Web Crawlers

Get crawler HTTP request distribution by dimension

radar.bots.web_crawlers.summary(, ) -> WebCrawlerSummaryResponse

GET/radar/bots/crawlers/summary/{dimension}

Get time series of crawler HTTP request distribution by dimension

radar.bots.web_crawlers.timeseries_groups(, ) -> WebCrawlerTimeseriesGroupsResponse

GET/radar/bots/crawlers/timeseries_groups/{dimension}

ModelsExpand Collapse

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.

One of the following:

"ALL"

"AI_BOTS"

"AI_GATEWAY"

"BGP"

"BOTS"

"CONNECTION_ANOMALY"

"CT"

"DNS"

"DNS_MAGNITUDE"

"DNS_AS112"

"DOS"

"EMAIL_ROUTING"

"EMAIL_SECURITY"

"FW"

"FW_PG"

"HTTP"

"HTTP_CONTROL"

"HTTP_CRAWLER_REFERER"

"HTTP_ORIGINS"

"IQI"

"LEAKED_CREDENTIALS"

"NET"

"ROBOTS_TXT"

"SPEED"

"WORKERS_AI"

description: str

end_date: datetime

formatdate-time

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

Event type for annotations.

One of the following:

"EVENT"

"GENERAL"

"OUTAGE"

"PARTIAL_PROJECTION"

"PIPELINE"

"TRAFFIC_ANOMALY"

is_instantaneous: bool

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

linked_url: str

formaturi

start_date: datetime

formatdate-time

level: int

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

date_range: List[MetaDateRange]

end_time: datetime

Adjusted end of date range.

formatdate-time

start_time: datetime

Adjusted start of date range.

formatdate-time

last_updated: datetime

Timestamp of the last dataset update.

formatdate-time

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

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

One of the following:

"PERCENTAGE"

"MIN0_MAX"

"MIN_MAX"

"RAW_VALUES"

"PERCENTAGE_CHANGE"

"ROLLING_AVERAGE"

"OVERLAPPED_PERCENTAGE"

"RATIO"

units: List[MetaUnit]

Measurement units for the results.

name: str

value: str

summary_0: Dict[str, str]

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.

One of the following:

"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.

One of the following:

"ALL"

"AI_BOTS"

"AI_GATEWAY"

"BGP"

"BOTS"

"CONNECTION_ANOMALY"

"CT"

"DNS"

"DNS_MAGNITUDE"

"DNS_AS112"

"DOS"

"EMAIL_ROUTING"

"EMAIL_SECURITY"

"FW"

"FW_PG"

"HTTP"

"HTTP_CONTROL"

"HTTP_CRAWLER_REFERER"

"HTTP_ORIGINS"

"IQI"

"LEAKED_CREDENTIALS"

"NET"

"ROBOTS_TXT"

"SPEED"

"WORKERS_AI"

description: str

end_date: datetime

formatdate-time

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

Event type for annotations.

One of the following:

"EVENT"

"GENERAL"

"OUTAGE"

"PARTIAL_PROJECTION"

"PIPELINE"

"TRAFFIC_ANOMALY"

is_instantaneous: bool

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

linked_url: str

formaturi

start_date: datetime

formatdate-time

level: int

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

date_range: List[MetaDateRange]

end_time: datetime

Adjusted end of date range.

formatdate-time

start_time: datetime

Adjusted start of date range.

formatdate-time

last_updated: datetime

Timestamp of the last dataset update.

formatdate-time

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

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

One of the following:

"PERCENTAGE"

"MIN0_MAX"

"MIN_MAX"

"RAW_VALUES"

"PERCENTAGE_CHANGE"

"ROLLING_AVERAGE"

"OVERLAPPED_PERCENTAGE"

"RATIO"

units: List[MetaUnit]

Measurement units for the results.

name: str

value: str

serie_0: Serie0

timestamps: List[datetime]