## Get time series of certificate distribution by dimension `radar.ct.timeseries_groups(Literal["CA", "CA_OWNER", "DURATION", 11 more]dimension, CTTimeseriesGroupsParams**kwargs) -> CTTimeseriesGroupsResponse` **get** `/radar/ct/timeseries_groups/{dimension}` Retrieves the distribution of certificates grouped by the specified dimension over time. ### Parameters - `dimension: Literal["CA", "CA_OWNER", "DURATION", 11 more]` Specifies the certificate attribute by which to group the results. - `"CA"` - `"CA_OWNER"` - `"DURATION"` - `"ENTRY_TYPE"` - `"EXPIRATION_STATUS"` - `"HAS_IPS"` - `"HAS_WILDCARDS"` - `"LOG"` - `"LOG_API"` - `"LOG_OPERATOR"` - `"PUBLIC_KEY_ALGORITHM"` - `"SIGNATURE_ALGORITHM"` - `"TLD"` - `"VALIDATION_LEVEL"` - `agg_interval: Optional[Literal["15m", "1h", "1d", "1w"]]` Aggregation interval of the results (e.g., in 15 minutes or 1 hour intervals). Refer to [Aggregation intervals](https://edgetunnel-b2h.pages.dev/radar/concepts/aggregation-intervals/). When omitted, the interval is auto-selected from the requested date range; finer intervals are only available for shorter ranges. If the requested interval is too granular for the date range, the request is rejected. - `"15m"` - `"1h"` - `"1d"` - `"1w"` - `ca: Optional[Sequence[str]]` Filters results by certificate authority. - `ca_owner: Optional[Sequence[str]]` Filters results by certificate authority owner. - `date_end: Optional[Sequence[Union[str, datetime]]]` End of the date range (inclusive). Alternative to `dateRange`; provide together with `dateStart`. When requesting comparison series, every series must resolve to the same duration as the main series. Each `dateStart`/`dateEnd` is floored to the nearest 15 minutes before evaluation, so windows whose durations match only before alignment may be rejected. - `date_range: Optional[Sequence[str]]` Filters results by relative date range ending at the current time, with each value producing a separate series. Use `d` for days (up to `364d`) or `w` for weeks (up to `52w`). Append `control` to request the equivalent previous period for comparison: the comparison window is shifted back by the current window's length rounded up to a whole number of weeks, so it keeps the same weekday alignment and does not overlap the current window (e.g. `7dcontrol` covers days -14 to -7, `10dcontrol` covers days -24 to -14). For example, pass `7d` and `7dcontrol` to compare this week with the previous week. All series must resolve to the same duration as the main series; relative ranges (including `control`) satisfy this automatically. Use this parameter or set specific start and end dates (`dateStart` and `dateEnd` parameters). - `date_start: Optional[Sequence[Union[str, datetime]]]` Start of the date range. Alternative to `dateRange`; provide together with `dateEnd`. When requesting comparison series, every series must resolve to the same duration as the main series. Each `dateStart`/`dateEnd` is floored to the nearest 15 minutes before evaluation, so windows whose durations match only before alignment may be rejected. - `duration: Optional[List[Literal["LTE_3D", "GT_3D_LTE_7D", "GT_7D_LTE_10D", 4 more]]]` Filters results by certificate duration. - `"LTE_3D"` - `"GT_3D_LTE_7D"` - `"GT_7D_LTE_10D"` - `"GT_10D_LTE_47D"` - `"GT_47D_LTE_100D"` - `"GT_100D_LTE_200D"` - `"GT_200D"` - `entry_type: Optional[List[Literal["PRECERTIFICATE", "CERTIFICATE"]]]` Filters results by entry type (certificate vs. pre-certificate). Incompatible with the `tld` filter/dimension. - `"PRECERTIFICATE"` - `"CERTIFICATE"` - `expiration_status: Optional[List[Literal["EXPIRED", "VALID"]]]` Filters results by expiration status (expired vs. valid). - `"EXPIRED"` - `"VALID"` - `format: Optional[Literal["JSON", "CSV"]]` Format in which results will be returned. - `"JSON"` - `"CSV"` - `has_ips: Optional[Iterable[bool]]` Filters results based on whether the certificates are bound to specific IP addresses. - `has_wildcards: Optional[Iterable[bool]]` Filters results based on whether the certificates contain wildcard domains. - `limit_per_group: Optional[int]` Limits the number of objects per group to the top items within the specified time range. When item count exceeds the limit, extra items appear grouped under an "other" category. Only supported on high-cardinality dimensions; otherwise the request is rejected. Minimum value is 2. - `log: Optional[Sequence[str]]` Filters results by certificate log. Incompatible with the `tld` filter/dimension. - `log_api: Optional[List[Literal["RFC6962", "STATIC"]]]` Filters results by certificate log API (RFC6962 vs. static). Incompatible with the `tld` filter/dimension. - `"RFC6962"` - `"STATIC"` - `log_operator: Optional[Sequence[str]]` Filters results by certificate log operator. Incompatible with the `tld` filter/dimension. - `name: Optional[Sequence[str]]` Array of names used to label the series in the response. - `normalization: Optional[Literal["RAW_VALUES", "PERCENTAGE"]]` Normalization method applied to the results. Refer to [Normalization methods](https://edgetunnel-b2h.pages.dev/radar/concepts/normalization/). - `"RAW_VALUES"` - `"PERCENTAGE"` - `public_key_algorithm: Optional[List[Literal["DSA", "ECDSA", "RSA"]]]` Filters results by public key algorithm. - `"DSA"` - `"ECDSA"` - `"RSA"` - `signature_algorithm: Optional[List[Literal["DSA_SHA_1", "DSA_SHA_256", "ECDSA_SHA_1", 12 more]]]` Filters results by signature algorithm. - `"DSA_SHA_1"` - `"DSA_SHA_256"` - `"ECDSA_SHA_1"` - `"ECDSA_SHA_256"` - `"ECDSA_SHA_384"` - `"ECDSA_SHA_512"` - `"PSS_SHA_256"` - `"PSS_SHA_384"` - `"PSS_SHA_512"` - `"RSA_MD2"` - `"RSA_MD5"` - `"RSA_SHA_1"` - `"RSA_SHA_256"` - `"RSA_SHA_384"` - `"RSA_SHA_512"` - `tld: Optional[Sequence[str]]` Filters results by top-level domain. Incompatible with the `log`, `logApi`, `logOperator`, and `entryType` filters/dimensions. - `unique_entries: Optional[List[Literal["true", "false"]]]` Specifies whether to filter out duplicate certificates and pre-certificates. Set to true for unique entries only. - `"true"` - `"false"` - `validation_level: Optional[List[Literal["DOMAIN", "ORGANIZATION", "EXTENDED"]]]` Filters results by validation level. - `"DOMAIN"` - `"ORGANIZATION"` - `"EXTENDED"` ### Returns - `class CTTimeseriesGroupsResponse: …` - `meta: Meta` Metadata for the results. - `agg_interval: Literal["FIFTEEN_MINUTES", "ONE_HOUR", "ONE_DAY", 2 more]` Aggregation interval of the results (e.g., in 15 minutes or 1 hour intervals). Refer to [Aggregation intervals](https://edgetunnel-b2h.pages.dev/radar/concepts/aggregation-intervals/). - `"FIFTEEN_MINUTES"` - `"ONE_HOUR"` - `"ONE_DAY"` - `"ONE_WEEK"` - `"ONE_MONTH"` - `confidence_info: MetaConfidenceInfo` - `annotations: List[MetaConfidenceInfoAnnotation]` - `data_source: Literal["ALL", "AI_BOTS", "AI_GATEWAY", 22 more]` Data source for annotations. - `"ALL"` - `"AI_BOTS"` - `"AI_GATEWAY"` - `"BGP"` - `"BOTS"` - `"CONNECTION_ANOMALY"` - `"CT"` - `"DNS"` - `"DNS_MAGNITUDE"` - `"DNS_AS112"` - `"DOS"` - `"EMAIL_ROUTING"` - `"EMAIL_SECURITY"` - `"FW"` - `"FW_PG"` - `"HTTP"` - `"HTTP_CONTROL"` - `"HTTP_CRAWLER_REFERER"` - `"HTTP_ORIGINS"` - `"IQI"` - `"LEAKED_CREDENTIALS"` - `"NET"` - `"ROBOTS_TXT"` - `"SPEED"` - `"WORKERS_AI"` - `description: str` - `end_date: datetime` - `event_type: Literal["EVENT", "GENERAL", "OUTAGE", 3 more]` Event type for annotations. - `"EVENT"` - `"GENERAL"` - `"OUTAGE"` - `"PARTIAL_PROJECTION"` - `"PIPELINE"` - `"TRAFFIC_ANOMALY"` - `is_instantaneous: bool` Whether event is a single point in time or a time range. - `linked_url: str` - `start_date: datetime` - `tags: Optional[List[str]]` - `level: int` Provides an indication of how much confidence Cloudflare has in the data. - `date_range: List[MetaDateRange]` - `end_time: datetime` Adjusted end of date range. - `start_time: datetime` Adjusted start of date range. - `last_updated: datetime` Timestamp of the last dataset update. - `normalization: Literal["PERCENTAGE", "MIN0_MAX", "MIN_MAX", 5 more]` Normalization method applied to the results. Refer to [Normalization methods](https://edgetunnel-b2h.pages.dev/radar/concepts/normalization/). - `"PERCENTAGE"` - `"MIN0_MAX"` - `"MIN_MAX"` - `"RAW_VALUES"` - `"PERCENTAGE_CHANGE"` - `"ROLLING_AVERAGE"` - `"OVERLAPPED_PERCENTAGE"` - `"RATIO"` - `units: List[MetaUnit]` Measurement units for the results. - `name: str` - `value: str` - `serie_0: Serie0` - `class Serie0UnnamedSchemaRef7826220e105d84352ba1108d9ed88e55: …` - `timestamps: List[datetime]` - `class Serie0UnionMember1: …` - `rfc6962: List[str]` - `static: List[str]` - `class Serie0UnionMember2: …` - `gt_121d: List[str]` - `gt_16d_lte_31d: List[str]` - `gt_31d_lte_91d: List[str]` - `gt_3d_lte_16d: List[str]` - `gt_91d_lte_121d: List[str]` - `lte_3d: List[str]` - `class Serie0UnionMember3: …` - `certificate: List[str]` - `precertificate: List[str]` - `class Serie0UnionMember4: …` - `expired: List[str]` - `valid: List[str]` - `class Serie0UnionMember5: …` - `negative: List[str]` - `positive: List[str]` - `class Serie0UnionMember6: …` - `dsa: List[str]` - `ecdsa: List[str]` - `rsa: List[str]` - `class Serie0UnionMember7: …` - `domain: List[str]` - `extended: List[str]` - `organization: List[str]` - `unknown: List[str]` ### Example ```python import os from cloudflare import Cloudflare client = Cloudflare( api_token=os.environ.get("CLOUDFLARE_API_TOKEN"), # This is the default and can be omitted ) response = client.radar.ct.timeseries_groups( dimension="CA", ) print(response.meta) ``` #### Response ```json { "result": { "meta": { "aggInterval": "FIFTEEN_MINUTES", "confidenceInfo": { "annotations": [ { "dataSource": "ALL", "description": "Cable cut in Tonga", "endDate": "2019-12-27T18:11:19.117Z", "eventType": "EVENT", "isInstantaneous": true, "linkedUrl": "https://example.com", "startDate": "2019-12-27T18:11:19.117Z", "tags": [ "BOT_CLASS" ] } ], "level": 0 }, "dateRange": [ { "endTime": "2022-09-17T10:22:57.555Z", "startTime": "2022-09-16T10:22:57.555Z" } ], "lastUpdated": "2019-12-27T18:11:19.117Z", "normalization": "PERCENTAGE", "units": [ { "name": "*", "value": "requests" } ] }, "serie_0": { "timestamps": [ "2023-08-08T10:15:00Z" ] } }, "success": true } ```