# Bots ## List bots `radar.bots.list(BotListParams**kwargs) -> BotListResponse` **get** `/radar/bots` Retrieves a list of bots. ### Parameters - `bot_category: Optional[Literal["SEARCH_ENGINE_CRAWLER", "SEARCH_ENGINE_OPTIMIZATION", "MONITORING_AND_ANALYTICS", 13 more]]` Filters results by bot category. - `"SEARCH_ENGINE_CRAWLER"` - `"SEARCH_ENGINE_OPTIMIZATION"` - `"MONITORING_AND_ANALYTICS"` - `"ADVERTISING_AND_MARKETING"` - `"SOCIAL_MEDIA_MARKETING"` - `"PAGE_PREVIEW"` - `"ACADEMIC_RESEARCH"` - `"SECURITY"` - `"ACCESSIBILITY"` - `"WEBHOOKS"` - `"FEED_FETCHER"` - `"AI_CRAWLER"` - `"AGGREGATOR"` - `"AI_ASSISTANT"` - `"AI_SEARCH"` - `"ARCHIVER"` - `bot_operator: Optional[str]` Filters results by bot operator. - `bot_verification_status: Optional[Literal["VERIFIED"]]` Filters results by bot verification status. - `"VERIFIED"` - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` - `kind: Optional[Literal["AGENT", "BOT"]]` Filters results by bot kind. - `"AGENT"` - `"BOT"` - `limit: Optional[int]` Limits the number of objects returned in the response. - `offset: Optional[int]` Skips the specified number of objects before fetching the results. ### Returns - `class BotListResponse: …` - `bots: List[Bot]` - `category: str` The category of the bot. - `description: str` A summary for the bot (e.g., purpose). - `kind: str` The kind of the bot. - `name: str` The name of the bot. - `operator: str` The organization that owns and operates the bot. - `slug: str` A kebab-case identifier derived from the bot name. - `user_agent_patterns: List[str]` ### Example ```python import os from cloudflare import Cloudflare client = Cloudflare( api_token=os.environ.get("CLOUDFLARE_API_TOKEN"), # This is the default and can be omitted ) bots = client.radar.bots.list() print(bots.bots) ``` #### Response ```json { "result": { "bots": [ { "category": "AI_CRAWLER", "description": "OpenAI/ChatGPT's web crawler", "kind": "AGENT", "name": "GPTBot", "operator": "OpenAI", "slug": "gptbot", "userAgentPatterns": [ "GPTBot" ] } ] }, "success": true } ``` ## Get bot details `radar.bots.get(strbot_slug, BotGetParams**kwargs) -> BotGetResponse` **get** `/radar/bots/{bot_slug}` Retrieves the requested bot information. ### Parameters - `bot_slug: str` Bot slug. - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` ### Returns - `class BotGetResponse: …` - `bot: Bot` - `category: str` The category of the bot. - `description: str` A summary for the bot (e.g., purpose). - `kind: str` The kind of the bot. - `name: str` The name of the bot. - `operator: str` The organization that owns and operates the bot. - `operator_url: str` The link to the bot documentation. - `slug: str` A kebab-case identifier derived from the bot name. - `user_agent_patterns: List[str]` - `user_agents: List[str]` ### Example ```python import os from cloudflare import Cloudflare client = Cloudflare( api_token=os.environ.get("CLOUDFLARE_API_TOKEN"), # This is the default and can be omitted ) bot = client.radar.bots.get( bot_slug="gptbot", ) print(bot.bot) ``` #### Response ```json { "result": { "bot": { "category": "AI_CRAWLER", "description": "OpenAI/ChatGPT's web crawler", "kind": "AGENT", "name": "GPTBot", "operator": "OpenAI", "operatorUrl": "https://platform.openai.com/docs/bots", "slug": "gptbot", "userAgentPatterns": [ "GPTBot" ], "userAgents": [ "GPTBot" ] } }, "success": true } ``` ## Get bots HTTP requests distribution by dimension `radar.bots.summary(Literal["BOT", "BOT_KIND", "BOT_OPERATOR", "BOT_CATEGORY"]dimension, BotSummaryParams**kwargs) -> BotSummaryResponse` **get** `/radar/bots/summary/{dimension}` Retrieves an aggregated summary of bots HTTP requests grouped by the specified dimension. ### Parameters - `dimension: Literal["BOT", "BOT_KIND", "BOT_OPERATOR", "BOT_CATEGORY"]` Specifies the attribute by which to group the results. - `"BOT"` - `"BOT_KIND"` - `"BOT_OPERATOR"` - `"BOT_CATEGORY"` - `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. - `bot: Optional[SequenceNotStr[str]]` Filters results by bot name. - `bot_category: Optional[List[Literal["SEARCH_ENGINE_CRAWLER", "SEARCH_ENGINE_OPTIMIZATION", "MONITORING_AND_ANALYTICS", 13 more]]]` Filters results by bot category. - `"SEARCH_ENGINE_CRAWLER"` - `"SEARCH_ENGINE_OPTIMIZATION"` - `"MONITORING_AND_ANALYTICS"` - `"ADVERTISING_AND_MARKETING"` - `"SOCIAL_MEDIA_MARKETING"` - `"PAGE_PREVIEW"` - `"ACADEMIC_RESEARCH"` - `"SECURITY"` - `"ACCESSIBILITY"` - `"WEBHOOKS"` - `"FEED_FETCHER"` - `"AI_CRAWLER"` - `"AGGREGATOR"` - `"AI_ASSISTANT"` - `"AI_SEARCH"` - `"ARCHIVER"` - `bot_kind: Optional[List[Literal["AGENT", "BOT"]]]` Filters results by bot kind. - `"AGENT"` - `"BOT"` - `bot_operator: Optional[SequenceNotStr[str]]` Filters results by bot operator. - `bot_verification_status: Optional[List[Literal["VERIFIED"]]]` Filters results by bot verification status (Verified vs. Unverified). - `"VERIFIED"` - `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 BotSummaryResponse: …` - `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.bots.summary( dimension="BOT", ) 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": { "Facebook": "10.274394", "GPTBot": "63.40249", "GoogleBot": "8.381743" } }, "success": true } ``` ## Get bots HTTP requests time series `radar.bots.timeseries(BotTimeseriesParams**kwargs) -> BotTimeseriesResponse` **get** `/radar/bots/timeseries` Retrieves 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. - `bot: Optional[SequenceNotStr[str]]` Filters results by bot name. - `bot_category: Optional[List[Literal["SEARCH_ENGINE_CRAWLER", "SEARCH_ENGINE_OPTIMIZATION", "MONITORING_AND_ANALYTICS", 13 more]]]` Filters results by bot category. - `"SEARCH_ENGINE_CRAWLER"` - `"SEARCH_ENGINE_OPTIMIZATION"` - `"MONITORING_AND_ANALYTICS"` - `"ADVERTISING_AND_MARKETING"` - `"SOCIAL_MEDIA_MARKETING"` - `"PAGE_PREVIEW"` - `"ACADEMIC_RESEARCH"` - `"SECURITY"` - `"ACCESSIBILITY"` - `"WEBHOOKS"` - `"FEED_FETCHER"` - `"AI_CRAWLER"` - `"AGGREGATOR"` - `"AI_ASSISTANT"` - `"AI_SEARCH"` - `"ARCHIVER"` - `bot_kind: Optional[List[Literal["AGENT", "BOT"]]]` Filters results by bot kind. - `"AGENT"` - `"BOT"` - `bot_operator: Optional[SequenceNotStr[str]]` Filters results by bot operator. - `bot_verification_status: Optional[List[Literal["VERIFIED"]]]` Filters results by bot verification status (Verified vs. Unverified). - `"VERIFIED"` - `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"` - `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 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.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 bots HTTP requests by dimension. `radar.bots.timeseries_groups(Literal["BOT", "BOT_KIND", "BOT_OPERATOR", "BOT_CATEGORY"]dimension, BotTimeseriesGroupsParams**kwargs) -> BotTimeseriesGroupsResponse` **get** `/radar/bots/timeseries_groups/{dimension}` Retrieves the distribution of HTTP requests from bots, grouped by the specified dimension over time. ### Parameters - `dimension: Literal["BOT", "BOT_KIND", "BOT_OPERATOR", "BOT_CATEGORY"]` Specifies the attribute by which to group the results. - `"BOT"` - `"BOT_KIND"` - `"BOT_OPERATOR"` - `"BOT_CATEGORY"` - `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. - `bot: Optional[SequenceNotStr[str]]` Filters results by bot name. - `bot_category: Optional[List[Literal["SEARCH_ENGINE_CRAWLER", "SEARCH_ENGINE_OPTIMIZATION", "MONITORING_AND_ANALYTICS", 13 more]]]` Filters results by bot category. - `"SEARCH_ENGINE_CRAWLER"` - `"SEARCH_ENGINE_OPTIMIZATION"` - `"MONITORING_AND_ANALYTICS"` - `"ADVERTISING_AND_MARKETING"` - `"SOCIAL_MEDIA_MARKETING"` - `"PAGE_PREVIEW"` - `"ACADEMIC_RESEARCH"` - `"SECURITY"` - `"ACCESSIBILITY"` - `"WEBHOOKS"` - `"FEED_FETCHER"` - `"AI_CRAWLER"` - `"AGGREGATOR"` - `"AI_ASSISTANT"` - `"AI_SEARCH"` - `"ARCHIVER"` - `bot_kind: Optional[List[Literal["AGENT", "BOT"]]]` Filters results by bot kind. - `"AGENT"` - `"BOT"` - `bot_operator: Optional[SequenceNotStr[str]]` Filters results by bot operator. - `bot_verification_status: Optional[List[Literal["VERIFIED"]]]` Filters results by bot verification status (Verified vs. Unverified). - `"VERIFIED"` - `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 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.bots.timeseries_groups( dimension="BOT", ) 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 List Response - `class BotListResponse: …` - `bots: List[Bot]` - `category: str` The category of the bot. - `description: str` A summary for the bot (e.g., purpose). - `kind: str` The kind of the bot. - `name: str` The name of the bot. - `operator: str` The organization that owns and operates the bot. - `slug: str` A kebab-case identifier derived from the bot name. - `user_agent_patterns: List[str]` ### Bot Get Response - `class BotGetResponse: …` - `bot: Bot` - `category: str` The category of the bot. - `description: str` A summary for the bot (e.g., purpose). - `kind: str` The kind of the bot. - `name: str` The name of the bot. - `operator: str` The organization that owns and operates the bot. - `operator_url: str` The link to the bot documentation. - `slug: str` A kebab-case identifier derived from the bot name. - `user_agent_patterns: List[str]` - `user_agents: List[str]` ### Bot Summary Response - `class BotSummaryResponse: …` - `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]` # Web Crawlers ## Get crawler HTTP request distribution by dimension `radar.bots.web_crawlers.summary(Literal["CLIENT_TYPE", "USER_AGENT", "REFERER", 3 more]dimension, WebCrawlerSummaryParams**kwargs) -> WebCrawlerSummaryResponse` **get** `/radar/bots/crawlers/summary/{dimension}` Retrieves an aggregated summary of HTTP requests from crawlers, grouped by the specified dimension. ### Parameters - `dimension: Literal["CLIENT_TYPE", "USER_AGENT", "REFERER", 3 more]` Specifies the attribute by which to group the results. - `"CLIENT_TYPE"` - `"USER_AGENT"` - `"REFERER"` - `"CRAWL_REFER_RATIO"` - `"VERTICAL"` - `"INDUSTRY"` - `bot_operator: Optional[SequenceNotStr[str]]` Filters results by bot operator. - `client_type: Optional[List[Literal["HUMAN", "NON_AI_BOT", "AI_BOT", "MIXED_PURPOSE"]]]` Filters results by agent type. - `"HUMAN"` - `"NON_AI_BOT"` - `"AI_BOT"` - `"MIXED_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. - `name: Optional[SequenceNotStr[str]]` Array of names used to label the series in the response. - `vertical: Optional[SequenceNotStr[str]]` Filters results by vertical. ### Returns - `class WebCrawlerSummaryResponse: …` - `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.bots.web_crawlers.summary( dimension="CLIENT_TYPE", ) 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": { "Claude": "63.40249", "DuckDuckGo": "10.274394", "Google": "8.381743" } }, "success": true } ``` ## Get time series of crawler HTTP request distribution by dimension `radar.bots.web_crawlers.timeseries_groups(Literal["CLIENT_TYPE", "USER_AGENT", "REFERER", 3 more]dimension, WebCrawlerTimeseriesGroupsParams**kwargs) -> WebCrawlerTimeseriesGroupsResponse` **get** `/radar/bots/crawlers/timeseries_groups/{dimension}` Retrieves the distribution of HTTP requests from crawlers, grouped by the specified dimension over time. ### Parameters - `dimension: Literal["CLIENT_TYPE", "USER_AGENT", "REFERER", 3 more]` Specifies the attribute by which to group the results. - `"CLIENT_TYPE"` - `"USER_AGENT"` - `"REFERER"` - `"CRAWL_REFER_RATIO"` - `"VERTICAL"` - `"INDUSTRY"` - `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"` - `bot_operator: Optional[SequenceNotStr[str]]` Filters results by bot operator. - `client_type: Optional[List[Literal["HUMAN", "NON_AI_BOT", "AI_BOT", "MIXED_PURPOSE"]]]` Filters results by agent type. - `"HUMAN"` - `"NON_AI_BOT"` - `"AI_BOT"` - `"MIXED_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. - `name: Optional[SequenceNotStr[str]]` Array of names used to label the series in the response. - `vertical: Optional[SequenceNotStr[str]]` Filters results by vertical. ### Returns - `class WebCrawlerTimeseriesGroupsResponse: …` - `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.bots.web_crawlers.timeseries_groups( dimension="CLIENT_TYPE", ) 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 ### Web Crawler Summary Response - `class WebCrawlerSummaryResponse: …` - `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]` ### Web Crawler Timeseries Groups Response - `class WebCrawlerTimeseriesGroupsResponse: …` - `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]`