - `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://developers.cloudflare.com/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` ### 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.ai.timeseries_groups.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" } ], "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" } ] } }, "success": true } ``` ## Get time series distribution of AI bots HTTP requests by dimension. `radar.ai.timeseries_groups.timeseries_groups(Literal["USER_AGENT", "CRAWL_PURPOSE", "INDUSTRY", 2 more]dimension, TimeseriesGroupTimeseriesGroupsParams**kwargs) -> TimeseriesGroupTimeseriesGroupsResponse` **get** `/radar/ai/bots/timeseries_groups/{dimension}` Retrieves the distribution of HTTP requests from AI bots, grouped by the specified dimension over time. ### Parameters - `dimension: Literal["USER_AGENT", "CRAWL_PURPOSE", "INDUSTRY", 2 more]` Specifies the attribute by which to group the results. - `"USER_AGENT"` - `"CRAWL_PURPOSE"` - `"INDUSTRY"` - `"VERTICAL"` - `"CONTENT_TYPE"` - `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://developers.cloudflare.com/radar/concepts/aggregation-intervals/). - `"15m"` - `"1h"` - `"1d"` - `"1w"` - `asn: Optional[SequenceNotStr[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. - `content_type: Optional[List[Literal["HTML", "IMAGES", "JSON", 13 more]]]` Filters results by content type category. - `"HTML"` - `"IMAGES"` - `"JSON"` - `"JAVASCRIPT"` - `"CSS"` - `"PLAIN_TEXT"` - `"FONTS"` - `"XML"` - `"YAML"` - `"VIDEO"` - `"AUDIO"` - `"MARKDOWN"` - `"DOCUMENTS"` - `"BINARY"` - `"SERIALIZATION"` - `"OTHER"` - `continent: Optional[SequenceNotStr[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. - `crawl_purpose: Optional[SequenceNotStr[str]]` Filters results by bot crawl purpose. - `date_end: Optional[SequenceNotStr[Union[str, datetime]]]` End of the date range (inclusive). - `date_range: Optional[SequenceNotStr[str]]` Filters results by date range. For example, use `7d` and `7dcontrol` to compare this week with the previous week. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters). - `date_start: Optional[SequenceNotStr[Union[str, datetime]]]` Start of the date range. - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` - `industry: Optional[SequenceNotStr[str]]` Filters results by industry. - `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. - `location: Optional[SequenceNotStr[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[SequenceNotStr[str]]` Array of names used to label the series in the response. - `normalization: Optional[Literal["PERCENTAGE", "MIN0_MAX"]]` Normalization method applied to the results. Refer to [Normalization methods](https://developers.cloudflare.com/radar/concepts/normalization/). - `"PERCENTAGE"` - `"MIN0_MAX"` - `user_agent: Optional[SequenceNotStr[str]]` Filters results by user agent. - `vertical: Optional[SequenceNotStr[str]]` Filters results by vertical. ### Returns - `class TimeseriesGroupTimeseriesGroupsResponse: …` - `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://developers.cloudflare.com/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` - `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://developers.cloudflare.com/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]` ### 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.ai.timeseries_groups.timeseries_groups( dimension="USER_AGENT", ) 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" } ], "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": [ "2023-08-08T10:15:00Z" ] } }, "success": true } ``` ## Domain Types ### Timeseries Group User Agent Response - `class TimeseriesGroupUserAgentResponse: …` - `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://developers.cloudflare.com/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` - `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://developers.cloudflare.com/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]` ### Timeseries Group Summary Response - `class TimeseriesGroupSummaryResponse: …` - `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. - `"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` - `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://developers.cloudflare.com/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` - `summary_0: Dict[str, str]` ### Timeseries Group Timeseries Response - `class TimeseriesGroupTimeseriesResponse: …` - `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://developers.cloudflare.com/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` - `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://developers.cloudflare.com/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` ### Timeseries Group Timeseries Groups Response - `class TimeseriesGroupTimeseriesGroupsResponse: …` - `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://developers.cloudflare.com/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` - `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://developers.cloudflare.com/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]`